{"pageNumber":"416","pageRowStart":"10375","pageSize":"25","recordCount":40804,"records":[{"id":70191285,"text":"70191285 - 2017 - Science advancements key to increasing management value of life stage monitoring networks for endangered Sacramento River winter-run Chinook salmon in California","interactions":[],"lastModifiedDate":"2017-10-03T14:20:42","indexId":"70191285","displayToPublicDate":"2017-10-03T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3331,"text":"San Francisco Estuary and Watershed Science","active":true,"publicationSubtype":{"id":10}},"title":"Science advancements key to increasing management value of life stage monitoring networks for endangered Sacramento River winter-run Chinook salmon in California","docAbstract":"<p>A robust monitoring network that provides quantitative information about the status of imperiled species at key life stages and geographic locations over time is fundamental for sustainable management of fisheries resources. For anadromous species, management actions in one geographic domain can substantially affect abundance of subsequent life stages that span broad geographic regions. Quantitative metrics (e.g., abundance, movement, survival, life history diversity, and condition) at multiple life stages are needed to inform how management actions (e.g., hatcheries, harvest, hydrology, and habitat restoration) influence salmon population dynamics. The existing monitoring network for endangered Sacramento River winterrun Chinook Salmon (SRWRC, Oncorhynchus tshawytscha) in California’s Central Valley was compared to conceptual models developed for each life stage and geographic region of the life cycle to identify relevant SRWRC metrics. We concluded that the current monitoring network was insufficient to diagnose when (life stage) and where (geographic domain) chronic or episodic reductions in SRWRC cohorts occur, precluding within- and among-year comparisons. The strongest quantitative data exist in the Upper Sacramento River, where abundance estimates are generated for adult spawners and emigrating juveniles. However, once SRWRC leave the upper river, our knowledge of their identity,&nbsp;abundance, and condition diminishes, despite the juvenile monitoring enterprise. We identified six system-wide recommended actions to strengthen the value of data generated from the existing monitoring network to assess resource management actions: (1) incorporate genetic run identification; (2) develop juvenile abundance estimates; (3) collect data for life history diversity metrics at multiple life stages; (4) expand and enhance real-time fish survival and movement monitoring; (5) collect fish condition data; and (6) provide timely public access to monitoring data in open data formats. To illustrate how updated technologies can enhance the existing monitoring to provide quantitative data on SRWRC, we provide examples of how each recommendation can address specific management issues.</p>","language":"English","publisher":"Delta Science Program and the UC Davis John Muir Instutute of the Environment","doi":"10.15447/sfews.2017v15iss3art1","usgsCitation":"Johnson, R.C., Windell, S., Brandes, P.L., Conrad, J.L., Ferguson, J., Goertler, P.A., Harvey, B.N., Heublein, J., Isreal, J.A., Kratville, D.W., Kirsch, J.E., Perry, R.W., Pisciotto, J., Poytress, W.R., Reece, K., and Swart, B.G., 2017, Science advancements key to increasing management value of life stage monitoring networks for endangered Sacramento River winter-run Chinook salmon in California: San Francisco Estuary and Watershed Science, v. 15, no. 3, p. 1-41, https://doi.org/10.15447/sfews.2017v15iss3art1.","productDescription":"Article 1; 41 p.","startPage":"1","endPage":"41","ipdsId":"IP-076305","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":469459,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.15447/sfews.2017v15iss3art1","text":"Publisher Index Page"},{"id":346362,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.6019287109375,\n              37.400710068740565\n            ],\n            [\n              -121.39343261718749,\n              37.400710068740565\n            ],\n            [\n              -121.39343261718749,\n              40.643135583312805\n            ],\n            [\n              -122.6019287109375,\n              40.643135583312805\n            ],\n            [\n              -122.6019287109375,\n              37.400710068740565\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"15","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-27","publicationStatus":"PW","scienceBaseUri":"59d4a1a2e4b05fe04cc4e0d6","contributors":{"authors":[{"text":"Johnson, Rachel C.","contributorId":196877,"corporation":false,"usgs":false,"family":"Johnson","given":"Rachel","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":711845,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Windell, Sean","contributorId":196878,"corporation":false,"usgs":false,"family":"Windell","given":"Sean","email":"","affiliations":[],"preferred":false,"id":711846,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brandes, Patricia L.","contributorId":196879,"corporation":false,"usgs":false,"family":"Brandes","given":"Patricia","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":711847,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conrad, J. Louise","contributorId":196880,"corporation":false,"usgs":false,"family":"Conrad","given":"J.","email":"","middleInitial":"Louise","affiliations":[],"preferred":false,"id":711848,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ferguson, John","contributorId":196881,"corporation":false,"usgs":false,"family":"Ferguson","given":"John","affiliations":[],"preferred":false,"id":711849,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Goertler, Pascale A. L.","contributorId":196882,"corporation":false,"usgs":false,"family":"Goertler","given":"Pascale","email":"","middleInitial":"A. L.","affiliations":[],"preferred":false,"id":711850,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Harvey, Brett N.","contributorId":196883,"corporation":false,"usgs":false,"family":"Harvey","given":"Brett","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":711851,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Heublein, Joseph","contributorId":196884,"corporation":false,"usgs":false,"family":"Heublein","given":"Joseph","email":"","affiliations":[],"preferred":false,"id":711852,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Isreal, Joshua A.","contributorId":196885,"corporation":false,"usgs":false,"family":"Isreal","given":"Joshua","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":711853,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kratville, Daniel W.","contributorId":196892,"corporation":false,"usgs":false,"family":"Kratville","given":"Daniel","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":711864,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kirsch, Joseph E.","contributorId":171939,"corporation":false,"usgs":false,"family":"Kirsch","given":"Joseph","email":"","middleInitial":"E.","affiliations":[{"id":5128,"text":"U.S. Fish and Wildlife Service, University of Montana, Missoula, MT 59812","active":true,"usgs":false}],"preferred":false,"id":711854,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":711844,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Pisciotto, Joseph","contributorId":196886,"corporation":false,"usgs":false,"family":"Pisciotto","given":"Joseph","email":"","affiliations":[],"preferred":false,"id":711856,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Poytress, William R.","contributorId":196887,"corporation":false,"usgs":false,"family":"Poytress","given":"William","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":711857,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Reece, Kevin","contributorId":196888,"corporation":false,"usgs":false,"family":"Reece","given":"Kevin","email":"","affiliations":[],"preferred":false,"id":711858,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Swart, Brycen G.","contributorId":196889,"corporation":false,"usgs":false,"family":"Swart","given":"Brycen","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":711859,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}}
,{"id":70191276,"text":"70191276 - 2017 - UAS-SfM for coastal research: Geomorphic feature extraction and land cover classification from high-resolution elevation and optical imagery","interactions":[],"lastModifiedDate":"2017-10-03T10:46:10","indexId":"70191276","displayToPublicDate":"2017-10-03T00:00:00","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}},"title":"UAS-SfM for coastal research: Geomorphic feature extraction and land cover classification from high-resolution elevation and optical imagery","docAbstract":"<p><span>The vulnerability of coastal systems to hazards such as storms and sea-level rise is typically characterized using a combination of ground and manned airborne systems that have limited spatial or temporal scales. Structure-from-motion (SfM) photogrammetry applied to imagery acquired by unmanned aerial systems (UAS) offers a rapid and inexpensive means to produce high-resolution topographic and visual reflectance datasets that rival existing lidar and imagery standards. Here, we use SfM to produce an elevation point cloud, an orthomosaic, and a digital elevation model (DEM) from data collected by UAS at a beach and wetland site in Massachusetts, USA. We apply existing methods to (a) determine the position of shorelines and foredunes using a feature extraction routine developed for lidar point clouds and (b) map land cover from the rasterized surfaces using a supervised classification routine. In both analyses, we experimentally vary the input datasets to understand the benefits and limitations of UAS-SfM for coastal vulnerability assessment. We find that (a) geomorphic features are extracted from the SfM point cloud with near-continuous coverage and sub-meter precision, better than was possible from a recent lidar dataset covering the same area; and (b) land cover classification is greatly improved by including topographic data with visual reflectance, but changes to resolution (when &lt;50 cm) have little influence on the classification accuracy.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/rs9101020","usgsCitation":"Sturdivant, E.J., Lentz, E.E., Thieler, E.R., Farris, A.S., Weber, K.M., Remsen, D.P., Miner, S., and Henderson, R.E., 2017, UAS-SfM for coastal research: Geomorphic feature extraction and land cover classification from high-resolution elevation and optical imagery: Remote Sensing, v. 9, no. 10, p. 1-20, https://doi.org/10.3390/rs9101020.","productDescription":"20 p.","startPage":"1","endPage":"20","ipdsId":"IP-090271","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469461,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs9101020","text":"Publisher Index Page"},{"id":438194,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7KW5F04","text":"USGS data release","linkHelpText":"Topographic, imagery, and raw data associated with unmanned aerial systems (UAS) flights over Black Beach, Falmouth, Massachusetts on 18 March 2016"},{"id":346346,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Buzzards Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -70.95451354980469,\n              41.51834634058004\n            ],\n            [\n              -70.60089111328125,\n              41.51834634058004\n            ],\n            [\n              -70.60089111328125,\n              41.77028745790557\n            ],\n            [\n              -70.95451354980469,\n              41.77028745790557\n            ],\n            [\n              -70.95451354980469,\n              41.51834634058004\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"9","issue":"10","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-03","publicationStatus":"PW","scienceBaseUri":"59d4a1a3e4b05fe04cc4e0da","contributors":{"authors":[{"text":"Sturdivant, Emily J. 0000-0002-2420-3115 esturdivant@usgs.gov","orcid":"https://orcid.org/0000-0002-2420-3115","contributorId":175325,"corporation":false,"usgs":true,"family":"Sturdivant","given":"Emily","email":"esturdivant@usgs.gov","middleInitial":"J.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":711828,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lentz, Erika E. 0000-0002-0621-8954 elentz@usgs.gov","orcid":"https://orcid.org/0000-0002-0621-8954","contributorId":173964,"corporation":false,"usgs":true,"family":"Lentz","given":"Erika","email":"elentz@usgs.gov","middleInitial":"E.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":711829,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thieler, E. Robert 0000-0003-4311-9717 rthieler@usgs.gov","orcid":"https://orcid.org/0000-0003-4311-9717","contributorId":2488,"corporation":false,"usgs":true,"family":"Thieler","given":"E.","email":"rthieler@usgs.gov","middleInitial":"Robert","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":711830,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Farris, Amy S. 0000-0002-4668-7261 afarris@usgs.gov","orcid":"https://orcid.org/0000-0002-4668-7261","contributorId":196866,"corporation":false,"usgs":true,"family":"Farris","given":"Amy","email":"afarris@usgs.gov","middleInitial":"S.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":711831,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Weber, Kathryn M. 0000-0002-5498-7117 kweber@usgs.gov","orcid":"https://orcid.org/0000-0002-5498-7117","contributorId":196867,"corporation":false,"usgs":true,"family":"Weber","given":"Kathryn","email":"kweber@usgs.gov","middleInitial":"M.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":711832,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Remsen, David P.","contributorId":196868,"corporation":false,"usgs":false,"family":"Remsen","given":"David","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":711833,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Miner, Simon","contributorId":196869,"corporation":false,"usgs":false,"family":"Miner","given":"Simon","email":"","affiliations":[],"preferred":false,"id":711834,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Henderson, Rachel E. 0000-0001-5810-7941 rehenderson@contractor.usgs.gov","orcid":"https://orcid.org/0000-0001-5810-7941","contributorId":196870,"corporation":false,"usgs":true,"family":"Henderson","given":"Rachel","email":"rehenderson@contractor.usgs.gov","middleInitial":"E.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":711835,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70239816,"text":"70239816 - 2017 - Influence of the megathrust earthquake cycle on upper-plate deformation in the Cascadia forearc of Washington State, USA","interactions":[],"lastModifiedDate":"2023-01-20T12:43:03.220753","indexId":"70239816","displayToPublicDate":"2017-10-02T06:39:27","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Influence of the megathrust earthquake cycle on upper-plate deformation in the Cascadia forearc of Washington State, USA","docAbstract":"<div id=\"107806598\" class=\"article-section-wrapper js-article-section js-content-section  \" data-section-parent-id=\"0\"><p>The influence of subduction zone earthquake cycle processes on permanent forearc deformation is poorly understood. In the Cascadia subduction zone forearc of Washington State, USA, deformed and incised fluvial terraces serve as archives of longer-term (10<sup>3</sup>–10<sup>4</sup><span>&nbsp;</span>yr) strain manifest as both fluvial incision and slip on upper-plate faults. We focus on comparing these geomorphic records in the Wynoochee River valley in the southern Olympic Mountains with short-term (10<sup>1</sup><span>&nbsp;</span>yr) deformation driven by interseismic subduction zone coupling. We use optically stimulated luminescence dating and high-resolution elevation data to characterize strath terrace incision and differential uplift across the Canyon River fault, which cuts Wynoochee River terraces. This analysis demonstrates reverse slip rates of ∼0.1–0.3 mm/yr over the past ∼12–37 k.y., which agree with rates predicted by a GPS-constrained boundary element model of interseismic stress from Cascadia subduction zone coupling. Similarly, model-predicted patterns of interseismic uplift mimic the overall pattern of incision in the lower Wynoochee River valley, as revealed by strath elevations dated at 14.1 ± 1.2 ka. Agreement between modeled short-term and observed long-term records of forearc strain suggests that interseismic stress drives slip on upper-plate faults and fluvial incision in Cascadia. Consistency over multiple time scales may indicate relative stability in spatial patterns of subduction zone coupling over at least ∼10<sup>4</sup><span>&nbsp;</span>yr intervals.</p></div>","language":"English","publisher":"Geological Society of America","doi":"10.1130/G39070.1","usgsCitation":"Delano, J.E., Amos, C.B., Loveless, J.P., Rittenour, T.M., Sherrod, B.L., and Emerson, L.M., 2017, Influence of the megathrust earthquake cycle on upper-plate deformation in the Cascadia forearc of Washington State, USA: Geology, v. 45, no. 11, p. 1051-1054, https://doi.org/10.1130/G39070.1.","productDescription":"4 p.","startPage":"1051","endPage":"1054","ipdsId":"IP-088920","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":469464,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://scholarworks.smith.edu/geo_facpubs/24","text":"External Repository"},{"id":412110,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Cascadia forearc","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -125.2032729732052,\n              48.680479170986615\n            ],\n            [\n              -125.2032729732052,\n              46.36730413682102\n            ],\n            [\n              -121.86484698690327,\n              46.36730413682102\n            ],\n            [\n              -121.86484698690327,\n              48.680479170986615\n            ],\n            [\n              -125.2032729732052,\n              48.680479170986615\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"45","issue":"11","noUsgsAuthors":false,"publicationDate":"2017-10-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Delano, Jaime E. 0000-0003-2601-2600","orcid":"https://orcid.org/0000-0003-2601-2600","contributorId":210604,"corporation":false,"usgs":true,"family":"Delano","given":"Jaime","email":"","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":862028,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Amos, Colin B. 0000-0002-3862-9344","orcid":"https://orcid.org/0000-0002-3862-9344","contributorId":266018,"corporation":false,"usgs":false,"family":"Amos","given":"Colin","email":"","middleInitial":"B.","affiliations":[{"id":54859,"text":"Geology Department, Western Washington University, 516 High St., Bellingham, WA, 98225","active":true,"usgs":false}],"preferred":false,"id":862029,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Loveless, John P.","contributorId":301106,"corporation":false,"usgs":false,"family":"Loveless","given":"John","email":"","middleInitial":"P.","affiliations":[{"id":47946,"text":"Smith College","active":true,"usgs":false}],"preferred":false,"id":862030,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rittenour, Tammy M.","contributorId":140755,"corporation":false,"usgs":false,"family":"Rittenour","given":"Tammy","email":"","middleInitial":"M.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":862031,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sherrod, Brian L. 0000-0002-4492-8631 bsherrod@usgs.gov","orcid":"https://orcid.org/0000-0002-4492-8631","contributorId":2834,"corporation":false,"usgs":true,"family":"Sherrod","given":"Brian","email":"bsherrod@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":862032,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Emerson, Lynch M.","contributorId":301108,"corporation":false,"usgs":false,"family":"Emerson","given":"Lynch","email":"","middleInitial":"M.","affiliations":[{"id":47946,"text":"Smith College","active":true,"usgs":false}],"preferred":false,"id":862033,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70191268,"text":"70191268 - 2017 - Model parameters for representative wetland plant functional groups","interactions":[],"lastModifiedDate":"2017-10-08T12:16:12","indexId":"70191268","displayToPublicDate":"2017-10-02T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Model parameters for representative wetland plant functional groups","docAbstract":"<p><span>Wetlands provide a wide variety of ecosystem services including water quality remediation, biodiversity refugia, groundwater recharge, and floodwater storage. Realistic estimation of ecosystem service benefits associated with wetlands requires reasonable simulation of the hydrology of each site and realistic simulation of the upland and wetland plant growth cycles. Objectives of this study were to quantify leaf area index (LAI), light extinction coefficient (</span><i>k</i><span>), and plant nitrogen (N), phosphorus (P), and potassium (K) concentrations in natural stands of representative plant species for some major plant functional groups in the United States. Functional groups in this study were based on these parameters and plant growth types to enable process-based modeling. We collected data at four locations representing some of the main wetland regions of the United States. At each site, we collected on-the-ground measurements of fraction of light intercepted, LAI, and dry matter within the 2013–2015 growing seasons. Maximum LAI and<span>&nbsp;</span></span><i>k</i><span><span>&nbsp;</span>variables showed noticeable variations among sites and years, while overall averages and functional group averages give useful estimates for multisite simulation modeling. Variation within each species gives an indication of what can be expected in such natural ecosystems. For P and K, the concentrations from highest to lowest were spikerush (</span><i>Eleocharis macrostachya</i><span>), reed canary grass (</span><i>Phalaris arundinacea</i><span>), smartweed (</span><i>Polygonum</i><span><span>&nbsp;</span>spp.), cattail (</span><i>Typha</i><span><span>&nbsp;</span>spp.), and hardstem bulrush (</span><i>Schoenoplectus acutus</i><span>). Spikerush had the highest N concentration, followed by smartweed, bulrush, reed canary grass, and then cattail. These parameters will be useful for the actual wetland species measured and for the wetland plant functional groups they represent. These parameters and the associated process-based models offer promise as valuable tools for evaluating environmental benefits of wetlands and for evaluating impacts of various agronomic practices in adjacent areas as they affect wetlands.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1958","usgsCitation":"Williams, A.S., Kiniry, J.R., Mushet, D.M., Smith, L., McMurry, S.T., Attebury, K., Lang, M., McCarty, G.W., Shaffer, J.A., Effland, W.R., and Johnson, M., 2017, Model parameters for representative wetland plant functional groups: Ecosphere, v. 8, no. 10, p. 1-14, https://doi.org/10.1002/ecs2.1958.","productDescription":"Article e01958; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-075940","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":469465,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1958","text":"Publisher Index Page"},{"id":346339,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"10","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-02","publicationStatus":"PW","scienceBaseUri":"59d35025e4b05fe04cc34d45","contributors":{"authors":[{"text":"Williams, Amber S.","contributorId":196855,"corporation":false,"usgs":false,"family":"Williams","given":"Amber","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":711793,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kiniry, James R.","contributorId":66918,"corporation":false,"usgs":true,"family":"Kiniry","given":"James","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":711794,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":711795,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Loren M.","contributorId":88876,"corporation":false,"usgs":true,"family":"Smith","given":"Loren M.","affiliations":[],"preferred":false,"id":711796,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McMurry, Scott T.","contributorId":191876,"corporation":false,"usgs":false,"family":"McMurry","given":"Scott","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":711797,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Attebury, Kelly","contributorId":196857,"corporation":false,"usgs":false,"family":"Attebury","given":"Kelly","email":"","affiliations":[],"preferred":false,"id":711798,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lang, Megan","contributorId":156431,"corporation":false,"usgs":false,"family":"Lang","given":"Megan","affiliations":[{"id":7261,"text":"Department of Geographical Sciences, University of Maryland, College Park, MD, 20742","active":true,"usgs":false}],"preferred":false,"id":711799,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McCarty, Gregory W.","contributorId":192367,"corporation":false,"usgs":false,"family":"McCarty","given":"Gregory","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":711800,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Shaffer, Jill A. 0000-0003-3172-0708 jshaffer@usgs.gov","orcid":"https://orcid.org/0000-0003-3172-0708","contributorId":3184,"corporation":false,"usgs":true,"family":"Shaffer","given":"Jill","email":"jshaffer@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":711801,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Effland, William R.","contributorId":196858,"corporation":false,"usgs":false,"family":"Effland","given":"William","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":711802,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Johnson, Mari-Vaughn V.","contributorId":196859,"corporation":false,"usgs":false,"family":"Johnson","given":"Mari-Vaughn V.","affiliations":[],"preferred":false,"id":711803,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70191271,"text":"70191271 - 2017 - Detection and characterization of pulses in broadband seismometers","interactions":[],"lastModifiedDate":"2017-10-02T18:00:51","indexId":"70191271","displayToPublicDate":"2017-10-02T00:00:00","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":"Detection and characterization of pulses in broadband seismometers","docAbstract":"<p>Pulsing - caused either by mechanical or electrical glitches, or by microtilt local to a seismometer - can significantly compromise the long‐period noise performance of broadband seismometers. High‐fidelity long‐period recordings are needed for accurate calculation of quantities such as moment tensors, fault‐slip models, and normal‐mode measurements. Such pulses have long been recognized in accelerometers, and methods have been developed to correct these acceleration steps, but considerable work remains to be done in order to detect and correct similar pulses in broadband seismic data. We present a method for detecting and characterizing the pulses using data from a range of broadband sensor types installed in the Global Seismographic Network. The technique relies on accurate instrument response removal and employs a moving‐window approach looking for acceleration baseline shifts. We find that pulses are present at varying levels in all sensor types studied. Pulse‐detection results compared with average daily station noise values are consistent with predicted noise levels of acceleration steps. This indicates that we can calculate maximum pulse amplitude allowed per time window that would be acceptable without compromising long‐period data analysis.</p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120170089","usgsCitation":"Wilson, D.C., Ringler, A.T., and Hutt, C.R., 2017, Detection and characterization of pulses in broadband seismometers: Bulletin of the Seismological Society of America, v. 107, no. 4, p. 1173-1180, https://doi.org/10.1785/0120170089.","productDescription":"8 p.","startPage":"1173","endPage":"1180","ipdsId":"IP-085630","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":346341,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"107","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-04","publicationStatus":"PW","scienceBaseUri":"59d35024e4b05fe04cc34d42","contributors":{"authors":[{"text":"Wilson, David C. 0000-0003-2582-5159 dwilson@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-5159","contributorId":145580,"corporation":false,"usgs":true,"family":"Wilson","given":"David","email":"dwilson@usgs.gov","middleInitial":"C.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":711804,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ringler, Adam T. 0000-0002-9839-4188 aringler@usgs.gov","orcid":"https://orcid.org/0000-0002-9839-4188","contributorId":145576,"corporation":false,"usgs":true,"family":"Ringler","given":"Adam","email":"aringler@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":711805,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hutt, Charles R. 0000-0001-9033-9195 bhutt@usgs.gov","orcid":"https://orcid.org/0000-0001-9033-9195","contributorId":1622,"corporation":false,"usgs":true,"family":"Hutt","given":"Charles","email":"bhutt@usgs.gov","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":711806,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70188528,"text":"70188528 - 2017 - Application of paleoecology to ecosystem restoration: A case study from south Florida’s estuaries","interactions":[],"lastModifiedDate":"2018-10-16T09:55:31","indexId":"70188528","displayToPublicDate":"2017-10-01T15:40:27","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Application of paleoecology to ecosystem restoration: A case study from south Florida’s estuaries","docAbstract":"<p><span>Paleoecological analyses of biotic assemblages from cores collected throughout south Florida’s estuaries indicate gradually increasing salinities over approximately the last 2000 years, consistent with rising sea level. Around the beginning of the twentieth century these gradual patterns of change began to shift, corresponding to the beginning of human alteration of the environment via canal construction, railroad construction and other land use changes. Between 1950 and 1960, at a time of significant construction of water management structures another distinctive shift in the biological assemblages occurred. Analysis of the assemblages provides essential information on long-term patterns of change in the estuaries and provides a basis for predicting future trajectories of change. Paleosalinity estimates derived from the cores are providing input to linear regression models to determine related freshwater flow into the estuaries of south Florida. These analyses are being used to help establish performance measures and targets for the Comprehensive Everglades Restoration, established following an Act of Congress in 2000. Restoration of south Florida’s ecosystems is slated to be a 30–50 year effort that will require detailed knowledge of past decadal to centennial-scale changes in climate, freshwater flow and salinity. This historical perspective provides information that allows land managers to set realistic and sustainable goals for restoration, and provides insight into the potential response of south Florida’s ecosystem to various future scenarios of global change.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Applications of paleoenvironmental techniques in estuarine studies. Part of the Developments in Paleoenvironmental Research book series. ","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-94-024-0990-1_22","usgsCitation":"Wingard, G.L., 2017, Application of paleoecology to ecosystem restoration: A case study from south Florida’s estuaries, chap. <i>of</i> Applications of paleoenvironmental techniques in estuarine studies. Part of the Developments in Paleoenvironmental Research book series. , v. 20, p. 551-585, https://doi.org/10.1007/978-94-024-0990-1_22.","productDescription":"35 p.","startPage":"551","endPage":"585","ipdsId":"IP-017977","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":358397,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -82.869873046875,\n              24.43714786161562\n            ],\n            [\n              -78.9312744140625,\n              24.43714786161562\n            ],\n            [\n              -78.9312744140625,\n              27.259512784361693\n            ],\n            [\n              -82.869873046875,\n              27.259512784361693\n            ],\n            [\n              -82.869873046875,\n              24.43714786161562\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"20","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-15","publicationStatus":"PW","scienceBaseUri":"5c10ab02e4b034bf6a7e5f39","contributors":{"editors":[{"text":"Weckstrom, Kaarina","contributorId":209733,"corporation":false,"usgs":false,"family":"Weckstrom","given":"Kaarina","email":"","affiliations":[],"preferred":false,"id":748662,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Saunders, Krystyna M.","contributorId":209734,"corporation":false,"usgs":false,"family":"Saunders","given":"Krystyna","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":748663,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Gell, Peter A.","contributorId":66602,"corporation":false,"usgs":true,"family":"Gell","given":"Peter","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":748664,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Skilbeck, C. Gregory","contributorId":209735,"corporation":false,"usgs":false,"family":"Skilbeck","given":"C.","email":"","middleInitial":"Gregory","affiliations":[],"preferred":false,"id":748665,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Wingard, G. Lynn 0000-0002-3833-5207 lwingard@usgs.gov","orcid":"https://orcid.org/0000-0002-3833-5207","contributorId":605,"corporation":false,"usgs":true,"family":"Wingard","given":"G.","email":"lwingard@usgs.gov","middleInitial":"Lynn","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":698150,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70191112,"text":"70191112 - 2017 - Hypogene caves of the central Appalachian Shenandoah Valley in Virginia","interactions":[],"lastModifiedDate":"2017-10-03T12:48:06","indexId":"70191112","displayToPublicDate":"2017-10-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Hypogene caves of the central Appalachian Shenandoah Valley in Virginia","docAbstract":"<p><span>Several caves in the Shenandoah Valley in Virginia show evidence for early hypogenic conduit development with later-enhanced solution under partly confined phreatic conditions guided by geologic structures. Many (but not all) of these caves have been subsequently invaded by surface waters as a result of erosion and exhumation. Those not so affected are relict phreatic caves, bearing no relation to modern drainage patterns. Field and petrographic evidence shows that carbonate rocks hosting certain relict phreatic caves were dolomitized and/or silicified by early hydrothermal fluid migration in zones that served to locally enhance rock porosity, thus providing preferential pathways for later solution by groundwater flow, and making the surrounding bedrock more resistant to surficial weathering to result in caves that reside within isolated hills on the land surface. Features suggesting that deep phreatic processes dominated the development of these relict caves include (1) cave passage morphologies indicative of ascending fluids, (2) cave plans of irregular pattern, reflecting early maze or anastomosing development, (3) a general lack of cave breakdown and cave streams or cave stream deposits, and (4) calcite wall and pool coatings within isolated caves intersecting the local water table, and within unroofed caves at topographic locations elevated well above the local base level. Episodes of deep karstification were likely separated by long periods of geologic time, encompassing multiple phases of sedimentary fill and excavation within caves, and reflect a complex history of deep fluid migration that set the stage for later shallow speleogenesis that continues today.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Hypogene karst regions and caves of the world","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-319-53348-3_46","usgsCitation":"Doctor, D.H., and Orndorff, W., 2017, Hypogene caves of the central Appalachian Shenandoah Valley in Virginia, chap. <i>of</i> Hypogene karst regions and caves of the world, p. 691-707, https://doi.org/10.1007/978-3-319-53348-3_46.","productDescription":"17 p.","startPage":"691","endPage":"707","ipdsId":"IP-081438","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":346351,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Shenandoah Valley","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-18","publicationStatus":"PW","scienceBaseUri":"59d4a1a5e4b05fe04cc4e0eb","contributors":{"authors":[{"text":"Doctor, Daniel H. 0000-0002-8338-9722 dhdoctor@usgs.gov","orcid":"https://orcid.org/0000-0002-8338-9722","contributorId":2037,"corporation":false,"usgs":true,"family":"Doctor","given":"Daniel","email":"dhdoctor@usgs.gov","middleInitial":"H.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":711262,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Orndorff, Wil","contributorId":127487,"corporation":false,"usgs":false,"family":"Orndorff","given":"Wil","affiliations":[{"id":6970,"text":"Virginia Department of Conservation and Recreation, Natural Heritage Program","active":true,"usgs":false}],"preferred":false,"id":711263,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70191363,"text":"70191363 - 2017 - A fault‐based model for crustal deformation in the western United States based on a combined inversion of GPS and geologic inputs","interactions":[],"lastModifiedDate":"2018-03-28T14:55:47","indexId":"70191363","displayToPublicDate":"2017-10-01T00:00:00","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 fault‐based model for crustal deformation in the western United States based on a combined inversion of GPS and geologic inputs","docAbstract":"<p><span>We develop a crustal deformation model to determine fault‐slip rates for the western United States (WUS) using the&nbsp;</span><a class=\"link link-ref link-reveal xref-bibr\" data-open=\"rf42\">Zeng and Shen (2014)</a><span><span>&nbsp;</span>method that is based on a combined inversion of Global Positioning System (GPS) velocities and geological slip‐rate constraints. The model consists of six blocks with boundaries aligned along major faults in California and the Cascadia subduction zone, which are represented as buried dislocations in the Earth. Faults distributed within blocks have their geometrical structure and locking depths specified by the Uniform California Earthquake Rupture Forecast, version 3 (UCERF3) and the 2008 U.S. Geological Survey National Seismic Hazard Map Project model. Faults slip beneath a predefined locking depth, except for a few segments where shallow creep is allowed. The slip rates are estimated using a least‐squares inversion. The model resolution analysis shows that the resulting model is influenced heavily by geologic input, which fits the UCERF3 geologic bounds on California B faults and ±one‐half of the geologic slip rates for most other WUS faults. The modeled slip rates for the WUS faults are consistent with the observed GPS velocity field. Our fit to these velocities is measured in terms of a normalized chi‐square, which is 6.5. This updated model fits the data better than most other geodetic‐based inversion models. Major discrepancies between well‐resolved GPS inversion rates and geologic‐consensus rates occur along some of the northern California A faults, the Mojave to San Bernardino segments of the San Andreas fault, the western Garlock fault, the southern segment of the Wasatch fault, and other faults. Off‐fault strain‐rate distributions are consistent with regional tectonics, with a total off‐fault moment rate of<span>&nbsp;</span></span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mn xmlns=&quot;&quot;>7.2</mn><mo xmlns=&quot;&quot;>&amp;#xD7;</mo><msup xmlns=&quot;&quot;><mn>10</mn><mn>18</mn></msup></math>\"><span id=\"MathJax-Span-1\" class=\"math\"><span><span><span id=\"MathJax-Span-2\" class=\"mrow\"><span id=\"MathJax-Span-3\" class=\"mn\">7.2</span><span id=\"MathJax-Span-4\" class=\"mo\">×</span><span id=\"MathJax-Span-5\" class=\"msup\"><span><span><span id=\"MathJax-Span-6\" class=\"mn\">10</span></span><sup><span><span id=\"MathJax-Span-7\" class=\"mn\">18&nbsp;</span></span></sup></span></span></span></span></span></span></span></span><span>and<span>&nbsp;</span></span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-2-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mn xmlns=&quot;&quot;>8.5</mn><mo xmlns=&quot;&quot;>&amp;#xD7;</mo><msup xmlns=&quot;&quot;><mn>10</mn><mn>18</mn></msup><mtext xmlns=&quot;&quot;>&amp;#x2009;&amp;#x2009;</mtext><mi xmlns=&quot;&quot; mathvariant=&quot;normal&quot;>N</mi><mo xmlns=&quot;&quot; lspace=&quot;0em&quot; rspace=&quot;0em&quot;>&amp;#xB7;</mo><mi xmlns=&quot;&quot; mathvariant=&quot;normal&quot;>m</mi><mo xmlns=&quot;&quot;>/</mo><mi xmlns=&quot;&quot;>year</mi></math>\"><span id=\"MathJax-Span-8\" class=\"math\"><span><span><span id=\"MathJax-Span-9\" class=\"mrow\"><span id=\"MathJax-Span-10\" class=\"mn\">8.5</span><span id=\"MathJax-Span-11\" class=\"mo\">×</span><span id=\"MathJax-Span-12\" class=\"msup\"><span><span><span id=\"MathJax-Span-13\" class=\"mn\">10</span></span><sup><span><span id=\"MathJax-Span-14\" class=\"mn\">18</span></span></sup></span></span><span id=\"MathJax-Span-15\" class=\"mtext\">  </span><span id=\"MathJax-Span-16\" class=\"mi\">N</span><span id=\"MathJax-Span-17\" class=\"mo\">⋅</span><span id=\"MathJax-Span-18\" class=\"mi\">m</span><span id=\"MathJax-Span-19\" class=\"mo\">/</span><span id=\"MathJax-Span-20\" class=\"mi\">year</span></span></span></span></span></span></span><span><span>&nbsp;</span>for California and the WUS outside California, respectively.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120150362","usgsCitation":"Zeng, Y., and Shen, Z., 2017, A fault‐based model for crustal deformation in the western United States based on a combined inversion of GPS and geologic inputs: Bulletin of the Seismological Society of America, v. 107, no. 6, p. 2597-2612, https://doi.org/10.1785/0120150362.","productDescription":"16 p.","startPage":"2597","endPage":"2612","ipdsId":"IP-077581","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":352869,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"107","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-10","publicationStatus":"PW","scienceBaseUri":"5afee7eae4b0da30c1bfc3a7","contributors":{"authors":[{"text":"Zeng, Yuehua 0000-0003-1161-1264 zeng@usgs.gov","orcid":"https://orcid.org/0000-0003-1161-1264","contributorId":145693,"corporation":false,"usgs":true,"family":"Zeng","given":"Yuehua","email":"zeng@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":712093,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shen, Zheng-Kang","contributorId":196962,"corporation":false,"usgs":false,"family":"Shen","given":"Zheng-Kang","email":"","affiliations":[],"preferred":false,"id":712094,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70191531,"text":"70191531 - 2017 - Forecasting the (un)productivity of the 2014 M 6.0 South Napa aftershock sequence","interactions":[],"lastModifiedDate":"2017-10-17T11:26:13","indexId":"70191531","displayToPublicDate":"2017-10-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Forecasting the (un)productivity of the 2014 M 6.0 South Napa aftershock sequence","docAbstract":"<p><span>The 24 August 2014&nbsp;</span><i>M</i><sub>w</sub><span>&nbsp;6.0 South Napa mainshock produced fewer aftershocks than expected for a California earthquake of its magnitude. In the first 4.5 days, only 59<span>&nbsp;</span></span><i>M</i><span>≥1.8 aftershocks occurred, the largest of which was an<span>&nbsp;</span></span><i>M</i><span>&nbsp;3.9 that happened a little over two days after the mainshock. We investigate the aftershock productivity of the South Napa sequence and compare it with other<span>&nbsp;</span></span><i>M</i><span>≥5.5 California strike‐slip mainshock–aftershock sequences. While the productivity of the South Napa sequence is among the lowest, northern California mainshocks generally have fewer aftershocks than mainshocks further south, although the productivities vary widely in both regions. An epidemic‐type aftershock sequence (ETAS) model (</span><span id=\"xref-ref-23-1\" class=\"xref-bibr\">Ogata, 1988</span><span>) fit to Napa seismicity from 1980 to 23 August 2014 fits the sequence well and suggests that low‐productivity sequences are typical of this area. Utilizing regional variations in productivity could improve operational earthquake forecasting (OEF) by improving the model used immediately after the mainshock. We show this by comparing the daily rate of<span>&nbsp;</span></span><i>M</i><span>≥2 aftershocks to forecasts made with the generic California model (</span><span id=\"xref-ref-32-1\" class=\"xref-bibr\">Reasenberg and Jones, 1989</span><span>; hereafter, RJ89), RJ89 models with productivity updated daily, a generic California ETAS model, an ETAS model based on premainshock seismicity, and ETAS models updated daily following the mainshock. RJ89 models for which only the productivity is updated provide better forecasts than the generic RJ89 California model, and the Napa‐specific ETAS models forecast the aftershock rates more accurately than either generic model. Therefore, forecasts that use localized initial parameters and that rapidly update the productivity may be better for OEF than using a generic model and/or updating all parameters.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220170050","usgsCitation":"Llenos, A.L., and Michael, A.J., 2017, Forecasting the (un)productivity of the 2014 M 6.0 South Napa aftershock sequence: Seismological Research Letters, v. 88, no. 5, p. 1241-1251, https://doi.org/10.1785/0220170050.","productDescription":"11 p.","startPage":"1241","endPage":"1251","ipdsId":"IP-083327","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":346683,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -124,\n              32\n            ],\n            [\n              -115,\n              32\n            ],\n            [\n              -115,\n              42\n            ],\n            [\n              -124,\n              42\n            ],\n            [\n              -124,\n              32\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"88","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-19","publicationStatus":"PW","scienceBaseUri":"59e71690e4b05fe04cd33190","contributors":{"authors":[{"text":"Llenos, Andrea L. 0000-0002-4088-6737 allenos@usgs.gov","orcid":"https://orcid.org/0000-0002-4088-6737","contributorId":4455,"corporation":false,"usgs":true,"family":"Llenos","given":"Andrea","email":"allenos@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":712646,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Michael, Andrew J. 0000-0002-2403-5019 michael@usgs.gov","orcid":"https://orcid.org/0000-0002-2403-5019","contributorId":1280,"corporation":false,"usgs":true,"family":"Michael","given":"Andrew","email":"michael@usgs.gov","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":712647,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70191529,"text":"70191529 - 2017 - Performance of Irikura recipe rupture model generator in earthquake ground motion simulations with Graves and Pitarka hybrid approach","interactions":[],"lastModifiedDate":"2017-10-17T11:35:35","indexId":"70191529","displayToPublicDate":"2017-10-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3208,"text":"Pure and Applied Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Performance of Irikura recipe rupture model generator in earthquake ground motion simulations with Graves and Pitarka hybrid approach","docAbstract":"<p>We analyzed the performance of the Irikura and Miyake (Pure and Applied Geophysics 168(2011):85–104, 2011) (IM2011) asperity-based kinematic rupture model generator, as implemented in the hybrid broadband ground motion simulation methodology of Graves and Pitarka (Bulletin of the Seismological Society of America 100(5A):2095–2123, 2010), for simulating ground motion from crustal earthquakes of intermediate size. The primary objective of our study is to investigate the transportability of IM2011 into the framework used by the Southern California Earthquake Center broadband simulation platform. In our analysis, we performed broadband (0–20 Hz) ground motion simulations for a suite of M6.7 crustal scenario earthquakes in a hard rock seismic velocity structure using rupture models produced with both IM2011 and the rupture generation method of Graves and Pitarka (Bulletin of the Seismological Society of America, 2016) (GP2016). The level of simulated ground motions for the two approaches compare favorably with median estimates obtained from the 2014 Next Generation Attenuation-West2 Project (NGA-West2) ground motion prediction equations (GMPEs) over the frequency band 0.1–10 Hz and for distances out to 22 km from the fault. We also found that, compared to GP2016, IM2011 generates ground motion with larger variability, particularly at near-fault distances (&lt;12 km) and at long periods (&gt;1 s). For this specific scenario, the largest systematic difference in ground motion level for the two approaches occurs in the period band 1–3 s where the IM2011 motions are about 20–30% lower than those for GP2016. We found that increasing the rupture speed by 20% on the asperities in IM2011 produced ground motions in the 1–3 s bandwidth that are in much closer agreement with the GMPE medians and similar to those obtained with GP2016. The potential implications of this modification for other rupture mechanisms and magnitudes are not yet fully understood, and this topic is the subject of ongoing study. We concluded that IM2011 rupture generator performs well in ground motion simulations using Graves and Pitarka hybrid method. Therefore, we recommend it to be considered for inclusion into the framework used by the Southern California Earthquake Center broadband simulation platform.</p>","language":"English","publisher":"Springer","doi":"10.1007/s00024-017-1504-3","usgsCitation":"Pitarka, A., Graves, R., Irikura, K., Miyake, H., and Rodgers, A., 2017, Performance of Irikura recipe rupture model generator in earthquake ground motion simulations with Graves and Pitarka hybrid approach: Pure and Applied Geophysics, v. 174, no. 9, p. 3537-3555, https://doi.org/10.1007/s00024-017-1504-3.","productDescription":"19 p.","startPage":"3537","endPage":"3555","ipdsId":"IP-083244","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":488726,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00024-017-1504-3","text":"Publisher Index Page"},{"id":346685,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"174","issue":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-28","publicationStatus":"PW","scienceBaseUri":"59e71690e4b05fe04cd33195","contributors":{"authors":[{"text":"Pitarka, Arben","contributorId":184062,"corporation":false,"usgs":false,"family":"Pitarka","given":"Arben","email":"","affiliations":[],"preferred":false,"id":712633,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graves, Robert 0000-0001-9758-453X rwgraves@usgs.gov","orcid":"https://orcid.org/0000-0001-9758-453X","contributorId":140738,"corporation":false,"usgs":true,"family":"Graves","given":"Robert","email":"rwgraves@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":712632,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Irikura, Kojiro","contributorId":197122,"corporation":false,"usgs":false,"family":"Irikura","given":"Kojiro","email":"","affiliations":[],"preferred":false,"id":712634,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miyake, Hiroe","contributorId":197123,"corporation":false,"usgs":false,"family":"Miyake","given":"Hiroe","email":"","affiliations":[],"preferred":false,"id":712635,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rodgers, Arthur","contributorId":197124,"corporation":false,"usgs":false,"family":"Rodgers","given":"Arthur","affiliations":[],"preferred":false,"id":712636,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70192157,"text":"70192157 - 2017 - Evaluating a kinematic method for generating broadband ground motions for great subduction zone earthquakes: Application to the 2003  Mw 8.3 Tokachi‐Oki earthquake","interactions":[],"lastModifiedDate":"2017-10-23T14:06:59","indexId":"70192157","displayToPublicDate":"2017-10-01T00:00:00","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}},"displayTitle":"Evaluating a kinematic method for generating broadband ground motions for great subduction zone earthquakes: Application to the 2003  M<sub>w</sub> 8.3 Tokachi‐Oki earthquake","title":"Evaluating a kinematic method for generating broadband ground motions for great subduction zone earthquakes: Application to the 2003  Mw 8.3 Tokachi‐Oki earthquake","docAbstract":"<p><span>We compare broadband synthetic seismograms with recordings of the 2003&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-3-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>M</mi><mi mathvariant=&quot;normal&quot;>w</mi></msub></math>\"><span id=\"MathJax-Span-11\" class=\"math\"><span><span><span id=\"MathJax-Span-12\" class=\"mrow\"><span id=\"MathJax-Span-13\" class=\"msub\"><span><span><span id=\"MathJax-Span-14\" class=\"mi\">M</span></span><span><span id=\"MathJax-Span-15\" class=\"mi\">w</span></span></span></span></span></span></span></span><span class=\"MJX_Assistive_MathML\">Mw</span></span></span><span>&nbsp;8.3 Tokachi‐Oki earthquake to evaluate a compound rupture model, in which slip on the fault consists of multiple high‐stress‐drop asperities superimposed on a background slip distribution with longer rise times. Low‐frequency synthetics (</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-4-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo xmlns=&quot;&quot; rspace=&quot;0em&quot;>&amp;lt;</mo><mn xmlns=&quot;&quot;>1</mn><mtext xmlns=&quot;&quot;>&amp;#x2009;&amp;#x2009;</mtext><mi xmlns=&quot;&quot;>Hz</mi></math>\"><span id=\"MathJax-Span-16\" class=\"math\"><span><span><span id=\"MathJax-Span-17\" class=\"mrow\"><span id=\"MathJax-Span-18\" class=\"mo\">&lt;</span><span id=\"MathJax-Span-19\" class=\"mn\">1</span><span id=\"MathJax-Span-20\" class=\"mtext\">  </span><span id=\"MathJax-Span-21\" class=\"mi\">Hz</span></span></span></span></span><span class=\"MJX_Assistive_MathML\">&lt;1  Hz</span></span></span><span>) are calculated using deterministic, 3D finite‐difference simulations and are combined with high‐frequency (</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-5-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo xmlns=&quot;&quot; rspace=&quot;0em&quot;>&amp;gt;</mo><mn xmlns=&quot;&quot;>1</mn><mtext xmlns=&quot;&quot;>&amp;#x2009;&amp;#x2009;</mtext><mi xmlns=&quot;&quot;>Hz</mi></math>\"><span id=\"MathJax-Span-22\" class=\"math\"><span><span><span id=\"MathJax-Span-23\" class=\"mrow\"><span id=\"MathJax-Span-24\" class=\"mo\">&gt;</span><span id=\"MathJax-Span-25\" class=\"mn\">1</span><span id=\"MathJax-Span-26\" class=\"mtext\">  </span><span id=\"MathJax-Span-27\" class=\"mi\">Hz</span></span></span></span></span><span class=\"MJX_Assistive_MathML\">&gt;1  Hz</span></span></span><span>) stochastic synthetics using a matched filter at 1&nbsp;Hz. We show that this compound rupture model and overall approach accurately reproduces waveform envelopes and observed response spectral accelerations (SAs) from the Tokachi‐Oki event. We find that sufficiently short subfault rise times (i.e.,<span>&nbsp;</span></span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-6-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo xmlns=&quot;&quot;>&amp;lt;</mo><mo xmlns=&quot;&quot;>&amp;#x223C;</mo><mn xmlns=&quot;&quot;>1</mn><mo xmlns=&quot;&quot;>&amp;#x2013;</mo><mn xmlns=&quot;&quot;>2</mn><mtext xmlns=&quot;&quot;>&amp;#x2009;&amp;#x2009;</mtext><mi xmlns=&quot;&quot; mathvariant=&quot;normal&quot;>s</mi></math>\"><span id=\"MathJax-Span-28\" class=\"math\"><span><span><span id=\"MathJax-Span-29\" class=\"mrow\"><span id=\"MathJax-Span-30\" class=\"mo\">&lt;</span><span id=\"MathJax-Span-31\" class=\"mo\">∼</span><span id=\"MathJax-Span-32\" class=\"mn\">1</span><span id=\"MathJax-Span-33\" class=\"mo\">–</span><span id=\"MathJax-Span-34\" class=\"mn\">2</span><span id=\"MathJax-Span-35\" class=\"mtext\">  </span><span id=\"MathJax-Span-36\" class=\"mi\">s</span></span></span></span></span><span class=\"MJX_Assistive_MathML\">&lt;∼1–2  s</span></span></span><span>) are necessary to reproduce energy<span>&nbsp;</span></span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-7-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo xmlns=&quot;&quot;>&amp;#x223C;</mo><mn xmlns=&quot;&quot;>1</mn><mtext xmlns=&quot;&quot;>&amp;#x2009;&amp;#x2009;</mtext><mi xmlns=&quot;&quot;>Hz</mi></math>\"><span id=\"MathJax-Span-37\" class=\"math\"><span><span><span id=\"MathJax-Span-38\" class=\"mrow\"><span id=\"MathJax-Span-39\" class=\"mo\">∼</span><span id=\"MathJax-Span-40\" class=\"mn\">1</span><span id=\"MathJax-Span-41\" class=\"mtext\">  </span><span id=\"MathJax-Span-42\" class=\"mi\">Hz</span></span></span></span></span><span class=\"MJX_Assistive_MathML\">∼1  Hz</span></span></span><span>. This is achieved by either (1)&nbsp;including distinct subevents with short rise times, as may be suggested by the Tokachi‐Oki data, or (2)&nbsp;imposing a fast‐slip velocity over the entire rupture area. We also include a systematic study on the effects of varying several kinematic rupture parameters. We find that simulated strong ground motions are sensitive to the average rupture velocity and coherence of the rupture front, with more coherent ruptures yielding higher response SAs. We also assess the effects of varying the average slip velocity and the character (i.e., area, magnitude, and location) of high‐stress‐drop subevents. Even in the absence of precise constraints on these kinematic rupture parameters, our simulations still reproduce major features in the Tokachi‐Oki earthquake data, supporting its accuracy in modeling future large earthquakes.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120170065","usgsCitation":"Wirth, E.A., Frankel, A.D., and Vidale, J.E., 2017, Evaluating a kinematic method for generating broadband ground motions for great subduction zone earthquakes: Application to the 2003  Mw 8.3 Tokachi‐Oki earthquake: Bulletin of the Seismological Society of America, v. 107, no. 4, p. 1737-1753, https://doi.org/10.1785/0120170065.","productDescription":"17 p.","startPage":"1737","endPage":"1753","ipdsId":"IP-082673","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":347131,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Japan","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              141.9873046875,\n              41.430371882652814\n            ],\n            [\n              144.8272705078125,\n              41.430371882652814\n            ],\n            [\n              144.8272705078125,\n              43.50075243569041\n            ],\n            [\n              141.9873046875,\n              43.50075243569041\n            ],\n            [\n              141.9873046875,\n              41.430371882652814\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"107","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-11","publicationStatus":"PW","scienceBaseUri":"59eeffa4e4b0220bbd988f69","contributors":{"authors":[{"text":"Wirth, Erin A. 0000-0002-8592-4442","orcid":"https://orcid.org/0000-0002-8592-4442","contributorId":197865,"corporation":false,"usgs":true,"family":"Wirth","given":"Erin","email":"","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":714475,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Frankel, Arthur D. 0000-0001-9119-6106 afrankel@usgs.gov","orcid":"https://orcid.org/0000-0001-9119-6106","contributorId":146285,"corporation":false,"usgs":true,"family":"Frankel","given":"Arthur","email":"afrankel@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":714474,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vidale, John E.","contributorId":197866,"corporation":false,"usgs":false,"family":"Vidale","given":"John","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":714476,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70191351,"text":"70191351 - 2017 - Evaluating spatial and temporal relationships between an earthquake cluster near Entiat, central Washington, and the large December 1872 Entiat earthquake","interactions":[],"lastModifiedDate":"2017-12-19T16:50:38","indexId":"70191351","displayToPublicDate":"2017-10-01T00:00:00","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":"Evaluating spatial and temporal relationships between an earthquake cluster near Entiat, central Washington, and the large December 1872 Entiat earthquake","docAbstract":"<p><span>We investigate spatial and temporal relations between an ongoing and prolific seismicity cluster in central Washington, near Entiat, and the 14 December 1872 Entiat earthquake, the largest historic crustal earthquake in Washington. A fault scarp produced by the 1872 earthquake lies within the Entiat cluster; the locations and areas of both the cluster and the estimated 1872 rupture surface are comparable. Seismic intensities and the 1–2&nbsp;m of coseismic displacement suggest a magnitude range between 6.5 and 7.0 for the 1872 earthquake. Aftershock forecast models for (1)&nbsp;the first several hours following the 1872 earthquake, (2)&nbsp;the largest felt earthquakes from 1900 to 1974, and (3)&nbsp;the seismicity within the Entiat cluster from 1976 through 2016 are also consistent with this magnitude range. Based on this aftershock modeling, most of the current seismicity in the Entiat cluster could represent aftershocks of the 1872 earthquake. Other earthquakes, especially those with long recurrence intervals, have long‐lived aftershock sequences, including the&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>M</mi><mi mathvariant=&quot;normal&quot;>w</mi></msub></math>\"><span id=\"MathJax-Span-1\" class=\"math\"><span><span><span id=\"MathJax-Span-2\" class=\"mrow\"><span id=\"MathJax-Span-3\" class=\"msub\"><span><span><span id=\"MathJax-Span-4\" class=\"mi\">M</span></span><span><span id=\"MathJax-Span-5\" class=\"mi\">w</span></span></span></span></span></span></span></span><span class=\"MJX_Assistive_MathML\">Mw</span></span></span><span>&nbsp;7.5 1891 Nobi earthquake in Japan, with aftershocks continuing 100 yrs after the mainshock. Although we do not rule out ongoing tectonic deformation in this region, a long‐lived aftershock sequence can account for these observations.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120170113","usgsCitation":"Brocher, T.M., Blakely, R.J., and Sherrod, B.L., 2017, Evaluating spatial and temporal relationships between an earthquake cluster near Entiat, central Washington, and the large December 1872 Entiat earthquake: Bulletin of the Seismological Society of America, v. 107, no. 5, p. 2380-2393, https://doi.org/10.1785/0120170113.","productDescription":"14 p.","startPage":"2380","endPage":"2393","ipdsId":"IP-085412","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":346431,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -120.5,\n              47.5\n            ],\n            [\n              -119.75,\n              47.5\n            ],\n            [\n              -119.75,\n              48\n            ],\n            [\n              -120.5,\n              48\n            ],\n            [\n              -120.5,\n              47.5\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"107","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-25","publicationStatus":"PW","scienceBaseUri":"59d7449de4b05fe04cc7e301","contributors":{"authors":[{"text":"Brocher, Thomas M. 0000-0002-9740-839X brocher@usgs.gov","orcid":"https://orcid.org/0000-0002-9740-839X","contributorId":262,"corporation":false,"usgs":true,"family":"Brocher","given":"Thomas","email":"brocher@usgs.gov","middleInitial":"M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":712040,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blakely, Richard J. 0000-0003-1701-5236 blakely@usgs.gov","orcid":"https://orcid.org/0000-0003-1701-5236","contributorId":1540,"corporation":false,"usgs":true,"family":"Blakely","given":"Richard","email":"blakely@usgs.gov","middleInitial":"J.","affiliations":[{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":712041,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sherrod, Brian L. 0000-0002-4492-8631 bsherrod@usgs.gov","orcid":"https://orcid.org/0000-0002-4492-8631","contributorId":2834,"corporation":false,"usgs":true,"family":"Sherrod","given":"Brian","email":"bsherrod@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":712042,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70191512,"text":"70191512 - 2017 - Using dissolved carbon dioxide to alter the behavior of invasive round goby","interactions":[],"lastModifiedDate":"2017-10-16T09:48:44","indexId":"70191512","displayToPublicDate":"2017-10-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2655,"text":"Management of Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Using dissolved carbon dioxide to alter the behavior of invasive round goby","docAbstract":"<p><span>Fisheries managers need effective methods to limit the spread of invasive round goby&nbsp;</span><i>Neogobius melanostomus</i><span><span>&nbsp;</span>in North America. Elevating carbon dioxide (CO</span><sub><span class=\"style1\">2</span></sub><span>) in water at pinch points of rivers (e.g., inside locks) is one approach showing potential to deter the passage of invasive fishes, such as bigheaded carps<span>&nbsp;</span></span><i>Hypophthalmichthys</i><span><span>&nbsp;</span>spp., but the effectiveness of this method to alter round goby behavior has not been determined. The goal for this study was to determine CO</span><sub><span class=\"style1\">2</span></sub><span><span>&nbsp;</span>concentrations that alter round goby behavior across a range of water temperatures. Free-swimming avoidance (voluntary response) and loss of equilibrium (involuntary response) were quantified by exposing round goby to increasing CO</span><sub><span class=\"style1\">2</span></sub><span><span>&nbsp;</span>concentrations at 5, 15, and 25 °C using a shuttle box choice arena and static tank. Water chemistry was measured concurrent with behavioral endpoints and showed that round goby avoided a threshold of 99–169 mg/L CO</span><sub>2</sub><span>(79,000–178,000 µatm) and lost equilibrium at 197–280 mg/L CO</span><sub><span class=\"style1\">2</span></sub><span><span>&nbsp;</span>(163,000–303,000 µatm). Approximately 50% lower CO</span><sub><span class=\"style1\">2</span></sub><span><span>&nbsp;</span>concentrations were found to modify behavior at 5 °C relative to 25 °C, suggesting greater effectiveness at lower water temperatures. We conclude that CO</span><sub><span class=\"style1\">2</span></sub><span><span>&nbsp;</span>modified round goby behavior and concentrations determined in this study are intended to guide field testing of CO</span><sub><span class=\"style1\">2</span></sub><span><span>&nbsp;</span>as an invasive fish deterrent.</span></p>","language":"English","publisher":"Regional Euro-Asian Biological Invasions Centre","doi":"10.3391/mbi.2017.8.4.12","usgsCitation":"Cupp, A.R., Tix, J., Smerud, J.R., Erickson, R.A., Fredricks, K.T., Amberg, J., Suski, C., and Wakeman, R., 2017, Using dissolved carbon dioxide to alter the behavior of invasive round goby: Management of Biological Invasions, v. 8, no. 4, p. 567-574, https://doi.org/10.3391/mbi.2017.8.4.12.","productDescription":"8 p.","startPage":"567","endPage":"574","ipdsId":"IP-082653","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":469544,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/mbi.2017.8.4.12","text":"Publisher Index Page"},{"id":346620,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59e5c51be4b05fe04cd1c9d8","contributors":{"authors":[{"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":712539,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tix, John 0000-0002-9531-5624 jtix@usgs.gov","orcid":"https://orcid.org/0000-0002-9531-5624","contributorId":197014,"corporation":false,"usgs":true,"family":"Tix","given":"John","email":"jtix@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":712540,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smerud, Justin R. 0000-0003-4385-7437 jrsmerud@usgs.gov","orcid":"https://orcid.org/0000-0003-4385-7437","contributorId":5031,"corporation":false,"usgs":true,"family":"Smerud","given":"Justin","email":"jrsmerud@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":712541,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":712542,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fredricks, Kim T. 0000-0003-2363-7891 kfredricks@usgs.gov","orcid":"https://orcid.org/0000-0003-2363-7891","contributorId":173994,"corporation":false,"usgs":true,"family":"Fredricks","given":"Kim","email":"kfredricks@usgs.gov","middleInitial":"T.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":712543,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":712544,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Suski, C. D.","contributorId":190151,"corporation":false,"usgs":false,"family":"Suski","given":"C.","middleInitial":"D.","affiliations":[],"preferred":false,"id":712545,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wakeman, Robert","contributorId":197015,"corporation":false,"usgs":false,"family":"Wakeman","given":"Robert","email":"","affiliations":[],"preferred":false,"id":712546,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70192072,"text":"70192072 - 2017 - Accounting for imperfect detection of groups and individuals when estimating abundance","interactions":[],"lastModifiedDate":"2017-10-19T15:48:56","indexId":"70192072","displayToPublicDate":"2017-10-01T00:00:00","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":"Accounting for imperfect detection of groups and individuals when estimating abundance","docAbstract":"<p><span>If animals are independently detected during surveys, many methods exist for estimating animal abundance despite detection probabilities &lt;1. Common estimators include double-observer models, distance sampling models and combined double-observer and distance sampling models (known as mark-recapture-distance-sampling models; MRDS). When animals reside in groups, however, the assumption of independent detection is violated. In this case, the standard approach is to account for imperfect detection of groups, while assuming that individuals within groups are detected perfectly. However, this assumption is often unsupported. We introduce an abundance estimator for grouped animals when detection of groups is imperfect and group size may be under-counted, but not over-counted. The estimator combines an MRDS model with an N-mixture model to account for imperfect detection of individuals. The new MRDS-Nmix model requires the same data as an MRDS model (independent detection histories, an estimate of distance to transect, and an estimate of group size), plus a second estimate of group size provided by the second observer. We extend the model to situations in which detection of individuals within groups declines with distance. We simulated 12 data sets and used Bayesian methods to compare the performance of the new MRDS-Nmix model to an MRDS model. Abundance estimates generated by the MRDS-Nmix model exhibited minimal bias and nominal coverage levels. In contrast, MRDS abundance estimates were biased low and exhibited poor coverage. Many species of conservation interest reside in groups and could benefit from an estimator that better accounts for imperfect detection. Furthermore, the ability to relax the assumption of perfect detection of individuals within detected groups may allow surveyors to re-allocate resources toward detection of new groups instead of extensive surveys of known groups. We believe the proposed estimator is feasible because the only additional field data required are a second estimate of group size.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.3284","usgsCitation":"Clement, M.J., Converse, S.J., and Royle, J., 2017, Accounting for imperfect detection of groups and individuals when estimating abundance: Ecology and Evolution, v. 7, no. 18, p. 7304-7310, https://doi.org/10.1002/ece3.3284.","productDescription":"7 p.","startPage":"7304","endPage":"7310","ipdsId":"IP-086061","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":469478,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.3284","text":"Publisher Index Page"},{"id":347004,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"18","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-08","publicationStatus":"PW","scienceBaseUri":"59e9b992e4b05fe04cd65c51","contributors":{"authors":[{"text":"Clement, Matthew J. mclement@usgs.gov","contributorId":5278,"corporation":false,"usgs":true,"family":"Clement","given":"Matthew","email":"mclement@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":714185,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":173772,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":714063,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":138865,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":714064,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70193556,"text":"70193556 - 2017 - Ecological impacts of winter water level drawdowns on lake littoral zones: A review","interactions":[],"lastModifiedDate":"2017-11-14T12:48:00","indexId":"70193556","displayToPublicDate":"2017-10-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":873,"text":"Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Ecological impacts of winter water level drawdowns on lake littoral zones: A review","docAbstract":"<p><span>Freshwater littoral zones harbor diverse ecological communities and serve numerous ecosystem functions that are controlled, in part, by natural water level fluctuations. However, human alteration of lake hydrologic regimes beyond natural fluctuations threaten littoral zone ecological integrity. One type of hydrologic alteration in lakes is winter water level drawdowns, which are frequently employed for hydropower, flood control, and macrophyte control, among other purposes. Here, we synthesize the abiotic and biotic responses to annual and novel winter water level drawdowns in littoral zones of lakes and reservoirs. The dewatering, freezing, and increased erosion of exposed lakebeds drive changes in the littoral zone. Shoreline-specific physicochemical conditions such as littoral slope and shoreline exposure further induce modifications. Loss of fine sediment decreases nutrient availability over time, but desiccation may promote a temporary nutrient pulse upon re-inundation. Annual winter drawdowns can decrease taxonomic richness of macrophytes and benthic invertebrates and shift assemblage composition to favor taxa with r-selected life history strategies and with functional traits resistant to direct and indirect drawdown effects. Fish assemblages, though less directly affected by winter drawdowns (except where there is critically low dissolved oxygen), experience negative effects via indirect pathways like decreased food resources and spawning habitat. We identify eight general research gaps to guide future research that could improve our understanding about the complex effects of winter drawdowns on littoral zone ecology.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s00027-017-0549-9","usgsCitation":"Roy, A.H., 2017, Ecological impacts of winter water level drawdowns on lake littoral zones: A review: Aquatic Sciences, v. 79, no. 4, p. 803-824, https://doi.org/10.1007/s00027-017-0549-9.","productDescription":"22 p.","startPage":"803","endPage":"824","ipdsId":"IP-085344","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":469482,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00027-017-0549-9","text":"Publisher Index Page"},{"id":348793,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"79","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-06","publicationStatus":"PW","scienceBaseUri":"5a60fb3ae4b06e28e9c22e20","contributors":{"authors":[{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":719355,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70193536,"text":"70193536 - 2017 - Development of a foraging model framework to reliably estimate daily food consumption by young fishes","interactions":[],"lastModifiedDate":"2017-11-14T13:31:59","indexId":"70193536","displayToPublicDate":"2017-10-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Development of a foraging model framework to reliably estimate daily food consumption by young fishes","docAbstract":"<p><span>We developed a foraging model for young fishes that incorporates handling and digestion rate to estimate daily food consumption. Feeding trials were used to quantify functional feeding response, satiation, and gut evacuation rate. Once parameterized, the foraging model was then applied to evaluate effects of prey type, prey density, water temperature, and fish size on daily feeding rate by age-0 (19–70 mm) pallid sturgeon (</span><i>Scaphirhynchus albus</i><span>). Prey consumption was positively related to prey density (for fish &gt;30 mm) and water temperature, but negatively related to prey size and the presence of sand substrate. Model evaluation results revealed good agreement between observed estimates of daily consumption and those predicted by the model (</span><i>r</i><sup>2</sup><span><span>&nbsp;</span>= 0.95). Model simulations showed that fish feeding on Chironomidae or Ephemeroptera larvae were able to gain mass, whereas fish feeding solely on zooplankton lost mass under most conditions. By accounting for satiation and digestive processes in addition to handling time and prey density, the model provides realistic estimates of daily food consumption that can prove useful for evaluating rearing conditions for age-0 fishes.</span></p>","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2016-0331","usgsCitation":"Deslauriers, D., Rosburg, A.J., and Chipps, S.R., 2017, Development of a foraging model framework to reliably estimate daily food consumption by young fishes: Canadian Journal of Fisheries and Aquatic Sciences, v. 74, no. 10, p. 1668-1681, https://doi.org/10.1139/cjfas-2016-0331.","productDescription":"14 p.","startPage":"1668","endPage":"1681","ipdsId":"IP-084925","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":469490,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2016-0331","text":"External Repository"},{"id":348836,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"74","issue":"10","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb3ae4b06e28e9c22e26","contributors":{"authors":[{"text":"Deslauriers, David","contributorId":187586,"corporation":false,"usgs":false,"family":"Deslauriers","given":"David","email":"","affiliations":[],"preferred":false,"id":722043,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosburg, Alex J.","contributorId":200357,"corporation":false,"usgs":false,"family":"Rosburg","given":"Alex","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":722044,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chipps, Steven R. 0000-0001-6511-7582 steve_chipps@usgs.gov","orcid":"https://orcid.org/0000-0001-6511-7582","contributorId":2243,"corporation":false,"usgs":true,"family":"Chipps","given":"Steven","email":"steve_chipps@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":719301,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70193030,"text":"70193030 - 2017 - Prey partitioning and use of insects by juvenile sockeye salmon and a potential competitor, threespine stickleback, in Afognak Lake, Alaska","interactions":[],"lastModifiedDate":"2017-11-07T11:18:10","indexId":"70193030","displayToPublicDate":"2017-10-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"title":"Prey partitioning and use of insects by juvenile sockeye salmon and a potential competitor, threespine stickleback, in Afognak Lake, Alaska","docAbstract":"<p><span>Freshwater growth of juvenile sockeye salmon (</span><i>Oncorhynchus nerka</i><span>) depends upon the quality and quantity of prey and interactions with potential competitors in the foraging environment. To a large extent, knowledge about the ecology of lake-rearing juvenile sockeye salmon has emerged from studies of commercially important runs returning to deep nursery lakes, yet information from shallow nursery lakes (mean depth&nbsp;≤&nbsp;10&nbsp;m) is limited. We examined seasonal and ontogenetic variation in diets of juvenile sockeye salmon (</span><i>N</i><span>&nbsp;=&nbsp;219, 30–85&nbsp;mm) and an abundant potential competitor, threespine stickleback (</span><i>Gasterosteus aculeatus</i><span>;</span><i><span>&nbsp;</span>N</i><span>&nbsp;=&nbsp;198, 42–67&nbsp;mm), to understand their foraging ecology and potential trophic interactions in a shallow Alaska lake. This study revealed that adult insects made up 74% of all sockeye salmon diets by weight and were present in 98% of all stomachs in Afognak Lake during the summer of 2013. Diets varied temporally for all fishes, but small sockeye salmon (&lt;60&nbsp;mm) showed a distinct shift in consumption from zooplankton in early summer to adult insects in late summer. We found significant differences in diet composition between sockeye salmon and threespine stickleback and the origin of their prey indicated that they also separated their use of habitat on a fine scale; however, the two species showed overlap in size selectivity of zooplankton prey. Considering that aquatic insects can be a primary resource for juvenile sockeye salmon in Afognak Lake, we encourage the development of nursery lake carrying capacity models that include aquatic insects as a prey source for sockeye salmon.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/eff.12302","usgsCitation":"Richardson, N., Beaudreau, A.H., Wipfli, M.S., and Finkle, H., 2017, Prey partitioning and use of insects by juvenile sockeye salmon and a potential competitor, threespine stickleback, in Afognak Lake, Alaska: Ecology of Freshwater Fish, v. 26, no. 4, p. 586-601, https://doi.org/10.1111/eff.12302.","productDescription":"16 p.","startPage":"586","endPage":"601","ipdsId":"IP-077021","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":348357,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Afognak Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -152.9894256591797,\n              58.08677049395305\n            ],\n            [\n              -152.85261154174805,\n              58.08677049395305\n            ],\n            [\n              -152.85261154174805,\n              58.13682719052186\n            ],\n            [\n              -152.9894256591797,\n              58.13682719052186\n            ],\n            [\n              -152.9894256591797,\n              58.08677049395305\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"26","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-25","publicationStatus":"PW","scienceBaseUri":"5a07e873e4b09af898c8cb6e","contributors":{"authors":[{"text":"Richardson, Natura","contributorId":198967,"corporation":false,"usgs":false,"family":"Richardson","given":"Natura","email":"","affiliations":[],"preferred":false,"id":717710,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beaudreau, Anne H.","contributorId":198968,"corporation":false,"usgs":false,"family":"Beaudreau","given":"Anne","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":717711,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wipfli, Mark S. 0000-0002-4856-6068 mwipfli@usgs.gov","orcid":"https://orcid.org/0000-0002-4856-6068","contributorId":1425,"corporation":false,"usgs":true,"family":"Wipfli","given":"Mark","email":"mwipfli@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":717709,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Finkle, Heather","contributorId":198969,"corporation":false,"usgs":false,"family":"Finkle","given":"Heather","email":"","affiliations":[],"preferred":false,"id":717712,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70193035,"text":"70193035 - 2017 - Modeling watershed-scale impacts of stormwater management with traditional versus low impact development design","interactions":[],"lastModifiedDate":"2017-11-20T16:56:01","indexId":"70193035","displayToPublicDate":"2017-10-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Modeling watershed-scale impacts of stormwater management with traditional versus low impact development design","docAbstract":"<p><span>Stormwater runoff and associated pollutants from urban areas in the greater Chesapeake Bay Watershed (CBW) impair local streams and downstream ecosystems, despite urbanized land comprising only 7% of the CBW area. More recently, stormwater best management practices (BMPs) have been implemented in a low impact development (LID) manner to treat stormwater runoff closer to its source. This approach included the development of a novel BMP model to compare traditional and LID design, pioneering the use of comprehensively digitized storm sewer infrastructure and BMP design connectivity with spatial patterns in a geographic information system at the watershed scale. The goal was to compare total watershed pollutant removal efficiency in two study watersheds with differing spatial patterns of BMP design (traditional and LID), by quantifying the improved water quality benefit of LID BMP design. An estimate of uncertainty was included in the modeling framework by using ranges for BMP pollutant removal efficiencies that were based on the literature. Our model, using Monte Carlo analysis, predicted that the LID watershed removed approximately 78&nbsp;kg more nitrogen, 3&nbsp;kg more phosphorus, and 1,592&nbsp;kg more sediment per square kilometer as compared with the traditional watershed on an annual basis. Our research provides planners a valuable model to prioritize watersheds for BMP design based on model results or in optimizing BMP selection.</span></p>","language":"English","publisher":"American Water Resources Association","doi":"10.1111/1752-1688.12559","usgsCitation":"Sparkman, S.A., Hogan, D.M., Hopkins, K.G., and Loperfido, J.V., 2017, Modeling watershed-scale impacts of stormwater management with traditional versus low impact development design: Journal of the American Water Resources Association, v. 53, no. 5, p. 1081-1094, https://doi.org/10.1111/1752-1688.12559.","productDescription":"8 p.","startPage":"1081","endPage":"1094","ipdsId":"IP-079154","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":349167,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","county":"Montgomery County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-77.182,39.3481],[-77.185,39.3423],[-77.1827,39.3341],[-77.1732,39.3205],[-77.1673,39.3127],[-77.1614,39.3077],[-77.1549,39.3023],[-77.1442,39.2973],[-77.1407,39.2932],[-77.1371,39.2864],[-77.1377,39.2832],[-77.133,39.2782],[-77.133,39.2723],[-77.1301,39.2709],[-77.1194,39.27],[-77.1135,39.2659],[-77.1034,39.2668],[-77.0779,39.2585],[-77.0666,39.2535],[-77.0631,39.2463],[-77.0607,39.2399],[-77.0483,39.2385],[-77.0353,39.2257],[-77.0288,39.218],[-77.0188,39.2112],[-77.0134,39.2084],[-77.0111,39.2053],[-77.0111,39.2003],[-77.0111,39.1976],[-77.0111,39.1953],[-77.007,39.193],[-77.007,39.1921],[-77.0052,39.1894],[-77.0052,39.1876],[-77.0064,39.1862],[-77.0077,39.1839],[-77.0082,39.1826],[-77.0059,39.1812],[-77.0053,39.1794],[-77.0059,39.179],[-77.0059,39.1771],[-77.0041,39.1762],[-76.9994,39.1758],[-76.9988,39.1758],[-76.9988,39.1748],[-76.9988,39.1735],[-77,39.1703],[-76.9965,39.1667],[-76.9882,39.1666],[-76.9846,39.1653],[-76.9763,39.163],[-76.9728,39.162],[-76.9722,39.1598],[-76.9734,39.1553],[-76.9752,39.1525],[-76.9734,39.1516],[-76.9693,39.1498],[-76.9634,39.1489],[-76.9581,39.1461],[-76.9551,39.1456],[-76.9527,39.1461],[-76.951,39.1452],[-76.9504,39.1438],[-76.951,39.1425],[-76.9516,39.1402],[-76.9528,39.1384],[-76.9564,39.1375],[-76.9581,39.1371],[-76.9475,39.1311],[-76.9421,39.1334],[-76.938,39.1342],[-76.935,39.1351],[-76.9332,39.1379],[-76.932,39.1378],[-76.9273,39.1378],[-76.9249,39.1351],[-76.9184,39.1319],[-76.9167,39.131],[-76.9119,39.1282],[-76.9031,39.1268],[-76.8971,39.1282],[-76.8923,39.1309],[-76.8882,39.1317],[-76.9535,39.0437],[-76.9655,39.0265],[-76.9978,38.9827],[-77.0085,38.9696],[-77.0415,38.9951],[-77.0445,38.9928],[-77.054,38.9856],[-77.0546,38.9851],[-77.0897,38.9581],[-77.1205,38.9337],[-77.1229,38.936],[-77.1234,38.9365],[-77.1258,38.9391],[-77.1279,38.9411],[-77.1294,38.9423],[-77.1308,38.9438],[-77.1323,38.9455],[-77.1341,38.9482],[-77.1343,38.9488],[-77.1352,38.9507],[-77.1361,38.9523],[-77.1376,38.9546],[-77.1409,38.958],[-77.1413,38.9584],[-77.1455,38.9622],[-77.1472,38.9636],[-77.1488,38.9646],[-77.1548,38.9674],[-77.1553,38.9674],[-77.16,38.9678],[-77.1624,38.9678],[-77.1702,38.9682],[-77.1731,38.9682],[-77.185,38.9684],[-77.1877,38.9685],[-77.1885,38.9685],[-77.1902,38.9685],[-77.192,38.9688],[-77.1949,38.9692],[-77.2008,38.9711],[-77.205,38.9729],[-77.2073,38.9738],[-77.2114,38.9748],[-77.2161,38.9753],[-77.2203,38.9754],[-77.2235,38.9757],[-77.2257,38.9761],[-77.2271,38.9767],[-77.2345,38.9798],[-77.2401,38.9839],[-77.2447,38.9868],[-77.2482,38.9918],[-77.2493,38.9966],[-77.2489,39.0007],[-77.2485,39.0027],[-77.2478,39.0058],[-77.2471,39.0067],[-77.2467,39.0083],[-77.2463,39.0093],[-77.245,39.0124],[-77.2433,39.0148],[-77.2427,39.0175],[-77.2426,39.0198],[-77.2433,39.0233],[-77.2457,39.026],[-77.2483,39.0281],[-77.2508,39.0295],[-77.2521,39.0301],[-77.2551,39.031],[-77.2598,39.0324],[-77.2635,39.0333],[-77.2676,39.0342],[-77.2706,39.0348],[-77.2741,39.0367],[-77.2746,39.037],[-77.2787,39.0397],[-77.2829,39.0424],[-77.2882,39.0461],[-77.2891,39.0467],[-77.2944,39.0502],[-77.297,39.0517],[-77.2989,39.0524],[-77.3048,39.0546],[-77.3064,39.055],[-77.3114,39.0564],[-77.3202,39.0593],[-77.3267,39.061],[-77.3273,39.0611],[-77.3314,39.0617],[-77.3334,39.062],[-77.3361,39.0623],[-77.3439,39.0629],[-77.3444,39.0629],[-77.3464,39.0629],[-77.3545,39.063],[-77.3687,39.0637],[-77.3823,39.0644],[-77.3935,39.066],[-77.4073,39.0685],[-77.4096,39.0687],[-77.4165,39.0695],[-77.428,39.0707],[-77.4372,39.0717],[-77.4409,39.0718],[-77.4431,39.0718],[-77.449,39.0719],[-77.4532,39.0729],[-77.4547,39.0739],[-77.4564,39.0752],[-77.4606,39.0794],[-77.4624,39.0821],[-77.4647,39.087],[-77.4651,39.0878],[-77.4669,39.0903],[-77.4703,39.0954],[-77.4749,39.1006],[-77.4813,39.1079],[-77.4847,39.111],[-77.4872,39.1121],[-77.489,39.1129],[-77.4899,39.1132],[-77.4935,39.1143],[-77.4958,39.1152],[-77.4973,39.1156],[-77.4993,39.1162],[-77.5017,39.1167],[-77.504,39.1174],[-77.5065,39.1182],[-77.5089,39.119],[-77.5104,39.1196],[-77.5176,39.1238],[-77.5199,39.1265],[-77.5204,39.1274],[-77.5221,39.1302],[-77.5238,39.1339],[-77.5243,39.1363],[-77.5246,39.1387],[-77.5246,39.1428],[-77.5228,39.1474],[-77.521,39.1529],[-77.5192,39.1586],[-77.5169,39.1654],[-77.5151,39.1704],[-77.514,39.1723],[-77.5128,39.1736],[-77.511,39.1758],[-77.5104,39.1763],[-77.508,39.1777],[-77.5044,39.1799],[-77.4994,39.1815],[-77.4962,39.1825],[-77.4928,39.1837],[-77.4909,39.1843],[-77.488,39.1854],[-77.4831,39.1872],[-77.4789,39.189],[-77.476,39.1908],[-77.4736,39.1935],[-77.4734,39.1941],[-77.4728,39.1969],[-77.4727,39.1997],[-77.4727,39.2028],[-77.4718,39.2067],[-77.4706,39.2085],[-77.469,39.2102],[-77.4676,39.2117],[-77.4623,39.2153],[-77.4611,39.2162],[-77.4593,39.2176],[-77.4575,39.2198],[-77.4468,39.2248],[-77.2839,39.2999],[-77.182,39.3481]]]},\"properties\":{\"name\":\"Montgomery\",\"state\":\"MD\"}}]}","volume":"53","issue":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-13","publicationStatus":"PW","scienceBaseUri":"5a60fb44e4b06e28e9c22e94","contributors":{"authors":[{"text":"Sparkman, Stephanie A. 0000-0001-9208-507X ssparkman@usgs.gov","orcid":"https://orcid.org/0000-0001-9208-507X","contributorId":5482,"corporation":false,"usgs":true,"family":"Sparkman","given":"Stephanie","email":"ssparkman@usgs.gov","middleInitial":"A.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":717722,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hogan, Dianna M. 0000-0003-1492-4514 dhogan@usgs.gov","orcid":"https://orcid.org/0000-0003-1492-4514","contributorId":131137,"corporation":false,"usgs":true,"family":"Hogan","given":"Dianna","email":"dhogan@usgs.gov","middleInitial":"M.","affiliations":[{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":717724,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hopkins, Kristina G. 0000-0003-1699-9384 khopkins@usgs.gov","orcid":"https://orcid.org/0000-0003-1699-9384","contributorId":195604,"corporation":false,"usgs":true,"family":"Hopkins","given":"Kristina","email":"khopkins@usgs.gov","middleInitial":"G.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":717725,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Loperfido, J. V. 0000-0003-3328-2801 jloperfido@usgs.gov","orcid":"https://orcid.org/0000-0003-3328-2801","contributorId":195605,"corporation":false,"usgs":false,"family":"Loperfido","given":"J.","email":"jloperfido@usgs.gov","middleInitial":"V.","affiliations":[],"preferred":false,"id":717723,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70191679,"text":"70191679 - 2017 - Large-scale modeled contemporary and future water temperature estimates for 10774 Midwestern U.S. Lakes","interactions":[],"lastModifiedDate":"2017-10-17T16:24:36","indexId":"70191679","displayToPublicDate":"2017-10-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3907,"text":"Scientific Data","active":true,"publicationSubtype":{"id":10}},"title":"Large-scale modeled contemporary and future water temperature estimates for 10774 Midwestern U.S. Lakes","docAbstract":"<p><span>Climate change has already influenced lake temperatures globally, but understanding future change is challenging. The response of lakes to changing climate drivers is complex due to the nature of lake-atmosphere coupling, ice cover, and stratification. To better understand the diversity of lake responses to climate change and give managers insight on individual lakes, we modelled daily water temperature profiles for 10,774 lakes in Michigan, Minnesota, and Wisconsin for contemporary (1979–2015) and future (2020–2040 and 2080–2100) time periods with climate models based on the Representative Concentration Pathway 8.5, the worst-case emission scenario. In addition to lake-specific daily simulated temperatures, we derived commonly used, ecologically relevant annual metrics of thermal conditions for each lake. We include all supporting lake-specific model parameters, meteorological drivers, and archived code for the model and derived metric calculations. This unique dataset offers landscape-level insight into the impact of climate change on lakes.</span></p>","language":"English","publisher":"Nature","doi":"10.1038/sdata.2017.53","usgsCitation":"Winslow, L.A., Hansen, G.J., Read, J.S., and Notaro, M., 2017, Large-scale modeled contemporary and future water temperature estimates for 10774 Midwestern U.S. Lakes: Scientific Data, v. 4, p. 1-11, https://doi.org/10.1038/sdata.2017.53.","productDescription":"Article number: 170053; 11 p.","startPage":"1","endPage":"11","ipdsId":"IP-079867","costCenters":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"links":[{"id":482062,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/sdata.2017.53","text":"Publisher Index Page"},{"id":346755,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, Minnesota, Wisconsin","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-88.684434,48.115785],[-88.447236,48.182916],[-89.022736,47.858532],[-89.255202,47.876102],[-88.684434,48.115785]]],[[[-83.880387,41.720089],[-86.824828,41.76024],[-86.24971,42.480212],[-86.226305,42.988284],[-86.540916,43.633158],[-86.25395,44.64808],[-86.066745,44.905685],[-85.780439,44.977932],[-85.540497,45.210169],[-85.641652,44.810816],[-85.520205,44.960347],[-85.477423,44.813781],[-85.355478,45.282774],[-84.91585,45.393115],[-85.110884,45.526285],[-84.94565,45.708621],[-85.011433,45.757962],[-84.204218,45.627116],[-84.095905,45.497298],[-83.488826,45.355872],[-83.316118,45.141958],[-83.435822,45.000012],[-83.277213,44.7167],[-83.335248,44.357995],[-83.890145,43.934672],[-83.909479,43.672622],[-83.618602,43.628891],[-83.227093,43.981003],[-82.915976,44.070503],[-82.617955,43.768596],[-82.423086,42.988728],[-82.509935,42.637294],[-82.648776,42.550401],[-82.630922,42.64211],[-82.780817,42.652232],[-83.431103,41.757457],[-83.880387,41.720089]]],[[[-90.418136,46.566094],[-88.982483,46.99883],[-88.400224,47.379551],[-87.816958,47.471998],[-87.730804,47.449112],[-88.349952,47.076377],[-88.462349,46.786711],[-88.167373,46.9588],[-87.915943,46.909508],[-87.619747,46.79821],[-87.366767,46.507303],[-86.850111,46.434114],[-86.188024,46.654008],[-84.964652,46.772845],[-84.969464,46.47629],[-84.177428,46.52692],[-84.097766,46.256512],[-84.247687,46.17989],[-83.931175,46.017871],[-83.63498,46.103953],[-83.49484,45.999541],[-84.345451,45.946569],[-84.656567,46.052654],[-84.820557,45.868293],[-85.047028,46.020603],[-85.528403,46.087121],[-85.663966,45.967013],[-86.278007,45.942057],[-86.687208,45.634253],[-86.532989,45.882665],[-86.92106,45.697868],[-87.018902,45.838886],[-88.027103,44.578992],[-87.943801,44.529693],[-87.428144,44.890738],[-87.021088,45.296541],[-87.73063,43.893862],[-87.910172,43.236634],[-87.800477,42.49192],[-90.614589,42.508053],[-91.078097,42.806526],[-91.177728,43.118733],[-91.062562,43.243165],[-91.217706,43.50055],[-96.453049,43.500415],[-96.452948,45.268925],[-96.835451,45.586129],[-96.587093,45.816445],[-96.559271,46.058272],[-96.789572,46.639079],[-96.851293,47.589264],[-97.139497,48.153108],[-97.108655,48.691484],[-97.238387,48.982631],[-95.153711,48.998903],[-95.153314,49.384358],[-94.974286,49.367738],[-94.555835,48.716207],[-93.741843,48.517347],[-92.984963,48.623731],[-92.634931,48.542873],[-92.698824,48.494892],[-92.341207,48.23248],[-92.066269,48.359602],[-91.542512,48.053268],[-90.88548,48.245784],[-90.703702,48.096009],[-89.489226,48.014528],[-90.735927,47.624343],[-92.058888,46.809938],[-92.025789,46.710839],[-91.781928,46.697604],[-90.880358,46.957661],[-90.78804,46.844886],[-90.920813,46.637432],[-90.418136,46.566094]]],[[[-86.880572,45.331467],[-86.956192,45.351179],[-86.82177,45.427602],[-86.880572,45.331467]]]]},\"properties\":{\"name\":\"Michigan\",\"nation\":\"USA  \"}}]}","volume":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-25","publicationStatus":"PW","scienceBaseUri":"59e7168ee4b05fe04cd33182","contributors":{"authors":[{"text":"Winslow, Luke A. 0000-0002-8602-5510 lwinslow@usgs.gov","orcid":"https://orcid.org/0000-0002-8602-5510","contributorId":5919,"corporation":false,"usgs":true,"family":"Winslow","given":"Luke","email":"lwinslow@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":false,"id":713042,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hansen, Gretchen J. A.","contributorId":131099,"corporation":false,"usgs":false,"family":"Hansen","given":"Gretchen","email":"","middleInitial":"J. A.","affiliations":[{"id":7242,"text":"Wisconsin Department of Natural Resources, Madison, WI, USA","active":true,"usgs":false}],"preferred":false,"id":713043,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Read, Jordan S. 0000-0002-3888-6631 jread@usgs.gov","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":4453,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","email":"jread@usgs.gov","middleInitial":"S.","affiliations":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":713044,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Notaro, Michael","contributorId":197249,"corporation":false,"usgs":false,"family":"Notaro","given":"Michael","email":"","affiliations":[],"preferred":false,"id":713045,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70192666,"text":"70192666 - 2017 - Evaluating and improving count-based population inference: A case study from 31 years of monitoring Sandhill Cranes","interactions":[],"lastModifiedDate":"2017-11-08T15:29:25","indexId":"70192666","displayToPublicDate":"2017-10-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3551,"text":"The Condor","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating and improving count-based population inference: A case study from 31 years of monitoring Sandhill Cranes","docAbstract":"<p><span>Monitoring animal populations can be difficult. Limited resources often force monitoring programs to rely on unadjusted or smoothed counts as an index of abundance. Smoothing counts is commonly done using a moving-average estimator to dampen sampling variation. These indices are commonly used to inform management decisions, although their reliability is often unknown. We outline a process to evaluate the biological plausibility of annual changes in population counts and indices from a typical monitoring scenario and compare results with a hierarchical Bayesian time series (HBTS) model. We evaluated spring and fall counts, fall indices, and model-based predictions for the Rocky Mountain population (RMP) of Sandhill Cranes (</span><i>Antigone canadensis</i><span>) by integrating juvenile recruitment, harvest, and survival into a stochastic stage-based population model. We used simulation to evaluate population indices from the HBTS model and the commonly used 3-yr moving average estimator. We found counts of the RMP to exhibit biologically unrealistic annual change, while the fall population index was largely biologically realistic. HBTS model predictions suggested that the RMP changed little over 31 yr of monitoring, but the pattern depended on assumptions about the observational process. The HBTS model fall population predictions were biologically plausible if observed crane harvest mortality was compensatory up to natural mortality, as empirical evidence suggests. Simulations indicated that the predicted mean of the HBTS model was generally a more reliable estimate of the true population than population indices derived using a moving 3-yr average estimator. Practitioners could gain considerable advantages from modeling population counts using a hierarchical Bayesian autoregressive approach. Advantages would include: (1) obtaining measures of uncertainty; (2) incorporating direct knowledge of the observational and population processes; (3) accommodating missing years of data; and (4) forecasting population size.</span></p>","language":"English","publisher":"American Ornithological Society","doi":"10.1650/CONDOR-16-137.1","usgsCitation":"Gerber, B.D., and Kendall, W., 2017, Evaluating and improving count-based population inference: A case study from 31 years of monitoring Sandhill Cranes: The Condor, v. 119, no. 2, p. 191-206, https://doi.org/10.1650/CONDOR-16-137.1.","productDescription":"16 p.","startPage":"191","endPage":"206","ipdsId":"IP-070023","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":469556,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1650/condor-16-137.1","text":"Publisher Index Page"},{"id":348494,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"119","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a0425b3e4b0dc0b45b45321","contributors":{"authors":[{"text":"Gerber, Brian D.","contributorId":187620,"corporation":false,"usgs":false,"family":"Gerber","given":"Brian","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":721366,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kendall, William L. 0000-0003-0084-9891 wkendall@usgs.gov","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":166709,"corporation":false,"usgs":true,"family":"Kendall","given":"William L.","email":"wkendall@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":716678,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70191792,"text":"70191792 - 2017 - Shifts in an invasive rodent community favoring black rats (Rattus rattus) following restoration of native forest","interactions":[],"lastModifiedDate":"2018-01-08T14:37:38","indexId":"70191792","displayToPublicDate":"2017-10-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Shifts in an invasive rodent community favoring Black rats (<i>Rattus rattus</i>) following restoration of native forest","title":"Shifts in an invasive rodent community favoring black rats (Rattus rattus) following restoration of native forest","docAbstract":"<p><span>One potential, unintended ecological consequence accompanying forest restoration is a shift in invasive animal populations, potentially impacting conservation targets. Eighteen years after initial restoration (ungulate exclusion, invasive plant control, and out planting native species) at a 4 ha site on Maui, Hawai'i, we compared invasive rodent communities in a restored native dry forest and adjacent non-native grassland. Quarterly for 1 year, we trapped rodents on three replicate transects (107 rodent traps) in each habitat type for three consecutive nights. While repeated trapping may have reduced the rat (Black rat,&nbsp;</span><i>Rattus rattus</i><span>) population in the forest, it did not appear to reduce the mouse (House mouse,<span>&nbsp;</span></span><i>Mus musculus</i><span>) population in the grassland. In unrestored grassland, mouse captures outnumbered rat captures 220:1, with mice averaging 54.9 indiv./night versus rats averaging 0.25 indiv./night. In contrast, in restored native forest, rat captures outnumbered mouse captures by nearly 5:1, averaging 9.0 indiv./night versus 1.9 indiv./night for mice. Therefore, relatively recent native forest restoration increased Black rat abundance and also increased their total biomass in the restored ecosystem 36-fold while reducing House mouse biomass 35-fold. Such a community shift is worrisome because Black rats pose a much greater threat than do mice to native birds and plants, perhaps especially to large-seeded tree species. Land managers should be aware that forest restoration (i.e. converting grassland to native forest) can invoke shifts in invasive rodent populations, potentially favoring Black rats. Without intervention, this shift may pose risks for intended conservation targets and modify future forest restoration trajectories.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/rec.12494","usgsCitation":"Shiels, A.B., Medeiros, A.C., and von Allmen, E.I., 2017, Shifts in an invasive rodent community favoring black rats (Rattus rattus) following restoration of native forest: Restoration Ecology, v. 25, no. 5, p. 759-767, https://doi.org/10.1111/rec.12494.","productDescription":"9 p.","startPage":"759","endPage":"767","ipdsId":"IP-080123","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":347244,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"25","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-29","publicationStatus":"PW","scienceBaseUri":"59f05120e4b0220bbd9a1d81","contributors":{"authors":[{"text":"Shiels, Aaron B.","contributorId":197336,"corporation":false,"usgs":false,"family":"Shiels","given":"Aaron","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":713204,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Medeiros, Arthur C. 0000-0002-8090-8451 amedeiros@usgs.gov","orcid":"https://orcid.org/0000-0002-8090-8451","contributorId":2152,"corporation":false,"usgs":true,"family":"Medeiros","given":"Arthur","email":"amedeiros@usgs.gov","middleInitial":"C.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":713203,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"von Allmen, Erica I.","contributorId":197337,"corporation":false,"usgs":false,"family":"von Allmen","given":"Erica","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":713205,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70192569,"text":"70192569 - 2017 - Groundwater declines are linked to changes in Great Plains stream fish assemblages","interactions":[],"lastModifiedDate":"2017-10-26T13:09:59","indexId":"70192569","displayToPublicDate":"2017-10-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3165,"text":"Proceedings of the National Academy of Sciences of the United States of America","active":true,"publicationSubtype":{"id":10}},"title":"Groundwater declines are linked to changes in Great Plains stream fish assemblages","docAbstract":"<p><span>Groundwater pumping for agriculture is a major driver causing declines of global freshwater ecosystems, yet the ecological consequences for stream fish assemblages are rarely quantified. We combined retrospective (1950–2010) and prospective (2011–2060) modeling approaches within a multiscale framework to predict change in Great Plains stream fish assemblages associated with groundwater pumping from the United States High Plains Aquifer. We modeled the relationship between the length of stream receiving water from the High Plains Aquifer and the occurrence of fishes characteristic of small and large streams in the western Great Plains at a regional scale and for six subwatersheds nested within the region. Water development at the regional scale was associated with construction of 154 barriers that fragment stream habitats, increased depth to groundwater and loss of 558 km of stream, and transformation of fish assemblage structure from dominance by large-stream to small-stream fishes. Scaling down to subwatersheds revealed consistent transformations in fish assemblage structure among western subwatersheds with increasing depths to groundwater. Although transformations occurred in the absence of barriers, barriers along mainstem rivers isolate depauperate western fish assemblages from relatively intact eastern fish assemblages. Projections to 2060 indicate loss of an additional 286 km of stream across the region, as well as continued replacement of large-stream fishes by small-stream fishes where groundwater pumping has increased depth to groundwater. Our work illustrates the shrinking of streams and homogenization of Great Plains stream fish assemblages related to groundwater pumping, and we predict similar transformations worldwide where local and regional aquifer depletions occur.</span></p>","language":"English","publisher":"National Academy of Sciences of the United States of America","doi":"10.1073/pnas.1618936114","usgsCitation":"Prekins, J.S., Gido, K.B., Falke, J.A., Fausch, K., Crockett, H., Johnson, E.R., and Sanderson, J., 2017, Groundwater declines are linked to changes in Great Plains stream fish assemblages: Proceedings of the National Academy of Sciences of the United States of America, v. 114, no. 28, p. 7373-7378, https://doi.org/10.1073/pnas.1618936114.","productDescription":"6 p.","startPage":"7373","endPage":"7378","ipdsId":"IP-081390","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":469479,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1073/pnas.1618936114","text":"External Repository"},{"id":347468,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":" Colorado, Kansas, Nebraska","otherGeospatial":"Great Plains","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -104.3701171875,\n              39.13006024213511\n            ],\n            [\n              -99.47021484375,\n              39.13006024213511\n            ],\n            [\n              -99.47021484375,\n              41.19518982948959\n            ],\n            [\n              -104.3701171875,\n              41.19518982948959\n            ],\n            [\n              -104.3701171875,\n              39.13006024213511\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"114","issue":"28","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-26","publicationStatus":"PW","scienceBaseUri":"5a07e873e4b09af898c8cb72","contributors":{"authors":[{"text":"Prekins, Joshuah S.","contributorId":198486,"corporation":false,"usgs":false,"family":"Prekins","given":"Joshuah","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":716235,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gido, Keith B.","contributorId":198487,"corporation":false,"usgs":false,"family":"Gido","given":"Keith","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":716236,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Falke, Jeffrey A. 0000-0002-6670-8250 jfalke@usgs.gov","orcid":"https://orcid.org/0000-0002-6670-8250","contributorId":5195,"corporation":false,"usgs":true,"family":"Falke","given":"Jeffrey","email":"jfalke@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":716234,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fausch, Kurt D. 0000-0001-5825-7560","orcid":"https://orcid.org/0000-0001-5825-7560","contributorId":198488,"corporation":false,"usgs":false,"family":"Fausch","given":"Kurt D.","affiliations":[],"preferred":false,"id":716237,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Crockett, Harry","contributorId":198489,"corporation":false,"usgs":false,"family":"Crockett","given":"Harry","affiliations":[],"preferred":false,"id":716238,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Eric R.","contributorId":198490,"corporation":false,"usgs":false,"family":"Johnson","given":"Eric","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":716239,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sanderson, John","contributorId":172965,"corporation":false,"usgs":false,"family":"Sanderson","given":"John","affiliations":[],"preferred":false,"id":716240,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70192801,"text":"70192801 - 2017 - Presentation and analysis of a worldwide database of earthquake-induced landslide inventories","interactions":[],"lastModifiedDate":"2017-11-29T13:40:16","indexId":"70192801","displayToPublicDate":"2017-10-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2318,"text":"Journal of Geophysical Research F: Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Presentation and analysis of a worldwide database of earthquake-induced landslide inventories","docAbstract":"<p><span>Earthquake-induced landslide (EQIL) inventories are essential tools to extend our knowledge of the relationship between earthquakes and the landslides they can trigger. Regrettably, such inventories are difficult to generate and therefore scarce, and the available ones differ in terms of their quality and level of completeness. Moreover, access to existing EQIL inventories is currently difficult because there is no centralized database. To address these issues, we compiled EQIL inventories from around the globe based on an extensive literature study. The database contains information on 363 landslide-triggering earthquakes and includes 66 digital landslide inventories. To make these data openly available, we created a repository to host the digital inventories that we have permission to redistribute through the U.S. Geological Survey ScienceBase platform. It can grow over time as more authors contribute their inventories. We analyze the distribution of EQIL events by time period and location, more specifically breaking down the distribution by continent, country, and mountain region. Additionally, we analyze frequency distributions of EQIL characteristics, such as the approximate area affected by landslides, total number of landslides, maximum distance from fault rupture zone, and distance from epicenter when the fault plane location is unknown. For the available digital EQIL inventories, we examine the underlying characteristics of landslide size, topographic slope, roughness, local relief, distance to streams, peak ground acceleration, peak ground velocity, and Modified Mercalli Intensity. Also, we present an evaluation system to help users assess the suitability of the available inventories for different types of EQIL studies and model development.</span></p>","language":"English","publisher":"AGU","doi":"10.1002/2017JF004236","usgsCitation":"Tanyas, H., van Westen, C.J., Allstadt, K.E., Nowicki Jessee, M., Gorum, T., Jibson, R.W., Godt, J.W., Sato, H., Schmitt, R.G., Marc, O., and Hovius, N., 2017, Presentation and analysis of a worldwide database of earthquake-induced landslide inventories: Journal of Geophysical Research F: Earth Surface, v. 122, no. 10, p. 1991-2015, https://doi.org/10.1002/2017JF004236.","productDescription":"25 p.","startPage":"1991","endPage":"2015","ipdsId":"IP-087814","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":469483,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017jf004236","text":"Publisher Index Page"},{"id":349542,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"122","issue":"10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-30","publicationStatus":"PW","scienceBaseUri":"5a60fb44e4b06e28e9c22e9d","contributors":{"authors":[{"text":"Tanyas, Hakan","contributorId":198731,"corporation":false,"usgs":false,"family":"Tanyas","given":"Hakan","affiliations":[],"preferred":false,"id":716989,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Westen, Cees J.","contributorId":196188,"corporation":false,"usgs":false,"family":"van Westen","given":"Cees","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":716990,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allstadt, Kate E. 0000-0003-4977-5248 kallstadt@usgs.gov","orcid":"https://orcid.org/0000-0003-4977-5248","contributorId":167684,"corporation":false,"usgs":true,"family":"Allstadt","given":"Kate","email":"kallstadt@usgs.gov","middleInitial":"E.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":716991,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nowicki Jessee, M. Anna","contributorId":196186,"corporation":false,"usgs":false,"family":"Nowicki Jessee","given":"M. Anna","affiliations":[],"preferred":false,"id":716992,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gorum, Tolga","contributorId":196190,"corporation":false,"usgs":false,"family":"Gorum","given":"Tolga","affiliations":[],"preferred":false,"id":716993,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jibson, Randall W. 0000-0003-3399-0875 jibson@usgs.gov","orcid":"https://orcid.org/0000-0003-3399-0875","contributorId":2985,"corporation":false,"usgs":true,"family":"Jibson","given":"Randall","email":"jibson@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":716994,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Godt, Jonathan W. 0000-0002-8737-2493 jgodt@usgs.gov","orcid":"https://orcid.org/0000-0002-8737-2493","contributorId":1166,"corporation":false,"usgs":true,"family":"Godt","given":"Jonathan","email":"jgodt@usgs.gov","middleInitial":"W.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":716995,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sato, Hiroshi P.","contributorId":196189,"corporation":false,"usgs":false,"family":"Sato","given":"Hiroshi P.","affiliations":[],"preferred":false,"id":716996,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schmitt, Robert G. 0000-0001-8060-1954 rschmitt@usgs.gov","orcid":"https://orcid.org/0000-0001-8060-1954","contributorId":5611,"corporation":false,"usgs":true,"family":"Schmitt","given":"Robert","email":"rschmitt@usgs.gov","middleInitial":"G.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":716997,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Marc, Odin","contributorId":198732,"corporation":false,"usgs":false,"family":"Marc","given":"Odin","email":"","affiliations":[],"preferred":false,"id":716998,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Hovius, Niels","contributorId":198733,"corporation":false,"usgs":false,"family":"Hovius","given":"Niels","email":"","affiliations":[],"preferred":false,"id":716999,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70192612,"text":"70192612 - 2017 - Environmental conditions and prey-switching by a seabird predator impact juvenile salmon survival","interactions":[],"lastModifiedDate":"2017-11-29T14:04:49","indexId":"70192612","displayToPublicDate":"2017-10-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2381,"text":"Journal of Marine Systems","active":true,"publicationSubtype":{"id":10}},"title":"Environmental conditions and prey-switching by a seabird predator impact juvenile salmon survival","docAbstract":"<p><span>Due to spatio-temporal variability of lower trophic-level productivity along the California Current Ecosystem (CCE), predators must be capable of switching prey or foraging areas in response to changes in environmental conditions and available forage. The Gulf of the Farallones in central California represents a biodiversity hotspot and contains the largest common murre&nbsp;(</span><i>Uria aalge</i><span>) colonies along the CCE. During spring, one of the West Coast's most important Chinook salmon (</span><i>Oncorhynchus tshawytscha</i><span>) populations out-migrates into the Gulf of the Farallones. We quantify the effect of predation on juvenile Chinook salmon associated with ecosystem-level variability by integrating long-term time series of environmental conditions (upwelling, river discharge), forage species abundance within central CCE, and population size, at-sea distribution, and diet of the common murre. Our results demonstrate common murres typically forage in the vicinity of their offshore breeding sites, but in years in which their primary prey, pelagic young-of-year rockfish (</span><i>Sebastes</i><span>spp.), are less available they forage for adult<span> northern anchovies</span><span>&nbsp;</span>(</span><i>Engraulis mordax</i><span>)<span> nearshore</span><span><span>. Incidentally, while foraging inshore, common murre consumption of out-migrating juvenile Chinook salmon, which are collocated with northern anchovy, increases and population survival of the salmon is significantly reduced. Results support earlier findings that show timing and strength of<span> upwelling</span>, and the resultant forage fish assemblage, is related to Chinook salmon recruitment variability in the CCE, but we extend those results by demonstrating the significance of top-down impacts associated with these bottom-up dynamics. Our results demonstrate the complexity of ecosystem interactions and impacts between higher trophic-level predators and their prey, complexities necessary to quantify in order to parameterize<span> ecosystem models</span></span><span>&nbsp;</span>and evaluate likely outcomes of ecosystem management options.</span></span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jmarsys.2017.05.008","usgsCitation":"Wells, B.K., Santora, J.A., Henderson, M., Warzybok, P., Jahncke, J., Bradley, R.W., Huff, D.D., Schroeder, I.D., Nelson, P., Field, J.C., and Ainley, D.G., 2017, Environmental conditions and prey-switching by a seabird predator impact juvenile salmon survival: Journal of Marine Systems, v. 174, p. 54-63, https://doi.org/10.1016/j.jmarsys.2017.05.008.","productDescription":"10 p.","startPage":"54","endPage":"63","ipdsId":"IP-077038","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":469467,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jmarsys.2017.05.008","text":"Publisher Index Page"},{"id":349551,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.5,\n              36.5\n            ],\n            [\n              -121.5,\n              36.5\n            ],\n            [\n              -121.5,\n              38.3\n            ],\n            [\n              -123.5,\n              38.3\n            ],\n            [\n              -123.5,\n              36.5\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"174","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb44e4b06e28e9c22ea0","contributors":{"authors":[{"text":"Wells, Brian K.","contributorId":198610,"corporation":false,"usgs":false,"family":"Wells","given":"Brian","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":716549,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Santora, Jarrod A.","contributorId":198611,"corporation":false,"usgs":false,"family":"Santora","given":"Jarrod","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":716550,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Henderson, Mark J. 0000-0002-2861-8668 mhenderson@usgs.gov","orcid":"https://orcid.org/0000-0002-2861-8668","contributorId":198609,"corporation":false,"usgs":true,"family":"Henderson","given":"Mark J.","email":"mhenderson@usgs.gov","affiliations":[],"preferred":false,"id":716548,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Warzybok, Peter","contributorId":198612,"corporation":false,"usgs":false,"family":"Warzybok","given":"Peter","email":"","affiliations":[],"preferred":false,"id":716551,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jahncke, Jaime","contributorId":152294,"corporation":false,"usgs":false,"family":"Jahncke","given":"Jaime","email":"","affiliations":[{"id":18899,"text":"Point Blue Conservation Science; GFNMS SAC","active":true,"usgs":false}],"preferred":false,"id":716552,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bradley, Russell W.","contributorId":198614,"corporation":false,"usgs":false,"family":"Bradley","given":"Russell","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":716553,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Huff, David D.","contributorId":171694,"corporation":false,"usgs":false,"family":"Huff","given":"David","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":716554,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schroeder, Isaac D.","contributorId":198616,"corporation":false,"usgs":false,"family":"Schroeder","given":"Isaac","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":716555,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Nelson, Peter","contributorId":198617,"corporation":false,"usgs":false,"family":"Nelson","given":"Peter","affiliations":[],"preferred":false,"id":716556,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Field, John C.","contributorId":39304,"corporation":false,"usgs":true,"family":"Field","given":"John","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":716557,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ainley, David G.","contributorId":32039,"corporation":false,"usgs":false,"family":"Ainley","given":"David","email":"","middleInitial":"G.","affiliations":[{"id":34154,"text":"Point Reyes Bird Observatory, Stinson Beach, CA","active":true,"usgs":false}],"preferred":false,"id":716558,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70194310,"text":"70194310 - 2017 - Harvesting wildlife affected by climate change: a modelling and management approach for polar bears","interactions":[],"lastModifiedDate":"2017-11-22T11:41:08","indexId":"70194310","displayToPublicDate":"2017-10-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Harvesting wildlife affected by climate change: a modelling and management approach for polar bears","docAbstract":"<ol id=\"jpe12864-list-0001\" class=\"o-list--numbered o-list--paragraph\"><li>The conservation of many wildlife species requires understanding the demographic effects of climate change, including interactions between climate change and harvest, which can provide cultural, nutritional or economic value to humans.</li><li>We present a demographic model that is based on the polar bear<span>&nbsp;</span><i>Ursus maritimus</i><span>&nbsp;</span>life cycle and includes density-dependent relationships linking vital rates to environmental carrying capacity (<i>K</i>). Using this model, we develop a state-dependent management framework to calculate a harvest level that (i) maintains a population above its maximum net productivity level (MNPL; the population size that produces the greatest net increment in abundance) relative to a changing<span>&nbsp;</span><i>K</i>, and (ii) has a limited negative effect on population persistence.</li><li>Our density-dependent relationships suggest that MNPL for polar bears occurs at approximately 0·69 (95% CI&nbsp;=&nbsp;0·63–0·74) of<span>&nbsp;</span><i>K</i>. Population growth rate at MNPL was approximately 0·82 (95% CI&nbsp;=&nbsp;0·79–0·84) of the maximum intrinsic growth rate, suggesting relatively strong compensation for human-caused mortality.</li><li>Our findings indicate that it is possible to minimize the demographic risks of harvest under climate change, including the risk that harvest will accelerate population declines driven by loss of the polar bear's sea-ice habitat. This requires that (i) the harvest rate – which could be 0 in some situations – accounts for a population's intrinsic growth rate, (ii) the harvest rate accounts for the quality of population data (e.g. lower harvest when uncertainty is large), and (iii) the harvest level is obtained by multiplying the harvest rate by an updated estimate of population size. Environmental variability, the sex and age of removed animals and risk tolerance can also affect the harvest rate.</li><li><i>Synthesis and applications</i>. We present a coupled modelling and management approach for wildlife that accounts for climate change and can be used to balance trade-offs among multiple conservation goals. In our example application to polar bears experiencing sea-ice loss, the goals are to maintain population viability while providing continued opportunities for subsistence harvest. Our approach may be relevant to other species for which near-term management is focused on human factors that directly influence population dynamics within the broader context of climate-induced habitat degradation.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2664.12864","usgsCitation":"Regehr, E.V., Wilson, R.H., Rode, K.D., Runge, M.C., and Stern, H., 2017, Harvesting wildlife affected by climate change: a modelling and management approach for polar bears: Journal of Applied Ecology, v. 54, no. 5, p. 1534-1543, https://doi.org/10.1111/1365-2664.12864.","productDescription":"10 p.","startPage":"1534","endPage":"1543","ipdsId":"IP-076053","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":469471,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.12864","text":"Publisher Index Page"},{"id":349269,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"54","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-08","publicationStatus":"PW","scienceBaseUri":"5a60fb3ae4b06e28e9c22e17","contributors":{"authors":[{"text":"Regehr, Eric V. 0000-0003-4487-3105","orcid":"https://orcid.org/0000-0003-4487-3105","contributorId":66364,"corporation":false,"usgs":false,"family":"Regehr","given":"Eric","email":"","middleInitial":"V.","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":723217,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, Ryan H. 0000-0001-7740-7771","orcid":"https://orcid.org/0000-0001-7740-7771","contributorId":130989,"corporation":false,"usgs":false,"family":"Wilson","given":"Ryan","email":"","middleInitial":"H.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":723218,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rode, Karyn D. 0000-0002-3328-8202 krode@usgs.gov","orcid":"https://orcid.org/0000-0002-3328-8202","contributorId":5053,"corporation":false,"usgs":true,"family":"Rode","given":"Karyn","email":"krode@usgs.gov","middleInitial":"D.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":723216,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":723219,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stern, Harry","contributorId":192065,"corporation":false,"usgs":false,"family":"Stern","given":"Harry","email":"","affiliations":[],"preferred":false,"id":723290,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
]}