Rainfall-induced shallow landsliding is a persistent hazard to human life and property. Despite the observed connection between infiltration through the unsaturated zone and shallow landslide initiation, there is considerable uncertainty in how estimates of unsaturated soil-water retention properties affect slope stability assessment. This source of uncertainty is critical to evaluating the utility of physics-based hydrologic modeling as a tool for landslide early warning. We employ a numerical model of variably saturated groundwater flow parameterized with an ensemble of texture-, laboratory-, and field-based estimates of soil-water retention properties for an extensively monitored landslide-prone site in the San Francisco Bay Area, CA, USA. Simulations of soil-water content, pore-water pressure, and the resultant factor of safety show considerable variability across and within these different parameter estimation techniques. In particular, we demonstrate that with the same permeability structure imposed across all simulations, the variability in soil-water retention properties strongly influences predictions of positive pore-water pressure coincident with widespread shallow landsliding. We also find that the ensemble of soil-water retention properties imposes an order-of-magnitude and nearly two-fold variability in seasonal and event-scale landslide susceptibility, respectively. Despite the reduced factor of safety uncertainty during wet conditions, parameters that control the dry end of the soil-water retention function markedly impact the ability of a hydrologic model to capture soil-water content dynamics observed in the field. These results suggest that variability in soil-water retention properties should be considered for objective physics-based simulation of landslide early warning criteria.
","language":"English","publisher":"Springer","doi":"10.1007/s10346-018-0950-z","usgsCitation":"Thomas, M.A., Mirus, B.B., Collins, B.D., Lu, N., and Godt, J.W., 2018, Variability in soil-water retention properties and implications for physics-based simulation of landslide early warning criteria: Landslides, v. 15, no. 7, p. 1265-1277, https://doi.org/10.1007/s10346-018-0950-z.","productDescription":"13 p.","startPage":"1265","endPage":"1277","ipdsId":"IP-089282","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":438007,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7M0449D","text":"USGS data release","linkHelpText":"Field data used to support hydrologic modeling for the U.S. Geological Survey's San Francisco Bay Area "BALT1" landslide monitoring site"},{"id":351832,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-12","publicationStatus":"PW","scienceBaseUri":"5afee728e4b0da30c1bfc14a","contributors":{"authors":[{"text":"Thomas, Matthew A.","contributorId":138657,"corporation":false,"usgs":false,"family":"Thomas","given":"Matthew","email":"","middleInitial":"A.","affiliations":[{"id":12482,"text":"Department of Geological and Environmental Sciences, Stanford University, 450 Serra Mall, Building 320, Stanford, California 94305-2115, USA","active":true,"usgs":false}],"preferred":false,"id":729027,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mirus, Benjamin B. 0000-0001-5550-014X bbmirus@usgs.gov","orcid":"https://orcid.org/0000-0001-5550-014X","contributorId":4064,"corporation":false,"usgs":true,"family":"Mirus","given":"Benjamin","email":"bbmirus@usgs.gov","middleInitial":"B.","affiliations":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":5077,"text":"Northwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":729028,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collins, Brian D. bcollins@usgs.gov","contributorId":2406,"corporation":false,"usgs":true,"family":"Collins","given":"Brian","email":"bcollins@usgs.gov","middleInitial":"D.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":729029,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lu, Ning","contributorId":191360,"corporation":false,"usgs":false,"family":"Lu","given":"Ning","email":"","affiliations":[{"id":12620,"text":"U.S. Army Corp. of Engineers","active":true,"usgs":false}],"preferred":false,"id":729030,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":729031,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70195477,"text":"70195477 - 2018 - Clayey landslide initiation and acceleration strongly modulated by soil swelling","interactions":[],"lastModifiedDate":"2018-03-19T11:10:31","indexId":"70195477","displayToPublicDate":"2018-02-20T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Clayey landslide initiation and acceleration strongly modulated by soil swelling","docAbstract":"Largely unknown mechanisms restrain motion of clay-rich, slow-moving landslides that are widespread worldwide and rarely accelerate catastrophically. We studied a clayey, slow-moving landslide typical of thousands in northern California, USA, to decipher hydrologic-mechanical interactions that modulate landslide dynamics. Similar to some other studies, observed pore-water pressures correlated poorly with landslide reactivation and speed. In situ and laboratory measurements strongly suggested that variable pressure along the landslide's lateral shear boundaries resulting from seasonal soil expansion and contraction modulated its reactivation and speed. Slope-stability modeling suggested that the landslide's observed behavior could be predicted by including transient swell pressure as a resistance term, whereas modeling considering only transient hydrologic conditions predicted movement 5–6 months prior to when it was observed. All clayey soils swell to some degree; hence, our findings suggest that swell pressure likely modulates motion of many landslides and should be considered to improve forecasts of clayey landslide initiation and mobility.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017GL076807","usgsCitation":"Schulz, W.H., Smith, J.B., Wang, G., Jiang, Y., and Roering, J., 2018, Clayey landslide initiation and acceleration strongly modulated by soil swelling: Geophysical Research Letters, v. 45, no. 4, p. 1888-1896, https://doi.org/10.1002/2017GL076807.","productDescription":"9 p.","startPage":"1888","endPage":"1896","ipdsId":"IP-093100","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":468987,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017gl076807","text":"Publisher Index Page"},{"id":438006,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7GF0SFS","text":"USGS data release","linkHelpText":"Data from in-situ landslide monitoring, Trinity County, California"},{"id":351813,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","volume":"45","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-26","publicationStatus":"PW","scienceBaseUri":"5afee72ae4b0da30c1bfc15c","contributors":{"authors":[{"text":"Schulz, William H. 0000-0001-9980-3580 wschulz@usgs.gov","orcid":"https://orcid.org/0000-0001-9980-3580","contributorId":942,"corporation":false,"usgs":true,"family":"Schulz","given":"William","email":"wschulz@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":728780,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Joel B. 0000-0001-7219-7875 jbsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-7219-7875","contributorId":4925,"corporation":false,"usgs":true,"family":"Smith","given":"Joel","email":"jbsmith@usgs.gov","middleInitial":"B.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":728781,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Gonghui","contributorId":202546,"corporation":false,"usgs":false,"family":"Wang","given":"Gonghui","email":"","affiliations":[{"id":36476,"text":"Disaster Prevention Research Institute, Kyoto University","active":true,"usgs":false}],"preferred":false,"id":728782,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jiang, Yao","contributorId":202547,"corporation":false,"usgs":false,"family":"Jiang","given":"Yao","email":"","affiliations":[{"id":36476,"text":"Disaster Prevention Research Institute, Kyoto University","active":true,"usgs":false}],"preferred":false,"id":728783,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roering, Joshua J.","contributorId":194297,"corporation":false,"usgs":false,"family":"Roering","given":"Joshua J.","affiliations":[],"preferred":false,"id":728784,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70195521,"text":"70195521 - 2018 - Improving estimation of flight altitude in wildlife telemetry studies","interactions":[],"lastModifiedDate":"2018-07-03T11:37:03","indexId":"70195521","displayToPublicDate":"2018-02-20T00:00:00","publicationYear":"2018","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":"Improving estimation of flight altitude in wildlife telemetry studies","docAbstract":"In the traditional method of characteristics for groundwater solute-transport models, advective transport is represented by moving particles that track concentration. This approach can lead to global mass-balance problems because in models of aquifers having complex boundary conditions and heterogeneous properties, particles can originate in cells having different pore volumes and (or) be introduced (or removed) at cells representing fluid sources (or sinks) of varying strengths. Use of volume-weighted particles means that each particle tracks solute mass. In source or sink cells, the changes in particle weights will match the volume of water added or removed through external fluxes. This enables the new method to conserve mass in source or sink cells as well as globally. This approach also leads to potential efficiencies by allowing the number of particles per cell to vary spatially—using more particles where concentration gradients are high and fewer where gradients are low. The approach also eliminates the need for the model user to have to distinguish between “weak” and “strong” fluid source (or sink) cells. The new model determines whether solute mass added by fluid sources in a cell should be represented by (1) new particles having weights representing appropriate fractions of the volume of water added by the source, or (2) distributing the solute mass added over all particles already in the source cell. The first option is more appropriate for the condition of a strong source; the latter option is more appropriate for a weak source. At sinks, decisions whether or not to remove a particle are replaced by a reduction in particle weight in proportion to the volume of water removed. A number of test cases demonstrate that the new method works well and conserves mass. The method is incorporated into a new version of the U.S. Geological Survey’s MODFLOW–GWT solute-transport model.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section A: Groundwater in Book 6: Modeling techniques","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6A58","usgsCitation":"Winston, R.B., Konikow, L.F., and Hornberger, G.Z., 2018, Volume-weighted particle-tracking method for solute-transport modeling; Implementation in MODFLOW–GWT: U.S. Geological Survey Techniques and Methods, book 6, chap. A58, 44 p., https://doi.org/10.3133/tm6A58.","productDescription":"v, 44 p.","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-082949","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":351613,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/06/a58/coverthb.jpg"},{"id":351614,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/06/a58/tm6a58.pdf","text":"Report","size":"2.91 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 6-A58"}],"publicComments":"This report is Chapter 58 of Section A: Groundwater in Book 6 Modeling techniques.","contact":"Director, Integrated Modeling and Prediction Division
U.S. Geological Survey
MS 415 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Emerging infectious diseases are an increasingly common threat to wildlife. Chytridiomycosis, caused by the fungal pathogen Batrachochytrium dendrobatidis (Bd), is an emerging infectious disease that has been linked to amphibian declines around the world. Few studies exist that explore amphibian-Bd dynamics at the landscape scale, limiting our ability to identify which factors are associated with variation in population susceptibility and to develop effective in situdisease management. Declines of boreal toads (Anaxyrus boreas boreas) in the Southern Rocky Mountains are largely attributed to chytridiomycosis but variation exists in local extinction of boreal toads across this metapopulation. Using a large-scale historic dataset, we explored several potential factors influencing disease dynamics in the boreal toad-Bd system: geographic isolation of populations, amphibian community richness, elevational differences, and habitat permanence. We found evidence that boreal toad extinction risk was lowest at high elevations where temperatures may be sub-optimal for Bd growth and where small boreal toad populations may be below the threshold needed for efficient pathogen transmission. In addition, boreal toads were more likely to recolonize high elevation sites after local extinction, again suggesting that high elevations may provide refuge from disease for boreal toads. We illustrate a modeling framework that will be useful to natural resource managers striving to make decisions in amphibian-Bdsystems. Our data suggest that in the southern Rocky Mountains high elevation sites should be prioritized for conservation initiatives like reintroductions.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.1699","usgsCitation":"Mosher, B.A., Bailey, L.L., Muths, E.L., and Huyvaert, K.P., 2018, Host-pathogen metapopulation dynamics suggest high elevation refugia for boreal toads: Ecological Applications, v. 28, no. 4, p. 926-937, https://doi.org/10.1002/eap.1699.","productDescription":"12 p.","startPage":"926","endPage":"937","ipdsId":"IP-088106","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":351697,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-07","publicationStatus":"PW","scienceBaseUri":"5afee72ce4b0da30c1bfc176","contributors":{"authors":[{"text":"Mosher, Brittany A.","contributorId":189579,"corporation":false,"usgs":false,"family":"Mosher","given":"Brittany","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":728663,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bailey, Larissa L. 0000-0002-5959-2018","orcid":"https://orcid.org/0000-0002-5959-2018","contributorId":189578,"corporation":false,"usgs":false,"family":"Bailey","given":"Larissa","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":728664,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Muths, Erin L. 0000-0002-5498-3132 muthse@usgs.gov","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":1260,"corporation":false,"usgs":true,"family":"Muths","given":"Erin","email":"muthse@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":728662,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Huyvaert, Kathryn P.","contributorId":202514,"corporation":false,"usgs":false,"family":"Huyvaert","given":"Kathryn","email":"","middleInitial":"P.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":728665,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70195449,"text":"70195449 - 2018 - Spatial patterns and temporal changes in atmospheric-mercury deposition for the midwestern USA, 2001–2016","interactions":[],"lastModifiedDate":"2018-02-20T10:17:43","indexId":"70195449","displayToPublicDate":"2018-02-16T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5634,"text":"Atmosphere","active":true,"publicationSubtype":{"id":10}},"title":"Spatial patterns and temporal changes in atmospheric-mercury deposition for the midwestern USA, 2001–2016","docAbstract":"Spatial patterns and temporal changes in atmospheric-mercury (Hg) deposition were examined in a five-state study area in the Midwestern USA where 32% of the stationary sources of anthropogenic Hg emissions in the continental USA were located. An extensive monitoring record for wet and dry Hg deposition was compiled for 2001–2016, including 4666 weekly precipitation samples at 13 sites and 27 annual litterfall-Hg samples at 7 sites. This study is the first to examine these Hg data for the Midwestern USA. The median annual precipitation-Hg deposition at the study sites was 10.4 micrograms per square meter per year (ug/m2/year) and ranged from 5.8 ug/m2/year to 15.0 ug/m2/year. The median annual Hg concentration was 9.4 ng/L. Annual litterfall-Hg deposition had a median of 16.1 ug/m2/year and ranged from 9.7 to 23.4 ug/m2/year. Isopleth maps of annual precipitation-Hg deposition indicated a recurring spatial pattern similar to one revealed by statistical analysis of weekly precipitation-Hg deposition. In that pattern, high Hg deposition in southeastern Indiana was present each year, frequently extending to southern Illinois. Most of central Indiana and central Illinois had similar Hg deposition. Areas with comparatively lower annual Hg deposition were observed in Michigan and Ohio for many years and frequently included part of northern Indiana. The area in southern Indiana where high Hg deposition predominated had the highest number of extreme episodes of weekly Hg deposition delivering up to 15% of the annual Hg load from precipitation in a single week. Modeled 48-h back trajectories indicated air masses for these episodes often arrived from the south and southwest, crossing numerous stationary sources of Hg emissions releasing from 23 to more than 300 kg Hg per year. This analysis suggests that local and regional, rather than exclusively continental or global Hg emissions were likely contributing to the extreme episodes and at least in part, to the spatial patterns of precipitation-Hg deposition in the study area. Statistically significant temporal decreases in weekly precipitation-Hg concentrations in\nthe study area between the periods 2001–2013 and 2014–2016 were observed, coinciding with reported reductions in Hg emissions in the USA required by implementation of national Hg emissions-control rules. These decreases in atmospheric-Hg concentrations are believed to have resulted in the reduced atmospheric-Hg deposition recorded because precipitation depths between the two periods were not significantly different. The Hg-monitoring data for the study area identified an atmospheric deposition response to decreased local and regional Hg emissions.","language":"English","publisher":"MDPI","doi":"10.3390/atmos9010029","usgsCitation":"Risch, M.R., and Kenski, D.M., 2018, Spatial patterns and temporal changes in atmospheric-mercury deposition for the midwestern USA, 2001–2016: Atmosphere, v. 9, no. 1, p. 1-20, https://doi.org/10.3390/atmos9010029.","productDescription":"Article 29; 20 p.","startPage":"1","endPage":"20","ipdsId":"IP-091127","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":469098,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/atmos9010029","text":"Publisher Index Page"},{"id":351696,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Indiana, Kentucky, Michigan, Ohio","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-89.366031,42.500274],[-87.815872,42.49192],[-87.812461,42.232278],[-87.365439,41.629536],[-86.679672,41.844579],[-86.23528,42.564958],[-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],[-85.069573,45.459239],[-85.079528,45.617083],[-84.94565,45.708621],[-85.011433,45.757962],[-84.774156,45.788918],[-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],[-82.643166,43.852468],[-82.423086,42.988728],[-82.509935,42.637294],[-82.648776,42.550401],[-82.630922,42.64211],[-82.780817,42.652232],[-83.40822,41.832654],[-83.37573,41.686647],[-82.481214,41.381342],[-81.69325,41.514161],[-80.533774,41.973475],[-80.518991,40.638801],[-80.667957,40.582496],[-80.619297,40.26517],[-80.88036,39.620706],[-81.656138,39.277355],[-81.874857,38.881174],[-82.068864,38.984878],[-82.318111,38.457876],[-82.569368,38.406258],[-82.611343,38.171548],[-82.474635,37.905902],[-81.982479,37.541807],[-83.128813,36.757864],[-83.690714,36.582581],[-88.011792,36.677025],[-88.127378,36.49854],[-89.380085,36.500416],[-89.192542,36.635997],[-89.098843,36.95785],[-89.438275,37.161287],[-89.566704,37.707189],[-90.353902,38.213855],[-90.166409,38.876348],[-90.406367,38.962554],[-90.625122,38.888654],[-90.767648,39.280025],[-91.367753,39.729029],[-91.511073,40.188794],[-91.406202,40.542698],[-91.123928,40.669152],[-90.952233,40.954047],[-91.100829,41.230532],[-91.05158,41.385283],[-90.364128,41.579633],[-90.153362,41.915593],[-90.206369,42.1455],[-90.646727,42.471904],[-89.366031,42.500274]]],[[[-88.684434,48.115785],[-88.447236,48.182916],[-89.022736,47.858532],[-89.255202,47.876102],[-88.684434,48.115785]]],[[[-88.116846,45.921703],[-90.120489,46.336852],[-90.344338,46.552087],[-89.790663,46.818469],[-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],[-87.612019,45.123377],[-87.727276,45.216129],[-87.648476,45.352243],[-87.860432,45.423504],[-87.831442,45.714938],[-88.131834,45.811312],[-88.116846,45.921703]]]]},\"properties\":{\"name\":\"Illinois\",\"nation\":\"USA \"}}]}","volume":"9","issue":"1","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-18","publicationStatus":"PW","scienceBaseUri":"5afee72ce4b0da30c1bfc174","contributors":{"authors":[{"text":"Risch, Martin R. 0000-0002-7908-7887 mrrisch@usgs.gov","orcid":"https://orcid.org/0000-0002-7908-7887","contributorId":2118,"corporation":false,"usgs":true,"family":"Risch","given":"Martin","email":"mrrisch@usgs.gov","middleInitial":"R.","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":728666,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kenski, Donna M.","contributorId":202515,"corporation":false,"usgs":false,"family":"Kenski","given":"Donna","email":"","middleInitial":"M.","affiliations":[{"id":36467,"text":"Lake Michigan Air Directors Consortium","active":true,"usgs":false}],"preferred":false,"id":728667,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70195485,"text":"70195485 - 2018 - Phytoforensics: Trees as bioindicators of potential indoor exposure via vapor intrusion","interactions":[],"lastModifiedDate":"2018-02-16T15:40:38","indexId":"70195485","displayToPublicDate":"2018-02-16T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Phytoforensics: Trees as bioindicators of potential indoor exposure via vapor intrusion","docAbstract":"Human exposure to volatile organic compounds (VOCs) via vapor intrusion (VI) is an emerging public health concern with notable detrimental impacts on public health. Phytoforensics, plant sampling to semi-quantitatively delineate subsurface contamination, provides a potential non-invasive screening approach to detect VI potential, and plant sampling is effective and also time- and cost-efficient. Existing VI assessment methods are time- and resource-intensive, invasive, and require access into residential and commercial buildings to drill holes through basement slabs to install sampling ports or require substantial equipment to install groundwater or soil vapor sampling outside the home. Tree-core samples collected in 2 days at the PCE Southeast Contamination Site in York, Nebraska were analyzed for tetrachloroethene (PCE) and results demonstrated positive correlations with groundwater, soil, soil-gas, sub-slab, and indoor-air samples collected over a 2-year period. Because tree-core samples were not collocated with other samples, interpolated surfaces of PCE concentrations were estimated so that comparisons could be made between pairs of data. Results indicate moderate to high correlation with average indoor-air and sub-slab PCE concentrations over long periods of time (months to years) to an interpolated tree-core PCE concentration surface, with Spearman’s correlation coefficients (ρ) ranging from 0.31 to 0.53 that are comparable to the pairwise correlation between sub-slab and indoor-air PCE concentrations (ρ = 0.55, n = 89). Strong correlations between soil-gas, sub-slab, and indoor-air PCE concentrations and an interpolated tree-core PCE concentration surface indicate that trees are valid indicators of potential VI and human exposure to subsurface environment pollutants. The rapid and non-invasive nature of tree sampling are notable advantages: even with less than 60 trees in the vicinity of the source area, roughly 12 hours of tree-core sampling with minimal equipment at the PCE Southeast Contamination Site was sufficient to delineate vapor intrusion potential in the study area and offered comparable delineation to traditional sub-slab sampling performed at 140 properties over a period of approximately 2 years.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0193247","usgsCitation":"Wilson, J.L., Samaranayake, V., Limmer, M.A., and Burken, J.G., 2018, Phytoforensics: Trees as bioindicators of potential indoor exposure via vapor intrusion: PLoS ONE, v. 13, no. 2, p. 1-17, https://doi.org/10.1371/journal.pone.0193247.","productDescription":"e0193247; 17 p.","startPage":"1","endPage":"17","ipdsId":"IP-085495","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":468991,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0193247","text":"Publisher Index Page"},{"id":438010,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7CF9P06","text":"USGS data release","linkHelpText":"Concentrations of tetrachloroethylene in tree-core, groundwater, soil, soil-gas, indoor-air, and sub-slab samples from the Tetrachloroethene Southeast Contamination Site in York, Nebraska, 2014-2016."},{"id":351746,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","city":"York","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.595,\n 40.87\n ],\n [\n -97.575,\n 40.87\n ],\n [\n -97.575,\n 40.8639\n ],\n [\n -97.595,\n 40.8639\n ],\n [\n -97.595,\n 40.87\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-16","publicationStatus":"PW","scienceBaseUri":"5afee72be4b0da30c1bfc168","contributors":{"authors":[{"text":"Wilson, Jordan L. 0000-0003-0490-9062 jlwilson@usgs.gov","orcid":"https://orcid.org/0000-0003-0490-9062","contributorId":5416,"corporation":false,"usgs":true,"family":"Wilson","given":"Jordan","email":"jlwilson@usgs.gov","middleInitial":"L.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":728825,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Samaranayake, V.A. 0000-0002-1892-8363","orcid":"https://orcid.org/0000-0002-1892-8363","contributorId":201176,"corporation":false,"usgs":false,"family":"Samaranayake","given":"V.A.","email":"","affiliations":[],"preferred":false,"id":728826,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Limmer, Matthew A.","contributorId":200927,"corporation":false,"usgs":false,"family":"Limmer","given":"Matthew","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":728827,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burken, Joel G.","contributorId":21218,"corporation":false,"usgs":true,"family":"Burken","given":"Joel","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":728828,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70194917,"text":"fs20173090 - 2018 - Characterizing the subsurface geology in and around the U.S. Army Camp Stanley Storage Activity, south-central Texas","interactions":[],"lastModifiedDate":"2018-06-06T13:07:10","indexId":"fs20173090","displayToPublicDate":"2018-02-15T18:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-3090","title":"Characterizing the subsurface geology in and around the U.S. Army Camp Stanley Storage Activity, south-central Texas","docAbstract":"Several U.S. Geological Survey projects, supported by the National Cooperative Geologic Mapping Program, have used multi-disciplinary approaches over a 14-year period to reveal the surface and subsurface geologic frameworks of the Edwards and Trinity aquifers of central Texas and the Arbuckle-Simpson aquifer of south-central Oklahoma. Some of the project achievements include advancements in hydrostratigraphic mapping, three-dimensional subsurface framework modeling, and airborne geophysical surveys as well as new methodologies that link geologic and groundwater flow models. One area where some of these milestones were achieved was in and around the U.S. Army Camp Stanley Storage Activity, located in northwestern Bexar County, Texas, about 19 miles northwest of downtown San Antonio.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173090","usgsCitation":"Blome, C.D., and Clark, A.K., 2018, Characterizing the subsurface geology in and around the U.S. Army Camp Stanley Storage Activity, south-central Texas: U.S. Geological Survey Fact Sheet 2017-3090, 6 p., https://doi.org/10.3133/fs20173090.","productDescription":"6 p.","onlineOnly":"N","ipdsId":"IP-087931","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":351503,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3090/fs20173090.pdf","text":"Report","size":"13.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017-3090"},{"id":351502,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3090/coverthb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Camp Stanley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.7,\n 29.675\n ],\n [\n -98.5917,\n 29.675\n ],\n [\n -98.5917,\n 29.7417\n ],\n [\n -98.7,\n 29.7417\n ],\n [\n -98.7,\n 29.675\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geosciences and Environmental Change Science Center
U.S. Geological Survey
Box 25046, MS-980
Denver, CO 80225-0046
To improve understanding of the distribution of ecologically important, ephemeral wetland habitats across the Great Plains, the occurrence and distribution of surface water in playa wetland complexes were documented for four different years across the Great Plains Landscape Conservation Cooperative (GPLCC) region. This information is important because it informs land and wildlife managers about the timing and location of habitat availability. Data with an accurate timestamp that indicate the presence of water, the percent of the area inundated with water, and the spatial distribution of playa wetlands with water are needed for a host of resource inventory, monitoring, and research applications. For example, the distribution of inundated wetlands forms the spatial pattern of available habitat for resident shorebirds and water birds, stop-over habitats for migratory birds, connectivity and clustering of wetland habitats, and surface waters that recharge the Ogallala aquifer; there is considerable variability in the distribution of playa wetlands holding water through time. Documentation of these spatially and temporally intricate processes, here, provides data required to assess connections between inundation and multiple environmental drivers, such as climate, land use, soil, and topography. Climate drivers are understood to interact with land cover, land use and soil attributes in determining the amount of water that flows overland into playa wetlands. Results indicated significant spatial variability represented by differences in the percent of playas inundated among States within the GPLCC. Further, analysis-of-variance comparison of differences in inundation between years showed significant differences in all cases. Although some connections with seasonal moisture patterns may be observed, the complex spatial-temporal gradients of precipitation, temperature, soils, and land use need to be combined as covariates in multivariate models to effectively account for these patterns. We demonstrate the feasibility of using classification of Landsat satellite imagery to describe playa-wetland inundation across years and seasons. Evaluating classifications representing only 4 years of imagery, we found significant year-to-year and state-to-state differences in inundation rates.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171166","collaboration":"Prepared in cooperation with the Great Plains Landscape Conservation Cooperative, U.S. Fish and Wildlife Service, Albuquerque, New Mexico","usgsCitation":"Manier, D.J., and Rover, J.R., 2018, Landsat classification of surface-water presence during multiple years to assess response of playa wetlands to climatic variability across the Great Plains Landscape Conservation Cooperative region: U.S. Geological Survey Open-File Report 2017–1166, 20 p., https://doi.org/10.3133/ofr20171166.","productDescription":"iv, 20 p.","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-073569","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":438012,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7MW2GCN","text":"USGS data release","linkHelpText":"Landsat classification of surface water for multiple seasons to monitor inundation of playa wetlands"},{"id":351569,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1166/ofr20171166.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1166"},{"id":351568,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1166/coverthb.jpg"}],"country":"United States","otherGeospatial":"Great Plains Landscape Conservation Cooperative","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106,\n 30\n ],\n [\n -96,\n 30\n ],\n [\n -96,\n 44\n ],\n [\n -106,\n 44\n ],\n [\n -106,\n 30\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Building C
Fort Collins, CO 80526-8118
The greater sage-grouse (Centrocercus urophasianus; hereafter GRSG) has been a focus of scientific investigation and management action for the past two decades. The 2015 U.S. Fish and Wildlife Service listing determination of “not warranted” was in part due to a large-scale collaborative effort to develop strategies to conserve GRSG populations and their habitat and to reduce threats to both. New scientific information augments existing knowledge and can help inform updates or modifications to existing plans for managing GRSG and sagebrush ecosystems. However, the sheer number of scientific publications can be a challenge for managers tasked with evaluating and determining the need for potential updates to existing planning documents. To assist in this process, the U.S. Geological Survey (USGS) has reviewed and summarized the scientific literature published since January 1, 2015.
To identify articles and reports published about GRSG, we first conducted a structured search of three reference databases (Web of Science, Scopus, and Google Scholar) using the search term “greater sage-grouse.” We refined the initial list of products by (1) removing duplicates, (2) excluding products that were not published as research or scientific review articles in peer-reviewed journals or as formal government technical reports, and (3) retaining only those products for which GRSG or their habitat was a research focus.
We summarized the contents of each product by using a consistent structure (background, objectives, methods, location, findings, and implications) and assessed the content of each product relevant to a list of 31 management topics. These topics include GRSG biology and habitat characteristics along with potential management actions, land uses, and environmental factors related to GRSG management and conservation. We also noted which articles/reports created new geospatial data.
The final search was conducted on January 6, 2018, and application of our criteria resulted in the inclusion of 169 published products (2 of these products were published corrections to journal articles). The management topics most commonly addressed were GRSG behavior or demographics and GRSG habitat selection or habitat characteristics at broad or site scales. Few products addressed captive breeding, recreation, wild horses and burros, and range management structures (including fences). We include in this annotated bibliography the full citation, product summary, and management topics addressed by each product. The online version of this bibliography (https://apps.usgs.gov/gsgbib/index.php) is searchable by topic and location and includes links to the original publications.
A substantial body of literature has been compiled based on research explicitly related to the conservation, management, monitoring, and assessment of GRSG. These studies may inform planning and management actions that seek to balance conservation, economic, and social objectives and manage diverse resource uses and values across the western United States.
The review process for this product included requesting input on each summary from one or more authors of the original peer-reviewed article or report and a formal review of the entire document by three independent reviewers and, subsequently, the USGS Bureau Approving Official. This process is consistent with USGS Fundamental Science Practices.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181008","usgsCitation":"Carter, S.K., Manier, D.J., Arkle, R.S., Johnston, A.N., Phillips, S.L., Hanser, S.E., and Bowen, Z.H., 2018, Annotated bibliography of scientific research on greater sage-grouse published since January 2015: U.S. Geological Survey Open-File Report 2018–1008, 183 p., https://doi.org/10.3133/ofr20181008.","productDescription":"v, 183 p.","numberOfPages":"189","onlineOnly":"Y","ipdsId":"IP-093354","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":351662,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20181017","text":"Open-File Report 2018-1017:","linkHelpText":"Greater Sage-Grouse Science (2015–17)—Synthesis and Potential Management Implications"},{"id":351501,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://apps.usgs.gov/gsgbib/index.php","text":"Interactive, searchable version:","linkHelpText":"Annotated Bibliography of Scientific Research on Greater Sage-Grouse Published since January 2015"},{"id":351500,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1008/ofr20181008.pdf","text":"Report","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1008"},{"id":351499,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1008/coverthb2.jpg"}],"contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Building C
Fort Collins, CO 80526-8118
Our understanding of deglacial climate history in the southern Great Lakes region of the United States is primarily based upon fossil pollen data, with few independent and multi-proxy climate reconstructions. Here we introduce a new, well-dated fossil pollen record from Stotzel-Leis, OH, and a new deglacial temperature record based on branched glycerol dialkyl glycerol tetraethers (brGDGTs) at Silver Lake, OH. We compare these new data to previously published records and to a regional stack of pollen-based temperature reconstructions from Stotzel-Leis, Silver Lake, and three other well-dated sites. The new and previously published pollen records at Stotzel-Leis are similar, but our new age model brings vegetation events into closer alignment with known climatic events such as the Younger Dryas (YD). brGDGT-inferred temperatures correlate strongly with pollen-based regional temperature reconstructions, with the strongest correlation obtained for a global soil-based brGDGT calibration (r2 = 0.88), lending confidence to the deglacial reconstructions and the use of brGDGT and regional pollen stacks as paleotemperature proxies in eastern North America. However, individual pollen records show large differences in timing, rates, and amplitudes of inferred temperature change, indicating caution with paleoclimatic inferences based on single-site pollen records. From 16.0 to 10.0ka, both proxies indicate that regional temperatures rose by ∼10 °C, roughly double the ∼5 °C estimates for the Northern Hemisphere reported in prior syntheses. Change-point analysis of the pollen stack shows accelerated warming at 14.0 ± 1.2ka, cooling at 12.6 ± 0.4ka, and warming from 11.6 ± 0.5ka into the Holocene. The timing of Bølling-Allerød (B-A) warming and YD onset in our records lag by ∼300–500 years those reported in syntheses of temperature records from the northern mid-latitudes. This discrepancy is too large to be attributed to uncertainties in radiocarbon dating, and correlation between pollen and brGDGT temperature reconstructions rules out vegetation lags as a cause. However, the YD termination appears synchronous among the brGDGT record, regional pollen stack, and Northern Hemisphere stack. The cause of the larger and lagged temperature changes in the southern Great Lakes relative to Northern Hemisphere averages remains unclear, but may be due to the effects of continentality and ice sheet extent on regional climate evolution.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2017.12.011","usgsCitation":"Watson, B.I., Williams, J.W., Russell, J.M., Jackson, S.T., Shane, L., and Lowell, T.V., 2018, Temperature variations in the southern Great Lakes during the last deglaciation: Comparison between pollen and GDGT proxies: Quaternary Science Reviews, v. 182, p. 78-92, https://doi.org/10.1016/j.quascirev.2017.12.011.","productDescription":"15 p.","startPage":"78","endPage":"92","ipdsId":"IP-088633","costCenters":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"links":[{"id":468997,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quascirev.2017.12.011","text":"Publisher Index Page"},{"id":352887,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"182","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee72de4b0da30c1bfc180","contributors":{"authors":[{"text":"Watson, Benjamin I.","contributorId":203629,"corporation":false,"usgs":false,"family":"Watson","given":"Benjamin","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":731980,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, John W.","contributorId":16761,"corporation":false,"usgs":true,"family":"Williams","given":"John","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":731981,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Russell, James M.","contributorId":174740,"corporation":false,"usgs":false,"family":"Russell","given":"James","email":"","middleInitial":"M.","affiliations":[{"id":27506,"text":"Department of Earth, Environmental and Planetary Sciences, Brown University, Providence RI 02912 USA","active":true,"usgs":false}],"preferred":false,"id":731982,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, Stephen T. 0000-0002-1487-4652 stjackson@usgs.gov","orcid":"https://orcid.org/0000-0002-1487-4652","contributorId":344,"corporation":false,"usgs":true,"family":"Jackson","given":"Stephen","email":"stjackson@usgs.gov","middleInitial":"T.","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":560,"text":"South Central Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":731921,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shane, Linda","contributorId":203630,"corporation":false,"usgs":false,"family":"Shane","given":"Linda","email":"","affiliations":[],"preferred":false,"id":731983,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lowell, Thomas V.","contributorId":203631,"corporation":false,"usgs":false,"family":"Lowell","given":"Thomas","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":731984,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70195806,"text":"70195806 - 2018 - Modelling surface-water depression storage in a Prairie Pothole Region","interactions":[],"lastModifiedDate":"2018-03-02T11:12:22","indexId":"70195806","displayToPublicDate":"2018-02-15T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Modelling surface-water depression storage in a Prairie Pothole Region","docAbstract":"In this study, the Precipitation-Runoff Modelling System (PRMS) was used to simulate changes in surface-water depression storage in the 1,126-km2 Upper Pipestem Creek basin located within the Prairie Pothole Region of North Dakota, USA. The Prairie Pothole Region is characterized by millions of small water bodies (or surface-water depressions) that provide numerous ecosystem services and are considered an important contribution to the hydrologic cycle. The Upper Pipestem PRMS model was extracted from the U.S. Geological Survey's (USGS) National Hydrologic Model (NHM), developed to support consistent hydrologic modelling across the conterminous United States. The Geospatial Fabric database, created for the USGS NHM, contains hydrologic model parameter values derived from datasets that characterize the physical features of the entire conterminous United States for 109,951 hydrologic response units. Each hydrologic response unit in the Geospatial Fabric was parameterized using aggregated surface-water depression area derived from the National Hydrography Dataset Plus, an integrated suite of application-ready geospatial datasets. This paper presents a calibration strategy for the Upper Pipestem PRMS model that uses normalized lake elevation measurements to calibrate the parameters influencing simulated fractional surface-water depression storage. Results indicate that inclusion of measurements that give an indication of the change in surface-water depression storage in the calibration procedure resulted in accurate changes in surface-water depression storage in the water balance. Regionalized parameterization of the USGS NHM will require a proxy for change in surface-storage to accurately parameterize surface-water depression storage within the USGS NHM.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.11416","usgsCitation":"Hay, L.E., Norton, P.A., Viger, R.J., Markstrom, S.L., Regan, R.S., and Vanderhoof, M.K., 2018, Modelling surface-water depression storage in a Prairie Pothole Region: Hydrological Processes, v. 32, no. 4, p. 462-479, https://doi.org/10.1002/hyp.11416.","productDescription":"18 p.","startPage":"462","endPage":"479","ipdsId":"IP-080013","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":352175,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","otherGeospatial":"Upper Pipestem Creek basin","volume":"32","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-08","publicationStatus":"PW","scienceBaseUri":"5afee72de4b0da30c1bfc182","contributors":{"authors":[{"text":"Hay, Lauren E. 0000-0003-3763-4595 lhay@usgs.gov","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":1287,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","email":"lhay@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":729974,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Norton, Parker A. 0000-0002-4638-2601 pnorton@usgs.gov","orcid":"https://orcid.org/0000-0002-4638-2601","contributorId":2257,"corporation":false,"usgs":true,"family":"Norton","given":"Parker","email":"pnorton@usgs.gov","middleInitial":"A.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":729978,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Viger, Roland J. 0000-0003-2520-714X rviger@usgs.gov","orcid":"https://orcid.org/0000-0003-2520-714X","contributorId":168799,"corporation":false,"usgs":true,"family":"Viger","given":"Roland","email":"rviger@usgs.gov","middleInitial":"J.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":729976,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Markstrom, Steven L. 0000-0001-7630-9547 markstro@usgs.gov","orcid":"https://orcid.org/0000-0001-7630-9547","contributorId":146553,"corporation":false,"usgs":true,"family":"Markstrom","given":"Steven","email":"markstro@usgs.gov","middleInitial":"L.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":729977,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Regan, R. Steve 0000-0003-4803-8596 rsregan@usgs.gov","orcid":"https://orcid.org/0000-0003-4803-8596","contributorId":196973,"corporation":false,"usgs":true,"family":"Regan","given":"R.","email":"rsregan@usgs.gov","middleInitial":"Steve","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":729975,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":729979,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70191170,"text":"sir20175108 - 2018 - Stream-channel and watershed delineations and basin-characteristic measurements using lidar elevation data for small drainage basins within the Des Moines Lobe landform region in Iowa","interactions":[],"lastModifiedDate":"2018-02-14T15:01:18","indexId":"sir20175108","displayToPublicDate":"2018-02-14T13:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5108","title":"Stream-channel and watershed delineations and basin-characteristic measurements using lidar elevation data for small drainage basins within the Des Moines Lobe landform region in Iowa","docAbstract":"Basin-characteristic measurements related to stream length, stream slope, stream density, and stream order have been identified as significant variables for estimation of flood, flow-duration, and low-flow discharges in Iowa. The placement of channel initiation points, however, has always been a matter of individual interpretation, leading to differences in stream definitions between analysts.
This study investigated five different methods to define stream initiation using 3-meter light detection and ranging (lidar) digital elevation models (DEMs) data for 17 streamgages with drainage areas less than 50 square miles within the Des Moines Lobe landform region in north-central Iowa. Each DEM was hydrologically enforced and the five stream initiation methods were used to define channel initiation points and the downstream flow paths. The five different methods to define stream initiation were tested side-by-side for three watershed delineations: (1) the total drainage-area delineation, (2) an effective drainage-area delineation of basins based on a 2-percent annual exceedance probability (AEP) 12-hour rainfall, and (3) an effective drainage-area delineation based on a 20-percent AEP 12-hour rainfall.
Generalized least squares regression analysis was used to develop a set of equations for sites in the Des Moines Lobe landform region for estimating discharges for ungaged stream sites with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent AEPs. A total of 17 streamgages were included in the development of the regression equations. In addition, geographic information system software was used to measure 58 selected basin-characteristics for each streamgage.
Results of the regression analyses of the 15 lidar datasets indicate that the datasets that produce regional regression equations (RREs) with the best overall predictive accuracy are the National Hydrographic Dataset, Iowa Department of Natural Resources, and profile curvature of 0.5 stream initiation methods combined with the 20-percent AEP 12-hour rainfall watershed delineation method. These RREs have a mean average standard error of prediction (SEP) for 4-, 2-, and 1-percent AEP discharges of 53.9 percent and a mean SEP for all eight AEPs of 55.5 percent. Compared to the RREs developed in this study using the basin characteristics from the U.S. Geological Survey StreamStats application, the lidar basin characteristics provide better overall predictive accuracy.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175108","collaboration":"Prepared in cooperation with the Iowa Department of Transportation and the Iowa Highway Research Board (Project TR–692) ","usgsCitation":"Eash, D.A., Barnes, K.K., O’Shea, P.S., and Gelder, B.K., 2018, Stream-channel and watershed delineations and basin-characteristic measurements using lidar elevation data for small drainage basins within the Des Moines Lobe landform region in Iowa: U.S. Geological Survey Scientific Investigations Report 2017–5108, 23 p., https://doi.org/10.3133/sir20175108. ","productDescription":"vi, 23 p.","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-081688","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"links":[{"id":351551,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5108/coverthb.jpg"},{"id":351552,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5108/sir20175108.pdf","text":"Report","size":"1.48 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5108"}],"country":"United States","state":"Iowa","otherGeospatial":"Des Moines Lobe landform region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96,\n 41.5\n ],\n [\n -93,\n 41.5\n ],\n [\n -93,\n 43.50075243569041\n ],\n [\n -96,\n 43.50075243569041\n ],\n [\n -96,\n 41.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
400 S. Clinton St., Rm 269
Iowa City, IA 52240
Semisopochnoi Island, located in the Rat Islands group of the western Aleutian Islands and Aleutian volcanic arc, is a roughly circular island composed of scattered volcanic vents, the prominent caldera of Semisopochnoi volcano, and older, ancestral volcanic rocks. The oldest rocks on the island are gently radially dipping lavas that are the remnants of a shield volcano and of Ragged Top, which is an eroded stratocone southeast of the current caldera. None of these oldest rocks have been dated, but they all are likely Pleistocene in age. Anvil Peak, to the caldera’s north, has the morphology of a young stratocone and is latest Pleistocene to early Holocene in age. The oldest recognized Holocene deposits are those of the caldera-forming eruption, which produced the 7- by 6-km caldera in the center of the island, left nonwelded ignimbrite in valleys below the edifice, and left welded ignimbrite high on its flanks. The caldera-forming eruption produced rocks showing a range of intermediate whole-rock compositions throughout the eruption sequence, although a majority of clasts analyzed form a fairly tight cluster on SiO2-variation diagrams at 62.9 to 63.4 weight percent SiO2. This clustering of compositions at about 63 weight percent SiO2 includes black, dense, obsidian-like clasts, as well as tan, variably oxidized, highly inflated pumice clasts. The best estimate for the timing of the eruption is from a soil dated at 6,920±60 14C years before present underlying a thin facies of the ignimbrite deposit on the island’s north coast. Shortly after the caldera-forming eruption, two scoria cones on the northwest flank of the volcano outside the caldera, Ringworm crater and Threequarter Cone, simultaneously erupted small volumes of andesite.
The oldest intracaldera lavas, on the floor of the caldera, are andesitic to dacitic, but are mostly covered by younger lavas and tephras. These intracaldera lavas include the basaltic andesites of small Windy cone, as well as the more voluminous basaltic andesites of three-peaked Mount Cerberus, which takes up most of the west half of the caldera and has erupted lavas that flowed to the sea on the southwestern coast of the island. Apparently active at the same time as Mount Cerberus, extracaldera Sugarloaf Peak at the southern point of the island has exclusively erupted basalts. Its young satellite peak, Sugarloaf Head, has erupted morphologically young lavas and cinder cones and may be the source of the last historical eruption in 1987. Several tephra sections on the east half of the island record as many as 50 tephras, mostly from Mount Cerberus, Sugarloaf Peak, and Sugarloaf Head, over the past several thousand years.
Eruptive products of Semisopochnoi Island show an overall compositional range of basalt to dacite, though basaltic andesite and andesite constitute the largest proportions of rock types. They are tholeiitic, low to medium K, and have geochemical characteristics typical of magmatic arcs. The earliest Pleistocene lavas are mostly basalts that show the greatest geochemical diversity, as illustrated by, for example, LaN/YbN ratios of 1.9 to 3.5, suggesting fluctuations in the magma source region over the hundreds of thousands of years recorded by these older lavas. The Holocene rocks, in contrast, follow arrays in compositional space that suggest crystallization differentiation from discrete, subtly different batches of magma under varying pressure and temperature conditions. Increasingly negative Eu anomalies and an only modestly increasing alumina saturation index value with differentiation suggest that plagioclase and mafic silicates (amphibole and pyroxene) were involved to varying degrees in fractional crystallization to produce Semisopochnoi’s magmatic diversity. The crystal-poor, andesitic magmas that erupted during caldera formation likely separated from a plagioclase-, amphibole-, and clinopyroxene-dominated crystal residue in the upper crust at less than 900 °C, possibly following a period of decreased magmatic flux. During the Holocene, basaltic Sugarloaf Peak appears to bypass any upper crustal magmatic storage region and erupt crystal-rich basalts. Recent seismic swarms and long-lived warm springs attest to ongoing magmatic activity.
The Holocene eruptive record at Semisopochnoi volcano is one of diverse eruptive styles as well as frequent eruptions from multiple vents located within and outside the caldera. The number and diversity of postcaldera vents means that the sites of future eruptions cannot be predicted with certainty. Future eruptions of ash similar in magnitude to the VEI 3 or less eruptions recorded in the documented tephra deposits would pose a hazard to aircraft in the region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175150","usgsCitation":"Coombs, M.L., Larsen, J.F., and Neal, C.A., 2018, Postglacial eruptive history and geochemistry of Semisopochnoi volcano, western Aleutian Islands, Alaska: U.S. Geological Survey Scientific Investigations Report 2017–5150, 33 p., https://doi.org/10.3133/sir20175150.","productDescription":"Report: iv, 33 p.; 2 Tables","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-067229","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":438015,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P925UXOR","text":"USGS data release","linkHelpText":"Digital geologic map data for Semisopochnoi Island, Alaska"},{"id":351618,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5150/sir20175150_table2.xlsx","text":"Table 2","size":"65 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017-5150","linkHelpText":" - Matrix-glass compositions of pyroclasts from Semisopochnoi volcano and Amchitka Island, Alaska, as determined by electron microprobe"},{"id":351617,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5150/sir20175150_table1.xlsx","text":"Table 1","size":"100 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017-5150","linkHelpText":" - Whole-rock compositions, locations, and descriptions of lava and tephra samples from Semisopochnoi Island, Alaska"},{"id":351615,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5150/coverthb.jpg"},{"id":351616,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5150/sir20175150.pdf","text":"Report","size":"15 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5150"}],"country":"United States","state":"Alaska","otherGeospatial":"Semisopochnoi Volcano","contact":"Alaska Volcano Observatory
U.S. Geological Survey
4210 University Drive
Anchorage, AK 99508
Gill disease in Atlantic salmon, Salmo salar L., causes big losses in the salmon farming industry. Until now, tools to cultivate microorganisms causing gill disease and models to study the gill responses have been lacking. Here we describe the establishment and characterization of two cell lines from the gills of Atlantic salmon. Atlantic salmon gill cell ASG-10 consisted of cells staining for cytokeratin and e-cadherin and with desmosomes as seen by transmission electron microscopy suggesting the cells to be of epithelial origin. These structures were not seen in ASG-13. The cell lines have been maintained for almost 30 passages and both cell lines are fully susceptible to infection by infectious hematopoietic necrosis virus (IHNV), viral hemorrhagic septicemia virus (VHSV), infectious pancreatic necrosis virus (IPNV), Atlantic salmon reovirus TS (TSRV) and Pacific salmon paramyxovirus (PSPV). While infectious salmon anemia virus (ISAV) did not cause visible CPE, immunofluorescent staining revealed a sub-fraction of cells in both the ASG-10 and ASG-13 lines may be permissive to infection. ASG-10 is able to proliferate and migrate to close scratches in the monolayer within seven days in vitro contrary to ASG-13, which does not appear to do have the same proliferative and migratory ability. These cell lines will be useful in studies of gill diseases in Atlantic salmon and may represent an important contribution for alternatives to experimental animals and studies of epithelial–mesenchymal cell biology.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0191792","usgsCitation":"Gjessing, M.C., Aamelfot, M., Batts, W.N., Benestad, S.L., Dale, O.B., Thoen, E., Weli, S.C., and Winton, J.R., 2018, Development and characterization of two cell lines from gills of Atlantic salmon: PLoS ONE, v. 13, no. 2, p. 1-13, https://doi.org/10.1371/journal.pone.0191792.","productDescription":"e0191792; 13 p.","startPage":"1","endPage":"13","ipdsId":"IP-092153","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":468999,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0191792","text":"Publisher Index Page"},{"id":353161,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-14","publicationStatus":"PW","scienceBaseUri":"5afee72ee4b0da30c1bfc18c","contributors":{"authors":[{"text":"Gjessing, Mona C.","contributorId":203944,"corporation":false,"usgs":false,"family":"Gjessing","given":"Mona","email":"","middleInitial":"C.","affiliations":[{"id":36770,"text":"Norwegian Veterinary Institute, Oslo, Norway","active":true,"usgs":false}],"preferred":false,"id":732696,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aamelfot, Maria","contributorId":203945,"corporation":false,"usgs":false,"family":"Aamelfot","given":"Maria","email":"","affiliations":[{"id":36770,"text":"Norwegian Veterinary Institute, Oslo, Norway","active":true,"usgs":false}],"preferred":false,"id":732697,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Batts, William N. 0000-0002-6469-9004 bbatts@usgs.gov","orcid":"https://orcid.org/0000-0002-6469-9004","contributorId":3815,"corporation":false,"usgs":true,"family":"Batts","given":"William","email":"bbatts@usgs.gov","middleInitial":"N.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":732695,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Benestad, Sylvie L.","contributorId":203946,"corporation":false,"usgs":false,"family":"Benestad","given":"Sylvie","email":"","middleInitial":"L.","affiliations":[{"id":36770,"text":"Norwegian Veterinary Institute, Oslo, Norway","active":true,"usgs":false}],"preferred":false,"id":732698,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dale, Ole B.","contributorId":127582,"corporation":false,"usgs":false,"family":"Dale","given":"Ole","email":"","middleInitial":"B.","affiliations":[{"id":7064,"text":"Norwegian Veterinary Institute, Ullevalsveien 68, Oslo, Norway","active":true,"usgs":false}],"preferred":false,"id":732699,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thoen, Even","contributorId":203947,"corporation":false,"usgs":false,"family":"Thoen","given":"Even","email":"","affiliations":[{"id":36771,"text":"Norwegian University of Life Sciences, Oslo, Norway","active":true,"usgs":false}],"preferred":false,"id":732700,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Weli, Simon C.","contributorId":203948,"corporation":false,"usgs":false,"family":"Weli","given":"Simon","email":"","middleInitial":"C.","affiliations":[{"id":36770,"text":"Norwegian Veterinary Institute, Oslo, Norway","active":true,"usgs":false}],"preferred":false,"id":732701,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Winton, James R. 0000-0002-3505-5509 jwinton@usgs.gov","orcid":"https://orcid.org/0000-0002-3505-5509","contributorId":1944,"corporation":false,"usgs":true,"family":"Winton","given":"James","email":"jwinton@usgs.gov","middleInitial":"R.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":732694,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70247739,"text":"70247739 - 2018 - On the depth extent of co-seismic rupture","interactions":[],"lastModifiedDate":"2023-08-15T14:24:25.063401","indexId":"70247739","displayToPublicDate":"2018-02-13T09:21:08","publicationYear":"2018","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":"On the depth extent of co-seismic rupture","docAbstract":"We investigate the implications of deformation experiments for the coseismic down‐dip extent of rupture in quasi‐dynamic, whole‐cycle earthquake models of a fault for which the depth of the transition between seismic and aseisimic fault slip depends on strain rate. The calculations use a dislocation fault model from Tse and Rice (1986) with a vertical strike‐slip orientation, mode III rupture, and variable along‐strike length. Our reference calculation is the original rheological representation of Tse and Rice with a strain‐rate‐independent transition. The primary calculations use two different representations of a strain‐rate‐dependent transition: (1) between rate‐weakening friction and dislocation creep and (2) between rate‐weakening and rate‐strengthening frictions. For both these cases, when fault strength is high (friction between 0.5 and 0.6) and the transition is sharp, coseismic slip extends a small distance (1–2 km) below the fixed temperature (depth) that is commonly used to define the rheological transition at the plate‐motion rate. Thus, coseismic slip occurs below the depth assumed in seismic hazard models using microseismicity or a chosen fixed‐temperature contour. Though significant coseismic slip occurs below the plate‐rate transition depth, the added moment is
The processes and biomass that characterize any ecosystem are fundamentally constrained by the total amount of energy that is either fixed within or delivered across its boundaries. Ultimately, ecosystems may be understood and classified by their rates of total and net productivity and by the seasonal patterns of photosynthesis and respiration. Such understanding is well developed for terrestrial and lentic ecosystems but our understanding of ecosystem phenology has lagged well behind for rivers. The proliferation of reliable and inexpensive sensors for monitoring dissolved oxygen and carbon dioxide is underpinning a revolution in our understanding of the ecosystem energetics of rivers. Here, we synthesize our current understanding of the drivers and constraints on river metabolism, and set out a research agenda aimed at characterizing, classifying and modeling the current and future metabolic regimes of flowing waters.
","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lno.10726","usgsCitation":"Bernhardt, E., Heffernan, J.B., Grimm, N.B., Stanley, E.H., Harvey, J., Arroita, M., Appling, A.P., Cohen, M., McDowell, W.H., Hall, R., Read, J.S., Roberts, B., Stets, E.G., and Yackulic, C.B., 2018, The metabolic regimes of flowing waters: Limnology and Oceanography, v. 63, no. S1, p. S99-S118, https://doi.org/10.1002/lno.10726.","productDescription":"20 p.","startPage":"S99","endPage":"S118","ipdsId":"IP-090174","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":461041,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lno.10726","text":"Publisher Index Page"},{"id":351535,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"63","issue":"S1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-12","publicationStatus":"PW","scienceBaseUri":"5afee730e4b0da30c1bfc19c","contributors":{"authors":[{"text":"Bernhardt, Emily S.","contributorId":92143,"corporation":false,"usgs":false,"family":"Bernhardt","given":"Emily S.","affiliations":[{"id":27331,"text":"Duke University, Durham, NC","active":true,"usgs":false}],"preferred":false,"id":728399,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heffernan, Jim B.","contributorId":202432,"corporation":false,"usgs":false,"family":"Heffernan","given":"Jim","email":"","middleInitial":"B.","affiliations":[{"id":36435,"text":"Nicholas School of the Environment, Duke University","active":true,"usgs":false}],"preferred":false,"id":728398,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grimm, Nancy B.","contributorId":44058,"corporation":false,"usgs":false,"family":"Grimm","given":"Nancy","email":"","middleInitial":"B.","affiliations":[{"id":24511,"text":"Arizona State University, Tempe AZ USA 85287","active":true,"usgs":false}],"preferred":false,"id":728400,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stanley, Emily H.","contributorId":55725,"corporation":false,"usgs":false,"family":"Stanley","given":"Emily","email":"","middleInitial":"H.","affiliations":[{"id":12951,"text":"Center for Limnology, University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":728401,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harvey, Judson 0000-0002-2654-9873 jwharvey@usgs.gov","orcid":"https://orcid.org/0000-0002-2654-9873","contributorId":140228,"corporation":false,"usgs":true,"family":"Harvey","given":"Judson","email":"jwharvey@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - 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Without humans or other land mammals, diverse and peculiar birds evolved in isolation, including several flightless moa species, the giant pouakai eagle (Harpagornis moorei), the kiwi (Apteryx mantelli), and the kakapo parrot (Strigops habroptila). This unique community has fascinated paleoecologists, who have spent almost two centuries devising new ways to glean information from ancient bird remains. In PNAS, Boast et al. (1) apply one recent technological advance, ancient DNA (aDNA) metabarcoding, to confirm previous discoveries and report new details about moa and kakapo diets, parasites, and niches. Their efforts confirm Zealandia was a lot different before humans arrived.
","language":"English","publisher":"National Academy of Sciences of United States of America","doi":"10.1073/pnas.1722598115","usgsCitation":"Lafferty, K.D., and Hopkins, S.R., 2018, Unique parasite aDNA in moa coprolites from New Zealand suggests mass parasite extinctions followed human-induced megafauna extinctions: PNAS, v. 115, no. 7, p. 1411-1413, https://doi.org/10.1073/pnas.1722598115.","productDescription":"3 p.","startPage":"1411","endPage":"1413","ipdsId":"IP-093819","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":469003,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.1722598115","text":"Publisher Index Page"},{"id":352774,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"115","issue":"7","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-13","publicationStatus":"PW","scienceBaseUri":"5afee730e4b0da30c1bfc198","contributors":{"authors":[{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":731685,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hopkins, Skylar R.","contributorId":203515,"corporation":false,"usgs":false,"family":"Hopkins","given":"Skylar","email":"","middleInitial":"R.","affiliations":[{"id":36642,"text":"National Center for Ecological Analysis and Synthesis, Santa Barbara,","active":true,"usgs":false}],"preferred":false,"id":731686,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70195383,"text":"70195383 - 2018 - Beyond clay: Towards an improved set of variables for predicting soil organic matter content","interactions":[],"lastModifiedDate":"2018-02-22T13:00:21","indexId":"70195383","displayToPublicDate":"2018-02-13T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1007,"text":"Biogeochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Beyond clay: Towards an improved set of variables for predicting soil organic matter content","docAbstract":"Improved quantification of the factors controlling soil organic matter (SOM) stabilization at continental to global scales is needed to inform projections of the largest actively cycling terrestrial carbon pool on Earth, and its response to environmental change. Biogeochemical models rely almost exclusively on clay content to modify rates of SOM turnover and fluxes of climate-active CO2 to the atmosphere. Emerging conceptual understanding, however, suggests other soil physicochemical properties may predict SOM stabilization better than clay content. We addressed this discrepancy by synthesizing data from over 5,500 soil profiles spanning continental scale environmental gradients. Here, we demonstrate that other physicochemical parameters are much stronger predictors of SOM content, with clay content having relatively little explanatory power. We show that exchangeable calcium strongly predicted SOM content in water-limited, alkaline soils, whereas with increasing moisture availability and acidity, iron- and aluminum-oxyhydroxides emerged as better predictors, demonstrating that the relative importance of SOM stabilization mechanisms scales with climate and acidity. These results highlight the urgent need to modify biogeochemical models to better reflect the role of soil physicochemical properties in SOM cycling.
","language":"English","publisher":"Springer","doi":"10.1007/s10533-018-0424-3","usgsCitation":"Rasmussen, C., Heckman, K., Wieder, W.R., Keiluweit, M., Lawrence, C.R., Berhe, A., Blankinship, J.C., Crow, S.E., Druhan, J., Hicks Pries, C.E., Marin-Spiotta, E., Plante, A.F., Schadel, C., Schmiel, J.P., Sierra, C., Thompson, A., and Wagai, R., 2018, Beyond clay: Towards an improved set of variables for predicting soil organic matter content: Biogeochemistry, v. 137, no. 3, p. 297-306, https://doi.org/10.1007/s10533-018-0424-3.","productDescription":"10 p.","startPage":"297","endPage":"306","ipdsId":"IP-092121","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":461045,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10533-018-0424-3","text":"Publisher Index 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We developed nine questions reflecting the application of fundamental research topics in landscape ecology to the landscape planning process and reviewed two recent landscape-scale plans in western North America for evidence of these concepts in plan decisions. Both plans considered multiple resources, uses, and values, including energy development, recreation, conservation, and protection of cultural and historic resources. We found that land use change and multiscale perspectives of resource uses and values were very often apparent in planning decisions. Pattern-process relationships, connectivity and fragmentation, ecosystem services, landscape history, and climate change were reflected less frequently. Landscape sustainability was considered only once in the 295 decisions reviewed, and outputs of landscape models were not referenced. We suggest six actionable opportunities for further integrating landscape ecology concepts into landscape planning efforts: 1) use landscape sustainability as an overarching goal, 2) adopt a broad ecosystem services framework, 3) explore the role of landscape history more comprehensively, 4) regularly consider and accommodate potential effects of climate change, 5) use landscape models to support plan decisions, and 6) promote a greater presence of landscape ecologists within agencies that manage large land bases and encourage active involvement in agency planning efforts. Together these actions may improve the defensibility, durability, and sustainability of landscape plan decisions.
","language":"English","publisher":"Springer","doi":"10.1007/s40823-018-0029-5","usgsCitation":"Trammel, E.J., Carter, S.K., Haby, T.S., and Taylor, J.J., 2018, Evidence and opportunities for integrating landscape ecology into natural resource planning across multiple-use landscapes: Current Landscape Ecology Reports, v. 3, no. 1, p. 1-11, https://doi.org/10.1007/s40823-018-0029-5.","productDescription":"11 p.","startPage":"1","endPage":"11","ipdsId":"IP-086644","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":351523,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-16","publicationStatus":"PW","scienceBaseUri":"5afee731e4b0da30c1bfc1a0","contributors":{"authors":[{"text":"Trammel, E. Jamie","contributorId":202408,"corporation":false,"usgs":false,"family":"Trammel","given":"E.","email":"","middleInitial":"Jamie","affiliations":[{"id":36420,"text":"University of Alaska - Anchorage","active":true,"usgs":false}],"preferred":false,"id":728339,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carter, Sarah K. 0000-0003-3778-8615","orcid":"https://orcid.org/0000-0003-3778-8615","contributorId":192418,"corporation":false,"usgs":true,"family":"Carter","given":"Sarah","email":"","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":728338,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haby, Travis S. 0000-0003-2204-9967","orcid":"https://orcid.org/0000-0003-2204-9967","contributorId":138831,"corporation":false,"usgs":false,"family":"Haby","given":"Travis","email":"","middleInitial":"S.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":728340,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Taylor, Jason J.","contributorId":202410,"corporation":false,"usgs":false,"family":"Taylor","given":"Jason","email":"","middleInitial":"J.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":728341,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70195403,"text":"70195403 - 2018 - Estimating floodwater depths from flood inundation maps and topography","interactions":[],"lastModifiedDate":"2018-08-03T16:20:24","indexId":"70195403","displayToPublicDate":"2018-02-13T00:00:00","publicationYear":"2018","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":"Estimating floodwater depths from flood inundation maps and topography","docAbstract":"Information on flood inundation extent is important for understanding societal exposure, water storage volumes, flood wave attenuation, future flood hazard, and other variables. A number of organizations now provide flood inundation maps based on satellite remote sensing. These data products can efficiently and accurately provide the areal extent of a flood event, but do not provide floodwater depth, an important attribute for first responders and damage assessment. Here we present a new methodology and a GIS-based tool, the Floodwater Depth Estimation Tool (FwDET), for estimating floodwater depth based solely on an inundation map and a digital elevation model (DEM). We compare the FwDET results against water depth maps derived from hydraulic simulation of two flood events, a large-scale event for which we use medium resolution input layer (10 m) and a small-scale event for which we use a high-resolution (LiDAR; 1 m) input. Further testing is performed for two inundation maps with a number of challenging features that include a narrow valley, a large reservoir, and an urban setting. The results show FwDET can accurately calculate floodwater depth for diverse flooding scenarios but also leads to considerable bias in locations where the inundation extent does not align well with the DEM. In these locations, manual adjustment or higher spatial resolution input is required.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12609","usgsCitation":"Cohen, S., Brakenridge, G.R., Kettner, A., Bates, B., Nelson, J.M., McDonald, R.R., Huang, Y., Munasinghe, D., and Zhang, J., 2018, Estimating floodwater depths from flood inundation maps and topography: Journal of the American Water Resources Association, v. 54, no. 4, p. 847-858, https://doi.org/10.1111/1752-1688.12609.","productDescription":"12 p.","startPage":"847","endPage":"858","ipdsId":"IP-085532","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":469000,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.12609","text":"Publisher Index Page"},{"id":351559,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"54","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-17","publicationStatus":"PW","scienceBaseUri":"5afee730e4b0da30c1bfc19a","contributors":{"authors":[{"text":"Cohen, Sagy","contributorId":202461,"corporation":false,"usgs":false,"family":"Cohen","given":"Sagy","email":"","affiliations":[{"id":36450,"text":"Department of Geography, University of Alabama, Tuscaloosa, AL 35487, USA","active":true,"usgs":false}],"preferred":false,"id":728452,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brakenridge, G. Robert","contributorId":202462,"corporation":false,"usgs":false,"family":"Brakenridge","given":"G.","email":"","middleInitial":"Robert","affiliations":[{"id":36451,"text":"Institute of Arctic and Alpine Research, University of Colorado, Boulder, CO 80309, USA","active":true,"usgs":false}],"preferred":false,"id":728453,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kettner, Albert","contributorId":202463,"corporation":false,"usgs":false,"family":"Kettner","given":"Albert","affiliations":[{"id":36451,"text":"Institute of Arctic and Alpine Research, University of Colorado, Boulder, CO 80309, USA","active":true,"usgs":false}],"preferred":false,"id":728454,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bates, Bradford","contributorId":202464,"corporation":false,"usgs":false,"family":"Bates","given":"Bradford","email":"","affiliations":[{"id":36450,"text":"Department of Geography, University of Alabama, Tuscaloosa, AL 35487, USA","active":true,"usgs":false}],"preferred":false,"id":728455,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nelson, Jonathan M. 0000-0002-7632-8526 jmn@usgs.gov","orcid":"https://orcid.org/0000-0002-7632-8526","contributorId":2812,"corporation":false,"usgs":true,"family":"Nelson","given":"Jonathan","email":"jmn@usgs.gov","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":728451,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McDonald, Richard R. 0000-0002-0703-0638 rmcd@usgs.gov","orcid":"https://orcid.org/0000-0002-0703-0638","contributorId":2428,"corporation":false,"usgs":true,"family":"McDonald","given":"Richard","email":"rmcd@usgs.gov","middleInitial":"R.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":728456,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Huang, Yu-Fen","contributorId":202465,"corporation":false,"usgs":false,"family":"Huang","given":"Yu-Fen","email":"","affiliations":[{"id":36452,"text":"University of Hawaii at Manoa, HI 96822, USA","active":true,"usgs":false}],"preferred":false,"id":728457,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Munasinghe, Dinuke","contributorId":202466,"corporation":false,"usgs":false,"family":"Munasinghe","given":"Dinuke","email":"","affiliations":[{"id":36450,"text":"Department of Geography, University of Alabama, Tuscaloosa, AL 35487, USA","active":true,"usgs":false}],"preferred":false,"id":728458,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Zhang, Jiaqi","contributorId":202467,"corporation":false,"usgs":false,"family":"Zhang","given":"Jiaqi","email":"","affiliations":[{"id":36453,"text":"University of Texas, Arlington, TX, USA","active":true,"usgs":false}],"preferred":false,"id":728459,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70195382,"text":"70195382 - 2018 - Coastal knickpoints and the competition between fluvial and wave-driven erosion on rocky coastlines","interactions":[],"lastModifiedDate":"2018-02-13T10:42:23","indexId":"70195382","displayToPublicDate":"2018-02-13T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Coastal knickpoints and the competition between fluvial and wave-driven erosion on rocky coastlines","docAbstract":"Active margin coastlines are distinguished by rock erosion that acts in two different directions: waves erode the coast horizontally or landwards, a process that creates sea cliffs; and rivers and streams erode the landscape vertically via channel incision. The relative rates of each process exert a dominant control on coastline morphology. Using a model of river channel incision and sea-cliff retreat, we explore how terrestrial and marine erosion compete to shape coastal topography, and specifically what conditions encourage the development of coastal knickpoints (i.e., a river or stream channels that end at a raised sea-cliff edge). We then compare results to actual landscapes. Model results and observations show that coastal knickpoint development is strongly dependent on drainage basin area, where knickpoints typically occur in drainage basins smaller than 5 × 105–6 × 106 m2, as well as channel geometry and sea-cliff retreat rate. In our study area, coastal knickpoints with persistent flow (waterfalls) are uncommon and form only within a small morphological window when 1) drainage basin area is large enough to sustain steady stream discharge, but not large enough to out-compete sea-cliff formation, 2) sea-cliff retreat is rapid, and 3) channel concavity is low so that channel slopes at the coast are high. This particular geomorphic combination can sustain sea-cliff formation even when streams tap into larger drainage basins with greater discharge and more stream power, and provides an initial explanation of why persistent coastal waterfalls are, along many coastlines, relatively rare features.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2017.12.035","usgsCitation":"Limber, P.W., and Barnard, P., 2018, Coastal knickpoints and the competition between fluvial and wave-driven erosion on rocky coastlines: Geomorphology, v. 306, p. 1-12, https://doi.org/10.1016/j.geomorph.2017.12.035.","productDescription":"12 p.","startPage":"1","endPage":"12","ipdsId":"IP-085956","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469001,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geomorph.2017.12.035","text":"Publisher Index Page"},{"id":351512,"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 -124.67285156250001,\n 34.252676117101515\n ],\n [\n -119.72900390625001,\n 34.252676117101515\n ],\n [\n -119.72900390625001,\n 40.48038142908172\n ],\n [\n -124.67285156250001,\n 40.48038142908172\n ],\n [\n -124.67285156250001,\n 34.252676117101515\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"306","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee731e4b0da30c1bfc1a4","contributors":{"authors":[{"text":"Limber, Patrick W. 0000-0002-8207-3750 plimber@usgs.gov","orcid":"https://orcid.org/0000-0002-8207-3750","contributorId":196794,"corporation":false,"usgs":true,"family":"Limber","given":"Patrick","email":"plimber@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":728286,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":147147,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","email":"pbarnard@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":728287,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70195380,"text":"70195380 - 2018 - Stress rotation across the Cascadia megathrust requires a weak subduction plate boundary at seismogenic depths","interactions":[],"lastModifiedDate":"2018-02-13T11:43:43","indexId":"70195380","displayToPublicDate":"2018-02-13T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Stress rotation across the Cascadia megathrust requires a weak subduction plate boundary at seismogenic depths","docAbstract":"The Mendocino Triple Junction region is the most seismically active part of the Cascadia Subduction Zone. The northward moving Pacific plate collides with the subducting Gorda plate causing intense internal deformation within it. Here we show that the stress field rotates rapidly with depth across the thrust interface from a strike-slip regime within the subducting plate, reflecting the Pacific plate collision, to a thrust regime in the overriding plate. We utilize a dense focal mechanism dataset, including observations from the Cascadia Initiative ocean bottom seismograph experiment, to constrain the stress orientations. To quantify the implications of this rotation for the strength of the plate boundary, we designed an inversion that solves for the absolute stress tensors in a three-layer model subject to assumptions about the strength of the subducting mantle. Our results indicate that the shear stress on the plate boundary fault is likely no more than about ∼50 MPa at ∼20 km depth. Regardless of the assumed mantle strength, we infer a relatively weak megathrust fault with an effective friction coefficient of ∼0 to 0.2 at seismogenic depths. Such a low value for the effective friction coefficient requires a combination of high fluid pressures and/or fault-zone minerals with low inherent friction in the region where a great earthquake is expected in Cascadia.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2018.01.002","usgsCitation":"Li, D., McGuire, J.J., Liu, Y., and Hardebeck, J.L., 2018, Stress rotation across the Cascadia megathrust requires a weak subduction plate boundary at seismogenic depths: Earth and Planetary Science Letters, v. 485, p. 55-64, https://doi.org/10.1016/j.epsl.2018.01.002.","productDescription":"10 p.","startPage":"55","endPage":"64","ipdsId":"IP-088612","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":469002,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2018.01.002","text":"Publisher Index Page"},{"id":351522,"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 -125.2,\n 41.2\n ],\n [\n -123.6,\n 41.2\n ],\n [\n -123.6,\n 40\n ],\n [\n -125.2,\n 40\n ],\n [\n -125.2,\n 41.2\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"485","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee731e4b0da30c1bfc1a6","contributors":{"authors":[{"text":"Li, Duo","contributorId":202366,"corporation":false,"usgs":false,"family":"Li","given":"Duo","email":"","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":728275,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGuire, Jeffrey J. 0000-0001-9235-2166 jmcguire@whoi.edu","orcid":"https://orcid.org/0000-0001-9235-2166","contributorId":177447,"corporation":false,"usgs":false,"family":"McGuire","given":"Jeffrey","email":"jmcguire@whoi.edu","middleInitial":"J.","affiliations":[{"id":6706,"text":"Woods Hole Oceanographic Institution,","active":true,"usgs":false}],"preferred":false,"id":728276,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liu, Yajing","contributorId":202367,"corporation":false,"usgs":false,"family":"Liu","given":"Yajing","email":"","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":728277,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hardebeck, Jeanne L. 0000-0002-6737-7780 jhardebeck@usgs.gov","orcid":"https://orcid.org/0000-0002-6737-7780","contributorId":841,"corporation":false,"usgs":true,"family":"Hardebeck","given":"Jeanne","email":"jhardebeck@usgs.gov","middleInitial":"L.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":728274,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}