{"pageNumber":"447","pageRowStart":"11150","pageSize":"25","recordCount":40797,"records":[{"id":70189348,"text":"70189348 - 2017 - Variability of runoff-based drought conditions in the conterminous United States","interactions":[],"lastModifiedDate":"2017-08-29T09:35:36","indexId":"70189348","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2032,"text":"International Journal of Climatology","active":true,"publicationSubtype":{"id":10}},"title":"Variability of runoff-based drought conditions in the conterminous United States","docAbstract":"<p><span>In this study, a monthly water-balance model is used to simulate monthly runoff for 2109 hydrologic units (HUs) in the conterminous United States (CONUS) for water-years 1901 through 2014. The monthly runoff time series for each HU were smoothed with a 3-month moving average, and then the 3-month moving-average runoff values were converted to percentiles. For each HU, a drought was considered to occur when the HU runoff percentile dropped to the 20th percentile or lower. A drought was considered to end when the HU runoff percentile exceeded the 20th percentile. After identifying drought events for each HU, the frequency and length of drought events were examined. Results indicated that (1) the longest mean drought lengths occur in the eastern CONUS and parts of the Rocky Mountain region and the northwestern CONUS, (2) the frequency of drought is highest in the southwestern and central CONUS, and lowest in the eastern CONUS, the Rocky Mountain region, and the northwestern CONUS, (3) droughts have occurred during all months of the year and there does not appear to be a seasonal pattern to drought occurrence, (4) the variability of precipitation appears to have been the principal climatic factor determining drought, and (5) for most of the CONUS, drought frequency appears to have decreased during the 1901 through 2014 period.</span></p>","language":"English","publisher":"Royal Meteorological Society","doi":"10.1002/joc.4756","usgsCitation":"McCabe, G., Wolock, D.M., and Austin, S.H., 2017, Variability of runoff-based drought conditions in the conterminous United States: International Journal of Climatology, v. 37, no. 2, p. 1014-1021, https://doi.org/10.1002/joc.4756.","productDescription":"8 p.","startPage":"1014","endPage":"1021","ipdsId":"IP-073812","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":343608,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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 \"}}]}\n","volume":"37","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-06","publicationStatus":"PW","scienceBaseUri":"5965b227e4b0d1f9f05b37dd","contributors":{"authors":[{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":167116,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory J.","email":"gmccabe@usgs.gov","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":false,"id":704314,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wolock, David M. 0000-0002-6209-938X dwolock@usgs.gov","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":540,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"dwolock@usgs.gov","middleInitial":"M.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":704315,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Austin, Samuel H. 0000-0001-5626-023X saustin@usgs.gov","orcid":"https://orcid.org/0000-0001-5626-023X","contributorId":153,"corporation":false,"usgs":true,"family":"Austin","given":"Samuel","email":"saustin@usgs.gov","middleInitial":"H.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":704316,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70191538,"text":"70191538 - 2017 - Compartmentalization of the Coso East Flank geothermal field imaged by 3-D full-tensor MT inversion","interactions":[],"lastModifiedDate":"2017-10-17T11:10:13","indexId":"70191538","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"Compartmentalization of the Coso East Flank geothermal field imaged by 3-D full-tensor MT inversion","docAbstract":"<p><span>Previous magnetotelluric (MT) studies of the high-temperature Coso geothermal system in California identified a subvertical feature of low resistivity (2–5&nbsp;Ohm m) and appreciable lateral extent (&gt;1&nbsp;km) in the producing zone of the East Flank field. However, these models could not reproduce gross 3-D effects in the recorded data. We perform 3-D full-tensor inversion and retrieve a resistivity model that out-performs previous 2-D and 3-D off-diagonal models in terms of its fit to the complete 3-D MT data set as well as the degree of modelling bias. Inclusion of secondary&nbsp;</span><i>Z</i><sub><i>xx</i></sub><span><span>&nbsp;</span>and<span>&nbsp;</span></span><i>Z</i><sub><i>yy</i></sub><span><span>&nbsp;</span>data components leads to a robust east-dip (60†) to the previously identified conductive East Flank reservoir feature, which correlates strongly with recently mapped surface faults, downhole well temperatures, 3-D seismic reflection data, and local microseismicity. We perform synthetic forward modelling to test the best-fit dip of this conductor using the response at a nearby MT station. We interpret the dipping conductor as a fractured and fluidized compartment, which is structurally controlled by an unmapped blind East Flank fault zone.</span></p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/gji/ggw408","usgsCitation":"Lindsey, N.J., Kaven, J., Davatzes, N.C., and Newman, G.A., 2017, Compartmentalization of the Coso East Flank geothermal field imaged by 3-D full-tensor MT inversion: Geophysical Journal International, v. 208, no. 2, p. 652-662, https://doi.org/10.1093/gji/ggw408.","productDescription":"11 p.","startPage":"652","endPage":"662","ipdsId":"IP-073610","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":470088,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gji/ggw408","text":"Publisher Index Page"},{"id":346680,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Coso Range","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.8,\n              36\n            ],\n            [\n              -117.725,\n              36\n            ],\n            [\n              -117.725,\n              36.075\n            ],\n            [\n              -117.8,\n              36.075\n            ],\n            [\n              -117.8,\n              36\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"208","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-05","publicationStatus":"PW","scienceBaseUri":"59e71692e4b05fe04cd331b1","contributors":{"authors":[{"text":"Lindsey, Nathaniel J.","contributorId":197138,"corporation":false,"usgs":false,"family":"Lindsey","given":"Nathaniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":712679,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kaven, J. Ole 0000-0003-2625-2786 okaven@usgs.gov","orcid":"https://orcid.org/0000-0003-2625-2786","contributorId":3993,"corporation":false,"usgs":true,"family":"Kaven","given":"J. Ole","email":"okaven@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":712678,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davatzes, Nicholas C.","contributorId":138855,"corporation":false,"usgs":false,"family":"Davatzes","given":"Nicholas","email":"","middleInitial":"C.","affiliations":[{"id":12547,"text":"Temple University","active":true,"usgs":false}],"preferred":false,"id":712680,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Newman, Gregory A.","contributorId":197140,"corporation":false,"usgs":false,"family":"Newman","given":"Gregory","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":712681,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70182235,"text":"70182235 - 2017 - Predicting animal home-range structure and transitions using a multistate Ornstein-Uhlenbeck biased random walk","interactions":[],"lastModifiedDate":"2018-03-26T12:17:16","indexId":"70182235","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Predicting animal home-range structure and transitions using a multistate Ornstein-Uhlenbeck biased random walk","docAbstract":"<div class=\"article-section__content n/a main\"><p>The home‐range concept is central in animal ecology and behavior, and numerous mechanistic models have been developed to understand home range formation and maintenance. These mechanistic models usually assume a single, contiguous home range. Here we describe and implement a simple home‐range model that can accommodate multiple home‐range centers, form complex shapes, allow discontinuities in use patterns, and infer how external and internal variables affect movement and use patterns. The model assumes individuals associate with two or more home‐range centers and move among them with some estimable probability. Movement in and around home‐range centers is governed by a two‐dimensional Ornstein‐Uhlenbeck process, while transitions between centers are modeled as a stochastic state‐switching process. We augmented this base model by introducing environmental and demographic covariates that modify transition probabilities between home‐range centers and can be estimated to provide insight into the movement process. We demonstrate the model using telemetry data from sea otters (<i>Enhydra lutris</i>) in California. The model was fit using a Bayesian Markov Chain Monte Carlo method, which estimated transition probabilities, as well as unique Ornstein‐Uhlenbeck diffusion and centralizing tendency parameters. Estimated parameters could then be used to simulate movement and space use that was virtually indistinguishable from real data. We used Deviance Information Criterion (DIC) scores to assess model fit and determined that both wind and reproductive status were predictive of transitions between home‐range centers. Females were less likely to move between home‐range centers on windy days, less likely to move between centers when tending pups, and much more likely to move between centers just after weaning a pup. These tendencies are predicted by theoretical movement rules but were not previously known and show that our model can extract meaningful behavioral insight from complex movement data.</p></div>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.1615","usgsCitation":"Breed, G.A., Golson, E.A., and Tinker, M.T., 2017, Predicting animal home-range structure and transitions using a multistate Ornstein-Uhlenbeck biased random walk: Ecology, v. 98, no. 1, p. 32-47, https://doi.org/10.1002/ecy.1615.","productDescription":"16 p.","startPage":"32","endPage":"47","ipdsId":"IP-065876","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":336116,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"98","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-28","publicationStatus":"PW","scienceBaseUri":"58b002c6e4b01ccd54fb27c7","chorus":{"doi":"10.1002/ecy.1615","url":"http://dx.doi.org/10.1002/ecy.1615","publisher":"Wiley-Blackwell","authors":"Breed Greg A., Golson Emily A., Tinker M. Tim","journalName":"Ecology","publicationDate":"11/28/2016","auditedOn":"12/19/2016","publiclyAccessibleDate":"11/28/2016"},"contributors":{"authors":[{"text":"Breed, Greg A.","contributorId":181943,"corporation":false,"usgs":false,"family":"Breed","given":"Greg","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":670107,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Golson, Emily A.","contributorId":181944,"corporation":false,"usgs":false,"family":"Golson","given":"Emily","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":670108,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tinker, M. Tim 0000-0002-3314-839X ttinker@usgs.gov","orcid":"https://orcid.org/0000-0002-3314-839X","contributorId":2796,"corporation":false,"usgs":true,"family":"Tinker","given":"M.","email":"ttinker@usgs.gov","middleInitial":"Tim","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":670106,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70195839,"text":"70195839 - 2017 - Modeled ecohydrological responses to climate change at seven small watersheds in the northeastern United States","interactions":[],"lastModifiedDate":"2018-03-06T11:11:17","indexId":"70195839","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Modeled ecohydrological responses to climate change at seven small watersheds in the northeastern United States","docAbstract":"<p><span>A cross-site analysis was conducted on seven diverse, forested watersheds in the northeastern United States to evaluate hydrological responses (evapotranspiration, soil moisture, seasonal and annual streamflow, and water stress) to projections of future climate. We used output from four atmosphere–ocean general circulation models (AOGCMs; CCSM4, HadGEM2-CC, MIROC5, and MRI-CGCM3) included in Phase 5 of the Coupled Model Intercomparison Project, coupled with two Representative Concentration Pathways (RCP 8.5 and 4.5). The coarse resolution AOGCMs outputs were statistically downscaled using an asynchronous regional regression model to provide finer resolution future climate projections as inputs to the deterministic dynamic ecosystem model PnET-BGC. Simulation results indicated that projected warmer temperatures and longer growing seasons in the northeastern United States are anticipated to increase evapotranspiration across all sites, although invoking CO</span><sub>2</sub><span><span>&nbsp;</span>effects on vegetation (growth enhancement and increases in water use efficiency (WUE)) diminish this response. The model showed enhanced evapotranspiration resulted in drier growing season conditions across all sites and all scenarios in the future. Spruce-fir conifer forests have a lower optimum temperature for photosynthesis, making them more susceptible to temperature stress than more tolerant hardwood species, potentially giving hardwoods a competitive advantage in the future. However, some hardwood forests are projected to experience seasonal water stress, despite anticipated increases in precipitation, due to the higher temperatures, earlier loss of snow packs, longer growing seasons, and associated water deficits. Considering future CO</span><sub>2</sub><span>effects on WUE in the model alleviated water stress across all sites. Modeled streamflow responses were highly variable, with some sites showing significant increases in annual water yield, while others showed decreases. This variability in streamflow responses poses a challenge to water resource management in the northeastern United States. Our analyses suggest that dominant vegetation type and soil type are important attributes in determining future hydrological responses to climate change.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/gcb.13444","usgsCitation":"Pourmokhtarian, A., Driscoll, C.T., Campbell, J.L., Hayhoe, K., Stoner, A., Adams, M.B., Burns, D., Fernandez, I., Mitchell, M.J., and Shanley, J.B., 2017, Modeled ecohydrological responses to climate change at seven small watersheds in the northeastern United States: Global Change Biology, v. 23, no. 2, p. 840-856, https://doi.org/10.1111/gcb.13444.","productDescription":"17 p.","startPage":"840","endPage":"856","ipdsId":"IP-077080","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":352254,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","issue":"2","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-25","publicationStatus":"PW","scienceBaseUri":"5afee8d3e4b0da30c1bfc4ba","contributors":{"authors":[{"text":"Pourmokhtarian, Afshin","contributorId":202944,"corporation":false,"usgs":false,"family":"Pourmokhtarian","given":"Afshin","email":"","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":730243,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Driscoll, Charles T.","contributorId":167460,"corporation":false,"usgs":false,"family":"Driscoll","given":"Charles","email":"","middleInitial":"T.","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":730244,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Campbell, John L.","contributorId":178410,"corporation":false,"usgs":false,"family":"Campbell","given":"John","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":730245,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hayhoe, Katharine","contributorId":149192,"corporation":false,"usgs":false,"family":"Hayhoe","given":"Katharine","email":"","affiliations":[{"id":17667,"text":"Climate Science Center, Texas Tech University, Lubbock, Texas, United States","active":true,"usgs":false}],"preferred":false,"id":730246,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stoner, Anne M. K.","contributorId":202945,"corporation":false,"usgs":false,"family":"Stoner","given":"Anne M. K.","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":730247,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Adams, Mary Beth","contributorId":150354,"corporation":false,"usgs":false,"family":"Adams","given":"Mary","email":"","middleInitial":"Beth","affiliations":[],"preferred":false,"id":730248,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Burns, Douglas A. 0000-0001-6516-2869","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":202943,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":730242,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fernandez, Ivan","contributorId":178215,"corporation":false,"usgs":false,"family":"Fernandez","given":"Ivan","affiliations":[],"preferred":false,"id":730249,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mitchell, Myron J.","contributorId":73734,"corporation":false,"usgs":true,"family":"Mitchell","given":"Myron","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":730250,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Shanley, James B. 0000-0002-4234-3437 jshanley@usgs.gov","orcid":"https://orcid.org/0000-0002-4234-3437","contributorId":1953,"corporation":false,"usgs":true,"family":"Shanley","given":"James","email":"jshanley@usgs.gov","middleInitial":"B.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":730241,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70186151,"text":"70186151 - 2017 - Managing American Oystercatcher (<i>Haematopus palliatus</i>) population qrowth by targeting nesting season vital rates","interactions":[],"lastModifiedDate":"2017-03-30T11:16:32","indexId":"70186151","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3731,"text":"Waterbirds","onlineIssn":"19385390","printIssn":"15244695","active":true,"publicationSubtype":{"id":10}},"title":"Managing American Oystercatcher (<i>Haematopus palliatus</i>) population qrowth by targeting nesting season vital rates","docAbstract":"<p><span>In populations of long-lived species, adult survival typically has a relatively high influence on population growth. From a management perspective, however, adult survival can be difficult to increase in some instances, so other component rates must be considered to reverse population declines. In North Carolina, USA, management to conserve the American Oystercatcher (</span><i>Haematopus palliatus</i><span>) targets component vital rates related to fecundity, specifically nest and chick survival. The effectiveness of such a management approach in North Carolina was assessed by creating a three-stage female-based deterministic matrix model. Isoclines were produced from the matrix model to evaluate minimum nest and chick survival rates necessary to reverse population decline, assuming all other vital rates remained stable at mean values. Assuming accurate vital rates, breeding populations within North Carolina appear to be declining. To reverse this decline, combined nest and chick survival would need to increase from 0.14 to ≤ 0.27, a rate that appears to be attainable based on historical estimates. Results are heavily dependent on assumptions of other vital rates, most notably adult survival, revealing the need for accurate estimates of all vital rates to inform management actions. This approach provides valuable insights for evaluating conservation goals for species of concern.</span></p>","language":"English","publisher":"The Waterbird Society","doi":"10.1675/063.040.sp106","usgsCitation":"Felton, S.K., Hostetter, N.J., Pollock, K.H., and Simons, T.R., 2017, Managing American Oystercatcher (<i>Haematopus palliatus</i>) population qrowth by targeting nesting season vital rates: Waterbirds, v. 40, no. sp1, p. 44-54, https://doi.org/10.1675/063.040.sp106.","productDescription":"11 p.","startPage":"44","endPage":"54","ipdsId":"IP-071195","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":461763,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1675/063.040.sp106","text":"Publisher Index Page"},{"id":338800,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"40","issue":"sp1","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58de194ee4b02ff32c699c95","contributors":{"authors":[{"text":"Felton, Shilo K.","contributorId":190179,"corporation":false,"usgs":false,"family":"Felton","given":"Shilo","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":687694,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hostetter, Nathan J.","contributorId":171690,"corporation":false,"usgs":false,"family":"Hostetter","given":"Nathan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":687695,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pollock, Kenneth H.","contributorId":8590,"corporation":false,"usgs":false,"family":"Pollock","given":"Kenneth","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":687696,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Simons, Theodore R. 0000-0002-1884-6229 tsimons@usgs.gov","orcid":"https://orcid.org/0000-0002-1884-6229","contributorId":2623,"corporation":false,"usgs":true,"family":"Simons","given":"Theodore","email":"tsimons@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":687677,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70184967,"text":"70184967 - 2017 - Evaluating simplistic methods to understand current distributions and forecast distribution changes under climate change scenarios: An example with coypu (<i>Myocastor coypus</i>)","interactions":[],"lastModifiedDate":"2017-03-15T12:07:21","indexId":"70184967","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5071,"text":"NeoBiota","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating simplistic methods to understand current distributions and forecast distribution changes under climate change scenarios: An example with coypu (<i>Myocastor coypus</i>)","docAbstract":"<p><span>Invasive species provide a unique opportunity to evaluate factors controlling biogeographic distributions; we can consider introduction success as an experiment testing suitability of environmental conditions. Predicting potential distributions of spreading species is not easy, and forecasting potential distributions with changing climate is even more difficult. Using the globally invasive coypu (</span><i><span class=\"tn\"><span class=\"genus\">Myocastor</span> <span class=\"species\">coypus</span></span></i><span> [Molina, 1782]), we evaluate and compare the utility of a simplistic ecophysiological based model and a correlative model to predict current and future distribution. The ecophysiological model was based on winter temperature relationships with nutria survival. We developed correlative statistical models using the Software for Assisted Habitat Modeling and biologically relevant climate data with a global extent. We applied the ecophysiological based model to several global circulation model (</span><abbr id=\"ABBRID0EMF\" title=\"global circulation model\">GCM</abbr><span>) predictions for mid-century. We used global coypu introduction data to evaluate these models and to explore a hypothesized physiological limitation, finding general agreement with known coypu distribution locally and globally and support for an upper thermal tolerance threshold. Global circulation model based model results showed variability in coypu predicted distribution among </span><abbr id=\"ABBRID0EUF\" title=\"global climate projections\">GCMs</abbr><span>, but had general agreement of increasing suitable area in the USA. Our methods highlighted the dynamic nature of the edges of the coypu distribution due to climate non-equilibrium, and uncertainty associated with forecasting future distributions. Areas deemed suitable habitat, especially those on the edge of the current known range, could be used for early detection of the spread of coypu populations for management purposes. Combining approaches can be beneficial to predicting potential distributions of invasive species now and in the future and in exploring hypotheses of factors controlling distributions.</span></p>","language":"English","publisher":"Pensoft","doi":"10.3897/neobiota.32.8884","usgsCitation":"Jarnevich, C.S., Young, N.E., Sheffels, T.R., Carter, J., Systma, M.D., and Talbert, C., 2017, Evaluating simplistic methods to understand current distributions and forecast distribution changes under climate change scenarios: An example with coypu (<i>Myocastor coypus</i>): NeoBiota, v. 32, p. 107-125, https://doi.org/10.3897/neobiota.32.8884.","productDescription":"19 p.","startPage":"107","endPage":"125","ipdsId":"IP-065118","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":470099,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3897/neobiota.32.8884","text":"Publisher Index Page"},{"id":337613,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-04","publicationStatus":"PW","scienceBaseUri":"58ca52cce4b0849ce97c869a","contributors":{"authors":[{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":683741,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, Nicholas E.","contributorId":189060,"corporation":false,"usgs":false,"family":"Young","given":"Nicholas","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":683742,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sheffels, Trevor R.","contributorId":140176,"corporation":false,"usgs":false,"family":"Sheffels","given":"Trevor","email":"","middleInitial":"R.","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":683743,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carter, Jacoby 0000-0003-0110-0284 carterj@usgs.gov","orcid":"https://orcid.org/0000-0003-0110-0284","contributorId":2399,"corporation":false,"usgs":true,"family":"Carter","given":"Jacoby","email":"carterj@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":683744,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Systma, Mark D.","contributorId":140177,"corporation":false,"usgs":false,"family":"Systma","given":"Mark","email":"","middleInitial":"D.","affiliations":[{"id":13401,"text":"Portland State University, Portland Oregon","active":true,"usgs":false}],"preferred":false,"id":683745,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Talbert, Colin 0000-0002-9505-1876 talbertc@usgs.gov","orcid":"https://orcid.org/0000-0002-9505-1876","contributorId":181913,"corporation":false,"usgs":true,"family":"Talbert","given":"Colin","email":"talbertc@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":683746,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70188343,"text":"70188343 - 2017 - Modeling strong‐motion recordings of the 2010 Mw 8.8 Maule, Chile, earthquake with high stress‐drop subevents and background slip","interactions":[],"lastModifiedDate":"2017-06-06T16:25:26","indexId":"70188343","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Modeling strong‐motion recordings of the 2010 M<sub>w</sub> 8.8 Maule, Chile, earthquake with high stress‐drop subevents and background slip","title":"Modeling strong‐motion recordings of the 2010 Mw 8.8 Maule, Chile, earthquake with high stress‐drop subevents and background slip","docAbstract":"<p><span>Strong‐motion recordings of the </span><i>M</i><sub>w</sub><span>&nbsp;8.8 Maule earthquake were modeled using a compound rupture model consisting of (1)&nbsp;a background slip distribution with large correlation lengths, relatively low slip velocity, and long peak rise time of slip of about 10&nbsp;s and (2)&nbsp;high stress‐drop subevents (asperities) on the deeper portion of the rupture with moment magnitudes 7.9–8.2, high slip velocity, and rise times of slip of about 2&nbsp;s. In this model, the high‐frequency energy is not produced in the same location as the peak coseismic slip, but is generated in the deeper part of the rupture zone. Using synthetic seismograms generated for a plane‐layered velocity model, I find that the high stress‐drop subevents explain the observed Fourier spectral amplitude from about 0.1 to 1.0&nbsp;Hz. Broadband synthetics (0–10&nbsp;Hz) were calculated by combining deterministic synthetics derived from the background slip and asperities (≤1  Hz) with stochastic synthetics generated only at the asperities (≥1  Hz). The broadband synthetics produced response spectral accelerations with low bias compared to the data, for periods of 0.1–10&nbsp;s. A subevent stress drop of 200–350 bars for the high‐frequency stochastic synthetics was found to bracket the observed spectral accelerations at frequencies greater than 1&nbsp;Hz. For most of the stations, the synthetics had durations of the Arias intensity similar to the observed records.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120160127","usgsCitation":"Frankel, A.D., 2017, Modeling strong‐motion recordings of the 2010 Mw 8.8 Maule, Chile, earthquake with high stress‐drop subevents and background slip: Bulletin of the Seismological Society of America, v. 107, no. 1, p. 372-386, https://doi.org/10.1785/0120160127.","productDescription":"15 p.","startPage":"372","endPage":"386","ipdsId":"IP-074295","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":342191,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Chile","city":"Maule","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -74,\n              -33\n            ],\n            [\n              -70,\n              -33\n            ],\n            [\n              -70,\n              -39\n            ],\n            [\n              -74,\n              -39\n            ],\n            [\n              -74,\n              -33\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"107","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-22","publicationStatus":"PW","scienceBaseUri":"5937bf2ee4b0f6c2d0d9c760","contributors":{"authors":[{"text":"Frankel, Arthur D. 0000-0001-9119-6106 afrankel@usgs.gov","orcid":"https://orcid.org/0000-0001-9119-6106","contributorId":146285,"corporation":false,"usgs":true,"family":"Frankel","given":"Arthur","email":"afrankel@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":697332,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70193299,"text":"70193299 - 2017 - Quaternary displacement rates on the Meeman‐Shelby fault and Joiner ridge horst, eastern Arkansas: Results from coring Mississippi River alluvium","interactions":[],"lastModifiedDate":"2017-11-11T14:05:33","indexId":"70193299","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Quaternary displacement rates on the Meeman‐Shelby fault and Joiner ridge horst, eastern Arkansas: Results from coring Mississippi River alluvium","docAbstract":"<p>This research used coring and optically stimulated luminescence (OSL) dating of displaced, deeply buried Quaternary alluvium to determine vertical displacement rates for the Meeman‐Shelby fault and the Joiner ridge horst, two structures in northeastern Arkansas that have no modern seismicity associated with them. We drilled continuous cores of the entire alluvial section in the hanging wall of each structure, performed detailed core descriptions and analyses, and obtained three OSL ages from each core. The Meeman‐Shelby fault core consists of 36&nbsp;m of 4.3–5.2‐ka Holocene alluvium overlying 4&nbsp;m of 14.3‐ka Kennett alluvium that in turn overlies the upper part of Eocene Claiborne Group sediments at a depth of 41&nbsp;m. Seismic reflection indicates that the basal (Kennett) alluvium at the Meeman‐Shelby fault is displaced ∼28  m across the Meeman‐Shelby fault, which equates to a time‐averaged vertical displacement rate of 2  mm/yr within the last 14.3&nbsp;ka. The Joiner ridge horst core consists, in descending order, of 11&nbsp;m of 6.3‐ka Holocene alluvium, 14&nbsp;m of 11.5‐ka Morehouse alluvium, a paleosol, 6&nbsp;m of Kennett alluvium, and 4&nbsp;m of 20.3‐ka Sikeston alluvium that in turn overlies the upper part of Eocene Claiborne Group sediments at a depth of 36&nbsp;m. Lignite exploration drilling conducted in the 1970s indicates that basal (Sikeston) alluvium is displaced ∼20  m across the eastern bounding fault of the Joiner ridge horst, resulting in a time‐averaged vertical displacement rate of ∼1  mm/yr within the last 20.3&nbsp;ka. These late Quaternary displacement rates are comparable to time‐averaged displacement rates of faults within the active New Madrid seismic zone.</p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220160171","usgsCitation":"Ward, A., Counts, R.C., Van Arsdale, R., Larsen, D., and Mahan, S.A., 2017, Quaternary displacement rates on the Meeman‐Shelby fault and Joiner ridge horst, eastern Arkansas: Results from coring Mississippi River alluvium: Seismological Research Letters, v. 88, no. 2A, p. 442-455, https://doi.org/10.1785/0220160171.","productDescription":"14 p.","startPage":"442","endPage":"455","ipdsId":"IP-079369","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":348609,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas","otherGeospatial":"Mississippi River","volume":"88","issue":"2A","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-08","publicationStatus":"PW","scienceBaseUri":"5a07e93ee4b09af898c8cc07","contributors":{"authors":[{"text":"Ward, Alex","contributorId":199298,"corporation":false,"usgs":false,"family":"Ward","given":"Alex","email":"","affiliations":[{"id":17864,"text":"University of Memphis","active":true,"usgs":false}],"preferred":false,"id":718586,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Counts, Ronald C. 0000-0002-8426-1990 rcounts@usgs.gov","orcid":"https://orcid.org/0000-0002-8426-1990","contributorId":5343,"corporation":false,"usgs":true,"family":"Counts","given":"Ronald","email":"rcounts@usgs.gov","middleInitial":"C.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":718585,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Van Arsdale, Roy","contributorId":199299,"corporation":false,"usgs":false,"family":"Van Arsdale","given":"Roy","email":"","affiliations":[{"id":17864,"text":"University of Memphis","active":true,"usgs":false}],"preferred":false,"id":718587,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Larsen, Daniel","contributorId":199300,"corporation":false,"usgs":false,"family":"Larsen","given":"Daniel","email":"","affiliations":[{"id":17864,"text":"University of Memphis","active":true,"usgs":false}],"preferred":false,"id":718588,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mahan, Shannon A. 0000-0001-5214-7774 smahan@usgs.gov","orcid":"https://orcid.org/0000-0001-5214-7774","contributorId":147159,"corporation":false,"usgs":true,"family":"Mahan","given":"Shannon","email":"smahan@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":718589,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70192623,"text":"70192623 - 2017 - An integrated data model to estimate spatiotemporal occupancy, abundance, and colonization dynamics","interactions":[],"lastModifiedDate":"2018-05-13T12:10:31","indexId":"70192623","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"An integrated data model to estimate spatiotemporal occupancy, abundance, and colonization dynamics","docAbstract":"<p><span>Ecological invasions and colonizations occur dynamically through space and time. Estimating the distribution and abundance of colonizing species is critical for efficient management or conservation. We describe a statistical framework for simultaneously estimating spatiotemporal occupancy and abundance dynamics of a colonizing species. Our method accounts for several issues that are common when modeling spatiotemporal ecological data including multiple levels of detection probability, multiple data sources, and computational limitations that occur when making fine-scale inference over a large spatiotemporal domain. We apply the model to estimate the colonization dynamics of sea otters (</span><i>Enhydra lutris</i><span>) in Glacier Bay, in southeastern Alaska.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.1643","usgsCitation":"Williams, P.J., Hooten, M., Womble, J.N., Esslinger, G.G., Bower, M., and Hefley, T.J., 2017, An integrated data model to estimate spatiotemporal occupancy, abundance, and colonization dynamics: Ecology, v. 98, no. 2, p. 328-336, https://doi.org/10.1002/ecy.1643.","productDescription":"9 p.","startPage":"328","endPage":"336","ipdsId":"IP-076210","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":461769,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecy.1643","text":"Publisher Index Page"},{"id":348565,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"98","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-04","publicationStatus":"PW","scienceBaseUri":"5a06c8d2e4b09af898c8614e","contributors":{"authors":[{"text":"Williams, Perry J.","contributorId":169058,"corporation":false,"usgs":false,"family":"Williams","given":"Perry","email":"","middleInitial":"J.","affiliations":[{"id":25400,"text":"U.S. Fish and Wildlife Service, Big Oaks National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":721553,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":716573,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Womble, Jamie N.","contributorId":198631,"corporation":false,"usgs":false,"family":"Womble","given":"Jamie","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":721554,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Esslinger, George G. 0000-0002-3459-0083 gesslinger@usgs.gov","orcid":"https://orcid.org/0000-0002-3459-0083","contributorId":131009,"corporation":false,"usgs":true,"family":"Esslinger","given":"George","email":"gesslinger@usgs.gov","middleInitial":"G.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":721555,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bower, Michael R.","contributorId":44787,"corporation":false,"usgs":true,"family":"Bower","given":"Michael R.","affiliations":[],"preferred":false,"id":721556,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hefley, Trevor J.","contributorId":147146,"corporation":false,"usgs":false,"family":"Hefley","given":"Trevor","email":"","middleInitial":"J.","affiliations":[{"id":16796,"text":"Dept Fish, Wildlife & Cons Biol, Colorado St Univ, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":721557,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70180542,"text":"70180542 - 2017 - Linking dominant Hawaiian tree species to understory development in recovering pastures via impacts on soils and litter","interactions":[],"lastModifiedDate":"2018-01-04T08:31:26","indexId":"70180542","displayToPublicDate":"2017-01-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Linking dominant Hawaiian tree species to understory development in recovering pastures via impacts on soils and litter","docAbstract":"<p><span>Large areas of tropical forest have been cleared and planted with exotic grass species for use as cattle pasture. These often remain persistent grasslands after grazer removal, which is problematic for restoring native forest communities. It is often hoped that remnant and/or planted trees can jump-start forest succession; however, there is little mechanistic information on how different canopy species affect community trajectories. To investigate this, I surveyed understory communities, exotic grass biomass, standing litter pools, and soil properties under two dominant canopy trees—</span><i>Metrosideros polymorpha</i><span> (‘ōhi‘a) and </span><i>Acacia koa</i><span> (koa)—in recovering Hawaiian forests. I then used structural equation models (SEMs) to elucidate direct and indirect effects of trees on native understory. Native understory communities developed under ‘ōhi‘a, which had larger standing litter pools, lower soil nitrogen, and lower exotic grass biomass than koa. This pattern was variable, potentially due to historical site differences and/or distance to intact forest. Koa, in contrast, showed little understory development. Instead, data suggest that increased soil nitrogen under koa leads to high grass biomass that stalls native recruitment. SEMs suggested that indirect effects of trees via litter and soils were as or more important than direct effects for determining native cover. It is suggested that diverse plantings which incorporate species that have high carbon to nitrogen ratios may help ameliorate the negative indirect effects of koa on natural understory regeneration.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/rec.12377","usgsCitation":"Yelenik, S.G., 2017, Linking dominant Hawaiian tree species to understory development in recovering pastures via impacts on soils and litter: Restoration Ecology, v. 25, no. 1, p. 42-52, https://doi.org/10.1111/rec.12377.","productDescription":"11 p.","startPage":"42","endPage":"52","ipdsId":"IP-072291","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":334419,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai‘i","otherGeospatial":"Hakalau Forest National Wildlife Refuge","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -155.36178588867188,\n              19.75571800093756\n            ],\n            [\n              -155.36178588867188,\n              19.922358302239935\n            ],\n            [\n              -155.17845153808594,\n              19.922358302239935\n            ],\n            [\n              -155.17845153808594,\n              19.75571800093756\n            ],\n            [\n              -155.36178588867188,\n              19.75571800093756\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"25","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-20","publicationStatus":"PW","scienceBaseUri":"5891b0a5e4b072a7ac1298df","contributors":{"authors":[{"text":"Yelenik, Stephanie G. 0000-0002-9011-0769 syelenik@usgs.gov","orcid":"https://orcid.org/0000-0002-9011-0769","contributorId":5251,"corporation":false,"usgs":true,"family":"Yelenik","given":"Stephanie","email":"syelenik@usgs.gov","middleInitial":"G.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":661786,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70180534,"text":"70180534 - 2017 - Spatial variability of Chinook salmon spawning distribution and habitat preferences","interactions":[],"lastModifiedDate":"2017-11-22T10:26:57","indexId":"70180534","displayToPublicDate":"2017-01-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Spatial variability of Chinook salmon spawning distribution and habitat preferences","docAbstract":"<p><span>We investigated physical habitat conditions associated with the spawning sites of Chinook Salmon </span><i>Oncorhynchus tshawytscha</i><span> and the interannual consistency of spawning distribution across multiple spatial scales using a combination of spatially continuous and discrete sampling methods. We conducted a census of aquatic habitat in 76 km of the upper main-stem Yakima River in Washington and evaluated spawning site distribution using redd survey data from 2004 to 2008. Interannual reoccupation of spawning areas was high, ranging from an average Pearson’s correlation of 0.62 to 0.98 in channel subunits and 10-km reaches, respectively. Annual variance in the interannual correlation of spawning distribution was highest in channel units and subunits, but it was low at reach scales. In 13 of 15 models developed for individual years (2004–2008) and reach lengths (800 m, 3 km, 6 km), stream power and depth were the primary predictors of redd abundance. Multiple channels and overhead cover were patchy but were important secondary and tertiary predictors of reach-scale spawning site selection. Within channel units and subunits, pool tails and thermal variability, which may be associated with hyporheic exchange, were important predictors of spawning. We identified spawning habitat preferences within reaches and channel units that are relevant for salmonid habitat restoration planning. We also identified a threshold (i.e., 2-km reaches) beyond which interannual spawning distribution was markedly consistent, which may be informative for prioritizing habitat restoration or conservation. Management actions may be improved through enhanced understanding of spawning habitat preferences and the consistency with which Chinook Salmon reoccupy spawning areas at different spatial scales.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00028487.2016.1254112","usgsCitation":"Cram, J.M., Torgersen, C.E., Klett, R.S., Pess, G.R., May, D., Pearsons, T.N., and Dittman, A.H., 2017, Spatial variability of Chinook salmon spawning distribution and habitat preferences: Transactions of the American Fisheries Society, v. 146, no. 2, p. 206-221, https://doi.org/10.1080/00028487.2016.1254112.","productDescription":"16 p.","startPage":"206","endPage":"221","ipdsId":"IP-079878","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":334422,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Yakima River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -121.19705200195312,\n              46.97556750833867\n            ],\n            [\n              -121.19705200195312,\n              47.253135632244216\n            ],\n            [\n              -120.55709838867188,\n              47.253135632244216\n            ],\n            [\n              -120.55709838867188,\n              46.97556750833867\n            ],\n            [\n              -121.19705200195312,\n              46.97556750833867\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"146","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-19","publicationStatus":"PW","scienceBaseUri":"5891b0a5e4b072a7ac1298e1","contributors":{"authors":[{"text":"Cram, Jeremy M.","contributorId":178956,"corporation":false,"usgs":false,"family":"Cram","given":"Jeremy","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":661780,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Torgersen, Christian E. 0000-0001-8325-2737 ctorgersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8325-2737","contributorId":146935,"corporation":false,"usgs":true,"family":"Torgersen","given":"Christian","email":"ctorgersen@usgs.gov","middleInitial":"E.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":661779,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klett, Ryan S.","contributorId":178957,"corporation":false,"usgs":false,"family":"Klett","given":"Ryan","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":661781,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pess, George R.","contributorId":13501,"corporation":false,"usgs":false,"family":"Pess","given":"George","email":"","middleInitial":"R.","affiliations":[{"id":6578,"text":"National Marine Fisheries Service, Seattle, WA 98112, USA","active":true,"usgs":false}],"preferred":false,"id":661782,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"May, Darran","contributorId":178958,"corporation":false,"usgs":false,"family":"May","given":"Darran","email":"","affiliations":[],"preferred":false,"id":661783,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pearsons, Todd N.","contributorId":178959,"corporation":false,"usgs":false,"family":"Pearsons","given":"Todd","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":661784,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dittman, Andrew H.","contributorId":178960,"corporation":false,"usgs":false,"family":"Dittman","given":"Andrew","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":661785,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70180629,"text":"70180629 - 2017 - Potential distribution of the viral haemorrhagic septicaemia virus in the Great Lakes region","interactions":[],"lastModifiedDate":"2017-01-31T10:34:42","indexId":"70180629","displayToPublicDate":"2017-01-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2286,"text":"Journal of Fish Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Potential distribution of the viral haemorrhagic septicaemia virus in the Great Lakes region","docAbstract":"<p><span>Viral haemorrhagic septicaemia virus (VHSV) genotype IVb has been responsible for large-scale fish mortality events in the Great Lakes of North America. Anticipating the areas of potential VHSV occurrence is key to designing epidemiological surveillance and disease prevention strategies in the Great Lakes basin. We explored the environmental features that could shape the distribution of VHSV, based on remote sensing and climate data via ecological niche modelling. Variables included temperature measured during the day and night, precipitation, vegetation, bathymetry, solar radiation and topographic wetness. VHSV occurrences were obtained from available reports of virus confirmation in laboratory facilities. We fit a Maxent model using VHSV-IVb reports and environmental variables under different parameterizations to identify the best model to determine potential VHSV occurrence based on environmental suitability. VHSV reports were generated from both passive and active surveillance. VHSV occurrences were most abundant near shore sites. We were, however, able to capture the environmental signature of VHSV based on the environmental variables employed in our model, allowing us to identify patterns of VHSV potential occurrence. Our findings suggest that VHSV is not at an ecological equilibrium and more areas could be affected, including areas not in close geographic proximity to past VHSV reports.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/jfd.12490","usgsCitation":"Escobar, L.E., Kurath, G., Escobar-Dodero, J., Craft, M.E., and Phelps, N.B., 2017, Potential distribution of the viral haemorrhagic septicaemia virus in the Great Lakes region: Journal of Fish Diseases, v. 40, no. 1, p. 11-28, https://doi.org/10.1111/jfd.12490.","productDescription":"18 p.","startPage":"11","endPage":"28","ipdsId":"IP-072867","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":334415,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Great Lakes","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -92.35107421874999,\n              40.64730356252251\n            ],\n            [\n              -92.35107421874999,\n              47.264320080254805\n            ],\n            [\n              -75.4541015625,\n              47.264320080254805\n            ],\n            [\n              -75.4541015625,\n              40.64730356252251\n            ],\n            [\n              -92.35107421874999,\n              40.64730356252251\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"40","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-13","publicationStatus":"PW","scienceBaseUri":"5891b0a3e4b072a7ac1298db","contributors":{"authors":[{"text":"Escobar, Luis E.","contributorId":178962,"corporation":false,"usgs":false,"family":"Escobar","given":"Luis","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":661794,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kurath, Gael 0000-0003-3294-560X gkurath@usgs.gov","orcid":"https://orcid.org/0000-0003-3294-560X","contributorId":2629,"corporation":false,"usgs":true,"family":"Kurath","given":"Gael","email":"gkurath@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":661793,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Escobar-Dodero, Joaquim","contributorId":178963,"corporation":false,"usgs":false,"family":"Escobar-Dodero","given":"Joaquim","email":"","affiliations":[],"preferred":false,"id":661796,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Craft, Meggan E.","contributorId":168372,"corporation":false,"usgs":false,"family":"Craft","given":"Meggan","email":"","middleInitial":"E.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":661795,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Phelps, Nicholas B.D.","contributorId":95803,"corporation":false,"usgs":true,"family":"Phelps","given":"Nicholas","email":"","middleInitial":"B.D.","affiliations":[],"preferred":false,"id":661797,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70187565,"text":"70187565 - 2017 - The use of data-mining techniques for developing effective decisionsupport systems: A case study of simulating the effects ofclimate change on coastal salinity intrusion","interactions":[],"lastModifiedDate":"2017-05-09T09:46:33","indexId":"70187565","displayToPublicDate":"2017-01-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"seriesNumber":"408","title":"The use of data-mining techniques for developing effective decisionsupport systems: A case study of simulating the effects ofclimate change on coastal salinity intrusion","docAbstract":"<p>Natural-resource managers and stakeholders face difficult challenges when managing interactions between natural and societal systems. Potential changes in climate could alter interactions between environmental and societal systems and adversely affect the availability of water resources in many coastal communities. The availability of freshwater in coastal streams can be threatened by saltwater intrusion. Even though the collective interests and computer skills of the community of managers, scientists and other stakeholders are quite varied, there is an overarching need for equal access by all to the scientific knowledge needed to make the best possible decisions. This paper describes a decision support system, PRISM-2, developed to evaluate salinity intrusion due to potential climate change along the South Carolina coast in southeastern USA. The decision support system is disseminated as a spreadsheet application and integrates the output of global circulation models, watershed models and salinity intrusion models with real-time databases for simulation, graphical user interfaces, and streaming displays of results. The results from PRISM-2 showed that a 31-cm and 62-cm increase in sea level reduced the daily availability of freshwater supply to a coastal municipal intake by 4% and 12% of the time, respectively. Future climate change projections by a global circulation model showed a seasonal change in salinity intrusion events from the summer to the fall for the majority of events.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Integrated environmental modelling to solve real world problems: Methods, vision and challenges","language":"English","publisher":"Geological Society of London","doi":"10.1144/SP408.8","usgsCitation":"Conrads, P., and Edwin Roehl, J., 2017, The use of data-mining techniques for developing effective decisionsupport systems: A case study of simulating the effects ofclimate change on coastal salinity intrusion, chap. <i>of</i> Integrated environmental modelling to solve real world problems: Methods, vision and challenges, p. 222-234, https://doi.org/10.1144/SP408.8.","productDescription":"13 p.","startPage":"222","endPage":"234","ipdsId":"IP-042501","costCenters":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"links":[{"id":340987,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Carolina","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -81.2548828125,\n              32.48196313217176\n            ],\n            [\n              -81.15600585937499,\n              32.37996146435729\n            ],\n            [\n              -81.123046875,\n              32.25926542645933\n            ],\n            [\n              -81.05712890625,\n              32.045332838858506\n            ],\n            [\n              -80.9912109375,\n              31.93351676190369\n            ],\n            [\n              -80.804443359375,\n              31.85889704445453\n            ],\n            [\n              -80.5517578125,\n              32.12910537866883\n            ],\n            [\n              -80.299072265625,\n              32.33355894864106\n            ],\n            [\n              -80.068359375,\n              32.47269502206151\n            ],\n            [\n              -79.716796875,\n              32.58384932565662\n            ],\n            [\n              -79.4970703125,\n              32.76880048488168\n            ],\n            [\n              -79.07958984375,\n              32.98102014898148\n            ],\n            [\n              -79.013671875,\n              33.201924189778936\n            ],\n            [\n              -78.848876953125,\n              33.422272258866045\n            ],\n            [\n              -78.717041015625,\n              33.62376800118811\n            ],\n            [\n              -78.33251953125,\n              33.715201644740844\n            ],\n            [\n              -78.870849609375,\n              34.14363482031264\n            ],\n            [\n              -79.1015625,\n              34.05265942137599\n            ],\n            [\n              -79.552001953125,\n              33.76088200086917\n            ],\n            [\n              -79.771728515625,\n              33.38558626887102\n            ],\n            [\n              -80.1123046875,\n              33.128351191631566\n            ],\n            [\n              -80.694580078125,\n              32.88881315761995\n            ],\n            [\n              -81.2548828125,\n              32.48196313217176\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-16","publicationStatus":"PW","scienceBaseUri":"5912d537e4b0e541a03d4521","contributors":{"authors":[{"text":"Conrads, Paul 0000-0003-0408-4208 pconrads@usgs.gov","orcid":"https://orcid.org/0000-0003-0408-4208","contributorId":764,"corporation":false,"usgs":true,"family":"Conrads","given":"Paul","email":"pconrads@usgs.gov","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":694578,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Edwin Roehl, Jr.","contributorId":191874,"corporation":false,"usgs":false,"family":"Edwin Roehl","given":"Jr.","affiliations":[],"preferred":false,"id":694579,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70191879,"text":"70191879 - 2017 - Tambora and the mackerel year: Phenology and fisheries during an extreme climate event","interactions":[],"lastModifiedDate":"2020-07-29T13:49:19.930138","indexId":"70191879","displayToPublicDate":"2017-01-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5010,"text":"Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"Tambora and the mackerel year: Phenology and fisheries during an extreme climate event","docAbstract":"Global warming has increased the frequency of extreme climate events, yet responses of biological and human communities are poorly understood, particularly for aquatic ecosystems and fisheries. Retrospective analysis of known outcomes may provide insights into the nature of adaptations and trajectory of subsequent conditions. We consider the 1815 eruption of the Indonesian volcano Tambora and its impact on Gulf of Maine (GoM) coastal and riparian fisheries in 1816. Applying complex adaptive systems theory with historical methods, we analyzed fish export data and contemporary climate records to disclose human and piscine responses to Tambora’s extreme weather at different spatial and temporal scales while also considering sociopolitical influences. Results identified a tipping point in GoM fisheries induced by concatenating social and biological responses to extreme weather. Abnormal daily temperatures selectively affected targeted fish species—alewives, shad, herring, and mackerel—according to their migration and spawning phenologies and temperature tolerances. First to arrive, alewives suffered the worst. Crop failure and incipient famine intensified fishing pressure, especially in heavily settled regions where dams already compromised watersheds. Insufficient alewife runs led fishers to target mackerel, the next species appearing in abundance along the coast; thus, 1816 became the “mackerel year.” Critically, the shift from riparian to marine fisheries persisted and expanded after temperatures moderated and alewives recovered. We conclude that contingent human adaptations to extraordinary weather permanently altered this complex system. Understanding how adaptive responses to extreme events can trigger unintended consequences may advance long-term planning for resilience in an uncertain future.","language":"English","publisher":"American Association for the Advancement of Science","doi":"10.1126/sciadv.1601635","usgsCitation":"Alexander, K.E., Leavenworth, W.B., Hall, C., Mattocks, S., Bittner, S.M., Klein, E., Staudinger, M., Bryan, A., Rosset, J., Willis, T.V., Carr, B.H., and Jordaan, A., 2017, Tambora and the mackerel year: Phenology and fisheries during an extreme climate event: Science Advances, v. 3, no. 1, e1601635, 18 p., https://doi.org/10.1126/sciadv.1601635.","productDescription":"e1601635, 18 p.","ipdsId":"IP-075764","costCenters":[{"id":41705,"text":"Northeast Climate Science Center","active":true,"usgs":true}],"links":[{"id":470109,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.1601635","text":"Publisher Index 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Steven","contributorId":197443,"corporation":false,"usgs":false,"family":"Mattocks","given":"Steven","email":"","affiliations":[],"preferred":false,"id":713510,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bittner, Steven M.","contributorId":197444,"corporation":false,"usgs":false,"family":"Bittner","given":"Steven","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":713511,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Klein, Emily","contributorId":197445,"corporation":false,"usgs":false,"family":"Klein","given":"Emily","email":"","affiliations":[],"preferred":false,"id":713512,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Staudinger, Michelle D. 0000-0002-4535-2005","orcid":"https://orcid.org/0000-0002-4535-2005","contributorId":207908,"corporation":false,"usgs":true,"family":"Staudinger","given":"Michelle D.","affiliations":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":484,"text":"Northwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":713505,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bryan, Alexander 0000-0003-2040-7636","orcid":"https://orcid.org/0000-0003-2040-7636","contributorId":205786,"corporation":false,"usgs":true,"family":"Bryan","given":"Alexander","affiliations":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":713506,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rosset, Julianne","contributorId":197446,"corporation":false,"usgs":false,"family":"Rosset","given":"Julianne","email":"","affiliations":[],"preferred":false,"id":713513,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Willis, Theodore V.","contributorId":197447,"corporation":false,"usgs":false,"family":"Willis","given":"Theodore","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":713514,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Carr, Benjamin H.","contributorId":197448,"corporation":false,"usgs":false,"family":"Carr","given":"Benjamin","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":713515,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Jordaan, Adrian","contributorId":197449,"corporation":false,"usgs":false,"family":"Jordaan","given":"Adrian","affiliations":[],"preferred":false,"id":713516,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70198051,"text":"70198051 - 2017 - Paleomagnetism and 40Ar/39Ar geochronology of the Plio-Pleistocene Boring Volcanic Field: Implications for the geomagnetic polarity time scale and paleosecular variation","interactions":[],"lastModifiedDate":"2018-07-16T12:04:02","indexId":"70198051","displayToPublicDate":"2017-01-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3071,"text":"Physics of the Earth and Planetary Interiors","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Paleomagnetism and <sup>40</sup>Ar/<sup>39</sup>Ar geochronologyof the Plio-Pleistocene Boring Volcanic Field: Implications for the geomagnetic polarity time scale and paleosecular variation","title":"Paleomagnetism and 40Ar/39Ar geochronology of the Plio-Pleistocene Boring Volcanic Field: Implications for the geomagnetic polarity time scale and paleosecular variation","docAbstract":"<p>Paleomagnetic directions and <sup>40</sup>Ar/<sup>39</sup>Ar ages have been determined for samples of lava flows from the same outcrops, where possible, for 84 eruptive units ranging in age from 3200&nbsp;ka to 60&nbsp;ka within the Boring Volcanic Field (BVF) of the Pacific Northwest, USA. This study expands upon our previous results for the BVF, and compares the combined results with the current geomagnetic polarity time scale (GPTS). Lava flows with transitional directions were found within the BVF at the Matuyama-Brunhes and Jaramillo-Matuyama polarity boundaries, and replicate ages corresponding to these and other boundaries have been newly ascertained. Although the BVF data generally agree with GPTS chronozone boundaries, they indicate that onset of the Gauss-Matuyama transition and Olduvai subchron occurred significantly earlier than given in the current time scale calibration. Additional comparisons show that the BVF results are consistent with recent statistical models of geomagnetic paleosecular variation.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.pepi.2016.07.008","usgsCitation":"Hagstrum, J.T., Fleck, R.J., Evarts, R., and Calvert, A.T., 2017, Paleomagnetism and 40Ar/39Ar geochronology of the Plio-Pleistocene Boring Volcanic Field: Implications for the geomagnetic polarity time scale and paleosecular variation: Physics of the Earth and Planetary Interiors, v. 262, p. 101-115, https://doi.org/10.1016/j.pepi.2016.07.008.","productDescription":"15 p.","startPage":"101","endPage":"115","ipdsId":"IP-076015","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":470107,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.pepi.2016.07.008","text":"Publisher Index Page"},{"id":355622,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"262","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e766e4b060350a15d2ad","contributors":{"authors":[{"text":"Hagstrum, Jonathan T. 0000-0002-0689-280X jhag@usgs.gov","orcid":"https://orcid.org/0000-0002-0689-280X","contributorId":3474,"corporation":false,"usgs":true,"family":"Hagstrum","given":"Jonathan","email":"jhag@usgs.gov","middleInitial":"T.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":739779,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fleck, Robert J. 0000-0002-3149-8249 fleck@usgs.gov","orcid":"https://orcid.org/0000-0002-3149-8249","contributorId":1048,"corporation":false,"usgs":true,"family":"Fleck","given":"Robert","email":"fleck@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":739780,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Evarts, Russell C.","contributorId":206202,"corporation":false,"usgs":false,"family":"Evarts","given":"Russell C.","affiliations":[],"preferred":false,"id":739781,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Calvert, Andrew T. 0000-0001-5237-2218 acalvert@usgs.gov","orcid":"https://orcid.org/0000-0001-5237-2218","contributorId":2694,"corporation":false,"usgs":true,"family":"Calvert","given":"Andrew","email":"acalvert@usgs.gov","middleInitial":"T.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":739782,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70178937,"text":"ofr20161203 - 2017 - Noble gas isotopes in mineral springs and wells within the Cascadia forearc, Washington, Oregon, and California","interactions":[],"lastModifiedDate":"2017-01-31T09:53:14","indexId":"ofr20161203","displayToPublicDate":"2017-01-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1203","title":"Noble gas isotopes in mineral springs and wells within the Cascadia forearc, Washington, Oregon, and California","docAbstract":"<h1>Introduction</h1><p>This U.S. Geological Survey report presents laboratory analyses along with field notes for an exploratory study to document the relative abundance of noble gases in mineral springs and water wells within the Cascadia forearc of Washington, Oregon, and California (fig. 1). This report describes 14 samples collected in 2014 and 2015 and complements a previous report that describes 9 samples collected in 2012 and 2013 (McCrory and others, 2014b). Estimates of the depth to the underlying Juan de Fuca oceanic plate beneath sample sites are derived from the McCrory and others (2012) slab model. Some of the springs have been previously sampled for chemical analyses (Mariner and others, 2006), but none of the springs or wells currently has publicly available noble gas data. The helium and neon isotope values and ratios presented below are used to determine the sources and mixing history of these mineral and well waters (for example, McCrory and others, 2016).</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161203","usgsCitation":"McCrory, P.A., Constantz, J.E., and Hunt, A.G., 2017, Noble gas isotopes in mineral springs and wells within the Cascadia forearc, Washington, Oregon, and California: U.S. Geological Survey Open-File Report 2016–1203, 58 p., https://doi.org/10.3133/ofr20161203.","productDescription":"Report: vii, 58 p; Companion File","numberOfPages":"66","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-075367","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":334305,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1203/coverthb.jpg"},{"id":334306,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1203/ofr20161203.pdf","text":"Report","size":"15.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1203"},{"id":334307,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2016/1203/ofr20161203_NobleGasData.xlsx","text":"Noble Gas Data","size":"14 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016–1203 Noble Gas Data"}],"country":"United States","state":"California, Oregon, Washington","otherGeospatial":"Cascadia Forearc","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -132,\n              40\n            ],\n            [\n              -132,\n              52\n            ],\n            [\n              -120,\n              52\n            ],\n            [\n              -120,\n              40\n            ],\n            [\n              -132,\n              40\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"http://earthquake.usgs.gov/contactus/menlo/\" target=\"_blank\" data-mce-href=\"http://earthquake.usgs.gov/contactus/menlo/\">Contact Information</a>, Menlo Park, Calif. Office—Earthquake Science Center&nbsp;<br>U.S. Geological Survey&nbsp;<br>345 Middlefield Road, MS 977&nbsp;<br>Menlo Park, CA 94025<br><a href=\"http://earthquake.usgs.gov/\" target=\"_blank\" data-mce-href=\"http://earthquake.usgs.gov/\">http://earthquake.usgs.gov/</a></p>","tableOfContents":"<ul><li>Introduction<br></li><li>Methods<br></li><li>Mineral Spring and Well Sites Sampled for Noble Gas Isotopes<br></li><li>References Cited<br></li><li>Appendix 1<br></li></ul><p><br data-mce-bogus=\"1\"></p>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2017-01-31","noUsgsAuthors":false,"publicationDate":"2017-01-31","publicationStatus":"PW","scienceBaseUri":"5891b0a5e4b072a7ac1298e3","contributors":{"authors":[{"text":"McCrory, Patricia A. 0000-0003-2471-0018 pmccrory@usgs.gov","orcid":"https://orcid.org/0000-0003-2471-0018","contributorId":2728,"corporation":false,"usgs":true,"family":"McCrory","given":"Patricia","email":"pmccrory@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":655596,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Constantz, James E. 0000-0002-4062-2096 jconstan@usgs.gov","orcid":"https://orcid.org/0000-0002-4062-2096","contributorId":1962,"corporation":false,"usgs":true,"family":"Constantz","given":"James E.","email":"jconstan@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":655597,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hunt, Andrew G. 0000-0002-3810-8610 ahunt@usgs.gov","orcid":"https://orcid.org/0000-0002-3810-8610","contributorId":1582,"corporation":false,"usgs":true,"family":"Hunt","given":"Andrew","email":"ahunt@usgs.gov","middleInitial":"G.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":655598,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70177920,"text":"ofr20161177 - 2017 - Colorado River fish monitoring in Grand Canyon, Arizona; 2002–14 humpback chub aggregations","interactions":[],"lastModifiedDate":"2017-01-31T12:15:35","indexId":"ofr20161177","displayToPublicDate":"2017-01-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1177","title":"Colorado River fish monitoring in Grand Canyon, Arizona; 2002–14 humpback chub aggregations","docAbstract":"<p>The humpback chub (<i>Gila cypha</i>) is an endangered cyprinid species endemic to the Colorado River. The largest remaining population of the species spawns and rears in the Little Colorado River in Grand Canyon. Construction and operation of Glen Canyon Dam has altered the main-stem Colorado River in Glen and Grand Canyons. Cold, clear water releases from the dam result in a river that is generally unsuitable for successful humpback chub reproduction. During the early 1990s, nine locations within the main-stem Colorado River were identified as humpback chub aggregations—areas with a consistent and disjunct group of fish with no significant exchange of individuals with other aggregations. We monitored main-stem Colorado River aggregations of humpback chub in Grand Canyon during 2010 to 2014 and compared our results to previous investigations. Relative abundance, as described by catch per unit effort (fish per hour) of adult humpback chub at most main-stem aggregations, generally increased from the 1990s to 2014. In addition, distribution of humpback chub in the main-stem Colorado River has increased since the 1990s. Movement of humpback chub between the Little Colorado River and other aggregations likely adds fish to those aggregations. There is clear evidence of reproduction near the 30-Mile aggregation, and reproduction at Middle Granite Gorge and downstream seems likely based on catches of gravid fish and captures of very young fish, especially during relatively warm water releases from Glen Canyon Dam, 2004 to 2011. Humpback chub relative abundance at Shinumo and Havasu Creek inflows increased following translocations of young humpback chub starting in 2009. In light of this information, we modify the original nine aggregations, combining two previously separate aggregations and dropping two locations to form six distinct aggregations of humpback chub. Trends in humpback chub abundance at main-stem aggregations, relative to management actions (for example, translocations) or changing environmental conditions (for example, river warming), informs management of the species across a riverscape scale within the Colorado River.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161177","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Persons, W.R., Van Haverbeke, D.R., and Dodrill, M.J., 2017, Colorado River fish monitoring in Grand Canyon, Arizona; 2002–14 humpback chub aggregations: U.S. Geological Survey Open-File Report 2016–1177, 43 p., https://doi.org/10.3133/ofr20161177.","productDescription":"v, 43 p.","numberOfPages":"50","onlineOnly":"Y","ipdsId":"IP-077512","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":334348,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1177/coverthb.jpg"},{"id":334349,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1177/ofr20161177.pdf","text":"Report","size":"1.23 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1177"}],"country":"United States","state":"Colorado","otherGeospatial":"Grand Canyon","contact":"<p><span class=\"m_4911814228635689543gmail-m_-8979264818645400749gmail-m_1640138435850327079m_-142396895223328916m_1855944767564726836gmail-m_-5268158262813114351m_3271191788226044397m_-3921060801887555758gmail-m_-3366365647338320567gmail-s1\"><a href=\"https://www.gcmrc.gov/about/contact.aspx\" target=\"_blank\" data-mce-href=\"https://www.gcmrc.gov/about/contact.aspx\">GCMRC Staff</a></span>, Southwest Biological Science Center<br>U.S. Geological Survey<br>Grand Canyon Monitoring and Research Center<br>2255 N. Gemini Drive<br>Flagstaff, AZ 86001<br><a href=\"https://www.gcmrc.gov/\" target=\"_blank\" data-mce-href=\"https://www.gcmrc.gov/\">https://www.gcmrc.gov/</a></p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Methods of Investigation<br></li><li>Results and Discussion<br></li><li>Summary and Conclusions<br></li><li>Acknowledgments<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2017-01-31","noUsgsAuthors":false,"publicationDate":"2017-01-31","publicationStatus":"PW","scienceBaseUri":"5891b0a6e4b072a7ac1298e7","contributors":{"authors":[{"text":"Persons, William R.","contributorId":176343,"corporation":false,"usgs":false,"family":"Persons","given":"William R.","affiliations":[],"preferred":false,"id":652250,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Haverbeke, David R.","contributorId":176344,"corporation":false,"usgs":false,"family":"Van Haverbeke","given":"David","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":652251,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dodrill, Michael J. 0000-0002-7038-7170 mdodrill@usgs.gov","orcid":"https://orcid.org/0000-0002-7038-7170","contributorId":5468,"corporation":false,"usgs":true,"family":"Dodrill","given":"Michael","email":"mdodrill@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":652249,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70179204,"text":"sir20165155 - 2017 - Development and evaluation of a reservoir model for the Chain of Lakes in Illinois","interactions":[],"lastModifiedDate":"2017-02-13T11:17:33","indexId":"sir20165155","displayToPublicDate":"2017-01-27T11:30:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5155","title":"Development and evaluation of a reservoir model for the Chain of Lakes in Illinois","docAbstract":"<p>Forecasts of flows entering and leaving the Chain of Lakes reservoir on the Fox River in northeastern Illinois are critical information to water-resource managers who determine the optimal operation of the dam at McHenry, Illinois, to help minimize damages to property and loss of life because of flooding on the Fox River. In 2014, the U.S. Geological Survey; the Illinois Department of Natural Resources, Office of Water Resources; and National Weather Service, North Central River Forecast Center began a cooperative study to develop a system to enable engineers and planners to simulate and communicate flows and to prepare proactively for precipitation events in near real time in the upper Fox River watershed. The purpose of this report is to document the development and evaluation of the Chain of Lakes reservoir model developed in this study.</p><p>The reservoir model for the Chain of Lakes was developed using the Hydrologic Engineering Center–Reservoir System Simulation program. Because of the complex relation between the dam headwater and reservoir pool elevations, the reservoir model uses a linear regression model that relates dam headwater elevation to reservoir pool elevation. The linear regression model was developed using 17 U.S. Geological Survey streamflow measurements, along with the gage height in the reservoir pool and the gage height at the dam headwater. The Nash-Sutcliffe model efficiency coefficients for all three linear regression model variables ranged from 0.90 to 0.98.</p><p>The reservoir model performance was evaluated by graphically comparing simulated and observed reservoir pool elevation time series during nine periods of high pool elevation. In addition, the peak elevations during these time periods were graphically compared to the closest-in-time observed pool elevation peak. The mean difference in the simulated and observed peak elevations was -0.03 feet, with a standard deviation of 0.19 feet. The Nash-Sutcliffe coefficient for peak prediction was calculated as 0.94. Evaluation of the model based on accuracy of peak prediction and the ability to simulate an elevation time series showed the performance of the model was satisfactory.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165155","collaboration":"Prepared in cooperation with the llinois Department of Natural Resources and the National Weather Service","usgsCitation":"Domanski, M.M., 2017, Development and evaluation of a reservoir model for the Chain of Lakes in Illinois: U.S. Geological Survey Scientific Investigations Report 2016–5155, 21 p., https://doi.org/10.3133/sir20165155.","productDescription":"viii, 21 p.","numberOfPages":"34","onlineOnly":"Y","ipdsId":"IP-074336","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":334088,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5155/coverthb.jpg"},{"id":334089,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5155/sir20165155.pdf","text":"Report","size":"5.08 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5155"}],"country":"United States","state":"Illinois","otherGeospatial":"Chain of Lakes, Fox River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.27857971191406,\n              42.293564192170095\n            ],\n            [\n              -88.27857971191406,\n              42.49488409061174\n            ],\n            [\n              -88.10142517089844,\n              42.49488409061174\n            ],\n            [\n              -88.10142517089844,\n              42.293564192170095\n            ],\n            [\n              -88.27857971191406,\n              42.293564192170095\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_il@usgs.gov\" data-mce-href=\"mailto:dc_il@usgs.gov\">Director</a>, Illinois Water Science Center<br> U.S. Geological Survey<br> 405 N. Goodwin<br> Urbana, IL 61801<br> <a href=\"http://il.water.usgs.gov/\" data-mce-href=\"http://il.water.usgs.gov/\">http://il.water.usgs.gov/</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Purpose and Scope&nbsp;</li><li>Model Development&nbsp;</li><li>Model Evaluation&nbsp;</li><li>Summary</li><li>References</li></ul>","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"publishedDate":"2017-01-27","noUsgsAuthors":false,"publicationDate":"2017-01-27","publicationStatus":"PW","scienceBaseUri":"588c6a8ce4b08c8121c908fa","contributors":{"authors":[{"text":"Domanski, Marian M. 0000-0002-0468-314X mdomanski@usgs.gov","orcid":"https://orcid.org/0000-0002-0468-314X","contributorId":5035,"corporation":false,"usgs":true,"family":"Domanski","given":"Marian","email":"mdomanski@usgs.gov","middleInitial":"M.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":656380,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70180346,"text":"70180346 - 2017 - NDVI, scale invariance and the modifiable areal unit problem: An assessment of vegetation in the Adelaide Parklands","interactions":[],"lastModifiedDate":"2017-01-27T13:53:38","indexId":"70180346","displayToPublicDate":"2017-01-27T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"NDVI, scale invariance and the modifiable areal unit problem: An assessment of vegetation in the Adelaide Parklands","docAbstract":"<p><span>This research addresses the question as to whether or not the Normalised Difference Vegetation Index (NDVI) is scale invariant (i.e. constant over spatial aggregation) for pure pixels of urban vegetation. It has been long recognized that there are issues related to the modifiable areal unit problem (MAUP) pertaining to indices such as NDVI and images at varying spatial resolutions. These issues are relevant to using NDVI values in spatial analyses. We compare two different methods of calculation of a mean NDVI: 1) using pixel values of NDVI within feature/object boundaries and 2) first calculating the mean red and mean near-infrared across all feature pixels and then calculating NDVI. We explore the nature and magnitude of these differences for images taken from two sensors, a 1.24&nbsp;m resolution WorldView-3 and a 0.1&nbsp;m resolution digital aerial image. We apply these methods over an urban park located in the Adelaide Parklands of South Australia. We demonstrate that the MAUP is not an issue for calculation of NDVI within a sensor for pure urban vegetation pixels. This may prove useful for future rule-based monitoring of the ecosystem functioning of green infrastructure.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2017.01.130","usgsCitation":"Nouri, H., Anderson, S., Sutton, P., Beecham, S., Nagler, P.L., Jarchow, C.J., and Roberts, D.A., 2017, NDVI, scale invariance and the modifiable areal unit problem: An assessment of vegetation in the Adelaide Parklands: Science of the Total Environment, v. 584–585, p. 11-18, https://doi.org/10.1016/j.scitotenv.2017.01.130.","productDescription":"8 p.","startPage":"11","endPage":"18","ipdsId":"IP-070001","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":334208,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","otherGeospatial":"Adelaide Parklands","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              138.60041499137878,\n              -34.93567549371307\n            ],\n            [\n              138.59442830085752,\n              -34.93597453850782\n            ],\n            [\n              138.5945463180542,\n              -34.93783035094391\n            ],\n            [\n              138.60064029693604,\n              -34.93749613189923\n            ],\n            [\n              138.60041499137878,\n              -34.93567549371307\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"584–585","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"588c6a8de4b08c8121c90900","contributors":{"authors":[{"text":"Nouri, Hamideh","contributorId":178847,"corporation":false,"usgs":false,"family":"Nouri","given":"Hamideh","affiliations":[],"preferred":false,"id":661308,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Sharolyn","contributorId":178848,"corporation":false,"usgs":false,"family":"Anderson","given":"Sharolyn","email":"","affiliations":[],"preferred":false,"id":661309,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sutton, Paul","contributorId":172387,"corporation":false,"usgs":false,"family":"Sutton","given":"Paul","email":"","affiliations":[{"id":27030,"text":"School of Natural and Built Environments, University of South Australia, Adelaide, SA","active":true,"usgs":false}],"preferred":false,"id":661310,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beecham, Simon","contributorId":178849,"corporation":false,"usgs":false,"family":"Beecham","given":"Simon","email":"","affiliations":[],"preferred":false,"id":661311,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":661307,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jarchow, Christopher J. 0000-0002-0424-4104 cjarchow@usgs.gov","orcid":"https://orcid.org/0000-0002-0424-4104","contributorId":5813,"corporation":false,"usgs":true,"family":"Jarchow","given":"Christopher","email":"cjarchow@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":661313,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Roberts, Dar A.","contributorId":100503,"corporation":false,"usgs":false,"family":"Roberts","given":"Dar","email":"","middleInitial":"A.","affiliations":[{"id":12804,"text":"Univ. of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":661312,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70180311,"text":"70180311 - 2017 - Development of a coupled wave-flow-vegetation interaction model","interactions":[],"lastModifiedDate":"2018-02-07T19:04:20","indexId":"70180311","displayToPublicDate":"2017-01-27T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1315,"text":"Computers & Geosciences","printIssn":"0098-3004","active":true,"publicationSubtype":{"id":10}},"title":"Development of a coupled wave-flow-vegetation interaction model","docAbstract":"<p><span>Emergent and submerged vegetation can significantly affect coastal hydrodynamics. However, most deterministic numerical models do not take into account their influence on currents, waves, and turbulence. In this paper, we describe the implementation of a wave-flow-vegetation module into a Coupled-Ocean-Atmosphere-Wave-Sediment Transport (COAWST) modeling system that includes a flow model (ROMS) and a wave model (SWAN), and illustrate various interacting processes using an idealized shallow basin application. The flow model has been modified to include plant posture-dependent three-dimensional drag, in-canopy wave-induced streaming, and production of turbulent kinetic energy and enstrophy to parameterize vertical mixing. The coupling framework has been updated to exchange vegetation-related variables between the flow model and the wave model to account for wave energy dissipation due to vegetation. This study i) demonstrates the validity of the plant posture-dependent drag parameterization against field measurements, ii) shows that the model is capable of reproducing the mean and turbulent flow field in the presence of vegetation as compared to various laboratory experiments, iii) provides insight into the flow-vegetation interaction through an analysis of the terms in the momentum balance, iv) describes the influence of a submerged vegetation patch on tidal currents and waves separately and combined, and v) proposes future directions for research and development.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.cageo.2016.12.010","usgsCitation":"Beudin, A., Kalra, T., Ganju, N.K., and Warner, J., 2017, Development of a coupled wave-flow-vegetation interaction model: Computers & Geosciences, v. 100, p. 76-86, https://doi.org/10.1016/j.cageo.2016.12.010.","productDescription":"11 p.","startPage":"76","endPage":"86","ipdsId":"IP-074584","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":470115,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.cageo.2016.12.010","text":"Publisher Index Page"},{"id":334142,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"100","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"588c6a8de4b08c8121c90904","contributors":{"authors":[{"text":"Beudin, Alexis 0000-0001-9525-9450 abeudin@usgs.gov","orcid":"https://orcid.org/0000-0001-9525-9450","contributorId":178819,"corporation":false,"usgs":true,"family":"Beudin","given":"Alexis","email":"abeudin@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":661176,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kalra, Tarandeep S. 0000-0001-5468-248X tkalra@usgs.gov","orcid":"https://orcid.org/0000-0001-5468-248X","contributorId":178820,"corporation":false,"usgs":true,"family":"Kalra","given":"Tarandeep S.","email":"tkalra@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":661179,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ganju, Neil K. 0000-0002-1096-0465 nganju@usgs.gov","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":174763,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil","email":"nganju@usgs.gov","middleInitial":"K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":661177,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":661178,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70180310,"text":"70180310 - 2017 - Depositional environment and organic matter accumulation of Upper Ordovician–Lower Silurian marine shale in the Upper Yangtze Platform, South China","interactions":[],"lastModifiedDate":"2017-01-27T08:48:38","indexId":"70180310","displayToPublicDate":"2017-01-27T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2996,"text":"Palaeogeography, Palaeoclimatology, Palaeoecology","printIssn":"0031-0182","active":true,"publicationSubtype":{"id":10}},"title":"Depositional environment and organic matter accumulation of Upper Ordovician–Lower Silurian marine shale in the Upper Yangtze Platform, South China","docAbstract":"<p id=\"sp0040\">The main controlling factors of organic matter accumulation in the Upper Ordovician Wufeng–Lower Silurian Longmaxi Formations are complex and remain highly controversial. This study investigates the vertical variation of total organic carbon (TOC) content as well as major and trace element concentrations of four Ordovician–Silurian transition sections from the Upper Yangtze Platform of South China to reconstruct the paleoenvironment of these deposits and to improve our understanding of those factors that have influenced organic matter accumulation in these deposits.</p><p id=\"sp0045\">The residual TOC content of the Wufeng Formation averages 3.2% and ranges from 0.12 to 6.0%. The overlying lower Longmaxi Formation displays higher TOC content (avg. 4.4%), followed upsection by consistent and lower values that average 1.6% in the upper Longmaxi Formation. The concentration and covariation of redox-sensitive trace elements (Mo, U and V) suggest that organic-rich intervals of the Wufeng Formation accumulated under predominantly anoxic conditions. Organic-rich horizons of the lower Longmaxi Formation were deposited under strongly anoxic to euxinic conditions, whereas organic-poor intervals of the upper Longmaxi Formation accumulated under suboxic conditions. Positive correlations between redox proxies and TOC contents suggest that organic matter accumulation was predominantly controlled by preservation. Barium excess (Ba<sub>xs</sub>) values indicate high paleoproductivity throughout the entire depositional sequence, with an increase in the lower Longmaxi Formation. Increased productivity may have been induced by enhanced P recycling, as evidenced by elevated C<sub>org</sub>/P<sub>tot</sub> ratios. Mo–U covariation and Mo/TOC values reveal that the Wufeng Formation was deposited under extremely restricted conditions, whereas the Longmaxi Formation accumulated under moderately restricted conditions. During the Late Ordovician, the extremely restricted nature of ocean circulation on the Upper Yangtze Platform in tandem with enhanced stratification of the water column promoted anoxic conditions favorable for the preservation of organic matter. During Early Silurian time, organic matter accumulation was principally controlled by changes in sea level, which affected terrigenous flux, redox conditions, and the degree of nutrition recycling.</p>","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.palaeo.2016.11.037","usgsCitation":"Li, Y., Zhang, T., Ellis, G.S., and Shao, D., 2017, Depositional environment and organic matter accumulation of Upper Ordovician–Lower Silurian marine shale in the Upper Yangtze Platform, South China: Palaeogeography, Palaeoclimatology, Palaeoecology, v. 466, p. 252-264, https://doi.org/10.1016/j.palaeo.2016.11.037.","productDescription":"15 p.","startPage":"252","endPage":"264","ipdsId":"IP-073286","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":334124,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","otherGeospatial":"Upper Yangtze Platform","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              102,\n              26.5\n            ],\n            [\n              102,\n              33\n            ],\n            [\n              110,\n              33\n            ],\n            [\n              110,\n              26.5\n            ],\n            [\n              102,\n              26.5\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"466","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"588c6a8ee4b08c8121c90906","contributors":{"authors":[{"text":"Li, Yangfang","contributorId":178816,"corporation":false,"usgs":false,"family":"Li","given":"Yangfang","email":"","affiliations":[],"preferred":false,"id":661164,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhang, Tongwei","contributorId":107595,"corporation":false,"usgs":true,"family":"Zhang","given":"Tongwei","affiliations":[],"preferred":false,"id":661155,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ellis, Geoffrey S. 0000-0003-4519-3320 gsellis@usgs.gov","orcid":"https://orcid.org/0000-0003-4519-3320","contributorId":1058,"corporation":false,"usgs":true,"family":"Ellis","given":"Geoffrey","email":"gsellis@usgs.gov","middleInitial":"S.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":661152,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shao, Deyong","contributorId":178817,"corporation":false,"usgs":false,"family":"Shao","given":"Deyong","email":"","affiliations":[],"preferred":false,"id":661154,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70178110,"text":"sir20165159 - 2017 - Hydrologic and hydraulic analyses of Great Meadow wetland, Acadia National Park, Maine","interactions":[],"lastModifiedDate":"2017-01-26T14:12:01","indexId":"sir20165159","displayToPublicDate":"2017-01-26T14:30:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5159","title":"Hydrologic and hydraulic analyses of Great Meadow wetland, Acadia National Park, Maine","docAbstract":"<p>The U.S. Geological Survey completed hydrologic and hydraulic analyses of Cromwell Brook and the Sieur de Monts tributary in Acadia National Park, Maine, to better understand causes of flooding in complex hydrologic and hydraulic environments, like those in the Great Meadow wetland and Sieur de Monts Spring area. Regional regression equations were used to compute peak flows with from 2 to 100-year recurrence intervals at seven locations. Light detection and ranging data were adjusted for bias caused by dense vegetation in the Great Meadow wetland; and then combined with local ground surveys used to define the underwater topography and hydraulic structures in the study area. Hydraulic modeling was used to evaluate flood response in the study area to a variety of hydrologic and hydraulic scenarios.</p><p>Hydraulic modeling indicates that enlarging the culvert at Park Loop Road could help mitigate flooding near the Sieur de Monts Nature Center that is caused by streamflows with large recurrence intervals; however, hydraulic modeling also indicates that the Park Loop Road culvert does not aggravate flooding near the Nature Center caused by the more frequent high intensity rainstorms. That flooding is likely associated with overland flow resulting from (1) quick runoff from the steep Dorr Mountain hitting the lower gradient Great Meadow wetland area and (2) poor drainage aggravated by beaver dams holding water in the wetland.</p><p>Rapid geomorphic assessment data collected in June 2015 and again in April 2016 indicate that Cromwell Brook has evidence of aggradation, degradation, and channel widening throughout the drainage basin. Two of five reference cross sections developed for this report also indicate channel aggradation.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165159","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Lombard, P.J., 2017, Hydrologic and hydraulic analyses of Great Meadow wetland, Acadia National Park, Maine: U.S. Geological Survey Scientific Investigations Report 2016–5159, 39 p., https://doi.org/10.3133/sir20165159.","productDescription":"viii, 39 p.","numberOfPages":"52","onlineOnly":"Y","ipdsId":"IP-077064","costCenters":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"links":[{"id":333754,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5159/sir20165159.pdf","text":"Report","size":"7.66 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5159"},{"id":333753,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5159/coverthb.jpg"}],"country":"United States","state":"Maine","otherGeospatial":"Acadia National Park, Mount Desert Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -68.43795776367188,\n              44.22158376545796\n            ],\n            [\n              -68.43795776367188,\n              44.44554600843547\n            ],\n            [\n              -68.16329956054688,\n              44.44554600843547\n            ],\n            [\n              -68.16329956054688,\n              44.22158376545796\n            ],\n            [\n              -68.43795776367188,\n              44.22158376545796\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_nweng@usgs.gov\" data-mce-href=\"mailto:dc_nweng@usgs.gov\">Director</a>, New England Water Science Center<br> U.S. Geological Survey <br> 196 Whitten Road<br> Augusta, ME 04330</p><p>Or visit our Web site at:<br> <a href=\"http://newengland.water.usgs.gov\" data-mce-href=\"http://newengland.water.usgs.gov\">http://newengland.water.usgs.gov</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Data Collection</li><li>Hydrology</li><li>Hydraulic Model</li><li>Flood-Inundation Mapping</li><li>Modeled Flooding</li><li>Culvert Design Considerations</li><li>Additional Work</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2017-01-26","noUsgsAuthors":false,"publicationDate":"2017-01-26","publicationStatus":"PW","scienceBaseUri":"588b1975e4b0ad67323f97d8","contributors":{"authors":[{"text":"Lombard, Pamela J. plombard@usgs.gov","contributorId":176584,"corporation":false,"usgs":true,"family":"Lombard","given":"Pamela","email":"plombard@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":false,"id":652812,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70190140,"text":"70190140 - 2017 - Integrating landslide and liquefaction hazard and loss estimates with existing USGS real-time earthquake information products","interactions":[],"lastModifiedDate":"2018-01-03T09:45:01","indexId":"70190140","displayToPublicDate":"2017-01-26T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Integrating landslide and liquefaction hazard and loss estimates with existing USGS real-time earthquake information products","docAbstract":"<p><span>The U.S. Geological Survey (USGS) has made significant progress toward the rapid estimation of shaking and shakingrelated losses through their Did You Feel It? (DYFI), ShakeMap, ShakeCast, and PAGER products. However, quantitative estimates of the extent and severity of secondary hazards (e.g., landsliding, liquefaction) are not currently included in scenarios and real-time post-earthquake products despite their significant contributions to hazard and losses for many events worldwide. We are currently running parallel global statistical models for landslides and liquefaction developed with our collaborators in testing mode, but much work remains in order to operationalize these systems. We are expanding our efforts in this area by not only improving the existing statistical models, but also by (1) exploring more sophisticated, physics-based models where feasible; (2) incorporating uncertainties; and (3) identifying and undertaking research and product development to provide useful landslide and liquefaction estimates and their uncertainties. Although our existing models use standard predictor variables that are accessible globally or regionally, including peak ground motions, topographic slope, and distance to water bodies, we continue to explore readily available proxies for rock and soil strength as well as other susceptibility terms. This work is based on the foundation of an expanding, openly available, case-history database we are compiling along with historical ShakeMaps for each event. The expected outcome of our efforts is a robust set of real-time secondary hazards products that meet the needs of a wide variety of earthquake information users. We describe the available datasets and models, developments currently underway, and anticipated products.&nbsp;</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 16th World Conference on Earthquake Engineering","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":" 16th World Conference on Earthquake Engineering","conferenceDate":"January 9-13, 2017","conferenceLocation":"Santiago, Chile","language":"English","publisher":"International Association of Earthquake Engineering","usgsCitation":"Allstadt, K.E., Thompson, E.M., Hearne, M., Nowicki Jessee, M., Zhu, J., Wald, D.J., and Tanyas, H., 2017, Integrating landslide and liquefaction hazard and loss estimates with existing USGS real-time earthquake information products, <i>in</i> Proceedings of the 16th World Conference on Earthquake Engineering, Santiago, Chile, January 9-13, 2017, 13 p.","productDescription":"13 p.","ipdsId":"IP-080338","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":344787,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59b76f57e4b08b1644ddfaf4","contributors":{"authors":[{"text":"Allstadt, Kate E. 0000-0003-4977-5248 kallstadt@usgs.gov","orcid":"https://orcid.org/0000-0003-4977-5248","contributorId":167684,"corporation":false,"usgs":true,"family":"Allstadt","given":"Kate","email":"kallstadt@usgs.gov","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":false,"id":725403,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":146592,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":725404,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hearne, Mike 0000-0002-8225-2396 mhearne@usgs.gov","orcid":"https://orcid.org/0000-0002-8225-2396","contributorId":4659,"corporation":false,"usgs":true,"family":"Hearne","given":"Mike","email":"mhearne@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":725405,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nowicki Jessee, M. Anna","contributorId":196186,"corporation":false,"usgs":false,"family":"Nowicki Jessee","given":"M. Anna","affiliations":[],"preferred":false,"id":725406,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhu, J.","contributorId":6289,"corporation":false,"usgs":true,"family":"Zhu","given":"J.","email":"","affiliations":[],"preferred":false,"id":725407,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":725408,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tanyas, Hakan","contributorId":167686,"corporation":false,"usgs":false,"family":"Tanyas","given":"Hakan","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":707641,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70188466,"text":"70188466 - 2017 - Apparent late Quaternary fault slip rate increase in the southwestern Lower Rhine Graben, central Europe","interactions":[],"lastModifiedDate":"2017-06-13T11:08:29","indexId":"70188466","displayToPublicDate":"2017-01-26T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Apparent late Quaternary fault slip rate increase in the southwestern Lower Rhine Graben, central Europe","docAbstract":"<p id=\"p-1\">In regions of low strain, long earthquake recurrence intervals (10<sup>4</sup>–10<sup>6</sup>  yrs) and erosive processes limit preservation of Quaternary markers suitable for distinguishing whether faults slip at uniform or secularly varying rates. The Lower Rhine graben in the border region of Germany, The Netherlands, and Belgium provides a unique opportunity to explore Quaternary slip‐rate variations in a region of low strain using the basal (2.29±0.29  Ma) and surface (700±80  ka) contacts of the regionally extensive main terrace (“Hauptterrasse”), deposited by the Rhine and Maas Rivers. These surfaces are vertically offset 3–140&nbsp;m and 0–68&nbsp;m, respectively, across individual fault strands within a distributed network of northwest‐trending, slow‐slipping (&lt;0.1  mm/yr) normal faults. In this investigation, we construct Quaternary slip histories for the southern Lower Rhine graben faults using new main terrace surface vertical offset measurements made from light detection and ranging (lidar)‐derived bare‐earth digital terrain models, which we synthesize with existing constraints on the offset basal contact of this fluvial deposit (<i>n</i>=91 collocated sites with displacement constraints). We find that &gt;80% of the sites record an apparent increase in slip rate for the more recent interval from 700&nbsp;ka to present, which corresponds to a period of increased uplift of the nearby Rhenish Massif and regional volcanism. However, the apparent increase in slip rate could result, in part, from erosion of the footwall surface below the main terrace, leading to an apparent displacement that is smaller than the total vertical offset since the start of the Quaternary. Prior work focused on characterization of these faults as seismic sources in the Lower Rhine graben has preferentially relied on the average fault‐slip rate constrained using the base of the main terrace. We suggest that average fault‐slip rates calculated using the ∼700  ka main terrace surface are subjected to fewer uncertainties and sample a time interval that is more relevant for seismic‐hazard analysis.</p><p id=\"p-2\"><br></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120160197","usgsCitation":"Gold, R.D., Friedrich, A.M., Kubler, S., and Salamon, M., 2017, Apparent late Quaternary fault slip rate increase in the southwestern Lower Rhine Graben, central Europe: Bulletin of the Seismological Society of America, v. 107, no. 2, p. 563-580, https://doi.org/10.1785/0120160197.","productDescription":"18 p. ","startPage":"563","endPage":"580","ipdsId":"IP-080642","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":342418,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Belgium, Germany, Netherlands","otherGeospatial":"Lower Rhine graben","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              4.7900390625,\n              51.508742458803326\n            ],\n            [\n              4.9658203125,\n              50.38050249104245\n            ],\n            [\n              5.789794921875,\n              50.21206446065373\n            ],\n            [\n              7.437744140625,\n              50.3734961443035\n            ],\n            [\n              6.240234374999999,\n              51.91039070988962\n            ],\n            [\n              4.7900390625,\n              51.508742458803326\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"107","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-24","publicationStatus":"PW","scienceBaseUri":"5940f9b3e4b0764e6c63eabf","contributors":{"authors":[{"text":"Gold, Ryan D. 0000-0002-4464-6394 rgold@usgs.gov","orcid":"https://orcid.org/0000-0002-4464-6394","contributorId":3883,"corporation":false,"usgs":true,"family":"Gold","given":"Ryan","email":"rgold@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":697894,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Friedrich, Anke M.","contributorId":192852,"corporation":false,"usgs":false,"family":"Friedrich","given":"Anke","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":697895,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kubler, Simon","contributorId":192853,"corporation":false,"usgs":false,"family":"Kubler","given":"Simon","email":"","affiliations":[],"preferred":false,"id":697896,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Salamon, Martin","contributorId":192854,"corporation":false,"usgs":false,"family":"Salamon","given":"Martin","email":"","affiliations":[],"preferred":false,"id":697897,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70180260,"text":"70180260 - 2017 - Evaluating mountain meadow groundwater response to Pinyon-Juniper and temperature in a great basin watershed","interactions":[],"lastModifiedDate":"2017-01-27T11:10:10","indexId":"70180260","displayToPublicDate":"2017-01-26T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating mountain meadow groundwater response to Pinyon-Juniper and temperature in a great basin watershed","docAbstract":"<p><span>This research highlights development and application of an integrated hydrologic model (GSFLOW) to a semiarid, snow-dominated watershed in the Great Basin to evaluate Pinyon-Juniper (PJ) and temperature controls on mountain meadow shallow groundwater. The work used Google Earth Engine Landsat satellite and gridded climate archives for model evaluation. Model simulations across three decades indicated that the watershed operates on a threshold response to precipitation (P) &gt;400&nbsp;mm/y to produce a positive yield (P-ET; 9%) resulting in stream discharge and a rebound in meadow groundwater levels during these wetter years. Observed and simulated meadow groundwater response to large P correlates with above average predicted soil moisture and with a normalized difference vegetation index threshold value &gt;0.3. A return to assumed pre-expansion PJ conditions or an increase in temperature to mid-21st century shifts yielded by only ±1% during the multi-decade simulation period; but changes of approximately ±4% occurred during wet years. Changes in annual yield were largely dampened by the spatial and temporal redistribution of evapotranspiration across the watershed: Yet the influence of this redistribution and vegetation structural controls on snowmelt altered recharge to control water table depth in the meadow. Even a small-scale removal of PJ (0.5&nbsp;km</span><sup>2</sup><span>) proximal to the meadow will promote a stable, shallow groundwater system resilient to droughts, while modest increases in temperature will produce a meadow susceptible to declining water levels and a community structure likely to move toward dry and degraded conditions.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/eco.1792","usgsCitation":"Carroll, R.W., Huntington, J., Snyder, K.A., Niswonger, R.G., Morton, C., and Stringham, T.K., 2017, Evaluating mountain meadow groundwater response to Pinyon-Juniper and temperature in a great basin watershed: Ecohydrology, v. 10, no. 1, p. 1-18, https://doi.org/10.1002/eco.1792.","productDescription":"e1792; 18 p.","startPage":"1","endPage":"18","ipdsId":"IP-072881","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":461779,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eco.1792","text":"Publisher Index Page"},{"id":334058,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Great Basin","volume":"10","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-14","publicationStatus":"PW","scienceBaseUri":"588b1976e4b0ad67323f97dc","contributors":{"authors":[{"text":"Carroll, Rosemary W.H.","contributorId":39928,"corporation":false,"usgs":true,"family":"Carroll","given":"Rosemary","email":"","middleInitial":"W.H.","affiliations":[],"preferred":false,"id":660972,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huntington, Justin L.","contributorId":31279,"corporation":false,"usgs":true,"family":"Huntington","given":"Justin L.","affiliations":[],"preferred":false,"id":660973,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Snyder, Keirith A.","contributorId":178786,"corporation":false,"usgs":false,"family":"Snyder","given":"Keirith","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":660974,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Niswonger, Richard G. 0000-0001-6397-2403 rniswon@usgs.gov","orcid":"https://orcid.org/0000-0001-6397-2403","contributorId":152462,"corporation":false,"usgs":true,"family":"Niswonger","given":"Richard","email":"rniswon@usgs.gov","middleInitial":"G.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":false,"id":660975,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Morton, Charles","contributorId":178787,"corporation":false,"usgs":false,"family":"Morton","given":"Charles","affiliations":[],"preferred":false,"id":660976,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stringham, Tamzen K.","contributorId":178788,"corporation":false,"usgs":false,"family":"Stringham","given":"Tamzen","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":660977,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
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