{"pageNumber":"626","pageRowStart":"15625","pageSize":"25","recordCount":40818,"records":[{"id":70154903,"text":"70154903 - 2013 - A computer model to forecast wetland vegetation changes resulting from restoration and protection in coastal Louisiana","interactions":[],"lastModifiedDate":"2015-07-14T11:26:54","indexId":"70154903","displayToPublicDate":"2014-01-01T12:15:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"title":"A computer model to forecast wetland vegetation changes resulting from restoration and protection in coastal Louisiana","docAbstract":"<p>The coastal wetlands of Louisiana are a unique ecosystem that supports a diversity of wildlife as well as a diverse community of commercial interests of both local and national importance. The state of Louisiana has established a 5-year cycle of scientific investigation to provide up-to-date information to guide future legislation and regulation aimed at preserving this critical ecosystem. Here we report on a model that projects changes in plant community distribution and composition in response to environmental conditions. This model is linked to a suite of other models and requires input from those that simulate the hydrology and morphology of coastal Louisiana. Collectively, these models are used to assess how alternative management plans may affect the wetland ecosystem through explicit spatial modeling of the physical and biological processes affected by proposed modifications to the ecosystem. We have also taken the opportunity to advance the state-of-the-art in wetland plant community modeling by using a model that is more species-based in its description of plant communities instead of one based on aggregated community types such as brackish marsh and saline marsh. The resulting model provides an increased level of ecological detail about how wetland communities are expected to respond. In addition, the output from this model provides critical inputs for estimating the effects of management on higher trophic level species though a more complete description of the shifts in habitat.</p>","language":"English","publisher":"Coastal Education and Research Foundation, BioOne","doi":"10.2112/SI_67_4","usgsCitation":"Visser, J.M., Duke-Sylvester, S., Carter, J., and Broussard, W.P., 2013, A computer model to forecast wetland vegetation changes resulting from restoration and protection in coastal Louisiana: Journal of Coastal Research, no. 67, p. 51-59, https://doi.org/10.2112/SI_67_4.","productDescription":"9 p.","startPage":"51","endPage":"59","numberOfPages":"9","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-042146","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":305704,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":305597,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.2112/SI_67_4"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -93.878173828125,\n              29.008140362978157\n            ],\n            [\n              -93.878173828125,\n              30.183121842195515\n            ],\n            [\n              -88.934326171875,\n              30.183121842195515\n            ],\n            [\n              -88.934326171875,\n              29.008140362978157\n            ],\n            [\n              -93.878173828125,\n              29.008140362978157\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","issue":"67","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55a632a9e4b0183d66e45cc0","contributors":{"authors":[{"text":"Visser, Jenneke M.","contributorId":90397,"corporation":false,"usgs":true,"family":"Visser","given":"Jenneke","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":564333,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duke-Sylvester, Scott M.","contributorId":40661,"corporation":false,"usgs":true,"family":"Duke-Sylvester","given":"Scott M.","affiliations":[],"preferred":false,"id":564332,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carter, Jacoby 0000-0003-0110-0284 carterj@usgs.gov","orcid":"https://orcid.org/0000-0003-0110-0284","contributorId":2399,"corporation":false,"usgs":true,"family":"Carter","given":"Jacoby","email":"carterj@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":564330,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Broussard, Whitney P. III","contributorId":62101,"corporation":false,"usgs":true,"family":"Broussard","given":"Whitney","suffix":"III","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":564331,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70125277,"text":"70125277 - 2013 - The contributions of Donald Lee Johnson to understanding the Quaternary geologic and biogeographic history of the California Channel Islands","interactions":[],"lastModifiedDate":"2014-09-16T11:47:43","indexId":"70125277","displayToPublicDate":"2014-01-01T11:46:24","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2785,"text":"Monographs of the Western North American Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"The contributions of Donald Lee Johnson to understanding the Quaternary geologic and biogeographic history of the California Channel Islands","docAbstract":"Over a span of 50 years, native Californian Donald Lee Johnson made a number of memorable contributions to our understanding of the California Channel Islands. Among these are (1) recognizing that carbonate dunes, often cemented into eolianite and derived from offshore shelf sediments during lowered sea level, are markers of glacial periods on the Channel Islands; (2) identifying beach rock on the Channel Islands as the northernmost occurrence of this feature on the Pacific Coast of North America; (3) recognizing of the role of human activities in historic landscape modification; (4) identifying both the biogenic and pedogenic origins of caliche “ghost forests” and laminar calcrete forms on the Channel Islands; (5) providing the first soil maps of several of the islands, showing diverse pathways of pedogenesis; (6) pointing out the importance of fire in Quaternary landscape history on the Channel Islands, based on detailed stratigraphic studies; and (7), perhaps his greatest contribution, clarifying the origin of Pleistocene pygmy mammoths on the Channel Islands, due not to imagined ancient land bridges, but rather the superb swimming abilities of proboscideans combined with lowered sea level, favorable paleowinds, and an attractive paleovegetation on the Channel Islands. Don was a classic natural historian in the great tradition of Charles Darwin and George Gaylord Simpson, his role models. Don’s work will remain important and useful for many years and is an inspiration to those researching the California Channel Islands today.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Monographs of the Western North American Naturalist","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"M.L. Bean Museum","publisherLocation":"Provo, UT","usgsCitation":"Muhs, D.R., 2013, The contributions of Donald Lee Johnson to understanding the Quaternary geologic and biogeographic history of the California Channel Islands: Monographs of the Western North American Naturalist, v. 7, p. 1-20.","productDescription":"20 p.","startPage":"1","endPage":"20","numberOfPages":"20","ipdsId":"IP-050673","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":293941,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Channel Islands","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -118.4522588803,32.8153557197 ], [ -118.4522588803,32.8180536803 ], [ -118.4495609197,32.8180536803 ], [ -118.4495609197,32.8153557197 ], [ -118.4522588803,32.8153557197 ] ] ] } } ] }","volume":"7","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54195158e4b091c7ffc8e87e","contributors":{"authors":[{"text":"Muhs, Daniel R. 0000-0001-7449-251X dmuhs@usgs.gov","orcid":"https://orcid.org/0000-0001-7449-251X","contributorId":1857,"corporation":false,"usgs":true,"family":"Muhs","given":"Daniel","email":"dmuhs@usgs.gov","middleInitial":"R.","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"preferred":true,"id":501100,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70116317,"text":"sir20105070K - 2013 - A deposit model for magmatic iron-titanium-oxide deposits related to Proterozoic massif anorthosite plutonic suite","interactions":[{"subject":{"id":70047763,"text":"sir20135091 - 2013 - A deposit model for magmatic iron-titanium-oxide deposits related to Proterozoic massif anorthosite plutonic suites","indexId":"sir20135091","publicationYear":"2013","noYear":false,"title":"A deposit model for magmatic iron-titanium-oxide deposits related to Proterozoic massif anorthosite plutonic suites"},"predicate":"SUPERSEDED_BY","object":{"id":70116317,"text":"sir20105070K - 2013 - A deposit model for magmatic iron-titanium-oxide deposits related to Proterozoic massif anorthosite plutonic suite","indexId":"sir20105070K","publicationYear":"2013","noYear":false,"chapter":"K","title":"A deposit model for magmatic iron-titanium-oxide deposits related to Proterozoic massif anorthosite plutonic suite"},"id":1}],"lastModifiedDate":"2022-12-12T23:07:42.262855","indexId":"sir20105070K","displayToPublicDate":"2014-01-01T10:32:56","publicationYear":"2013","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":"2010-5070","chapter":"K","title":"A deposit model for magmatic iron-titanium-oxide deposits related to Proterozoic massif anorthosite plutonic suite","docAbstract":"<p>This descriptive model for magmatic iron-titanium-oxide (Fe-Ti-oxide) deposits hosted by Proterozoic age massif-type anorthosite and related rock types presents their geological, mineralogical, geochemical, and geoenvironmental attributes. Although these Proterozoic rocks are found worldwide, the majority of known deposits are found within exposed rocks of the Grenville Province, stretching from southwestern United States through eastern Canada; its extension into Norway is termed the Rogaland Anorthosite Province. This type of Fe-Ti-oxide deposit dominated by ilmenite rarely contains more than 300 million tons of ore, with between 10- to 45-percent titanium dioxide (TiO<sub>2</sub>), 32- to 45-percent iron oxide (FeO), and less than 0.2-percent vanadium (V).</p>\n<p>The origin of these typically discordant ore deposits remains as enigmatic as the magmatic evolution of their host rocks. The deposits clearly have a magmatic origin, hosted by an age-constrained unique suite of rocks that likely are the consequence of a particular combination of tectonic circumstances, rather than any a priori temporal control. Principal ore minerals are ilmenite and hemo-ilmenite (ilmenite with extensive hematite exsolution lamellae); occurrences of titanomagnetite, magnetite, and apatite that are related to this deposit type are currently of less economic importance. Ore-mineral paragenesis is somewhat obscured by complicated solid solution and oxidation behavior within the Fe-Ti-oxide system. Anorthosite suites hosting these deposits require an extensive history of voluminous plagioclase crystallization to develop plagioclase-melt diapirs with entrained Fe-Ti-rich melt rising from the base of the lithosphere to mid- and upper-crustal levels. Timing and style of oxide mineralization are related to magmatic and dynamic evolution of these diapiric systems and to development and movement of oxide cumulates and related melts.</p>\n<p>Active mines have developed large open pits with extensive waste-rock piles, but because of the nature of the ore and waste rock, the major environmental impacts documented at the mine sites are reported to be waste disposal issues and somewhat degraded water quality.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Mineral deposit models for resource assessment (Scientific Investigations Report 2010-5070)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20105070K","usgsCitation":"Woodruff, L.G., Nicholson, S.W., and Fey, D.L., 2013, A deposit model for magmatic iron-titanium-oxide deposits related to Proterozoic massif anorthosite plutonic suite: U.S. Geological Survey Scientific Investigations Report 2010-5070, vii, 47 p., https://doi.org/10.3133/sir20105070K.","productDescription":"vii, 47 p.","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":289714,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20105070K.gif"},{"id":289713,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2010/5070/k/pdf/sir2010-5070k.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":289712,"rank":11,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5070/k/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53bfb5e5e4b06d97a6487cfc","contributors":{"authors":[{"text":"Woodruff, Laurel G. 0000-0002-2514-9923 woodruff@usgs.gov","orcid":"https://orcid.org/0000-0002-2514-9923","contributorId":2224,"corporation":false,"usgs":true,"family":"Woodruff","given":"Laurel","email":"woodruff@usgs.gov","middleInitial":"G.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":495762,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nicholson, Suzanne W. 0000-0002-9365-1894 swnich@usgs.gov","orcid":"https://orcid.org/0000-0002-9365-1894","contributorId":880,"corporation":false,"usgs":true,"family":"Nicholson","given":"Suzanne","email":"swnich@usgs.gov","middleInitial":"W.","affiliations":[],"preferred":true,"id":495761,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fey, David L. dfey@usgs.gov","contributorId":713,"corporation":false,"usgs":true,"family":"Fey","given":"David","email":"dfey@usgs.gov","middleInitial":"L.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":495760,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70129217,"text":"70129217 - 2013 - Annual flood sensitivities to El Niño-Southern Oscillation at the global scale","interactions":[],"lastModifiedDate":"2014-10-21T10:00:29","indexId":"70129217","displayToPublicDate":"2014-01-01T09:59:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Annual flood sensitivities to El Niño-Southern Oscillation at the global scale","docAbstract":"Floods are amongst the most dangerous natural hazards in terms of economic damage. Whilst a growing number of studies have examined how river floods are influenced by climate change, the role of natural modes of interannual climate variability remains poorly understood. We present the first global assessment of the influence of El Niño–Southern Oscillation (ENSO) on annual river floods, defined here as the peak daily discharge in a given year. The analysis was carried out by simulating daily gridded discharges using the WaterGAP model (Water – a Global Assessment and Prognosis), and examining statistical relationships between these discharges and ENSO indices. We found that, over the period 1958–2000, ENSO exerted a significant influence on annual floods in river basins covering over a third of the world's land surface, and that its influence on annual floods has been much greater than its influence on average flows. We show that there are more areas in which annual floods intensify with La Niña and decline with El Niño than vice versa. However, we also found that in many regions the strength of the relationships between ENSO and annual floods have been non-stationary, with either strengthening or weakening trends during the study period. We discuss the implications of these findings for science and management. Given the strong relationships between ENSO and annual floods, we suggest that more research is needed to assess relationships between ENSO and flood impacts (e.g. loss of lives or economic damage). Moreover, we suggest that in those regions where useful relationships exist, this information could be combined with ongoing advances in ENSO prediction research, in order to provide year-to-year probabilistic flood risk forecasts.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Hydrology and Earth System Sciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"European Geophysical Society","publisherLocation":"Katlenburg-Lindau, Germany","doi":"10.5194/hess-18-47-2014","usgsCitation":"Ward, P.J., Eisner, S., Florke, M., Dettinger, M., and Kummu, M., 2013, Annual flood sensitivities to El Niño-Southern Oscillation at the global scale: Hydrology and Earth System Sciences, v. 18, p. 47-66, https://doi.org/10.5194/hess-18-47-2014.","productDescription":"20 p.","startPage":"47","endPage":"66","numberOfPages":"20","ipdsId":"IP-052126","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":473371,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-18-47-2014","text":"Publisher Index Page"},{"id":295520,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":295480,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.5194/hess-18-47-2014"},{"id":295481,"type":{"id":15,"text":"Index Page"},"url":"https://www.hydrol-earth-syst-sci.net/18/47/2014/hess-18-47-2014.html"}],"volume":"18","noUsgsAuthors":false,"publicationDate":"2014-01-06","publicationStatus":"PW","scienceBaseUri":"544775a3e4b0f888a81b82f4","contributors":{"authors":[{"text":"Ward, Philip J.","contributorId":67434,"corporation":false,"usgs":true,"family":"Ward","given":"Philip","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":503551,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eisner, S.","contributorId":48892,"corporation":false,"usgs":true,"family":"Eisner","given":"S.","email":"","affiliations":[],"preferred":false,"id":503550,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Florke, M.","contributorId":29335,"corporation":false,"usgs":true,"family":"Florke","given":"M.","email":"","affiliations":[],"preferred":false,"id":503548,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dettinger, Michael D. 0000-0002-7509-7332","orcid":"https://orcid.org/0000-0002-7509-7332","contributorId":8019,"corporation":false,"usgs":true,"family":"Dettinger","given":"Michael D.","affiliations":[],"preferred":false,"id":503547,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kummu, M.","contributorId":39711,"corporation":false,"usgs":true,"family":"Kummu","given":"M.","email":"","affiliations":[],"preferred":false,"id":503549,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70100905,"text":"70100905 - 2013 - Late Miocene-Pleistocene evolution of a Rio Grande rift subbasin, Sunshine Valley-Costilla Plain, San Luis Basin, New Mexico and Colorado","interactions":[],"lastModifiedDate":"2017-04-14T10:28:55","indexId":"70100905","displayToPublicDate":"2014-01-01T09:44:40","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1727,"text":"GSA Special Papers","active":true,"publicationSubtype":{"id":10}},"title":"Late Miocene-Pleistocene evolution of a Rio Grande rift subbasin, Sunshine Valley-Costilla Plain, San Luis Basin, New Mexico and Colorado","docAbstract":"<p>The Sunshine Valley-Costilla Plain, a structural subbasin of the greater San Luis Basin of the northern Rio Grande rift, is bounded to the north and south by the San Luis Hills and the Red River fault zone, respectively. Surficial mapping, neotectonic investigations, geochronology, and geophysics demonstrate that the structural, volcanic, and geomorphic evolution of the basin involves the intermingling of climatic cycles and spatially and temporally varying tectonic activity of the Rio Grande rift system. Tectonic activity has transferred between range-bounding and intrabasin faults creating relict landforms of higher tectonic-activity rates along the mountain-piedmont junction. Pliocene–Pleistocene average long-term slip rates along the southern Sangre de Cristo fault zone range between 0.1 and 0.2 mm/year with late Pleistocene slip rates approximately half (0.06 mm/year) of the longer Quaternary slip rate. During the late Pleistocene, climatic influences have been dominant over tectonic influences on mountain-front geomorphic processes. Geomorphic evidence suggests that this once-closed subbasin was integrated into the Rio Grande prior to the integration of the once-closed northern San Luis Basin, north of the San Luis Hills, Colorado; however, deep canyon incision, north of the Red River and south of the San Luis Hills, initiated relatively coeval to the integration of the northern San Luis Basin.</p><p><br></p><p>Long-term projections of slip rates applied to a 1.6 km basin depth defined from geophysical modeling suggests that rifting initiated within this subbasin between 20 and 10 Ma. Geologic mapping and geophysical interpretations reveal a complex network of northwest-, northeast-, and north-south–trending faults. Northwest- and northeast-trending faults show dual polarity and are crosscut by north-south– trending faults. This structural model possibly provides an analog for how some intracontinental rift structures evolve through time.</p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/2013.2494(03)","usgsCitation":"Ruleman, C., Thompson, R.A., Shroba, R., Anderson, M., Drenth, B., Rotzien, J., and Lyon, J., 2013, Late Miocene-Pleistocene evolution of a Rio Grande rift subbasin, Sunshine Valley-Costilla Plain, San Luis Basin, New Mexico and Colorado: GSA Special Papers, v. 494, p. 47-73, https://doi.org/10.1130/2013.2494(03).","productDescription":"27 p.","startPage":"47","endPage":"73","ipdsId":"IP-029946","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":285881,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, New Mexico","otherGeospatial":"San Luis Basin;San Luis Hills","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -106.4932,36.1484 ], [ -106.4932,38.2775 ], [ -105.2298,38.2775 ], [ -105.2298,36.1484 ], [ -106.4932,36.1484 ] ] ] } } ] }","volume":"494","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"535594a9e4b0120853e8c047","contributors":{"authors":[{"text":"Ruleman, C.A.","contributorId":50237,"corporation":false,"usgs":true,"family":"Ruleman","given":"C.A.","email":"","affiliations":[],"preferred":false,"id":492466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, R. A.","contributorId":100420,"corporation":false,"usgs":true,"family":"Thompson","given":"R.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":492469,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shroba, R. R.","contributorId":44133,"corporation":false,"usgs":true,"family":"Shroba","given":"R. R.","affiliations":[],"preferred":false,"id":492464,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anderson, M.","contributorId":63141,"corporation":false,"usgs":true,"family":"Anderson","given":"M.","affiliations":[],"preferred":false,"id":492468,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Drenth, B. J.","contributorId":49885,"corporation":false,"usgs":true,"family":"Drenth","given":"B. J.","affiliations":[],"preferred":false,"id":492465,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rotzien, J.","contributorId":20254,"corporation":false,"usgs":true,"family":"Rotzien","given":"J.","email":"","affiliations":[],"preferred":false,"id":492463,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lyon, J.","contributorId":57370,"corporation":false,"usgs":true,"family":"Lyon","given":"J.","affiliations":[],"preferred":false,"id":492467,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70093890,"text":"70093890 - 2013 - Blind test of methods for obtaining 2-D near-surface seismic velocity models from first-arrival traveltimes","interactions":[],"lastModifiedDate":"2017-11-07T10:30:12","indexId":"70093890","displayToPublicDate":"2014-01-01T08:43:07","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3928,"text":"Journal of Environmental & Engineering Geophysics","printIssn":"1083-1363","active":true,"publicationSubtype":{"id":10}},"title":"Blind test of methods for obtaining 2-D near-surface seismic velocity models from first-arrival traveltimes","docAbstract":"Seismic refraction methods are used in environmental and engineering studies to image the shallow subsurface. We present a blind test of inversion and tomographic refraction analysis methods using a synthetic first-arrival-time dataset that was made available to the community in 2010. The data are realistic in terms of the near-surface velocity model, shot-receiver geometry and the data's frequency and added noise. Fourteen estimated models were determined by ten participants using eight different inversion algorithms, with the true model unknown to the participants until it was revealed at a session at the 2011 SAGEEP meeting. The estimated models are generally consistent in terms of their large-scale features, demonstrating the robustness of refraction data inversion in general, and the eight inversion algorithms in particular. When compared to the true model, all of the estimated models contain a smooth expression of its two main features: a large offset in the bedrock and the top of a steeply dipping low-velocity fault zone. The estimated models do not contain a subtle low-velocity zone and other fine-scale features, in accord with conventional wisdom. Together, the results support confidence in the reliability and robustness of modern refraction inversion and tomographic methods.","language":"English","publisher":"Journal of Environmental and Engineering Geophysics","doi":"10.2113/JEEG18.3.183","usgsCitation":"Zelt, C.A., Haines, S., Powers, M.H., Sheehan, J., Rohdewald, S., Link, C., Hayashi, K., Zhao, D., Zhou, H., Burton, B., Petersen, U.K., Bonal, N.D., and Doll, W.E., 2013, Blind test of methods for obtaining 2-D near-surface seismic velocity models from first-arrival traveltimes: Journal of Environmental & Engineering Geophysics, v. 18, no. 3, p. 183-194, https://doi.org/10.2113/JEEG18.3.183.","productDescription":"12 p.","startPage":"183","endPage":"194","ipdsId":"IP-043837","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":282370,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2113/JEEG18.3.183"},{"id":282371,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd4fa1e4b0b290850f2d42","contributors":{"authors":[{"text":"Zelt, Colin A.","contributorId":99461,"corporation":false,"usgs":true,"family":"Zelt","given":"Colin","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":490258,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haines, Seth 0000-0003-2611-8165","orcid":"https://orcid.org/0000-0003-2611-8165","contributorId":97814,"corporation":false,"usgs":true,"family":"Haines","given":"Seth","affiliations":[],"preferred":false,"id":490257,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Powers, Michael H. 0000-0002-4480-7856 mhpowers@usgs.gov","orcid":"https://orcid.org/0000-0002-4480-7856","contributorId":851,"corporation":false,"usgs":true,"family":"Powers","given":"Michael","email":"mhpowers@usgs.gov","middleInitial":"H.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":490246,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sheehan, Jacob","contributorId":75059,"corporation":false,"usgs":true,"family":"Sheehan","given":"Jacob","email":"","affiliations":[],"preferred":false,"id":490256,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rohdewald, Siegfried","contributorId":64554,"corporation":false,"usgs":true,"family":"Rohdewald","given":"Siegfried","email":"","affiliations":[],"preferred":false,"id":490255,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Link, Curtis","contributorId":6368,"corporation":false,"usgs":true,"family":"Link","given":"Curtis","email":"","affiliations":[],"preferred":false,"id":490248,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hayashi, Koichi","contributorId":22675,"corporation":false,"usgs":true,"family":"Hayashi","given":"Koichi","email":"","affiliations":[],"preferred":false,"id":490251,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Zhao, Don","contributorId":58182,"corporation":false,"usgs":true,"family":"Zhao","given":"Don","email":"","affiliations":[],"preferred":false,"id":490254,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Zhou, Hua-wei","contributorId":11504,"corporation":false,"usgs":true,"family":"Zhou","given":"Hua-wei","email":"","affiliations":[],"preferred":false,"id":490249,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Burton, Bethany L. 0000-0001-5011-7862 blburton@usgs.gov","orcid":"https://orcid.org/0000-0001-5011-7862","contributorId":1341,"corporation":false,"usgs":true,"family":"Burton","given":"Bethany L.","email":"blburton@usgs.gov","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":490247,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Petersen, Uni K.","contributorId":34037,"corporation":false,"usgs":true,"family":"Petersen","given":"Uni","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":490253,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Bonal, Nedra D.","contributorId":26620,"corporation":false,"usgs":true,"family":"Bonal","given":"Nedra","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":490252,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Doll, William E.","contributorId":20249,"corporation":false,"usgs":true,"family":"Doll","given":"William","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":490250,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70171567,"text":"70171567 - 2013 - The impact environment of the Hadean Earth","interactions":[],"lastModifiedDate":"2016-06-06T10:17:27","indexId":"70171567","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1220,"text":"Chemie der Erde","active":true,"publicationSubtype":{"id":10}},"title":"The impact environment of the Hadean Earth","docAbstract":"<p><span>Impact bombardment in the first billion years of solar system history determined in large part the initial physical and chemical states of the inner planets and their potential to host biospheres. The range of physical states and thermal consequences of the impact epoch, however, are not well quantified. Here, we assess these effects on the young Earth's crust as well as the likelihood that a record of such effects could be preserved in the oldest terrestrial minerals and rocks. We place special emphasis on modeling the thermal effects of the late heavy bombardment (LHB) &ndash; a putative spike in the number of impacts at about 3.9&nbsp;Gyr ago &ndash; using several different numerical modeling and analytical techniques. A comprehensive array of impact-produced heat sources was evaluated which includes shock heating, impact melt generation, uplift, and ejecta heating. Results indicate that &sim;1.5&ndash;2.5&nbsp;vol.% of the upper 20&nbsp;km of Earth's crust was melted in the LHB, with only &sim;0.3&ndash;1.5&nbsp;vol.% in a molten state at any given time. The model predicts that approximately 5&ndash;10% of the planet's surface area was covered by &gt;1&nbsp;km deep impact melt sheets. A global average of &sim;600&ndash;800&nbsp;m of ejecta and &sim;800&ndash;1000&nbsp;m of condensed rock vapor is predicted to have been deposited in the LHB, with most of the condensed rock vapor produced by the largest (&gt;100-km) projectiles. To explore for a record of such catastrophic events, we created two- and three-dimensional models of post-impact cooling of ejecta and craters, coupled to diffusion models of radiogenic Pb*-loss in zircons. We used this to estimate what the cumulative effects of putative LHB-induced age resetting would be of Hadean zircons on a global scale. Zircons entrained in ejecta are projected to have the following average global distribution after the end of the LHB: &sim;59% with no impact-induced Pb*-loss, &sim;26% with partial Pb*-loss and &sim;15% with complete Pb*-loss or destruction of the grain. In addition to the relatively high erodibility of ejecta, our results show that if discordant ca. 3.9&nbsp;Gyr old zones in the Jack Hills zircons are a signature of the LHB, they were most likely sourced from impact ejecta.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemer.2013.08.004","usgsCitation":"Abramov, O., Kring, D.A., and Mojzsis, S.J., 2013, The impact environment of the Hadean Earth: Chemie der Erde, v. 73, no. 3, p. 227-248, https://doi.org/10.1016/j.chemer.2013.08.004.","productDescription":"22 p.","startPage":"227","endPage":"248","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-042682","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":322190,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"73","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57569eb7e4b023b96ec28480","contributors":{"authors":[{"text":"Abramov, Oleg oabramov@usgs.gov","contributorId":604,"corporation":false,"usgs":true,"family":"Abramov","given":"Oleg","email":"oabramov@usgs.gov","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":631834,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kring, David A. Kring","contributorId":170042,"corporation":false,"usgs":false,"family":"Kring","given":"David","email":"","middleInitial":"A. Kring","affiliations":[{"id":25656,"text":"Lunar and Planetary Institute, Universities Space Research Association, 3600 Bay Area Blvd., Houston, TX 77058, United States","active":true,"usgs":false}],"preferred":false,"id":631835,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mojzsis, Stephen J.","contributorId":170043,"corporation":false,"usgs":false,"family":"Mojzsis","given":"Stephen","email":"","middleInitial":"J.","affiliations":[{"id":25657,"text":"Univ. of Colo., Dept. of Geological Sciences, NASA Lunar Science Institute, Center for Lunar Origin and Evolution (CLOE), Boulder, Colo.; Ecole Normale Superieure de Lyon & Universite Claude Bernard Lyon; Hungarian Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":631836,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70169152,"text":"70169152 - 2013 - Niche overlap, threshold food densities, and limits to prey depletion for a diving duck assemblage in an estuarine bay","interactions":[],"lastModifiedDate":"2017-07-19T15:44:15","indexId":"70169152","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2663,"text":"Marine Ecology Progress Series","active":true,"publicationSubtype":{"id":10}},"title":"Niche overlap, threshold food densities, and limits to prey depletion for a diving duck assemblage in an estuarine bay","docAbstract":"<p><span>Planning for marine conservation often requires estimates of the amount of habitat needed to support assemblages of interacting species. During winter in subtidal San Pablo Bay, California, the 3 main diving duck species are lesser scaup&nbsp;</span><i>Aythya affinis</i><span>&nbsp;(LESC), greater scaup&nbsp;</span><i>A. marila</i><span>&nbsp;(GRSC), and surf scoter&nbsp;</span><i>Melanitta perspicillata</i><span>&nbsp;(SUSC), which all feed almost entirely on the bivalve&nbsp;</span><i>Corbula amurensis</i><span>. Decreased body mass and fat, increased foraging effort, and major departures of these birds appeared to result from food limitation. Broad overlap in prey size, water depth, and location suggested that the 3 species responded similarly to availability of the same prey. However, an energetics model that accounts for differing body size, locomotor mode, and dive behavior indicated that each species will become limited at different stages of prey depletion in the order SUSC, then GRSC, then LESC. Depending on year, 35 to 66% of the energy in&nbsp;</span><i>Corbula</i><span>&nbsp;standing stocks was below estimated threshold densities for profitable foraging. Ectothermic predators, especially flounders and sturgeons, could reduce excess carrying capacity for different duck species by 4 to 10%. A substantial quantity of prey above profitability thresholds was not exploited before most ducks left San Pablo Bay. Such pre-depletion departure has been attributed in other taxa to foraging aggression. However, in these diving ducks that showed no overt aggression, this pattern may result from high costs of locating all adequate prey patches, resulting reliance on existing flocks to find food, and propensity to stay near dense flocks to avoid avian predation. For interacting species assemblages, modeling profitability thresholds can indicate the species most vulnerable to food declines. However, estimates of total habitat needed require better understanding of factors affecting the amount of prey above thresholds that is not depleted before the predators move elsewhere.</span></p>","language":"English","publisher":"Inter-Research","doi":"10.3354/meps10104","usgsCitation":"Lovvorn, J.R., De La Cruz, S., Takekawa, J.Y., Shaskey, L.E., and Richman, S.E., 2013, Niche overlap, threshold food densities, and limits to prey depletion for a diving duck assemblage in an estuarine bay: Marine Ecology Progress Series, v. 476, p. 251-268, https://doi.org/10.3354/meps10104.","productDescription":"18 p.","startPage":"251","endPage":"268","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-028764","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":473379,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/meps10104","text":"Publisher Index Page"},{"id":319207,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"476","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56f3be47e4b0f59b85e02ebb","contributors":{"authors":[{"text":"Lovvorn, James R.","contributorId":167714,"corporation":false,"usgs":false,"family":"Lovvorn","given":"James","email":"","middleInitial":"R.","affiliations":[{"id":13212,"text":"Southern Illinois University","active":true,"usgs":false}],"preferred":false,"id":623239,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"De La Cruz, Susan sdelacruz@usgs.gov","contributorId":131159,"corporation":false,"usgs":true,"family":"De La Cruz","given":"Susan","email":"sdelacruz@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":623240,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Takekawa, John Y. 0000-0003-0217-5907 john_takekawa@usgs.gov","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":176168,"corporation":false,"usgs":true,"family":"Takekawa","given":"John","email":"john_takekawa@usgs.gov","middleInitial":"Y.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":623238,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shaskey, Laura E.","contributorId":167715,"corporation":false,"usgs":false,"family":"Shaskey","given":"Laura","email":"","middleInitial":"E.","affiliations":[{"id":17847,"text":"USGS-WERC","active":true,"usgs":false}],"preferred":false,"id":623241,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Richman, Samantha E.","contributorId":167716,"corporation":false,"usgs":false,"family":"Richman","given":"Samantha","email":"","middleInitial":"E.","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":623242,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70168413,"text":"70168413 - 2013 - Movements, cover-type selection, and survival of fledgling Ovenbirds in managed deciduous and mixed coniferous-deciduous forests","interactions":[],"lastModifiedDate":"2016-02-12T13:14:51","indexId":"70168413","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Movements, cover-type selection, and survival of fledgling Ovenbirds in managed deciduous and mixed coniferous-deciduous forests","docAbstract":"<p><span>We used radio telemetry to monitor movements, cover-type selection, and survival for fledglings of the mature-forest nesting Ovenbird (</span><i>Seiurus aurocapilla</i><span>) at two managed forest sites in north-central Minnesota. Both sites contained forested wetlands, regenerating clearcut stands of various ages, and logging roads, but differed in mature forest composition; one deciduous with open understory, and the other mixed coniferous-deciduous with dense understory. We used compositional analysis, modified to incorporate age-specific limitations in fledgling movements, to assess cover-type selection by fledglings throughout the dependent (on adult care) post-fledging period. Compared to those that were depredated, fledglings from nests in deciduous forest that survived the early post-fledging period had more older (sapling-dominated) clearcut available, directed movements toward older clearcuts and forested wetlands, and used older clearcuts more than other cover types relative to availability. Fledglings that were depredated had more young (shrub-dominated) clearcut and unpaved logging road available, and used mature forest and roads more than expected based on availability. For birds from nests in mixed mature forest with dense understory, movements and cover-type selection were similar between fledglings that survived and those that were depredated. However, fledglings that were depredated at that site also had more young clearcut available than fledglings that survived. We conclude that Ovenbird fledgling survival is influenced by distance of their nest to various non-nesting cover types, and by the subsequent selection among those cover types, but that the influence of non-nesting cover types varies depending on the availability of dense understory vegetation in mature forest.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2012.08.046","usgsCitation":"Streby, H.M., and Andersen, D., 2013, Movements, cover-type selection, and survival of fledgling Ovenbirds in managed deciduous and mixed coniferous-deciduous forests: Forest Ecology and Management, v. 287, p. 9-16, https://doi.org/10.1016/j.foreco.2012.08.046.","productDescription":"8 p.","startPage":"9","endPage":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-026539","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":317996,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","volume":"287","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56bf1058e4b06458514b6923","contributors":{"authors":[{"text":"Streby, Henry M.","contributorId":11024,"corporation":false,"usgs":false,"family":"Streby","given":"Henry","email":"","middleInitial":"M.","affiliations":[{"id":12455,"text":"University of Toledo","active":true,"usgs":false}],"preferred":false,"id":620123,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andersen, David E. 0000-0001-9535-3404 dea@usgs.gov","orcid":"https://orcid.org/0000-0001-9535-3404","contributorId":2168,"corporation":false,"usgs":true,"family":"Andersen","given":"David E.","email":"dea@usgs.gov","affiliations":[{"id":34539,"text":"Minnesota Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":619982,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70173432,"text":"70173432 - 2013 - Accuracy of stream habitat interpolations across spatial scales","interactions":[],"lastModifiedDate":"2016-06-21T16:13:26","indexId":"70173432","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5095,"text":"Journal of Geographic Information System","active":true,"publicationSubtype":{"id":10}},"title":"Accuracy of stream habitat interpolations across spatial scales","docAbstract":"<p>Stream habitat data are often collected across spatial scales because relationships among habitat, species occurrence, and management plans are linked at multiple spatial scales. Unfortunately, scale is often a factor limiting insight gained from spatial analysis of stream habitat data. Considerable cost is often expended to collect data at several spatial scales to provide accurate evaluation of spatial relationships in streams. To address utility of single scale set of stream habitat data used at varying scales, we examined the influence that data scaling had on accuracy of natural neighbor predictions of depth, flow, and benthic substrate. To achieve this goal, we measured two streams at gridded resolution of 0.33 &times; 0.33 meter cell size over a combined area of 934 m2 to create a baseline for natural neighbor interpolated maps at 12 incremental scales ranging from a raster cell size of 0.11 m2 to 16 m2 . Analysis of predictive maps showed a logarithmic linear decay pattern in RMSE values in interpolation accuracy for variables as resolution of data used to interpolate study areas became coarser. Proportional accuracy of interpolated models (r2 ) decreased, but it was maintained up to 78% as interpolation scale moved from 0.11 m2 to 16 m2 . Results indicated that accuracy retention was suitable for assessment and management purposes at various scales different from the data collection scale. Our study is relevant to spatial modeling, fish habitat assessment, and stream habitat management because it highlights the potential of using a single dataset to fulfill analysis needs rather than investing considerable cost to develop several scaled datasets.</p>","language":"English","publisher":"Scientific Research","doi":"10.4236/jgis.2013.56057","usgsCitation":"Sheehan, K.R., and Welsh, S., 2013, Accuracy of stream habitat interpolations across spatial scales: Journal of Geographic Information System, v. 5, p. 606-612, https://doi.org/10.4236/jgis.2013.56057.","productDescription":"7 p.","startPage":"606","endPage":"612","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-033558","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":473384,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.4236/jgis.2013.56057","text":"Publisher Index Page"},{"id":324171,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576a652fe4b07657d1a11cee","contributors":{"authors":[{"text":"Sheehan, Kenneth R.","contributorId":146541,"corporation":false,"usgs":false,"family":"Sheehan","given":"Kenneth","email":"","middleInitial":"R.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":637126,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Welsh, Stuart A. 0000-0003-0362-054X swelsh@usgs.gov","orcid":"https://orcid.org/0000-0003-0362-054X","contributorId":152088,"corporation":false,"usgs":true,"family":"Welsh","given":"Stuart A.","email":"swelsh@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":637125,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70155070,"text":"70155070 - 2013 - Quantitative and qualitative approaches to identifying migration chronology in a continental migrant","interactions":[],"lastModifiedDate":"2015-08-05T13:01:35","indexId":"70155070","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Quantitative and qualitative approaches to identifying migration chronology in a continental migrant","docAbstract":"<p>The degree to which extrinsic factors influence migration chronology in North American waterfowl has not been quantified, particularly for dabbling ducks. Previous studies have examined waterfowl migration using various methods, however, quantitative approaches to define avian migration chronology over broad spatio-temporal scales are limited, and the implications for using different approaches have not been assessed. We used movement data from 19 female adult mallards (Anas platyrhynchos) equipped with solar-powered global positioning system satellite transmitters to evaluate two individual level approaches for quantifying migration chronology. The first approach defined migration based on individual movements among geopolitical boundaries (state, provincial, international), whereas the second method modeled net displacement as a function of time using nonlinear models. Differences in migration chronologies identified by each of the approaches were examined with analysis of variance. The geopolitical method identified mean autumn migration midpoints at 15 November 2010 and 13 November 2011, whereas the net displacement method identified midpoints at 15 November 2010 and 14 November 2011. The mean midpoints for spring migration were 3 April 2011 and 20 March 2012 using the geopolitical method and 31 March 2011 and 22 March 2012 using the net displacement method. The duration, initiation date, midpoint, and termination date for both autumn and spring migration did not differ between the two individual level approaches. Although we did not detect differences in migration parameters between the different approaches, the net displacement metric offers broad potential to address questions in movement ecology for migrating species. Ultimately, an objective definition of migration chronology will allow researchers to obtain a comprehensive understanding of the extrinsic factors that drive migration at the individual and population levels. As a result, targeted conservation plans can be developed to support planning for habitat management and evaluation of long-term climate effects.</p>","language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0075673","usgsCitation":"Beatty, W.S., Kesler, D.C., Webb, E.B., Raedeke, A.H., Naylor, L.W., and Humburg, D.D., 2013, Quantitative and qualitative approaches to identifying migration chronology in a continental migrant: PLoS ONE, p. 1-9, https://doi.org/10.1371/journal.pone.0075673.","productDescription":"e75673; 9 p.","startPage":"1","endPage":"9","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2010-09-01","temporalEnd":"2012-12-31","ipdsId":"IP-045956","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":473373,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0075673","text":"Publisher Index Page"},{"id":306440,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2013-10-09","publicationStatus":"PW","scienceBaseUri":"57f7f1d6e4b0bc0bec0a0024","contributors":{"authors":[{"text":"Beatty, William S. 0000-0003-0013-3113","orcid":"https://orcid.org/0000-0003-0013-3113","contributorId":146301,"corporation":false,"usgs":false,"family":"Beatty","given":"William","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":567383,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kesler, Dylan C.","contributorId":14358,"corporation":false,"usgs":false,"family":"Kesler","given":"Dylan","email":"","middleInitial":"C.","affiliations":[{"id":6769,"text":"University of Missouri, Columbia, MO","active":true,"usgs":false}],"preferred":false,"id":567384,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Webb, Elisabeth B. 0000-0003-3851-6056 ewebb@usgs.gov","orcid":"https://orcid.org/0000-0003-3851-6056","contributorId":3981,"corporation":false,"usgs":true,"family":"Webb","given":"Elisabeth","email":"ewebb@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":564764,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Raedeke, Andrew H.","contributorId":94083,"corporation":false,"usgs":true,"family":"Raedeke","given":"Andrew","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":567385,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Naylor, Luke W.","contributorId":145840,"corporation":false,"usgs":false,"family":"Naylor","given":"Luke","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":567386,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Humburg, Dale D.","contributorId":79357,"corporation":false,"usgs":false,"family":"Humburg","given":"Dale","email":"","middleInitial":"D.","affiliations":[{"id":13073,"text":"Ducks Unlimited, Inc.","active":true,"usgs":false}],"preferred":false,"id":567387,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70173625,"text":"70173625 - 2013 - Landsat imagery reveals declining clarity of Maine’s lakes during 1995-2010","interactions":[],"lastModifiedDate":"2016-06-09T15:10:12","indexId":"70173625","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Landsat imagery reveals declining clarity of Maine’s lakes during 1995-2010","docAbstract":"<p><span>Water clarity is a strong indicator of regional water quality. Unlike other common water-quality metrics, such as chlorophyll&nbsp;</span><i>a</i><span>, total P, or trophic status, clarity can be accurately and efficiently estimated remotely on a regional scale. Satellite-based remote sensing is useful in regions with many lakes where traditional field-sampling techniques may be prohibitively expensive. Repeated sampling of easily accessed lakes can lead to spatially irregular, nonrandom samples of a region. Remote sensing remedies this problem. We applied a remote monitoring protocol we had previously developed for Maine lakes &gt;8&nbsp;ha based on Landsat satellite data recorded during 1995&ndash;2010 to identify spatial and temporal patterns in Maine lake clarity. We focused on the overlapping region of Landsat paths 11 and 12 to increase availability of cloud-free images in August and early September, a period of relative lake stability and seasonal poor-clarity conditions well suited for annual monitoring. We divided Maine into 3 regions (northeastern, south-central, western) based on morphometric and chemical lake features. We found a general decrease in average statewide lake clarity from 4.94 to 4.38&nbsp;m during 1995&ndash;2010. Water clarity ranged from 4 to 6&nbsp;m during 1995&ndash;2010, but it decreased consistently during 2005&ndash;2010. Clarity in both the northeastern and western lake regions has decreased from 5.22&nbsp;m in 1995 to 4.36 and 4.21&nbsp;m, respectively, in 2010, whereas lake clarity in the south-central lake region (4.50&nbsp;m) has not changed since 1995. Climate change, timber harvesting, or watershed morphometry may be responsible for regional water-clarity decline. Remote sensing of regional water clarity provides a more complete spatial perspective of lake water quality than existing, interest-based sampling. However, field sampling done under existing monitoring programs can be used to calibrate accurate models designed to estimate water clarity remotely.</span></p>","language":"English","publisher":"The University of Chicago Press","doi":"10.1899/12-070.1","usgsCitation":"McCullough, I.M., Loftin, C., and Sader, S., 2013, Landsat imagery reveals declining clarity of Maine’s lakes during 1995-2010: Freshwater Science, v. 32, no. 3, p. 741-752, https://doi.org/10.1899/12-070.1.","productDescription":"12 p.","startPage":"741","endPage":"752","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"1995-01-01","ipdsId":"IP-036854","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323411,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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A.","affiliations":[],"preferred":false,"id":638298,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70192250,"text":"70192250 - 2013 - The 2011 M = 9.0 Tohoku oki earthquake more than doubled the probability of large shocks beneath Tokyo","interactions":[],"lastModifiedDate":"2017-10-24T11:46:38","indexId":"70192250","displayToPublicDate":"2013-12-31T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The 2011 <i>M</i> = 9.0 Tohoku oki earthquake more than doubled the probability of large shocks beneath Tokyo","title":"The 2011 M = 9.0 Tohoku oki earthquake more than doubled the probability of large shocks beneath Tokyo","docAbstract":"1] The Kanto seismic corridor surrounding Tokyo has hosted four to five M ≥ 7 earthquakes in the past 400 years. Immediately after the Tohoku earthquake, the seismicity rate in the corridor jumped 10-fold, while the rate of normal focal mechanisms dropped in half. The seismicity rate decayed for 6–12 months, after which it steadied at three times the pre-Tohoku rate. The seismicity rate jump and decay to a new rate, as well as the focal mechanism change, can be explained by the static stress imparted by the Tohoku rupture and postseismic creep to Kanto faults. We therefore fit the seismicity observations to a rate/state Coulomb model, which we use to forecast the time-dependent probability of large earthquakes in the Kanto seismic corridor. We estimate a 17% probability of a M ≥ 7.0 shock over the 5 year prospective period 11 March 2013 to 10 March 2018, two-and-a-half times the probability had the Tohoku earthquake not struck","language":"English","publisher":"American Geophysical Union","doi":"10.1002/grl.50524","usgsCitation":"Toda, S., and Stein, R.S., 2013, The 2011 M = 9.0 Tohoku oki earthquake more than doubled the probability of large shocks beneath Tokyo: Geophysical Research Letters, v. 40, no. 11, p. 2562-2566, https://doi.org/10.1002/grl.50524.","productDescription":"5 p.","startPage":"2562","endPage":"2566","ipdsId":"IP-044008","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":347215,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Japan","state":"Tokyo","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              138,\n              34.075412438417395\n            ],\n            [\n              142,\n              34.075412438417395\n            ],\n            [\n              142,\n              37\n            ],\n            [\n              138,\n              37\n            ],\n            [\n              138,\n              34.075412438417395\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"40","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2013-06-06","publicationStatus":"PW","scienceBaseUri":"59f05124e4b0220bbd9a1dbe","contributors":{"authors":[{"text":"Toda, Shinji","contributorId":43062,"corporation":false,"usgs":true,"family":"Toda","given":"Shinji","email":"","affiliations":[],"preferred":false,"id":715009,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stein, Ross S. 0000-0001-7586-3933 rstein@usgs.gov","orcid":"https://orcid.org/0000-0001-7586-3933","contributorId":2604,"corporation":false,"usgs":true,"family":"Stein","given":"Ross","email":"rstein@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":715010,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70192414,"text":"70192414 - 2013 - Rapid chemical evolution of tropospheric volcanic emissions from Redoubt Volcano, Alaska, based on observations of ozone and halogen-containing gases","interactions":[],"lastModifiedDate":"2017-10-25T15:11:01","indexId":"70192414","displayToPublicDate":"2013-12-31T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Rapid chemical evolution of tropospheric volcanic emissions from Redoubt Volcano, Alaska, based on observations of ozone and halogen-containing gases","docAbstract":"<p><span>We report results from an observational and modeling study of reactive chemistry in the tropospheric plume emitted by Redoubt Volcano, Alaska. Our measurements include the first observations of Br and I degassing from an Alaskan volcano, the first study of O</span><sub>3</sub><span><span>&nbsp;</span>evolution in a volcanic plume, as well as the first detection of BrO in the plume of a passively degassing Alaskan volcano. This study also represents the first detailed spatially-resolved comparison of measured and modeled O</span><sub>3</sub><span><span>&nbsp;</span>depletion in a volcanic plume. The composition of the plume was measured on June 20, 2010 using base-treated filter packs (for F, Cl, Br, I, and S) at the crater rim and by an instrumented fixed-wing aircraft on June 21 and August 19, 2010. The aircraft was used to track the chemical evolution of the plume up to ~</span><span>&nbsp;</span><span>30</span><span>&nbsp;</span><span>km downwind (2</span><span>&nbsp;</span><span>h plume travel time) from the volcano and was equipped to make in situ observations of O</span><sub>3</sub><span>, water vapor, CO</span><sub>2</sub><span>, SO</span><sub>2</sub><span>, and H</span><sub>2</sub><span>S during both flights plus remote spectroscopic observations of SO</span><sub>2</sub><span><span>&nbsp;</span>and BrO on the August 19th flight. The airborne data from June 21 reveal rapid chemical O</span><sub>3</sub><span><span>&nbsp;</span>destruction in the plume as well as the strong influence chemical heterogeneity in background air had on plume composition. Spectroscopic retrievals from airborne traverses made under the plume on August 19 show that BrO was present ~</span><span>&nbsp;</span><span>6</span><span>&nbsp;</span><span>km downwind (20</span><span>&nbsp;</span><span>min plume travel time) and in situ measurements revealed several ppbv of O</span><sub>3</sub><span><span>&nbsp;</span>loss near the center of the plume at a similar location downwind. Simulations with the<span>&nbsp;</span></span><i>PlumeChem</i><span><span>&nbsp;</span>model reproduce the timing and magnitude of the observed O</span><sub>3</sub><span><span>&nbsp;</span>deficits and suggest that autocatalytic release of reactive bromine and in-plume formation of BrO were primarily responsible for the observed O</span><sub>3</sub><span><span>&nbsp;</span>destruction in the plume. The measurements are therefore in general agreement with recent model studies of reactive halogen formation in volcanic plumes, but also show that field studies must pay close attention to variations in the composition of ambient air entrained into volcanic plumes in order to unambiguously attribute observed O</span><sub>3</sub><span><span>&nbsp;</span>anomalies to specific chemical or dynamic processes. Our results suggest that volcanic eruptions in Alaska are sources of reactive halogen species to the subarctic troposphere.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2012.04.023","usgsCitation":"Werner, C.A., Kelly, P.J., Kern, C., Roberts, T., and Aluppe, A., 2013, Rapid chemical evolution of tropospheric volcanic emissions from Redoubt Volcano, Alaska, based on observations of ozone and halogen-containing gases: Journal of Volcanology and Geothermal Research, v. 259, p. 317-333, https://doi.org/10.1016/j.jvolgeores.2012.04.023.","productDescription":"17 p.","startPage":"317","endPage":"333","ipdsId":"IP-035796","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":473392,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10447/99077","text":"External Repository"},{"id":347388,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Redoubt Volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -154,\n              59\n            ],\n            [\n              -149,\n              59\n            ],\n            [\n              -149,\n              62\n            ],\n            [\n              -154,\n              62\n            ],\n            [\n              -154,\n              59\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"259","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f1a2a9e4b0220bbd9d9fa8","contributors":{"authors":[{"text":"Werner, Cynthia A. cwerner@usgs.gov","contributorId":2540,"corporation":false,"usgs":true,"family":"Werner","given":"Cynthia","email":"cwerner@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":715744,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kelly, Peter J. 0000-0002-3868-1046 pkelly@usgs.gov","orcid":"https://orcid.org/0000-0002-3868-1046","contributorId":5931,"corporation":false,"usgs":true,"family":"Kelly","given":"Peter","email":"pkelly@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":715747,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Kern, Christoph 0000-0002-8920-5701 ckern@usgs.gov","orcid":"https://orcid.org/0000-0002-8920-5701","contributorId":3387,"corporation":false,"usgs":true,"family":"Kern","given":"Christoph","email":"ckern@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":715746,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Roberts, T.J.","contributorId":198344,"corporation":false,"usgs":false,"family":"Roberts","given":"T.J.","email":"","affiliations":[],"preferred":false,"id":715748,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Aluppe, A.","contributorId":198341,"corporation":false,"usgs":false,"family":"Aluppe","given":"A.","email":"","affiliations":[],"preferred":false,"id":715745,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70192034,"text":"70192034 - 2013 - 4D petroleum system model of the Mississippian System in the Anadarko Basin Province, Oklahoma, Kansas, Texas, and Colorado, U.S.A.","interactions":[],"lastModifiedDate":"2018-01-08T13:10:38","indexId":"70192034","displayToPublicDate":"2013-12-31T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2789,"text":"Mountain Geologist","active":true,"publicationSubtype":{"id":10}},"title":"4D petroleum system model of the Mississippian System in the Anadarko Basin Province, Oklahoma, Kansas, Texas, and Colorado, U.S.A.","docAbstract":"<p>The Upper Devonian and Lower Mississippian Woodford Shale is an important petroleum source rock for Mississippian reservoirs in the Anadarko Basin Province of Oklahoma, Kansas, Texas, and Colorado, based on results from a 4D petroleum system model of the basin. The Woodford Shale underlies Mississippian strata over most of the Anadarko Basin portions of Oklahoma and northeastern Texas. The Kansas and Colorado portions of the province are almost entirely thermally immature for oil generation from the Woodford Shale or potential Mississippian source rocks, based mainly on measured vitrinite reflectance and modeled thermal maturation. Thermal maturities of the Woodford Shale range from mature for oil to overmature for gas generation at present-day depths of about 5,000 to 20,000 ft. Oil generation began at burial depths of about 6,000 to 6,500 ft. Modeled onset of Woodford Shale oil generation was about 330 million years ago (Ma); peak oil generation was from 300 to 220 Ma.</p><p>Mississippian production, including horizontal wells of the informal Mississippi limestone, is concentrated within and north of the Sooner Trend area in the northeast Oklahoma portion of the basin. This large pod of oil and gas production is within the area modeled as thermally mature for oil generation from the Woodford Shale. The southern boundary of the trend approximates the 99% transformation ratio of the Woodford Shale, which marks the end of oil generation. Because most of the Sooner Trend area is thermally mature for oil generation from the Woodford Shale, the trend probably includes short- and longer-distance vertical and lateral migration. The Woodford Shale is absent in the Mocane-Laverne Field area of the eastern Oklahoma panhandle; because of this, associated oil migrated from the south into the field. If the Springer Formation or deeper Mississippian strata generated oil, then the southern field area is within the oil window for associated petroleum source rocks. Mississippian fields along the western boundary of the study area were supplied by oil that flowed northward from the Panhandle Field area and westward from the deep basin.</p>","language":"English","publisher":"Rocky Mountain Association of Geologists","usgsCitation":"Higley, D.K., 2013, 4D petroleum system model of the Mississippian System in the Anadarko Basin Province, Oklahoma, Kansas, Texas, and Colorado, U.S.A.: Mountain Geologist, v. 50, no. 3, p. 81-98.","productDescription":"18 p.","startPage":"81","endPage":"98","ipdsId":"IP-044589","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":347376,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":346958,"type":{"id":15,"text":"Index Page"},"url":"https://archives.datapages.com/data/mountain-geologist-rmag/data/050/050003/81_rmag-mg500081.htm"}],"country":"United States","state":"Colorado, Kansas, New Mexico, Oklahoma, Texas","otherGeospatial":"Anadarko Basin Province","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -104,\n              34\n            ],\n            [\n              -96.75,\n              34\n            ],\n            [\n              -96.75,\n              40\n            ],\n            [\n              -104,\n              40\n            ],\n            [\n              -104,\n              34\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"50","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f1a2aae4b0220bbd9d9fc4","contributors":{"authors":[{"text":"Higley, Debra K. 0000-0001-8024-9954 higley@usgs.gov","orcid":"https://orcid.org/0000-0001-8024-9954","contributorId":152663,"corporation":false,"usgs":true,"family":"Higley","given":"Debra","email":"higley@usgs.gov","middleInitial":"K.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":713940,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70193778,"text":"70193778 - 2013 - Distance, dams and drift: What structures populations of an endangered, benthic stream fish?","interactions":[],"lastModifiedDate":"2017-11-09T12:55:17","indexId":"70193778","displayToPublicDate":"2013-12-31T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Distance, dams and drift: What structures populations of an endangered, benthic stream fish?","docAbstract":"<p>Spatial population structure plays an important role in species persistence, evolution and conservation. Benthic stream fishes are diverse and frequently imperilled, yet the determinants and spatial scaling of their population structure are understudied. We investigated the range-wide population genetic structure of Roanoke logperch (<i>Percina rex</i>), an endangered, benthic stream fish of the eastern United States. Fish were sampled from 35 sites and analysed at 11 microsatellite DNA loci. Clustering models were used to sort individuals into genetically cohesive groups and thereby estimate the spatial scaling of population structure. We then used Bayesian generalized linear mixed models (BGLMMs) to test alternative hypotheses about the environmental factors most responsible for generating structure, as measured by the differentiation statistic&nbsp;<i>F</i><sub>ST</sub>.&nbsp;Clustering models delineated seven discrete populations, whose boundaries coincided with agents of fragmentation, including hydroelectric dams and tailwaters. In the absence of hydrological barriers, gene flow was extensive throughout catchments, whereas there was no evidence for contemporary dispersal between catchments across barriers. In the best-supported BGLMM,&nbsp;<i>F</i><sub>ST</sub>&nbsp;was positively related to the spatial distance and degree of hydrological alteration between sites and negatively related to genetic diversity within sites. Whereas the effect of tailwaters was equivocal, dams strongly influenced differentiation: the effect of a dam on&nbsp;<i>F</i><sub>ST</sub>&nbsp;was comparable to that of a between-site distance of over 1200&nbsp;km of unimpounded river. Overall, the effect of distance-mediated dispersal was negligible compared to the combined effects of fragmentation and genetic drift.&nbsp;The contemporary population structure of&nbsp;<i>P. rex</i>&nbsp;comprises a few geographically extensive ‘islands’ that are fragmented by hydroelectric projects. This information clarifies the importance of a catchment-scale perspective on conserving the species and suggests that its recovery may require genetic and/or demographic reconnection of presently isolated populations.<br></p>","language":"English","publisher":"Wiley","doi":"10.1111/fwb.12190","usgsCitation":"Roberts, J.H., Angermeier, P.L., and Hallerman, E.M., 2013, Distance, dams and drift: What structures populations of an endangered, benthic stream fish?: Freshwater Biology, v. 58, no. 10, p. 2050-2064, https://doi.org/10.1111/fwb.12190.","productDescription":"15 p.","startPage":"2050","endPage":"2064","ipdsId":"IP-031963","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":348540,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina, Virginia","otherGeospatial":"Dan River, Nottoway River, Roanoke River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.244140625,\n              37.448696585910376\n            ],\n            [\n              -80.452880859375,\n              37.274052809979054\n            ],\n            [\n              -80.079345703125,\n              37.15156050223665\n            ],\n            [\n              -80.244140625,\n              36.94111143010769\n            ],\n            [\n              -80.540771484375,\n              36.87962060502676\n            ],\n            [\n              -80.66162109375,\n              36.54494944148322\n            ],\n            [\n              -80.79345703125,\n              35.96022296929667\n            ],\n            [\n              -80.68359375,\n              35.755428369259626\n            ],\n            [\n              -80.452880859375,\n              35.862343734896484\n            ],\n            [\n              -80.2880859375,\n              36.02244668175846\n            ],\n            [\n              -80.013427734375,\n              36.01356058518153\n            ],\n            [\n              -79.56298828125,\n              35.90684930677121\n            ],\n            [\n              -79.07958984375,\n              36.27970720524017\n            ],\n            [\n              -78.299560546875,\n              36.359374956015856\n            ],\n            [\n              -77.89306640625,\n              36.19995805932895\n            ],\n            [\n              -77.310791015625,\n              35.88905007936091\n            ],\n            [\n              -77.0361328125,\n              35.79108281624994\n            ],\n            [\n              -76.761474609375,\n              36.075742215627\n            ],\n            [\n              -76.75048828125,\n              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]\n}","volume":"58","issue":"10","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2013-06-20","publicationStatus":"PW","scienceBaseUri":"5a05771de4b09af898c70870","contributors":{"authors":[{"text":"Roberts, James H.","contributorId":83811,"corporation":false,"usgs":true,"family":"Roberts","given":"James","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":721459,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Angermeier, Paul L. 0000-0003-2864-170X biota@usgs.gov","orcid":"https://orcid.org/0000-0003-2864-170X","contributorId":166679,"corporation":false,"usgs":true,"family":"Angermeier","given":"Paul","email":"biota@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":720427,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hallerman, Eric M.","contributorId":40501,"corporation":false,"usgs":true,"family":"Hallerman","given":"Eric","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":721460,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70197842,"text":"70197842 - 2013 - Cross-scale modeling of surface temperature and tree seedling establishment inmountain landscapes","interactions":[],"lastModifiedDate":"2018-06-21T12:36:56","indexId":"70197842","displayToPublicDate":"2013-12-31T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1460,"text":"Ecological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Cross-scale modeling of surface temperature and tree seedling establishment inmountain landscapes","docAbstract":"Abstract:\n Introduction: Estimating surface temperature from above-ground field measurements is important for understanding the complex landscape patterns of plant seedling survival and establishment, processes which occur at heights of only several centimeters. Currently, future climate models predict temperature at 2 m above ground, leaving ground-surface microclimate not well characterized.\n Methods: Using a network of field temperature sensors and climate models, a ground-surface temperature method was used to estimate microclimate variability of minimum and maximum temperature. Temperature lapse rates were derived from field temperature sensors and distributed across the landscape capturing differences in solar radiation and cold air drainages modeled at a 30-m spatial resolution.\n Results: The surface temperature estimation method used for this analysis successfully estimated minimum surface temperatures on north-facing, south-facing, valley, and ridgeline topographic settings, and when compared to measured temperatures yielded an R2 of 0.88, 0.80, 0.88, and 0.80, respectively. Maximum surface temperatures generally had slightly more spatial variability than minimum surface temperatures, resulting in R2 values of 0.86, 0.77, 0.72, and 0.79 for north-facing, south-facing, valley, and ridgeline topographic settings. Quasi-Poisson regressions predicting recruitment of Quercus kelloggii (black oak) seedlings from temperature variables were significantly improved using these estimates of surface temperature compared to air temperature modeled at 2 m.\n Conclusion: \nPredicting minimum and maximum ground-surface temperatures using a downscaled climate model coupled with temperature lapse rates estimated from field measurements provides a method for modeling temperature effects on plant recruitment. Such methods could be applied to improve projections of species’ range shifts under climate change. Areas of complex topography can provide intricate microclimates that may allow species to redistribute locally as climate changes.","language":"English","publisher":"Springer","doi":"10.1186/2192-1709-2-30","usgsCitation":"Dingman, J., Sweet, L.C., McCullough, I.M., Davis, F.W., Flint, A.L., Franklin, J., and Flint, L.E., 2013, Cross-scale modeling of surface temperature and tree seedling establishment inmountain landscapes: Ecological Processes, v. 2, e30; 15 p., https://doi.org/10.1186/2192-1709-2-30.","productDescription":"e30; 15 p.","ipdsId":"IP-051373","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":473391,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/2192-1709-2-30","text":"Publisher Index Page"},{"id":355269,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2013-10-17","publicationStatus":"PW","scienceBaseUri":"5b46f227e4b060350a15d38a","contributors":{"authors":[{"text":"Dingman, John jdingman@usgs.gov","contributorId":205860,"corporation":false,"usgs":true,"family":"Dingman","given":"John","email":"jdingman@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738718,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sweet, Lynn C.","contributorId":149951,"corporation":false,"usgs":false,"family":"Sweet","given":"Lynn","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":738719,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCullough, Ian M.","contributorId":149952,"corporation":false,"usgs":false,"family":"McCullough","given":"Ian","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":738720,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davis, Frank W.","contributorId":150406,"corporation":false,"usgs":false,"family":"Davis","given":"Frank","email":"","middleInitial":"W.","affiliations":[{"id":18015,"text":"Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":738721,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738722,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Franklin, Janet","contributorId":90833,"corporation":false,"usgs":true,"family":"Franklin","given":"Janet","affiliations":[],"preferred":false,"id":738723,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738724,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70192257,"text":"70192257 - 2013 - Re‐estimated effects of deep episodic slip on the occurrence and probability of great earthquakes in Cascadia","interactions":[],"lastModifiedDate":"2017-10-24T11:10:17","indexId":"70192257","displayToPublicDate":"2013-12-31T00:00:00","publicationYear":"2013","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":"Re‐estimated effects of deep episodic slip on the occurrence and probability of great earthquakes in Cascadia","docAbstract":"<p><a class=\"link link-ref link-reveal xref-bibr\" data-open=\"rf40\">Mazzotti and Adams (2004)</a><span><span>&nbsp;</span>estimated that rapid deep slip during typically two week long episodes beneath northern Washington and southern British Columbia increases the probability of a great Cascadia earthquake by 30–100 times relative to the probability during the ∼58 weeks between slip events. Because the corresponding absolute probability remains very low at ∼0.03% per week, their conclusion is that though it is more likely that a great earthquake will occur during a rapid slip event than during other times, a great earthquake is unlikely to occur during any particular rapid slip event. This previous estimate used a failure model in which great earthquakes initiate instantaneously at a stress threshold. We refine the estimate, assuming a delayed failure model that is based on laboratory‐observed earthquake initiation. Laboratory tests show that failure of intact rock in shear and the onset of rapid slip on pre‐existing faults do not occur at a threshold stress. Instead, slip onset is gradual and shows a damped response to stress and loading rate changes. The characteristic time of failure depends on loading rate and effective normal stress. Using this model, the probability enhancement during the period of rapid slip in Cascadia is negligible (&lt;10%) for effective normal stresses of 10&nbsp;MPa or more and only increases by 1.5 times for an effective normal stress of 1&nbsp;MPa. We present arguments that the hypocentral effective normal stress exceeds 1&nbsp;MPa. In addition, the probability enhancement due to rapid slip extends into the interevent period. With this delayed failure model for effective normal stresses greater than or equal to 50&nbsp;kPa, it is more likely that a great earthquake will occur between the periods of rapid deep slip than during them. Our conclusion is that great earthquake occurrence is not significantly enhanced by episodic deep slip events.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120120022","usgsCitation":"Beeler, N.M., Roeloffs, E.A., and McCausland, W., 2013, Re‐estimated effects of deep episodic slip on the occurrence and probability of great earthquakes in Cascadia: Bulletin of the Seismological Society of America, v. 104, no. 1, p. 128-144, https://doi.org/10.1785/0120120022.","productDescription":"17 p.","startPage":"128","endPage":"144","ipdsId":"IP-030732","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":347207,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"British Columbia, Washington","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -133.41796874999997,\n              45.644768217751924\n            ],\n            [\n              -116.89453125,\n              45.644768217751924\n            ],\n            [\n              -116.89453125,\n              55.07836723201515\n            ],\n            [\n              -133.41796874999997,\n              55.07836723201515\n            ],\n            [\n              -133.41796874999997,\n              45.644768217751924\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"104","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2013-11-26","publicationStatus":"PW","scienceBaseUri":"59f05124e4b0220bbd9a1dba","contributors":{"authors":[{"text":"Beeler, Nicholas M. 0000-0002-3397-8481 nbeeler@usgs.gov","orcid":"https://orcid.org/0000-0002-3397-8481","contributorId":2682,"corporation":false,"usgs":true,"family":"Beeler","given":"Nicholas","email":"nbeeler@usgs.gov","middleInitial":"M.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":715031,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roeloffs, Evelyn A. 0000-0002-4761-0469 evelynr@usgs.gov","orcid":"https://orcid.org/0000-0002-4761-0469","contributorId":2680,"corporation":false,"usgs":true,"family":"Roeloffs","given":"Evelyn","email":"evelynr@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":715030,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCausland, Wendy wmccausland@usgs.gov","contributorId":5497,"corporation":false,"usgs":true,"family":"McCausland","given":"Wendy","email":"wmccausland@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":715032,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70192334,"text":"70192334 - 2013 - Incorporating probabilistic seasonal climate forecasts into river management using a risk-based framework","interactions":[],"lastModifiedDate":"2017-10-25T10:03:31","indexId":"70192334","displayToPublicDate":"2013-12-31T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Incorporating probabilistic seasonal climate forecasts into river management using a risk-based framework","docAbstract":"[1] Despite the influence of hydroclimate on river ecosystems, most efforts to date have focused on using climate information to predict streamflow for water supply. However, as water demands intensify and river systems are increasingly stressed, research is needed to explicitly integrate climate into streamflow forecasts that are relevant to river ecosystem management. To this end, we present a five step risk-based framework: (1) define risk tolerance, (2) develop a streamflow forecast model, (3) generate climate forecast ensembles, (4) estimate streamflow ensembles and associated risk, and (5) manage for climate risk. The framework is successfully demonstrated for an unregulated watershed in southwest Montana, where the combination of recent drought and water withdrawals has made it challenging to maintain flows needed for healthy fisheries. We put forth a generalized linear modeling (GLM) approach to develop a suite of tools that skillfully model decision-relevant low flow characteristics in terms of climate predictors. Probabilistic precipitation forecasts are used in conjunction with the GLMs, resulting in season-ahead prediction ensembles that provide the full risk profile. These tools are embedded in an end-to-end risk management framework that directly supports proactive fish conservation efforts. Results show that the use of forecasts can be beneficial to planning, especially in wet years, but historical precipitation forecasts are quite conservative (i.e., not very “sharp”). Synthetic forecasts show that a modest “sharpening” can strongly impact risk and improve skill. We emphasize that use in management depends on defining relevant environmental flows and risk tolerance, requiring local stakeholder involvement.","language":"English","publisher":"American Geophysical Union","doi":"10.1002/wrcr.20378","usgsCitation":"Sojda, R.S., Towler, E., Roberts, M., and Rajagopalan, B., 2013, Incorporating probabilistic seasonal climate forecasts into river management using a risk-based framework: Water Resources Research, v. 49, no. 8, p. 4997-5008, https://doi.org/10.1002/wrcr.20378.","productDescription":"12 p.","startPage":"4997","endPage":"5008","ipdsId":"IP-040992","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":347313,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -113.8623046875,\n              44.92591837128866\n            ],\n            [\n              -112.994384765625,\n              44.92591837128866\n            ],\n            [\n              -112.994384765625,\n              45.51789504294005\n            ],\n            [\n              -113.8623046875,\n              45.51789504294005\n            ],\n            [\n              -113.8623046875,\n              44.92591837128866\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"49","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2013-08-19","publicationStatus":"PW","scienceBaseUri":"59f1a2a9e4b0220bbd9d9fac","contributors":{"authors":[{"text":"Sojda, Richard S. sojda@usgs.gov","contributorId":1663,"corporation":false,"usgs":true,"family":"Sojda","given":"Richard","email":"sojda@usgs.gov","middleInitial":"S.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":715390,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Towler, Erin","contributorId":92904,"corporation":false,"usgs":true,"family":"Towler","given":"Erin","affiliations":[],"preferred":false,"id":715392,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Roberts, Mike","contributorId":149136,"corporation":false,"usgs":false,"family":"Roberts","given":"Mike","email":"","affiliations":[],"preferred":false,"id":715393,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Rajagopalan, Balaji","contributorId":145813,"corporation":false,"usgs":false,"family":"Rajagopalan","given":"Balaji","email":"","affiliations":[{"id":16240,"text":"U of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":715391,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70192301,"text":"70192301 - 2013 - Black bear density in Glacier National Park, Montana","interactions":[],"lastModifiedDate":"2017-10-26T09:57:40","indexId":"70192301","displayToPublicDate":"2013-12-31T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Black bear density in Glacier National Park, Montana","docAbstract":"<p>We report the first abundance and density estimates for American black bears (<i>Ursus americanus</i>) in Glacier National Park (NP),Montana, USA.We used data from 2 independent and concurrent noninvasive genetic sampling methods—hair traps and bear rubs—collected during 2004 to generate individual black bear encounter histories for use in closed population mark–recapture models. We improved the precision of our abundance estimate by using noninvasive genetic detection events to develop individual-level covariates of sampling effort within the full and one-half mean maximum distance moved (MMDM) from each bear’s estimated activity center to explain capture probability heterogeneity and inform our estimate of the effective sampling area.Models including the one-halfMMDMcovariate received overwhelming Akaike’s Information Criterion support suggesting that buffering our study area by this distance would be more appropriate than no buffer or the full MMDM buffer for estimating the effectively sampled area and thereby density. Our modelaveraged super-population abundance estimate was 603 (95% CI¼522–684) black bears for Glacier NP. Our black bear density estimate (11.4 bears/100 km2, 95% CI¼9.9–13.0) was consistent with published estimates for populations that are sympatric with grizzly bears (U. arctos) and without access to spawning salmonids. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.</p>","language":"English","publisher":"Wiley","doi":"10.1002/wsb.356","usgsCitation":"Stetz, J.B., Kendall, K.C., and Macleod, A.C., 2013, Black bear density in Glacier National Park, Montana: Wildlife Society Bulletin, v. 38, no. 1, p. 60-70, https://doi.org/10.1002/wsb.356.","productDescription":"11 p.","startPage":"60","endPage":"70","ipdsId":"IP-045361","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":500011,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/bbe229248951484a85366b0798f527ef","text":"External Repository"},{"id":347347,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Glacier National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -115.0543212890625,\n              49.001843917978526\n            ],\n            [\n              -114.993896484375,\n              48.929717630629554\n            ],\n            [\n              -114.884033203125,\n              48.89722676235673\n            ],\n            [\n              -114.72473144531251,\n              48.8936153614802\n            ],\n            [\n              -114.72473144531251,\n              48.79600890414036\n            ],\n            [\n              -114.697265625,\n              48.72358515157852\n            ],\n            [\n              -114.47753906249999,\n              48.56024979174329\n            ],\n            [\n              -114.3182373046875,\n              48.46199462233164\n            ],\n            [\n              -114.1644287109375,\n              48.46563710044979\n            ],\n            [\n              -114.0216064453125,\n              48.50932644976633\n            ],\n            [\n              -113.93920898437499,\n              48.50932644976633\n            ],\n            [\n              -113.8128662109375,\n              48.44013426398058\n            ],\n            [\n              -113.7744140625,\n              48.40367941865281\n            ],\n            [\n              -113.69750976562499,\n              48.334343174592014\n            ],\n            [\n              -113.65905761718749,\n              48.26491251331118\n            ],\n            [\n              -113.521728515625,\n              48.25759852914997\n            ],\n            [\n              -113.31298828125,\n              48.29781249243716\n            ],\n            [\n              -113.258056640625,\n              48.425555463221066\n            ],\n            [\n              -113.41735839843749,\n              48.69096039092549\n            ],\n            [\n              -113.4283447265625,\n              48.73807825631017\n            ],\n            [\n              -113.48876953125,\n              48.76343113791796\n            ],\n            [\n              -113.62060546875,\n              48.94415123418794\n            ],\n            [\n              -113.609619140625,\n              48.99463598353405\n            ],\n            [\n              -115.0543212890625,\n              49.001843917978526\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"38","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2013-11-08","publicationStatus":"PW","scienceBaseUri":"59f1a2a9e4b0220bbd9d9fb9","contributors":{"authors":[{"text":"Stetz, Jeff B.","contributorId":198142,"corporation":false,"usgs":false,"family":"Stetz","given":"Jeff","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":715190,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kendall, Katherine C. 0000-0002-4831-2287 kkendall@usgs.gov","orcid":"https://orcid.org/0000-0002-4831-2287","contributorId":3081,"corporation":false,"usgs":true,"family":"Kendall","given":"Katherine","email":"kkendall@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":715188,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Macleod, Amy C.","contributorId":198141,"corporation":false,"usgs":false,"family":"Macleod","given":"Amy","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":715189,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70055519,"text":"70055519 - 2013 - Surveillance theory applied to virus detection: a case for targeted discovery","interactions":[],"lastModifiedDate":"2014-02-07T15:04:22","indexId":"70055519","displayToPublicDate":"2013-12-30T15:01:42","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1715,"text":"Future Virology","active":true,"publicationSubtype":{"id":10}},"title":"Surveillance theory applied to virus detection: a case for targeted discovery","docAbstract":"Virus detection and mathematical modeling have gone through rapid developments in the past decade. Both offer new insights into the epidemiology of infectious disease and characterization of future risk; however, modeling has not yet been applied to designing the best surveillance strategies for viral and pathogen discovery. We review recent developments and propose methods to integrate viral and pathogen discovery and mathematical modeling through optimal surveillance theory, arguing for a more targeted approach to novel virus detection guided by the principles of adaptive management and structured decision-making.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Future Virology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Future Medicine","doi":"10.2217/fvl.13.105","usgsCitation":"Bogich, T., Anthony, S.J., and Nichols, J., 2013, Surveillance theory applied to virus detection: a case for targeted discovery: Future Virology, v. 8, no. 12, p. 1201-1206, https://doi.org/10.2217/fvl.13.105.","productDescription":"6 p.","startPage":"1201","endPage":"1206","ipdsId":"IP-052119","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":282128,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":282127,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2217/fvl.13.105"}],"volume":"8","issue":"12","noUsgsAuthors":false,"publicationDate":"2013-11-28","publicationStatus":"PW","scienceBaseUri":"53cd7605e4b0b2908510aa20","contributors":{"authors":[{"text":"Bogich, Tiffany L.","contributorId":40891,"corporation":false,"usgs":true,"family":"Bogich","given":"Tiffany L.","affiliations":[],"preferred":false,"id":486123,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anthony, Simon J.","contributorId":34387,"corporation":false,"usgs":true,"family":"Anthony","given":"Simon","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":486122,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nichols, James D. 0000-0002-7631-2890 jnichols@usgs.gov","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":405,"corporation":false,"usgs":true,"family":"Nichols","given":"James D.","email":"jnichols@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":486121,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70059790,"text":"70059790 - 2013 - Conflation and aggregation of spatial data improve predictive models for species with limited habitats: a case of the threatened yellow-billed cuckoo in Arizona, USA","interactions":[],"lastModifiedDate":"2018-09-18T16:29:07","indexId":"70059790","displayToPublicDate":"2013-12-30T14:56:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":836,"text":"Applied Geography","active":true,"publicationSubtype":{"id":10}},"title":"Conflation and aggregation of spatial data improve predictive models for species with limited habitats: a case of the threatened yellow-billed cuckoo in Arizona, USA","docAbstract":"Riparian vegetation provides important wildlife habitat in the Southwestern United States, but limited distributions and spatial complexity often leads to inaccurate representation in maps used to guide conservation. We test the use of data conflation and aggregation on multiple vegetation/land-cover maps to improve the accuracy of habitat models for the threatened western yellow-billed cuckoo (Coccyzus americanus occidentalis). We used species observations (n = 479) from a state-wide survey to develop habitat models from 1) three vegetation/land-cover maps produced at different geographic scales ranging from state to national, and 2) new aggregate maps defined by the spatial agreement of cover types, which were defined as high (agreement = all data sets), moderate (agreement ≥ 2), and low (no agreement required). Model accuracies, predicted habitat locations, and total area of predicted habitat varied considerably, illustrating the effects of input data quality on habitat predictions and resulting potential impacts on conservation planning. Habitat models based on aggregated and conflated data were more accurate and had higher model sensitivity than original vegetation/land-cover, but this accuracy came at the cost of reduced geographic extent of predicted habitat. Using the highest performing models, we assessed cuckoo habitat preference and distribution in Arizona and found that major watersheds containing high-probably habitat are fragmented by a wide swath of low-probability habitat. Focus on riparian restoration in these areas could provide more breeding habitat for the threatened cuckoo, offset potential future habitat losses in adjacent watershed, and increase regional connectivity for other threatened vertebrates that also use riparian corridors.","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeog.2013.12.003","usgsCitation":"Villarreal, M., van Riper, C., and Petrakis, R., 2013, Conflation and aggregation of spatial data improve predictive models for species with limited habitats: a case of the threatened yellow-billed cuckoo in Arizona, USA: Applied Geography, v. 47, p. 57-69, https://doi.org/10.1016/j.apgeog.2013.12.003.","productDescription":"13 p.","startPage":"57","endPage":"69","numberOfPages":"13","ipdsId":"IP-048880","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":280568,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280567,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.apgeog.2013.12.003"}],"country":"United States","state":"Arizona","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114.8184,31.3322 ], [ -114.8184,37.0043 ], [ -109.0452,37.0043 ], [ -109.0452,31.3322 ], [ -114.8184,31.3322 ] ] ] } } ] }","volume":"47","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52c29607e4b040b25da903da","contributors":{"authors":[{"text":"Villarreal, Miguel L.","contributorId":107012,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel L.","affiliations":[],"preferred":false,"id":487828,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Riper, Charles III 0000-0003-1084-5843 charles_van_riper@usgs.gov","orcid":"https://orcid.org/0000-0003-1084-5843","contributorId":169488,"corporation":false,"usgs":true,"family":"van Riper","given":"Charles","suffix":"III","email":"charles_van_riper@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":487826,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Petrakis, Roy E.","contributorId":46868,"corporation":false,"usgs":true,"family":"Petrakis","given":"Roy E.","affiliations":[],"preferred":false,"id":487827,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70059793,"text":"70059793 - 2013 - Advances and applications of occupancy models","interactions":[],"lastModifiedDate":"2014-12-12T14:42:58","indexId":"70059793","displayToPublicDate":"2013-12-30T14:37:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Advances and applications of occupancy models","docAbstract":"<p>Summary: The past decade has seen an explosion in the development and application of models aimed at estimating species occurrence and occupancy dynamics while accounting for possible non-detection or species misidentification. We discuss some recent occupancy estimation methods and the biological systems that motivated their development. Collectively, these models offer tremendous flexibility, but simultaneously place added demands on the investigator. Unlike many mark&ndash;recapture scenarios, investigators utilizing occupancy models have the ability, and responsibility, to define their sample units (i.e. sites), replicate sampling occasions, time period over which species occurrence is assumed to be static and even the criteria that constitute &lsquo;detection&rsquo; of a target species. Subsequent biological inference and interpretation of model parameters depend on these definitions and the ability to meet model assumptions. We demonstrate the relevance of these definitions by highlighting applications from a single biological system (an amphibian&ndash;pathogen system) and discuss situations where the use of occupancy models has been criticized. Finally, we use these applications to suggest future research and model development.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Methods in Ecology and Evolution","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/2041-210X.12100","usgsCitation":"Bailey, L., MacKenzie, D.I., and Nichols, J., 2013, Advances and applications of occupancy models: Methods in Ecology and Evolution, v. 5, no. 12, p. 1269-1279, https://doi.org/10.1111/2041-210X.12100.","productDescription":"11 p.","startPage":"1269","endPage":"1279","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-050552","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":280566,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280565,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/2041-210X.12100"}],"volume":"5","issue":"12","noUsgsAuthors":false,"publicationDate":"2013-09-04","publicationStatus":"PW","scienceBaseUri":"52c295dfe4b040b25da902eb","contributors":{"authors":[{"text":"Bailey, Larissa","contributorId":86059,"corporation":false,"usgs":true,"family":"Bailey","given":"Larissa","affiliations":[],"preferred":false,"id":487831,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"MacKenzie, Darry I.","contributorId":15926,"corporation":false,"usgs":true,"family":"MacKenzie","given":"Darry","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":487830,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nichols, James D. 0000-0002-7631-2890 jnichols@usgs.gov","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":405,"corporation":false,"usgs":true,"family":"Nichols","given":"James D.","email":"jnichols@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":487829,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70056564,"text":"sir20105070G - 2013 - Descriptive and geoenvironmental model for Co-Cu-Au deposits in metasedimentary rocks","interactions":[],"lastModifiedDate":"2022-12-12T23:19:59.000786","indexId":"sir20105070G","displayToPublicDate":"2013-12-30T13:46:00","publicationYear":"2013","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":"2010-5070","chapter":"G","title":"Descriptive and geoenvironmental model for Co-Cu-Au deposits in metasedimentary rocks","docAbstract":"<h1>Introduction</h1><p>This report is a revised model for a specific type of cobalt-copper-gold (Co-Cu-Au) deposit that will be evaluated in the next U.S. Geological Survey (USGS) assessment of undiscovered mineral resources in the United States (see Ferrero and others, 2012). Emphasis is on providing an up-to-date deposit model that includes both geologic and geoenvironmental aspects. The new model presented here supersedes previous USGS models by Earhart (1986) and Evans and others (1995), which are based solely on deposits in the Blackbird mining district of central Idaho. This report is a broader synthesis of information on 19 Co-Cu-Au deposits occurring in predominantly metasedimentary successions worldwide (table 1–1) that generally share common geologic, mineralogical, and geochemical features; preliminary summary versions were presented in Slack and others (2010) and Slack and others (2011), which are superseded by this report. As defined herein, the individual Co-Cu-Au deposits are located more than 500 meters from similar deposits and contain 0.1 percent or more by weight of Co in ore or mineralized rock; some deposits included in the database lack reported average Co grades, but they contain high Co concentrations, at least locally. Most of the deposits also have high As contents, present in Co arsenide and sulfarsenide minerals. Type examples of the Co-Cu-Au deposits are those in the Blackbird district, Skuterud in Norway, and Kouvervarra and Juomasuo in Finland. Some deposits in the database have low grades for Cu (for example, NICO in Canada) or Au (for example, Lemmonlampi in Finland), but these deposits are included because their geological, mineralogical, and alteration features are similar to those of the type examples. Several deposits included in the model are partly hosted by metavolcanic or metaigneous rocks (including granite), but regionally these deposits are within metasedimentary successions; no deposits are wholly within granite or other plutonic igneous intrusions.</p><p>Despite having a lower average Co grade, the Mt. Cobalt deposit in Australia is included here because it has past Co production from higher-grade ore zones (Nisbet and others, 1983). The Black Pine deposit in the Idaho cobalt belt is included because it contains mineable Co- and Au-rich lenses within Cu-rich mineralized zones (Formation Metals, Inc., 2012). Six deposits that lack data for average Co grades are also included because each reportedly contains abundant Co (&gt;0.1 weight percent Co), at least locally. Many of the deposits are noteworthy as possible resources of Ag, Bi, W, Ni, Y, REE, and (or) U. Detailed data on the deposits listed in table 1–1, including references, are available in appendix 1. Significantly, the grouping in this report of Co-Cu-Au deposits in metasedimentary rocks into a single model includes deposits that other workers have previously classified in different ways. For background information, a global overview of different types of Co deposits worldwide is given in Smith (2001).</p><p>Additional geologically and compositionally similar deposits are known, but have average Co grades less than 0.1 percent. Most of these deposits contain cobalt-rich pyrite and lack appreciable amounts of distinct Co sulfide and (or) sulfarsenide minerals. Such deposits are not discussed in detail in the following sections, but these deposits may be relevant to the descriptive and genetic models presented below. Examples include the Scadding Au-Co-Cu deposit in Ontario, Canada; the Vähäjoki Co-Cu-Au deposit in Finland; the Tuolugou Co-Au deposit in Qinghai Province, China; the Lala Co-Cu-UREE deposit in Sichuan Province, China; the Guelb Moghrein Cu-Au-Co deposit in Mauritania; and the Great Australia Co-Cu, Greenmount Cu-Au-Co, and Monakoff Cu-Au-Co-UAg deposits in Queensland, Australia. Detailed information on these deposits is presented in appendix 2.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Mineral deposit models for resource assessment (Scientific Investigations Report 2010-5070)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20105070G","usgsCitation":"Slack, J.F., Johnson, C.A., Causey, J.D., Lund, K., Schulz, K.J., Gray, J.E., and Eppinger, R.G., 2013, Descriptive and geoenvironmental model for Co-Cu-Au deposits in metasedimentary rocks: U.S. Geological Survey Scientific Investigations Report 2010-5070, xii, 218 p., https://doi.org/10.3133/sir20105070G.","productDescription":"xii, 218 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-040230","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":280564,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20105070G.jpg"},{"id":280563,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2010/5070/g/pdf/sir2010-5070-G.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":280562,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5070/g/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52c29608e4b040b25da903e1","contributors":{"editors":[{"text":"Slack, John F. 0000-0001-6600-3130 jfslack@usgs.gov","orcid":"https://orcid.org/0000-0001-6600-3130","contributorId":1032,"corporation":false,"usgs":true,"family":"Slack","given":"John","email":"jfslack@usgs.gov","middleInitial":"F.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":580212,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Slack, John F. 0000-0001-6600-3130 jfslack@usgs.gov","orcid":"https://orcid.org/0000-0001-6600-3130","contributorId":1032,"corporation":false,"usgs":true,"family":"Slack","given":"John","email":"jfslack@usgs.gov","middleInitial":"F.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":580205,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Craig A. 0000-0002-1334-2996 cjohnso@usgs.gov","orcid":"https://orcid.org/0000-0002-1334-2996","contributorId":909,"corporation":false,"usgs":true,"family":"Johnson","given":"Craig","email":"cjohnso@usgs.gov","middleInitial":"A.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":580206,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Causey, J. Douglas","contributorId":41398,"corporation":false,"usgs":true,"family":"Causey","given":"J.","email":"","middleInitial":"Douglas","affiliations":[],"preferred":false,"id":580207,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lund, Karen 0000-0002-4249-3582 klund@usgs.gov","orcid":"https://orcid.org/0000-0002-4249-3582","contributorId":1235,"corporation":false,"usgs":true,"family":"Lund","given":"Karen","email":"klund@usgs.gov","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":580208,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schulz, Klaus J. 0000-0003-2967-4765 kschulz@usgs.gov","orcid":"https://orcid.org/0000-0003-2967-4765","contributorId":2438,"corporation":false,"usgs":true,"family":"Schulz","given":"Klaus","email":"kschulz@usgs.gov","middleInitial":"J.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":580209,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gray, John E. jgray@usgs.gov","contributorId":1275,"corporation":false,"usgs":true,"family":"Gray","given":"John","email":"jgray@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":580210,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Eppinger, Robert G. eppinger@usgs.gov","contributorId":849,"corporation":false,"usgs":true,"family":"Eppinger","given":"Robert","email":"eppinger@usgs.gov","middleInitial":"G.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":580211,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70056529,"text":"sim3273 - 2013 - Characterization of hydrodynamic and sediment conditions in the lower Yampa River at Deerlodge Park, east entrance to Dinosaur National Monument, northwest Colorado, 2011","interactions":[],"lastModifiedDate":"2013-12-30T09:23:41","indexId":"sim3273","displayToPublicDate":"2013-12-30T09:07:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3273","title":"Characterization of hydrodynamic and sediment conditions in the lower Yampa River at Deerlodge Park, east entrance to Dinosaur National Monument, northwest Colorado, 2011","docAbstract":"The Yampa River in northwestern Colorado is the largest, relatively unregulated river system in the upper Colorado River Basin. Water from the Yampa River Basin continues to be sought for a number of municipal, industrial, and energy uses. It is anticipated that future water development within the Yampa River Basin above the amount of water development identified under the Upper Colorado River Endangered Fish Recovery Implementation Program and the Programmatic Biological Opinion may require additional analysis in order to understand the effects on habitat and river function. Water development in the Yampa River Basin could alter the streamflow regime and, consequently, could lead to changes in the transport and storage of sediment in the Yampa River at Deerlodge Park. These changes could affect the physical form of the reach and may impact aquatic and riparian habitat in and downstream from Deerlodge Park.\n\nThe U.S. Geological Survey, in cooperation with the Colorado Water Conservation Board, began a study in 2011 to characterize the current hydrodynamic and sediment-transport conditions for a 2-kilometer reach of the Yampa River in Deerlodge Park. Characterization of channel conditions in the Deerlodge Park reach was completed through topographic surveying, grain-size analysis of streambed sediment, and characterization of streamflow properties. This characterization provides (1) a basis for comparisons of current stream functions (channel geometry, sediment transport, and stream hydraulics) to future conditions and (2) a dataset that can be used to assess channel response to streamflow alteration scenarios indicated from computer modeling of streamflow and sediment-transport conditions.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3273","collaboration":"Prepared in cooperation with the Colorado Water Conservation Board","usgsCitation":"Williams, C.A., 2013, Characterization of hydrodynamic and sediment conditions in the lower Yampa River at Deerlodge Park, east entrance to Dinosaur National Monument, northwest Colorado, 2011: U.S. Geological Survey Scientific Investigations Map 3273, Map: 37.92 inches x 29.17 inches, https://doi.org/10.3133/sim3273.","productDescription":"Map: 37.92 inches x 29.17 inches","additionalOnlineFiles":"N","ipdsId":"IP-049562","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":280530,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3273/"},{"id":280546,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3273/pdf/sim3273.pdf"},{"id":280547,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3273.jpg"}],"projection":"2011 Universal Transverse Mercator, Zone 12 North","datum":"North American Datum of 1983","country":"United States","state":"Colorado","otherGeospatial":"Dinosaur National Monument","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -108.519001,40.441199 ], [ -108.519001,40.453087 ], [ -108.499947,40.453087 ], [ -108.499947,40.441199 ], [ -108.519001,40.441199 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52c29607e4b040b25da903d3","contributors":{"authors":[{"text":"Williams, Cory A. 0000-0003-1461-7848 cawillia@usgs.gov","orcid":"https://orcid.org/0000-0003-1461-7848","contributorId":689,"corporation":false,"usgs":true,"family":"Williams","given":"Cory","email":"cawillia@usgs.gov","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486588,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
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