{"pageNumber":"1333","pageRowStart":"33300","pageSize":"25","recordCount":165359,"records":[{"id":70046041,"text":"70046041 - 2014 - Self-imposed length limits in recreational fisheries","interactions":[],"lastModifiedDate":"2014-04-10T09:44:35","indexId":"70046041","displayToPublicDate":"2014-04-10T09:52:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1661,"text":"Fisheries Research","active":true,"publicationSubtype":{"id":10}},"title":"Self-imposed length limits in recreational fisheries","docAbstract":"A primary motivating factor on the decision to harvest a fish among consumptive-orientated anglers is the size of the fish. There is likely a cost-benefit trade-off for harvest of individual fish that is size and species dependent, which should produce a logistic-type response of fish fate (release or harvest) as a function of fish size and species. We define the self-imposed length limit as the length at which a captured fish had a 50% probability of being harvested, which was selected because it marks the length of the fish where the probability of harvest becomes greater than the probability of release. We assessed the influences of fish size, catch per unit effort, size distribution of caught fish, and creel limit on the self-imposed length limits for bluegill Lepomis macrochirus, channel catfish Ictalurus punctatus, black crappie Pomoxis nigromaculatus and white crappie Pomoxis annularis combined, white bass Morone chrysops, and yellow perch Perca flavescens at six lakes in Nebraska, USA. As we predicted, the probability of harvest increased with increasing size for all species harvested, which supported the concept of a size-dependent trade-off in costs and benefits of harvesting individual fish. It was also clear that probability of harvest was not simply defined by fish length, but rather was likely influenced to various degrees by interactions between species, catch rate, size distribution, creel-limit regulation and fish size. A greater understanding of harvest decisions within the context of perceived likelihood that a creel limit will be realized by a given angler party, which is a function of fish availability, harvest regulation and angler skill and orientation, is needed to predict the influence that anglers have on fish communities and to allow managers to sustainable manage exploited fish populations in recreational fisheries.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Fisheries Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2014.02.022","usgsCitation":"Chizinski, C.J., Martin, D., Hurley, K.L., and Pope, K.L., 2014, Self-imposed length limits in recreational fisheries: Fisheries Research, v. 155, p. 83-89, https://doi.org/10.1016/j.fishres.2014.02.022.","productDescription":"7 p.","startPage":"83","endPage":"89","numberOfPages":"7","ipdsId":"IP-039302","costCenters":[{"id":463,"text":"Nebraska Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":286133,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286132,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.fishres.2014.02.022"}],"country":"United States","state":"Nebraska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -104.0535,39.9999 ], [ -104.0535,43.0017 ], [ -95.3083,43.0017 ], [ -95.3083,39.9999 ], [ -104.0535,39.9999 ] ] ] } } ] }","volume":"155","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517060e4b05569d805a39c","contributors":{"authors":[{"text":"Chizinski, Christopher J.","contributorId":7178,"corporation":false,"usgs":false,"family":"Chizinski","given":"Christopher","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":478744,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Dustin R.","contributorId":43482,"corporation":false,"usgs":true,"family":"Martin","given":"Dustin R.","affiliations":[],"preferred":false,"id":478745,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hurley, Keith L.","contributorId":97422,"corporation":false,"usgs":true,"family":"Hurley","given":"Keith","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":478746,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pope, Kevin L. 0000-0003-1876-1687 kpope@usgs.gov","orcid":"https://orcid.org/0000-0003-1876-1687","contributorId":1574,"corporation":false,"usgs":true,"family":"Pope","given":"Kevin","email":"kpope@usgs.gov","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":478743,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70059037,"text":"70059037 - 2014 - Testing the accuracy of a 1-D volcanic plume model in estimating mass eruption rate","interactions":[],"lastModifiedDate":"2019-03-11T10:56:51","indexId":"70059037","displayToPublicDate":"2014-04-10T09:23:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2316,"text":"Journal of Geophysical Research D: Atmospheres","active":true,"publicationSubtype":{"id":10}},"title":"Testing the accuracy of a 1-D volcanic plume model in estimating mass eruption rate","docAbstract":"During volcanic eruptions, empirical relationships are used to estimate mass eruption rate from plume height. Although simple, such relationships can be inaccurate and can underestimate rates in windy conditions. One-dimensional plume models can incorporate atmospheric conditions and give potentially more accurate estimates. Here I present a 1-D model for plumes in crosswind and simulate 25 historical eruptions where plume height Hobs was well observed and mass eruption rate Mobs could be calculated from mapped deposit mass and observed duration. The simulations considered wind, temperature, and phase changes of water. Atmospheric conditions were obtained from the National Center for Atmospheric Research Reanalysis 2.5° model. Simulations calculate the minimum, maximum, and average values (Mmin, Mmax, and Mavg) that fit the plume height. Eruption rates were also estimated from the empirical formula Mempir = 140Hobs4.14 (Mempir is in kilogram per second, Hobs is in kilometer). For these eruptions, the standard error of the residual in log space is about 0.53 for Mavg and 0.50 for Mempir. Thus, for this data set, the model is slightly less accurate at predicting Mobs than the empirical curve. The inability of this model to improve eruption rate estimates may lie in the limited accuracy of even well-observed plume heights, inaccurate model formulation, or the fact that most eruptions examined were not highly influenced by wind. For the low, wind-blown plume of 14–18 April 2010 at Eyjafjallajökull, where an accurate plume height time series is available, modeled rates do agree better with Mobs than Mempir.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research D: Atmospheres","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Geophysical Union","doi":"10.1002/2013JD020604","usgsCitation":"Mastin, L.G., 2014, Testing the accuracy of a 1-D volcanic plume model in estimating mass eruption rate: Journal of Geophysical Research D: Atmospheres, v. 119, no. 5, p. 2474-2495, https://doi.org/10.1002/2013JD020604.","productDescription":"22 p.","startPage":"2474","endPage":"2495","numberOfPages":"22","ipdsId":"IP-046214","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":473059,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2013jd020604","text":"Publisher Index Page"},{"id":286120,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"119","issue":"5","noUsgsAuthors":false,"publicationDate":"2014-03-07","publicationStatus":"PW","scienceBaseUri":"53517066e4b05569d805a3dd","contributors":{"authors":[{"text":"Mastin, Larry G. 0000-0002-4795-1992 lgmastin@usgs.gov","orcid":"https://orcid.org/0000-0002-4795-1992","contributorId":555,"corporation":false,"usgs":true,"family":"Mastin","given":"Larry","email":"lgmastin@usgs.gov","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":487443,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70099232,"text":"fs20143023 - 2014 - The Southeast Stream Quality Assessment","interactions":[],"lastModifiedDate":"2016-08-05T12:16:39","indexId":"fs20143023","displayToPublicDate":"2014-04-10T09:19:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3023","title":"The Southeast Stream Quality Assessment","docAbstract":"

In 2014, the U.S. Geological Survey (USGS) National Water-Quality Assessment Program (NAWQA) is assessing stream quality across the Piedmont and southern Appalachian Mountains in the southeastern United States. The goal of the Southeast Stream Quality Assessment (SESQA) is to characterize multiple water-quality factors that are stressors to aquatic life—contaminants, nutrients, sediment, and streamflow alteration—and the relation of these stressors to ecological conditions in streams throughout the region. Findings will provide communities and policymakers with information on which human and environmental factors are the most critical in controlling stream quality and, thus, provide insights about possible approaches to protect or improve stream quality. The SESQA study will be the second regional study by the NAWQA program, and it will be of similar design and scope as the Midwest Stream Quality Assessment conducted in 2013 (Van Metre and others, 2012).

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143023","collaboration":"National Water-Quality Assessment Program","usgsCitation":"Van Metre, P., and Journey, C.A., 2014, The Southeast Stream Quality Assessment: U.S. Geological Survey Fact Sheet 2014-3023, 2 p., https://doi.org/10.3133/fs20143023.","productDescription":"2 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055400","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":286119,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143023.jpg"},{"id":286116,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3023/pdf/fs2014-3023.pdf"},{"id":286117,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3023/"}],"projection":"Web Mercator Projection","country":"United States","state":"Alabama, Georgia, Kentucky, North Carolina, Pennsylvania, South Carolina, Tennessee, West Virginia","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -84.0,34.0 ], [ -84.0,40.0 ], [ -79.0,40.0 ], [ -79.0,34.0 ], [ -84.0,34.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517069e4b05569d805a405","contributors":{"authors":[{"text":"Van Metre, Peter C.","contributorId":34104,"corporation":false,"usgs":true,"family":"Van Metre","given":"Peter C.","affiliations":[],"preferred":false,"id":491883,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Journey, Celeste A. 0000-0002-2284-5851 cjourney@usgs.gov","orcid":"https://orcid.org/0000-0002-2284-5851","contributorId":2617,"corporation":false,"usgs":true,"family":"Journey","given":"Celeste","email":"cjourney@usgs.gov","middleInitial":"A.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":491882,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70101165,"text":"70101165 - 2014 - High fidelity does not preclude colonization: range expansion of molting Black Brant on the Arctic coast of Alaska","interactions":[],"lastModifiedDate":"2018-06-20T20:25:41","indexId":"70101165","displayToPublicDate":"2014-04-10T09:01:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2284,"text":"Journal of Field Ornithology","active":true,"publicationSubtype":{"id":10}},"title":"High fidelity does not preclude colonization: range expansion of molting Black Brant on the Arctic coast of Alaska","docAbstract":"High rates of site fidelity have been assumed to infer static distributions of molting geese in some cases. To test this assumption, we examined movements of individually marked birds to understand the underlying mechanisms of range expansion of molting Black Brant (Branta bernicla nigricans) on the Arctic Coastal Plain (ACP) of Alaska. The Teshekpuk Lake Special Area (TLSA) on the ACP was created to protect the primary molting area of Brant. When established in 1977, the TLSA was thought to include most, if not all, wetlands used by molting Brant on the ACP. From 2010 to 2013, we surveyed areas outside the TLSA and counted an average of 9800 Brant per year, representing 29–37% of all molting Brant counted on the ACP. We captured and banded molting Brant in 2011 and 2012 both within the TLSA and outside the TLSA at the Piasuk River Delta and Cape Simpson to assess movements of birds among areas across years. Estimates of movement rates out of the TLSA exceeded those into the TLSA, demonstrating overall directional dispersal. We found differences in sex and age ratios and proportions of adult females with brood patches, but no differences in mass dynamics for birds captured within and outside the TLSA. Overall fidelity rates to specific lakes (0.81, range = 0.49–0.92) were unchanged from comparable estimates obtained in the early 1990s. We conclude that Brant are dispersing from the TLSA into new molting areas while simultaneously redistributing within the TLSA, likely as a consequence of changes in relative habitat quality. Shifts in distribution resulted from colonization of new areas by young birds as well as low levels of directional dispersal of birds that previously molted in the TLSA. Based on combined counts, the overall number of molting Brant across the ACP has increased substantially.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Field Ornithology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/jofo.12051","usgsCitation":"Flint, P.L., Meixell, B.W., and Mallek, E.J., 2014, High fidelity does not preclude colonization: range expansion of molting Black Brant on the Arctic coast of Alaska: Journal of Field Ornithology, v. 85, no. 1, p. 75-83, https://doi.org/10.1111/jofo.12051.","productDescription":"9 p.","startPage":"75","endPage":"83","numberOfPages":"9","ipdsId":"IP-048892","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":286115,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286078,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/jofo.12051"}],"country":"United States","state":"Alaska","otherGeospatial":"Artic Coastal Plain;Cape Simpson;Piasuk River Delta;Teshekpuk Lake","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -155.4236,70.3187 ], [ -155.4236,71.3114 ], [ -150.2051,71.3114 ], [ -150.2051,70.3187 ], [ -155.4236,70.3187 ] ] ] } } ] }","volume":"85","issue":"1","noUsgsAuthors":false,"publicationDate":"2014-02-26","publicationStatus":"PW","scienceBaseUri":"53517046e4b05569d805a251","contributors":{"authors":[{"text":"Flint, Paul L. 0000-0002-8758-6993 pflint@usgs.gov","orcid":"https://orcid.org/0000-0002-8758-6993","contributorId":3284,"corporation":false,"usgs":true,"family":"Flint","given":"Paul","email":"pflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":492629,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meixell, Brandt W. 0000-0002-6738-0349 bmeixell@usgs.gov","orcid":"https://orcid.org/0000-0002-6738-0349","contributorId":138716,"corporation":false,"usgs":true,"family":"Meixell","given":"Brandt","email":"bmeixell@usgs.gov","middleInitial":"W.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":492630,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mallek, Edward J.","contributorId":103964,"corporation":false,"usgs":true,"family":"Mallek","given":"Edward","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":492631,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70101175,"text":"70101175 - 2014 - Greenhouse gases generated from the anaerobic biodegradation of natural offshore asphalt seepages in southern California","interactions":[],"lastModifiedDate":"2014-05-29T14:48:17","indexId":"70101175","displayToPublicDate":"2014-04-10T08:40:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1742,"text":"Geo-Marine Letters","active":true,"publicationSubtype":{"id":10}},"title":"Greenhouse gases generated from the anaerobic biodegradation of natural offshore asphalt seepages in southern California","docAbstract":"Significant offshore asphaltic deposits with active seepage occur in the Santa Barbara Channel offshore southern California. The composition and isotopic signatures of gases sampled from the oil and gas seeps reveal that the coexisting oil in the shallow subsurface is anaerobically biodegraded, generating CO2 with secondary CH4 production. Biomineralization can result in the consumption of as much as 60% by weight of the original oil, with 13C enrichment of CO2. Analyses of gas emitted from asphaltic accumulations or seeps on the seafloor indicate up to 11% CO2 with 13C enrichment reaching +24.8‰. Methane concentrations range from less than 30% up to 98% with isotopic compositions of –34.9 to –66.1‰. Higher molecular weight hydrocarbon gases are present in strongly varying concentrations reflecting both oil-associated gas and biodegradation; propane is preferentially biodegraded, resulting in an enriched 13C isotopic composition as enriched as –19.5‰. Assuming the 132 million barrels of asphaltic residues on the seafloor represent ~40% of the original oil volume and mass, the estimated gas generated is 5.0×1010 kg (~76×109 m3) CH4 and/or 1.4×1011 kg CO2 over the lifetime of seepage needed to produce the volume of these deposits. Geologic relationships and oil weathering inferences suggest the deposits are of early Holocene age or even younger. Assuming an age of ~1,000 years, annual fluxes are on the order of 5.0×107 kg (~76×106 m3) and/or 1.4×108 kg for CH4 and CO2, respectively. The daily volumetric emission rate (2.1×105 m3) is comparable to current CH4 emission from Coal Oil Point seeps (1.5×105 m3/day), and may be a significant source of both CH4 and CO2 to the atmosphere provided that the gas can be transported through the water column.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geo-Marine Letters","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s00367-014-0359-1","usgsCitation":"Lorenson, T., Wong, F.L., Dartnell, P., and Sliter, R.W., 2014, Greenhouse gases generated from the anaerobic biodegradation of natural offshore asphalt seepages in southern California: Geo-Marine Letters, v. 34, no. 2-3, p. 281-295, https://doi.org/10.1007/s00367-014-0359-1.","productDescription":"15 p.","startPage":"281","endPage":"295","numberOfPages":"15","ipdsId":"IP-049273","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":286112,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286081,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s00367-014-0359-1"}],"country":"United States","state":"California","otherGeospatial":"Santa Barbara Channel","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -120.562226,34.01231 ], [ -120.562226,34.526411 ], [ -119.498612,34.526411 ], [ -119.498612,34.01231 ], [ -120.562226,34.01231 ] ] ] } } ] }","volume":"34","issue":"2-3","noUsgsAuthors":false,"publicationDate":"2014-02-20","publicationStatus":"PW","scienceBaseUri":"53517043e4b05569d805a238","contributors":{"authors":[{"text":"Lorenson, T.D. tlorenson@usgs.gov","contributorId":2622,"corporation":false,"usgs":true,"family":"Lorenson","given":"T.D.","email":"tlorenson@usgs.gov","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":false,"id":492639,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wong, Florence L. 0000-0002-3918-5896 fwong@usgs.gov","orcid":"https://orcid.org/0000-0002-3918-5896","contributorId":1990,"corporation":false,"usgs":true,"family":"Wong","given":"Florence","email":"fwong@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":492637,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dartnell, Peter 0000-0002-9554-729X pdartnell@usgs.gov","orcid":"https://orcid.org/0000-0002-9554-729X","contributorId":2688,"corporation":false,"usgs":true,"family":"Dartnell","given":"Peter","email":"pdartnell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":492640,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sliter, Ray W. 0000-0003-0337-3454 rsliter@usgs.gov","orcid":"https://orcid.org/0000-0003-0337-3454","contributorId":1992,"corporation":false,"usgs":true,"family":"Sliter","given":"Ray","email":"rsliter@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":492638,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70138813,"text":"70138813 - 2014 - Research, monitoring, and evaluation of emerging issues and measures to recover the Snake River fall Chinook salmon ESU, 1/1/2012 – 12/31/2013: Annual report, 1991-029-00","interactions":[],"lastModifiedDate":"2016-04-26T15:44:23","indexId":"70138813","displayToPublicDate":"2014-04-10T06:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Research, monitoring, and evaluation of emerging issues and measures to recover the Snake River fall Chinook salmon ESU, 1/1/2012 – 12/31/2013: Annual report, 1991-029-00","docAbstract":"

The portion of the Snake River fall Chinook Salmon Oncorhynchus tshawytscha ESU that spawns upstream of Lower Granite Dam transitioned from low to high abundance during 1992–2014 in association with U.S. Endangered Species Act recovery efforts and other Federally mandated actions. This annual report focuses on (1) numeric and habitat use responses by natural- and hatchery-origin spawners, (2) phenotypic and numeric responses by natural-origin juveniles, and (3) predator responses in the Snake River upper and lower reaches as abundance of adult and juvenile fall Chinook Salmon increased. Spawners have located and used most of the available spawning habitat and that habitat is gradually approaching redd capacity. Timing of spawning and fry emergence has been relatively stable; whereas the timing of parr dispersal from riverine rearing habitat into Lower Granite Reservoir has become earlier as apparent abundance of juveniles has increased. Growth rate (g/d) and dispersal size of parr also declined as apparent abundance of juveniles increased. Passage timing of smolts from the two Snake River reaches has become earlier and downstream movement rate faster as estimated abundance of fall Chinook Salmon smolts in Lower Granite Reservoir has increased. In 2014, consumption of subyearlings by Smallmouth Bass was highest in the upper reach which had the highest abundance of Bass. With a few exceptions, predation tended to decrease seasonally from April through early July. A release of hatchery fish in mid-May significantly increased subyearling consumption by the following day. We estimated that over 600,000 subyearling fall Chinook Salmon were lost to Smallmouth Bass predation along the free-flowing Snake River in 2014. More information on predation is presented in Appendix A.3 (page 51). These findings coupled with stock-recruitment analyses presented in this report provide evidence for density-dependence in the Snake River reaches and in Lower Granite Reservoir that was influenced by the expansion of the recovery program. The long-term goal is to use the information covered here in a comprehensive modeling effort to conduct action effectiveness and uncertainty research and to inform fish population, hydrosystem, harvest, hatchery, and predation and invasive species management RM&E.

","language":"English","publisher":"Bonneville Power Administration","collaboration":"Report covers work performed under Bonneville Power Administration Contract # 272492","usgsCitation":"Connor, W.P., Mullins, F., Tiffan, K.F., Perry, R.W., Erhardt, J.M., St. John, S., Bickford, B.K., and Rhodes, T.N., 2014, Research, monitoring, and evaluation of emerging issues and measures to recover the Snake River fall Chinook salmon ESU, 1/1/2012 – 12/31/2013: Annual report, 1991-029-00, 186 p.","productDescription":"186 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057389","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":320566,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":297443,"type":{"id":11,"text":"Document"},"url":"https://pisces.bpa.gov/release/documents/documentviewer.aspx?doc=P137822","text":"Report","size":"1.05 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Oregon, Washington","otherGeospatial":"Hells Canyon Reach, Snake River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.7569580078125,\n 45.251688256117646\n ],\n [\n -117.7569580078125,\n 46.76244305208004\n ],\n [\n -116.53198242187499,\n 46.76244305208004\n ],\n [\n -116.53198242187499,\n 45.251688256117646\n ],\n [\n -117.7569580078125,\n 45.251688256117646\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57209137e4b071321fe65683","contributors":{"authors":[{"text":"Connor, William P.","contributorId":107589,"corporation":false,"usgs":false,"family":"Connor","given":"William","email":"","middleInitial":"P.","affiliations":[{"id":16677,"text":"U.S. Fish and Wildlife Service, Idaho Fishery Resource Office, 276 Dworshak Complex Drive, Orofino, ID 83544","active":true,"usgs":false}],"preferred":false,"id":538926,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mullins, Frank","contributorId":36440,"corporation":false,"usgs":true,"family":"Mullins","given":"Frank","affiliations":[],"preferred":false,"id":538927,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tiffan, Kenneth F. 0000-0002-5831-2846 ktiffan@usgs.gov","orcid":"https://orcid.org/0000-0002-5831-2846","contributorId":3200,"corporation":false,"usgs":true,"family":"Tiffan","given":"Kenneth","email":"ktiffan@usgs.gov","middleInitial":"F.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":538925,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":538928,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Erhardt, John M. 0000-0002-5170-285X jerhardt@usgs.gov","orcid":"https://orcid.org/0000-0002-5170-285X","contributorId":5380,"corporation":false,"usgs":true,"family":"Erhardt","given":"John","email":"jerhardt@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":538929,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"St. John, Scott J.","contributorId":19873,"corporation":false,"usgs":true,"family":"St. John","given":"Scott J.","affiliations":[],"preferred":false,"id":538930,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bickford, Brad K. 0000-0003-3756-6588 bbickford@usgs.gov","orcid":"https://orcid.org/0000-0003-3756-6588","contributorId":140889,"corporation":false,"usgs":true,"family":"Bickford","given":"Brad","email":"bbickford@usgs.gov","middleInitial":"K.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":538931,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rhodes, Tobyn N. 0000-0002-4023-4827 trhodes@usgs.gov","orcid":"https://orcid.org/0000-0002-4023-4827","contributorId":140890,"corporation":false,"usgs":true,"family":"Rhodes","given":"Tobyn","email":"trhodes@usgs.gov","middleInitial":"N.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":538932,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70188049,"text":"70188049 - 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Accurately quantifying the spatial and temporal variability of net primary production (NPP) for croplands is essential to understand regional cropland carbon dynamics. We compared three NPP estimates for croplands in the Midwestern United States: inventory-based estimates using crop yield data from the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS); estimates from the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) NPP product; and estimates from the General Ensemble biogeochemical Modeling System (GEMS) process-based model. The three methods estimated mean NPP in the range of 469–687 g C m−2 yr−1and total NPP in the range of 318–490 Tg C yr−1 for croplands in the Midwest in 2007 and 2008. The NPP estimates from crop yield data and the GEMS model showed the mean NPP for croplands was over 650 g C m−2 yr−1 while the MODIS NPP product estimated the mean NPP was less than 500 g C m−2 yr−1. MODIS NPP also showed very different spatial variability of the cropland NPP from the other two methods. We found these differences were mainly caused by the difference in the land cover data and the crop specific information used in the methods. Our study demonstrated that the detailed mapping of the temporal and spatial change of crop species is critical for estimating the spatial and temporal variability of cropland NPP. We suggest that high resolution land cover data with species–specific crop information should be used in satellite-based and process-based models to improve carbon estimates for croplands.

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The updated roads data resolves known concerns of omission, commission, and inconsistent representation of map scale, attribution, and ground reference dates which were present in the original source data. To ensure a systematic and repeatable approach of capturing roads on the landscape using on-screen digitizing from true color National Agriculture Imagery Program imagery, we developed a photogrammetry key and quality assurance/quality control protocols. Therefore, the updated statewide roads data will support the Bureau of Land Management’s resource management requirements with a standardized map product representing 2009 ground conditions. The updated Geographic Information System roads data set product, represented at 1:4,000 and +/- 10 meters spatial accuracy, contains 425,275 kilometers within eight attribute classes. The quality control of these products indicated a 97.7 percent accuracy of aspatial information and 98.0 percent accuracy of spatial locations. Approximately 48 percent of the updated roads data was corrected for spatial errors of greater than 1 meter relative to the pre-existing road data. Twenty-six percent of the updated roads involved correcting spatial errors of greater than 5 meters and 17 percent of the updated roads involved correcting spatial errors of greater than 9 meters. The Bureau of Land Management, other land managers, and researchers can use these new statewide roads data set products to support important studies and management decisions regarding land use changes, transportation and planning needs, transportation safety, wildlife applications, and other studies.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds821","issn":"2327-638X","collaboration":"Prepared in cooperation with Resource Ecology Laboratory, Colorado State University","usgsCitation":"O'Donnell, M., Fancher, T., Freeman, A.T., Ziegler, A.E., Bowen, Z.H., and Aldridge, C.L., 2014, Large scale Wyoming transportation data: a resource planning tool: U.S. Geological Survey Data Series 821, Report: v, 21 p.; Downloads directory, https://doi.org/10.3133/ds821.","productDescription":"Report: v, 21 p.; Downloads directory","numberOfPages":"29","onlineOnly":"Y","ipdsId":"IP-049829","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":286026,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds821.jpg"},{"id":286024,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/821/pdf/ds821.pdf"},{"id":286023,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/821/"},{"id":286025,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/821/downloads/"}],"country":"United States","state":"Wyoming","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.0,41.0 ], [ -111.0,45.0 ], [ -104.0,45.0 ], [ -104.0,41.0 ], [ -111.0,41.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517051e4b05569d805a301","contributors":{"authors":[{"text":"O'Donnell, Michael S.","contributorId":40667,"corporation":false,"usgs":true,"family":"O'Donnell","given":"Michael S.","affiliations":[],"preferred":false,"id":489206,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fancher, Tammy S.","contributorId":17689,"corporation":false,"usgs":true,"family":"Fancher","given":"Tammy S.","affiliations":[],"preferred":false,"id":489205,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Freeman, Aaron T. 0000-0001-9395-5604 afreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-9395-5604","contributorId":5293,"corporation":false,"usgs":true,"family":"Freeman","given":"Aaron","email":"afreeman@usgs.gov","middleInitial":"T.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":489203,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ziegler, Abra E. aeziegler@usgs.gov","contributorId":5294,"corporation":false,"usgs":true,"family":"Ziegler","given":"Abra","email":"aeziegler@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":489204,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bowen, Zachary H. 0000-0002-8656-1831 bowenz@usgs.gov","orcid":"https://orcid.org/0000-0002-8656-1831","contributorId":821,"corporation":false,"usgs":true,"family":"Bowen","given":"Zachary","email":"bowenz@usgs.gov","middleInitial":"H.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":489202,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":489207,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70101080,"text":"70101080 - 2014 - From headwaters to coast: Influence of human activities on water quality of the Potomac River Estuary","interactions":[],"lastModifiedDate":"2019-12-02T07:05:42","indexId":"70101080","displayToPublicDate":"2014-04-09T13:26:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":866,"text":"Aquatic Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"From headwaters to coast: Influence of human activities on water quality of the Potomac River Estuary","docAbstract":"The natural aging process of Chesapeake Bay and its tributary estuaries has been accelerated by human activities around the shoreline and within the watershed, increasing sediment and nutrient loads delivered to the bay. Riverine nutrients cause algal growth in the bay leading to reductions in light penetration with consequent declines in sea grass growth, smothering of bottom-dwelling organisms, and decreases in bottom-water dissolved oxygen as algal blooms decay. Historically, bay waters were filtered by oysters, but declines in oyster populations from overfishing and disease have led to higher concentrations of fine-sediment particles and phytoplankton in the water column. Assessments of water and biological resource quality in Chesapeake Bay and tributaries, such as the Potomac River, show a continual degraded state. In this paper, we pay tribute to Owen Bricker’s comprehensive, holistic scientific perspective using an approach that examines the connection between watershed and estuary. We evaluated nitrogen inputs from Potomac River headwaters, nutrient-related conditions within the estuary, and considered the use of shellfish aquaculture as an in-the-water nutrient management measure. Data from headwaters, nontidal, and estuarine portions of the Potomac River watershed and estuary were analyzed to examine the contribution from different parts of the watershed to total nitrogen loads to the estuary. An eutrophication model was applied to these data to evaluate eutrophication status and changes since the early 1990s and for comparison to regional and national conditions. A farm-scale aquaculture model was applied and results scaled to the estuary to determine the potential for shellfish (oyster) aquaculture to mediate eutrophication impacts. Results showed that (1) the contribution to nitrogen loads from headwater streams is small (about 2 %) of total inputs to the Potomac River Estuary; (2) eutrophic conditions in the Potomac River Estuary have improved in the upper estuary since the early 1990s, but have worsened in the lower estuary. The overall system-wide eutrophication impact is high, despite a decrease in nitrogen loads from the upper basin and declining surface water nitrate nitrogen concentrations over that period; (3) eutrophic conditions in the Potomac River Estuary are representative of Chesapeake Bay region and other US estuaries; moderate to high levels of nutrient-related degradation occur in about 65 % of US estuaries, particularly river-dominated low-flow systems such as the Potomac River Estuary; and (4) shellfish (oyster) aquaculture could remove eutrophication impacts directly from the estuary through harvest but should be considered a complement—not a substitute—for land-based measures. The total nitrogen load could be removed if 40 % of the Potomac River Estuary bottom was in shellfish cultivation; a combination of aquaculture and restoration of oyster reefs may provide larger benefits.","language":"English","publisher":"Springer","doi":"10.1007/s10498-014-9226-y","issn":"13806165","usgsCitation":"Bricker, S.B., Rice, K.C., and Bricker, O.P., 2014, From headwaters to coast: Influence of human activities on water quality of the Potomac River Estuary: Aquatic Geochemistry, v. 20, no. 2, p. 291-323, https://doi.org/10.1007/s10498-014-9226-y.","productDescription":"33 p.","startPage":"291","endPage":"323","ipdsId":"IP-046228","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":286015,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":333173,"rank":2,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/70115891","text":"Response to comment"}],"country":"United States","state":"Maryland, Pennsylvania, Virginia, West Virginia","otherGeospatial":"Potomac River Estuary","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -80.4772,37.8139 ], [ -80.4772,40.788 ], [ -75.9119,40.788 ], [ -75.9119,37.8139 ], [ -80.4772,37.8139 ] ] ] } } ] }","volume":"20","issue":"2","noUsgsAuthors":false,"publicationDate":"2014-02-26","publicationStatus":"PW","scienceBaseUri":"5351703de4b05569d805a20c","contributors":{"authors":[{"text":"Bricker, Suzanne B.","contributorId":64555,"corporation":false,"usgs":false,"family":"Bricker","given":"Suzanne","email":"","middleInitial":"B.","affiliations":[{"id":12448,"text":"U.S. National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":492591,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rice, Karen C. 0000-0002-9356-5443 kcrice@usgs.gov","orcid":"https://orcid.org/0000-0002-9356-5443","contributorId":1998,"corporation":false,"usgs":true,"family":"Rice","given":"Karen","email":"kcrice@usgs.gov","middleInitial":"C.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":false,"id":492589,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bricker, Owen P. III","contributorId":34432,"corporation":false,"usgs":true,"family":"Bricker","given":"Owen","suffix":"III","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":492590,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70099978,"text":"fs20143024 - 2014 - Groundwater studies: principal aquifer surveys","interactions":[],"lastModifiedDate":"2017-01-23T09:59:01","indexId":"fs20143024","displayToPublicDate":"2014-04-09T13:24:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3024","title":"Groundwater studies: principal aquifer surveys","docAbstract":"

In 1991, the U.S. Congress established the National Water-Quality Assessment (NAWQA) program within the U.S. Geological Survey (USGS) to develop nationally consistent long-term datasets and provide information about the quality of the Nation’s streams and groundwater. The USGS uses objective and reliable data, water-quality models, and systematic scientific studies to assess current water-quality conditions, to identify changes in water quality over time, and to determine how natural factors and human activities affect the quality of streams and groundwater. NAWQA is the only non-regulatory Federal program to perform these types of studies; participation is voluntary.

\n\n
\n\n

In the third decade (Cycle 3) of the NAWQA program (2013–2023), the USGS will evaluate the quality and availability of groundwater for drinking supply, improve our understanding of where and why water quality is degraded, and assess how groundwater quality could respond to changes in climate and land use. These goals will be addressed through the implementation of a new monitoring component in Cycle 3: Principal Aquifer Surveys.

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Permafrost thaw and the subsequent mobilization of carbon (C) stored in previously frozen soil organic matter (SOM) have the potential to be a strong positive feedback to climate. As the northern permafrost region experiences as much as a doubling of the rate of warming as the rest of the Earth, the vast amount of C in permafrost soils is vulnerable to thaw, decomposition and release as atmospheric greenhouse gases. Diagnostic and predictive estimates of high-latitude terrestrial C fluxes vary widely among different models depending on how dynamics in permafrost, and the seasonally thawed 'active layer' above it, are represented. Here, we employ a process-based model simulation experiment to assess the net effect of active layer dynamics on this 'permafrost carbon feedback' in recent decades, from 1970 to 2006, over the circumpolar domain of continuous and discontinuous permafrost. Over this time period, the model estimates a mean increase of 6.8 cm in active layer thickness across the domain, which exposes a total of 11.6 Pg C of thawed SOM to decomposition. According to our simulation experiment, mobilization of this previously frozen C results in an estimated cumulative net source of 3.7 Pg C to the atmosphere since 1970 directly tied to active layer dynamics. Enhanced decomposition from the newly exposed SOM accounts for the release of both CO2 (4.0 Pg C) and CH4 (0.03 Pg C), but is partially compensated by CO2 uptake (0.3 Pg C) associated with enhanced net primary production of vegetation. This estimated net C transfer to the atmosphere from permafrost thaw represents a significant factor in the overall ecosystem carbon budget of the Pan-Arctic, and a non-trivial additional contribution on top of the combined fossil fuel emissions from the eight Arctic nations over this time period.

","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Research Letters","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Institute of Physics Publishing","publisherLocation":"London","doi":"10.1088/1748-9326/9/4/045005","usgsCitation":"Hayes, D.J., Kicklighter, D.W., McGuire, A.D., Chen, M., Zhuang, Q., Yuan, F., Melillo, J.M., and Wullschleger, S.D., 2014, The impacts of recent permafrost thaw on land-atmosphere greenhouse gas exchange: Environmental Research Letters, v. 9, no. 4, 12 p., https://doi.org/10.1088/1748-9326/9/4/045005.","productDescription":"12 p.","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-050867","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":473060,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/9/4/045005","text":"Publisher Index Page"},{"id":318554,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-04-09","publicationStatus":"PW","scienceBaseUri":"56dabff4e4b015c306f84d14","contributors":{"authors":[{"text":"Hayes, Daniel J.","contributorId":100237,"corporation":false,"usgs":true,"family":"Hayes","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":621870,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kicklighter, David W.","contributorId":48872,"corporation":false,"usgs":false,"family":"Kicklighter","given":"David","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":621871,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGuire, A. David 0000-0003-4646-0750 ffadm@usgs.gov","orcid":"https://orcid.org/0000-0003-4646-0750","contributorId":166708,"corporation":false,"usgs":true,"family":"McGuire","given":"A.","email":"ffadm@usgs.gov","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":621847,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chen, Min","contributorId":56140,"corporation":false,"usgs":true,"family":"Chen","given":"Min","email":"","affiliations":[],"preferred":false,"id":621872,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhuang, Qianlai","contributorId":101975,"corporation":false,"usgs":true,"family":"Zhuang","given":"Qianlai","affiliations":[],"preferred":false,"id":621873,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yuan, Fengming","contributorId":81819,"corporation":false,"usgs":true,"family":"Yuan","given":"Fengming","email":"","affiliations":[],"preferred":false,"id":621874,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Melillo, Jerry M.","contributorId":87847,"corporation":false,"usgs":false,"family":"Melillo","given":"Jerry","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":621875,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wullschleger, Stan D.","contributorId":167343,"corporation":false,"usgs":false,"family":"Wullschleger","given":"Stan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":621876,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70098028,"text":"fs20143021 - 2014 - Decision support system development at the Upper Midwest Environmental Sciences Center","interactions":[],"lastModifiedDate":"2023-01-20T16:11:10.614395","indexId":"fs20143021","displayToPublicDate":"2014-04-09T10:13:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3021","title":"Decision support system development at the Upper Midwest Environmental Sciences Center","docAbstract":"A Decision Support System (DSS) can be defined in many ways. The working definition used by the U.S. Geological Survey Upper Midwest Environmental Sciences Center (UMESC) is, “A spatially based computer application or data that assists a researcher or manager in making decisions.” This is quite a broad definition—and it needs to be, because the possibilities for types of DSSs are limited only by the user group and the developer’s imagination. There is no one DSS; the types of DSSs are as diverse as the problems they help solve. This diversity requires that DSSs be built in a variety of ways, using the most appropriate methods and tools for the individual application. The skills of potential DSS users vary widely as well, further necessitating multiple approaches to DSS development. Some small, highly trained user groups may want a powerful modeling tool with extensive functionality at the expense of ease of use. Other user groups less familiar with geographic information system (GIS) and spatial data may want an easy-to-use application for a nontechnical audience. UMESC has been developing DSSs for almost 20 years. Our DSS developers offer our partners a wide variety of technical skills and development options, ranging from the most simple Web page or small application to complex modeling application development.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143021","usgsCitation":"Fox, T.J., Nelson, J., and Rohweder, J., 2014, Decision support system development at the Upper Midwest Environmental Sciences Center: U.S. Geological Survey Fact Sheet 2014-3021, 2 p., https://doi.org/10.3133/fs20143021.","productDescription":"2 p.","ipdsId":"IP-049834","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":285944,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143021.jpg"},{"id":285941,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3021/"},{"id":285940,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3021/pdf/fs2014-3021.pdf"}],"country":"United States","otherGeospatial":"Upper Midwest","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -91.27417,43.746041 ], [ -91.27417,43.898447 ], [ -91.157089,43.898447 ], [ -91.157089,43.746041 ], [ -91.27417,43.746041 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517032e4b05569d805a1b1","contributors":{"authors":[{"text":"Fox, Timothy J. 0000-0002-6167-3001 tfox@usgs.gov","orcid":"https://orcid.org/0000-0002-6167-3001","contributorId":1701,"corporation":false,"usgs":true,"family":"Fox","given":"Timothy","email":"tfox@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":491543,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nelson, J. C. 0000-0002-7105-0107 jcnelson@usgs.gov","orcid":"https://orcid.org/0000-0002-7105-0107","contributorId":459,"corporation":false,"usgs":true,"family":"Nelson","given":"J. C.","email":"jcnelson@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":491542,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rohweder, Jason J.","contributorId":25629,"corporation":false,"usgs":true,"family":"Rohweder","given":"Jason J.","affiliations":[],"preferred":false,"id":491544,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70101379,"text":"70101379 - 2014 - Water use characteristics of black mangrove (Avicennia germinans) communities along an ecotone with marsh at a northern geographical limit","interactions":[],"lastModifiedDate":"2014-04-11T10:17:26","indexId":"70101379","displayToPublicDate":"2014-04-09T10:03:07","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"Water use characteristics of black mangrove (Avicennia germinans) communities along an ecotone with marsh at a northern geographical limit","docAbstract":"Mangroves are expanding into warm temperate-zone salt marsh communities in several locations globally. Although scientists have discovered that expansion might have modest effects on ecosystem functioning, water use characteristics have not been assessed relative to this transition. We measured early growing season sapflow (Js) and leaf transpiration (Tr) in Avicennia germinans at a latitudinal limit along the northern Gulf of Mexico (Louisiana, United States) under both flooded and drained states and used these data to scale vegetation water use responses in comparison with Spartina alterniflora. We discovered strong convergence when using either Js or Tr for determining individual tree water use, indicating tight connection between transpiration and xylem water movement in small Avicennia trees. When Tr data were combined with leaf area indices for the region with the use of three separate approaches, we determined that Avicennia stands use approximately 1·0–1·3 mm d–1 less water than Spartina marsh. Differences were only significant with the use of two of the three approaches, but are suggestive of net conservation of water as Avicennia expands into Spartina marshes at this location. Average Js for Avicennia trees was not influenced by flooding, but maximum Js was greater when sites were flooded. Avicennia and Spartina closest to open water (shoreline) used more water than interior locations of the same assemblages by an average of 1·3 mm d−1. Lower water use by Avicennia may indicate a greater overall resilience to drought relative to Spartina, such that aperiodic drought may interact with warmer winter temperatures to facilitate expansion of Avicennia in some years.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecohydrology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley Online Library","doi":"10.1002/eco.1353","usgsCitation":"Krauss, K.W., McKee, K.L., and Hester, M.W., 2014, Water use characteristics of black mangrove (Avicennia germinans) communities along an ecotone with marsh at a northern geographical limit: Ecohydrology, v. 7, no. 2, p. 354-365, https://doi.org/10.1002/eco.1353.","startPage":"354","endPage":"365","ipdsId":"IP-038229","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":286249,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286246,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/eco.1353"}],"country":"United States","state":"Louisiana","otherGeospatial":"Gulf Of Mexico","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -91,28.5 ], [ -91,8.333333333333334E-4 ], [ -89,8.333333333333334E-4 ], [ -89,28.5 ], [ -91,28.5 ] ] ] } } ] }","volume":"7","issue":"2","edition":"12 p.","noUsgsAuthors":false,"publicationDate":"2012-12-05","publicationStatus":"PW","scienceBaseUri":"5351706ee4b05569d805a44a","contributors":{"authors":[{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":492679,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McKee, Karen L. 0000-0001-7042-670X","orcid":"https://orcid.org/0000-0001-7042-670X","contributorId":8927,"corporation":false,"usgs":true,"family":"McKee","given":"Karen","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":492680,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hester, Mark W.","contributorId":9566,"corporation":false,"usgs":true,"family":"Hester","given":"Mark","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":492681,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70101050,"text":"70101050 - 2014 - Accuracy of aging ducks in the U.S. Fish and Wildlife Service Waterfowl Parts Collection Survey","interactions":[],"lastModifiedDate":"2018-01-04T12:51:45","indexId":"70101050","displayToPublicDate":"2014-04-09T09:54:00","publicationYear":"2014","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":"Accuracy of aging ducks in the U.S. Fish and Wildlife Service Waterfowl Parts Collection Survey","docAbstract":"The U.S. Fish and Wildlife Service conducts an annual Waterfowl Parts Collection Survey to estimate composition of harvested waterfowl by species, sex, and age (i.e., juv or ad). The survey relies on interpretation of duck wings by a group of experienced biologists at annual meetings (hereafter, flyway wingbees). Our objectives were to estimate accuracy of age assignment at flyway wingbees and to explore how accuracy rates may influence bias of age composition estimates. We used banded mallards (Anas platyrhynchos; n = 791), wood ducks (Aix sponsa; n = 242), and blue-winged teal (Anas discors; n = 39) harvested and donated by hunters as our source of birds used in accuracy assessments. We sent wings of donated birds to wingbees after the 2002–2003 and 2003–2004 hunting seasons and compared species, sex, and age determinations made at wingbees with our assessments based on internal and external examination of birds and corresponding banding records. Determinations of species and sex of mallards, wood ducks, and blue-winged teal were accurate (>99%). Accuracy of aging adult mallards increased with harvest date, whereas accuracy of aging juvenile male wood ducks and juvenile blue-winged teal decreased with harvest date. Accuracy rates were highest (96% and 95%) for adult and juvenile mallards, moderate for adult and juvenile wood ducks (92% and 92%), and lowest for adult and juvenile blue-winged teal (84% and 82%). We used these estimates to calculate bias for all possible age compositions (0–100% proportion juv) and determined the range of age compositions estimated with acceptable levels of bias. Comparing these ranges with age compositions estimated from Parts Collection Surveys conducted from 1961 to 2008 revealed that mallard and wood duck age compositions were estimated with insignificant levels of bias in all national surveys. However, 69% of age compositions for blue-winged teal were estimated with an unacceptable level of bias. The low preliminary accuracy rates of aging blue-winged teal based on our limited sample suggest a more extensive accuracy assessment study may be considered for interpreting age compositions of this species.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Wildlife Society Bulletin","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/wsb.373","usgsCitation":"Pearse, A.T., Johnson, D.H., Richkus, K.D., Rohwer, F.C., Cox, R.R., and Padding, P.I., 2014, Accuracy of aging ducks in the U.S. Fish and Wildlife Service Waterfowl Parts Collection Survey: Wildlife Society Bulletin, v. 38, no. 1, p. 26-32, https://doi.org/10.1002/wsb.373.","productDescription":"7 p.","startPage":"26","endPage":"32","ipdsId":"IP-044048","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":499926,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/7138f8f40aad432ebe8a479cdbd7d1f3","text":"External Repository"},{"id":285936,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":285925,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/wsb.373"}],"volume":"38","issue":"1","noUsgsAuthors":false,"publicationDate":"2013-11-08","publicationStatus":"PW","scienceBaseUri":"53516f28e4b05569d805a021","chorus":{"doi":"10.1002/wsb.373","url":"http://dx.doi.org/10.1002/wsb.373","publisher":"Wiley-Blackwell","authors":"Pearse Aaron T., Johnson Douglas H., Richkus Kenneth D., Rohwer Frank C., Cox Robert R., Padding Paul I.","journalName":"Wildlife Society Bulletin","publicationDate":"11/8/2013","auditedOn":"11/17/2015"},"contributors":{"authors":[{"text":"Pearse, Aaron T. 0000-0002-6137-1556 apearse@usgs.gov","orcid":"https://orcid.org/0000-0002-6137-1556","contributorId":1772,"corporation":false,"usgs":true,"family":"Pearse","given":"Aaron","email":"apearse@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":492554,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Douglas H. 0000-0002-7778-6641 douglas_h_johnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7778-6641","contributorId":1387,"corporation":false,"usgs":true,"family":"Johnson","given":"Douglas","email":"douglas_h_johnson@usgs.gov","middleInitial":"H.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":492553,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richkus, Kenneth D.","contributorId":34428,"corporation":false,"usgs":true,"family":"Richkus","given":"Kenneth","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":492556,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rohwer, Frank C.","contributorId":71477,"corporation":false,"usgs":true,"family":"Rohwer","given":"Frank","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":492558,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cox, Robert R. Jr.","contributorId":6575,"corporation":false,"usgs":true,"family":"Cox","given":"Robert","suffix":"Jr.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":492555,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Padding, Paul I.","contributorId":38411,"corporation":false,"usgs":true,"family":"Padding","given":"Paul","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":492557,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70100875,"text":"ofr20141073 - 2014 - Laharz_py: GIS tools for automated mapping of lahar inundation hazard zones","interactions":[],"lastModifiedDate":"2014-04-09T10:25:22","indexId":"ofr20141073","displayToPublicDate":"2014-04-09T09:25:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1073","title":"Laharz_py: GIS tools for automated mapping of lahar inundation hazard zones","docAbstract":"Laharz_py is written in the Python programming language as a suite of tools for use in ArcMap Geographic Information System (GIS). Primarily, Laharz_py is a computational model that uses statistical descriptions of areas inundated by past mass-flow events to forecast areas likely to be inundated by hypothetical future events. The forecasts use physically motivated and statistically calibrated power-law equations that each has a form A = cV2/3, relating mass-flow volume (V) to planimetric or cross-sectional areas (A) inundated by an average flow as it descends a given drainage. Calibration of the equations utilizes logarithmic transformation and linear regression to determine the best-fit values of c. The software uses values of V, an algorithm for idenitifying mass-flow source locations, and digital elevation models of topography to portray forecast hazard zones for lahars, debris flows, or rock avalanches on maps. Laharz_py offers two methods to construct areas of potential inundation for lahars: (1) Selection of a range of plausible V values results in a set of nested hazard zones showing areas likely to be inundated by a range of hypothetical flows; and (2) The user selects a single volume and a confidence interval for the prediction. In either case, Laharz_py calculates the mean expected A and B value from each user-selected value of V. However, for the second case, a single value of V yields two additional results representing the upper and lower values of the confidence interval of prediction. Calculation of these two bounding predictions require the statistically calibrated prediction equations, a user-specified level of confidence, and t-distribution statistics to calculate the standard error of regression, standard error of the mean, and standard error of prediction. The portrayal of results from these two methods on maps compares the range of inundation areas due to prediction uncertainties with uncertainties in selection of V values. The Open-File Report document contains an explanation of how to install and use the software. The Laharz_py software includes an example data set for Mount Rainier, Washington. The second part of the documentation describes how to use all of the Laharz_py tools in an example dataset at Mount Rainier, Washington.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141073","usgsCitation":"Schilling, S.P., 2014, Laharz_py: GIS tools for automated mapping of lahar inundation hazard zones: U.S. Geological Survey Open-File Report 2014-1073, Report: iv, 78 p.; Laharz_py example ZIP, https://doi.org/10.3133/ofr20141073.","productDescription":"Report: iv, 78 p.; Laharz_py example ZIP","numberOfPages":"82","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-043956","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":285932,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141073.PNG"},{"id":285930,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1073/pdf/ofr2014-1073.pdf"},{"id":285912,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1073/"},{"id":285931,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1073/downloads/laharz_py_example.zip"}],"country":"United States","state":"Washington","otherGeospatial":"Mount St. Helens","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.258,46.160 ], [ -122.258,46.222 ], [ -122.130,46.222 ], [ -122.130,46.160 ], [ -122.258,46.160 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517051e4b05569d805a2f8","contributors":{"authors":[{"text":"Schilling, Steve P. sschilli@usgs.gov","contributorId":634,"corporation":false,"usgs":true,"family":"Schilling","given":"Steve","email":"sschilli@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":492440,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70057376,"text":"fs20133113 - 2014 - Assessment of potential shale oil and tight sandstone gas resources of the Assam, Bombay, Cauvery, and Krishna-Godavari Provinces, India, 2013","interactions":[],"lastModifiedDate":"2014-04-09T09:39:24","indexId":"fs20133113","displayToPublicDate":"2014-04-09T09:18:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-3113","title":"Assessment of potential shale oil and tight sandstone gas resources of the Assam, Bombay, Cauvery, and Krishna-Godavari Provinces, India, 2013","docAbstract":"Using a well performance-based geologic assessment methodology, the U.S. Geological Survey estimated a technically recoverable mean volume of 62 million barrels of oil in shale oil reservoirs, and more than 3,700 billion cubic feet of gas in tight sandstone gas reservoirs in the Bombay and Krishna-Godavari Provinces of India. The term “provinces” refer to geologically defined units assessed by the USGS for the purposes of this report and carries no political or diplomatic connotation. Shale oil and tight sandstone gas reservoirs were evaluated in the Assam and Cauvery Provinces, but these reservoirs were not quantitatively assessed.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133113","collaboration":"World Petroleum Resources Project","usgsCitation":"Klett, T., Schenk, C.J., Wandrey, C.J., Brownfield, M.E., Charpentier, R., Tennyson, M., and Gautier, D.L., 2014, Assessment of potential shale oil and tight sandstone gas resources of the Assam, Bombay, Cauvery, and Krishna-Godavari Provinces, India, 2013: U.S. Geological Survey Fact Sheet 2013-3113, 4 p., https://doi.org/10.3133/fs20133113.","productDescription":"4 p.","additionalOnlineFiles":"Y","ipdsId":"IP-052206","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":285933,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133113.jpg"},{"id":285928,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3113/"},{"id":285929,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3113/pdf/fs2013-3113.pdf"}],"country":"India","state":"Assam","city":"Bombay","otherGeospatial":"Cauvery River;Krishna-godavari Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 60.0,5.0 ], [ 60.0,35.0 ], [ 100.0,35.0 ], [ 100.0,5.0 ], [ 60.0,5.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517025e4b05569d805a16a","contributors":{"authors":[{"text":"Klett, Timothy R. 0000-0001-9779-1168 tklett@usgs.gov","orcid":"https://orcid.org/0000-0001-9779-1168","contributorId":709,"corporation":false,"usgs":true,"family":"Klett","given":"Timothy R.","email":"tklett@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":486653,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schenk, Christopher J. 0000-0002-0248-7305 schenk@usgs.gov","orcid":"https://orcid.org/0000-0002-0248-7305","contributorId":826,"corporation":false,"usgs":true,"family":"Schenk","given":"Christopher","email":"schenk@usgs.gov","middleInitial":"J.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":486654,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wandrey, Craig J. cwandrey@usgs.gov","contributorId":1590,"corporation":false,"usgs":true,"family":"Wandrey","given":"Craig","email":"cwandrey@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":486659,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brownfield, Michael E. 0000-0003-3633-1138 mbrownfield@usgs.gov","orcid":"https://orcid.org/0000-0003-3633-1138","contributorId":1548,"corporation":false,"usgs":true,"family":"Brownfield","given":"Michael","email":"mbrownfield@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":486658,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Charpentier, Ronald R. charpentier@usgs.gov","contributorId":934,"corporation":false,"usgs":true,"family":"Charpentier","given":"Ronald R.","email":"charpentier@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":486655,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tennyson, Marilyn E. 0000-0002-5166-2421 tennyson@usgs.gov","orcid":"https://orcid.org/0000-0002-5166-2421","contributorId":1433,"corporation":false,"usgs":true,"family":"Tennyson","given":"Marilyn E.","email":"tennyson@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":486657,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gautier, Donald L. gautier@usgs.gov","contributorId":1310,"corporation":false,"usgs":true,"family":"Gautier","given":"Donald","email":"gautier@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":486656,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70098414,"text":"ofr20141047 - 2014 - A brief test of the Hewlett-Packard MEMS seismic accelerometer","interactions":[],"lastModifiedDate":"2014-04-09T09:20:30","indexId":"ofr20141047","displayToPublicDate":"2014-04-09T09:11:06","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1047","title":"A brief test of the Hewlett-Packard MEMS seismic accelerometer","docAbstract":"

Testing was performed on a prototype of Hewlett-Packard (HP) Micro-Electro-Mechanical Systems (MEMS) seismic accelerometer at the U.S. Geological Survey’s Albuquerque Seismological Laboratory. This prototype was built using discrete electronic components. The self-noise level was measured during low seismic background conditions and found to be 9.8 ng/√Hz at periods below 0.2 s (frequencies above 5 Hz). The six-second microseism noise was also discernible. The HP MEMS accelerometer was compared to a Geotech Model GS-13 reference seismometer during seismic noise and signal levels well above the self-noise of the accelerometer. Matching power spectral densities (corrected for accelerometer and seismometer responses to represent true ground motion) indicated that the HP MEMS accelerometer has a flat (constant) response to acceleration from 0.0125 Hz to at least 62.5 Hz. Tilt calibrations of the HP MEMS accelerometer verified that the flat response to acceleration extends to 0 Hz.

\n\n
\n\n

Future development of the HP MEMS accelerometer includes replacing the discreet electronic boards with a low power application-specific integrated circuit (ASIC) and increasing the dynamic range of the sensor to detect strong motion signals above one gravitational acceleration, while maintaining the self-noise observed during these tests.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141047","usgsCitation":"Homeijer, B.D., Milligan, D.J., and Hutt, C.R., 2014, A brief test of the Hewlett-Packard MEMS seismic accelerometer: U.S. Geological Survey Open-File Report 2014-1047, iv, 18 p., https://doi.org/10.3133/ofr20141047.","productDescription":"iv, 18 p.","numberOfPages":"22","onlineOnly":"Y","ipdsId":"IP-053277","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":285927,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141047.jpg"},{"id":285911,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1047/"},{"id":285926,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1047/pdf/ofr2014-1047.pdf"}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd497be4b0b290850ef38b","contributors":{"authors":[{"text":"Homeijer, Brian D.","contributorId":24685,"corporation":false,"usgs":true,"family":"Homeijer","given":"Brian","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":491696,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Milligan, Donald J.","contributorId":74674,"corporation":false,"usgs":true,"family":"Milligan","given":"Donald","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":491697,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hutt, Charles R. 0000-0001-9033-9195 bhutt@usgs.gov","orcid":"https://orcid.org/0000-0001-9033-9195","contributorId":1622,"corporation":false,"usgs":true,"family":"Hutt","given":"Charles","email":"bhutt@usgs.gov","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":491695,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70139238,"text":"70139238 - 2014 - Pacific walrus (Odobenus rosmarus divergens) resource selection in the northern Bering Sea","interactions":[],"lastModifiedDate":"2018-06-16T17:48:12","indexId":"70139238","displayToPublicDate":"2014-04-09T00:00:00","publicationYear":"2014","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":"Pacific walrus (Odobenus rosmarus divergens) resource selection in the northern Bering Sea","docAbstract":"

The Pacific walrus is a large benthivore with an annual range extending across the continental shelves of the Bering and Chukchi Seas. We used a discrete choice model to estimate site selection by adult radio-tagged walruses relative to the availability of the caloric biomass of benthic infauna and sea ice concentration in a prominent walrus wintering area in the northern Bering Sea (St. Lawrence Island polynya) in 2006, 2008, and 2009. At least 60% of the total caloric biomass of dominant macroinfauna in the study area was composed of members of the bivalve families Nuculidae, Tellinidae, and Nuculanidae. Model estimates indicated walrus site selection was related most strongly to tellinid bivalve caloric biomass distribution and that walruses selected lower ice concentrations from the mostly high ice concentrations that were available to them (quartiles: 76%, 93%, and 99%). Areas with high average predicted walrus site selection generally coincided with areas of high organic carbon input identified in other studies. Projected decreases in sea ice in the St. Lawrence Island polynya and the potential for a concomitant decline of bivalves in the region could result in a northward shift in the wintering grounds of walruses in the northern Bering Sea.

","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0093035","usgsCitation":"Jay, C.V., Grebmeier, J.M., Fischbach, A.S., McDonald, T.L., Cooper, L.W., and Hornsby, F., 2014, Pacific walrus (Odobenus rosmarus divergens) resource selection in the northern Bering Sea: PLoS ONE, v. 9, no. 4, e93035; 11 p., https://doi.org/10.1371/journal.pone.0093035.","productDescription":"e93035; 11 p.","numberOfPages":"11","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-050862","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":473061,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0093035","text":"Publisher Index Page"},{"id":297564,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Bering Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -175.9130859375,\n 61.02637030866051\n ],\n [\n -175.9130859375,\n 63.6267446447533\n ],\n [\n -169.189453125,\n 63.6267446447533\n ],\n [\n -169.189453125,\n 61.02637030866051\n ],\n [\n -175.9130859375,\n 61.02637030866051\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-04-09","publicationStatus":"PW","scienceBaseUri":"54dd2c20e4b08de9379b3648","contributors":{"authors":[{"text":"Jay, Chadwick V. 0000-0002-9559-2189 cjay@usgs.gov","orcid":"https://orcid.org/0000-0002-9559-2189","contributorId":192736,"corporation":false,"usgs":true,"family":"Jay","given":"Chadwick","email":"cjay@usgs.gov","middleInitial":"V.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":539260,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grebmeier, Jacqueline M.","contributorId":48815,"corporation":false,"usgs":false,"family":"Grebmeier","given":"Jacqueline","email":"","middleInitial":"M.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":539324,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fischbach, Anthony S. 0000-0002-6555-865X afischbach@usgs.gov","orcid":"https://orcid.org/0000-0002-6555-865X","contributorId":2865,"corporation":false,"usgs":true,"family":"Fischbach","given":"Anthony","email":"afischbach@usgs.gov","middleInitial":"S.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":539261,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McDonald, Trent L.","contributorId":92193,"corporation":false,"usgs":false,"family":"McDonald","given":"Trent","email":"","middleInitial":"L.","affiliations":[{"id":6660,"text":"Western EcoSystems Technology, Inc","active":true,"usgs":false}],"preferred":false,"id":539325,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cooper, Lee W.","contributorId":106806,"corporation":false,"usgs":false,"family":"Cooper","given":"Lee","email":"","middleInitial":"W.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":539326,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hornsby, Fawn","contributorId":138933,"corporation":false,"usgs":false,"family":"Hornsby","given":"Fawn","email":"","affiliations":[{"id":6660,"text":"Western EcoSystems Technology, Inc","active":true,"usgs":false}],"preferred":false,"id":539327,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70100985,"text":"70100985 - 2014 - Land-use threats and protected areas: a scenario-based, landscape level approach","interactions":[],"lastModifiedDate":"2014-04-09T09:13:58","indexId":"70100985","displayToPublicDate":"2014-04-08T11:22:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2596,"text":"Land","active":true,"publicationSubtype":{"id":10}},"title":"Land-use threats and protected areas: a scenario-based, landscape level approach","docAbstract":"Anthropogenic land use will likely present a greater challenge to biodiversity than climate change this century in the Pacific Northwest, USA. Even if species are equipped with the adaptive capacity to migrate in the face of a changing climate, they will likely encounter a human-dominated landscape as a major dispersal obstacle. Our goal was to identify, at the ecoregion-level, protected areas in close proximity to lands with a higher likelihood of future land-use conversion. Using a state-and-transition simulation model, we modeled spatially explicit (1 km2) land use from 2000 to 2100 under seven alternative land-use and emission scenarios for ecoregions in the Pacific Northwest. We analyzed scenario-based land-use conversion threats from logging, agriculture, and development near existing protected areas. A conversion threat index (CTI) was created to identify ecoregions with highest projected land-use conversion potential within closest proximity to existing protected areas. Our analysis indicated nearly 22% of land area in the Coast Range, over 16% of land area in the Puget Lowland, and nearly 11% of the Cascades had very high CTI values. Broader regional-scale land-use change is projected to impact nearly 40% of the Coast Range, 30% of the Puget Lowland, and 24% of the Cascades (i.e., two highest CTI classes). A landscape level, scenario-based approach to modeling future land use helps identify ecoregions with existing protected areas at greater risk from regional land-use threats and can help prioritize future conservation efforts.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Land","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"MDPI","publisherLocation":"Basel, Switzerland","doi":"10.3390/land3020362","usgsCitation":"Wilson, T.S., Sleeter, B.M., Sleeter, R., and Soulard, C.E., 2014, Land-use threats and protected areas: a scenario-based, landscape level approach: Land, v. 3, no. 2, p. 362-389, https://doi.org/10.3390/land3020362.","productDescription":"28 p.","startPage":"362","endPage":"389","numberOfPages":"28","ipdsId":"IP-052848","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":473062,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/land3020362","text":"Publisher Index Page"},{"id":285882,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3390/land3020362"},{"id":285886,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Pacific Northwest","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -132.0,34.0 ], [ -132.0,50.0 ], [ -115.0,50.0 ], [ -115.0,34.0 ], [ -132.0,34.0 ] ] ] } } ] }","volume":"3","issue":"2","noUsgsAuthors":false,"publicationDate":"2014-04-08","publicationStatus":"PW","scienceBaseUri":"53517051e4b05569d805a2fd","contributors":{"authors":[{"text":"Wilson, Tamara S.","contributorId":36640,"corporation":false,"usgs":true,"family":"Wilson","given":"Tamara","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":492487,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sleeter, Benjamin M. 0000-0003-2371-9571 bsleeter@usgs.gov","orcid":"https://orcid.org/0000-0003-2371-9571","contributorId":3479,"corporation":false,"usgs":true,"family":"Sleeter","given":"Benjamin","email":"bsleeter@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":492485,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sleeter, Rachel R.","contributorId":7946,"corporation":false,"usgs":true,"family":"Sleeter","given":"Rachel R.","affiliations":[],"preferred":false,"id":492486,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Soulard, Christopher E. 0000-0002-5777-9516 csoulard@usgs.gov","orcid":"https://orcid.org/0000-0002-5777-9516","contributorId":2642,"corporation":false,"usgs":true,"family":"Soulard","given":"Christopher","email":"csoulard@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":492484,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70099612,"text":"70099612 - 2014 - Adverse moisture events predict seasonal abundance of Lyme disease vector ticks (Ixodes scapularis)","interactions":[],"lastModifiedDate":"2017-06-14T14:37:02","indexId":"70099612","displayToPublicDate":"2014-04-08T10:04:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3010,"text":"Parasites & Vectors","printIssn":"1756-3305","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Adverse moisture events predict seasonal abundance of Lyme disease vector ticks (Ixodes scapularis)","title":"Adverse moisture events predict seasonal abundance of Lyme disease vector ticks (Ixodes scapularis)","docAbstract":"

Background: Lyme borreliosis (LB) is the most commonly reported vector-borne disease in north temperate regions worldwide, affecting an estimated 300,000 people annually in the United States alone. The incidence of LB is correlated with human exposure to its vector, the blacklegged tick (Ixodes scapularis). To date, attempts to model tick encounter risk based on environmental parameters have been equivocal. Previous studies have not considered (1) the differences between relative humidity (RH) in leaf litter and at weather stations, (2) the RH threshold that affects nymphal blacklegged tick survival, and (3) the time required below the threshold to induce mortality. We clarify the association between environmental moisture and tick survival by presenting a significant relationship between the total number of tick adverse moisture events (TAMEs - calculated as microclimatic periods below a RH threshold) and tick abundance each year.

Methods: We used a 14-year continuous statewide tick surveillance database and corresponding weather data from Rhode Island (RI), USA, to assess the effects of TAMEs on nymphal populations of I. scapularis. These TAMEs were defined as extended periods of time (>8 h below 82% RH in leaf litter). We fit a sigmoid curve comparing weather station data to those collected by loggers placed in tick habitats to estimate RH experienced by nymphal ticks, and compiled the number of historical TAMEs during the 14-year record.

Results: The total number of TAMEs in June of each year was negatively related to total seasonal nymphal tick densities, suggesting that sub-threshold humidity episodes >8 h in duration naturally lowered nymphal blacklegged tick abundance. Furthermore, TAMEs were positively related to the ratio of tick abundance early in the season when compared to late season, suggesting that lower than average tick abundance for a given year resulted from tick mortality and not from other factors.

Conclusions: Our results clarify the mechanism by which environmental moisture affects blacklegged tick populations, and offers the possibility to more accurately predict tick abundance and human LB incidence. We describe a method to forecast LB risk in endemic regions and identify the predictive role of microclimatic moisture conditions on tick encounter risk.

","language":"English","publisher":"BioMed Central","doi":"10.1186/1756-3305-7-181","usgsCitation":"Berger, K.A., Ginsberg, H.S., Dugas, K.D., Hamel, L.H., and Mather, T., 2014, Adverse moisture events predict seasonal abundance of Lyme disease vector ticks (Ixodes scapularis): Parasites & Vectors, v. 7, no. 181, 8 p., https://doi.org/10.1186/1756-3305-7-181.","productDescription":"8 p.","ipdsId":"IP-055702","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":473063,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/1756-3305-7-181","text":"Publisher Index Page"},{"id":288056,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288055,"rank":1,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1186/1756-3305-7-181"}],"country":"United States","state":"Rhode Island","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -71.8923,41.1467 ], [ -71.8923,42.0188 ], [ -71.1205,42.0188 ], [ -71.1205,41.1467 ], [ -71.8923,41.1467 ] ] ] } } ] }","volume":"7","issue":"181","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53903fe1e4b04eea98bf84df","contributors":{"authors":[{"text":"Berger, Kathryn A.","contributorId":22693,"corporation":false,"usgs":true,"family":"Berger","given":"Kathryn","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":491984,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ginsberg, Howard S. 0000-0002-4933-2466 hginsberg@usgs.gov","orcid":"https://orcid.org/0000-0002-4933-2466","contributorId":3204,"corporation":false,"usgs":true,"family":"Ginsberg","given":"Howard","email":"hginsberg@usgs.gov","middleInitial":"S.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":491983,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dugas, Katherine D.","contributorId":46878,"corporation":false,"usgs":true,"family":"Dugas","given":"Katherine","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":491986,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hamel, Lutz H.","contributorId":41747,"corporation":false,"usgs":true,"family":"Hamel","given":"Lutz","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":491985,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mather, Thomas N.","contributorId":67419,"corporation":false,"usgs":true,"family":"Mather","given":"Thomas N.","affiliations":[],"preferred":false,"id":491987,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70099600,"text":"sir20145037 - 2014 - Statistics for stochastic modeling of volume reduction, hydrograph extension, and water-quality treatment by structural stormwater runoff best management practices (BMPs)","interactions":[],"lastModifiedDate":"2014-04-07T14:30:37","indexId":"sir20145037","displayToPublicDate":"2014-04-07T14:25:00","publicationYear":"2014","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":"2014-5037","title":"Statistics for stochastic modeling of volume reduction, hydrograph extension, and water-quality treatment by structural stormwater runoff best management practices (BMPs)","docAbstract":"

The U.S. Geological Survey (USGS) developed the Stochastic Empirical Loading and Dilution Model (SELDM) in cooperation with the Federal Highway Administration (FHWA) to indicate the risk for stormwater concentrations, flows, and loads to be above user-selected water-quality goals and the potential effectiveness of mitigation measures to reduce such risks. SELDM models the potential effect of mitigation measures by using Monte Carlo methods with statistics that approximate the net effects of structural and nonstructural best management practices (BMPs). In this report, structural BMPs are defined as the components of the drainage pathway between the source of runoff and a stormwater discharge location that affect the volume, timing, or quality of runoff. SELDM uses a simple stochastic statistical model of BMP performance to develop planning-level estimates of runoff-event characteristics. This statistical approach can be used to represent a single BMP or an assemblage of BMPs. The SELDM BMP-treatment module has provisions for stochastic modeling of three stormwater treatments: volume reduction, hydrograph extension, and water-quality treatment. In SELDM, these three treatment variables are modeled by using the trapezoidal distribution and the rank correlation with the associated highway-runoff variables. This report describes methods for calculating the trapezoidal-distribution statistics and rank correlation coefficients for stochastic modeling of volume reduction, hydrograph extension, and water-quality treatment by structural stormwater BMPs and provides the calculated values for these variables. This report also provides robust methods for estimating the minimum irreducible concentration (MIC), which is the lowest expected effluent concentration from a particular BMP site or a class of BMPs. These statistics are different from the statistics commonly used to characterize or compare BMPs. They are designed to provide a stochastic transfer function to approximate the quantity, duration, and quality of BMP effluent given the associated inflow values for a population of storm events. A database application and several spreadsheet tools are included in the digital media accompanying this report for further documentation of methods and for future use.

\n
\n

In this study, analyses were done with data extracted from a modified copy of the January 2012 version of International Stormwater Best Management Practices Database, designated herein as the January 2012a version. Statistics for volume reduction, hydrograph extension, and water-quality treatment were developed with selected data. Sufficient data were available to estimate statistics for 5 to 10 BMP categories by using data from 40 to more than 165 monitoring sites. Water-quality treatment statistics were developed for 13 runoff-quality constituents commonly measured in highway and urban runoff studies including turbidity, sediment and solids; nutrients; total metals; organic carbon; and fecal coliforms. The medians of the best-fit statistics for each category were selected to construct generalized cumulative distribution functions for the three treatment variables. For volume reduction and hydrograph extension, interpretation of available data indicates that selection of a Spearman’s rho value that is the average of the median and maximum values for the BMP category may help generate realistic simulation results in SELDM. The median rho value may be selected to help generate realistic simulation results for water-quality treatment variables.

\n
\n

MIC statistics were developed for 12 runoff-quality constituents commonly measured in highway and urban runoff studies by using data from 11 BMP categories and more than 167 monitoring sites. Four statistical techniques were applied for estimating MIC values with monitoring data from each site. These techniques produce a range of lower-bound estimates for each site. Four MIC estimators are proposed as alternatives for selecting a value from among the estimates from multiple sites. Correlation analysis indicates that the MIC estimates from multiple sites were weakly correlated with the geometric mean of inflow values, which indicates that there may be a qualitative or semiquantitative link between the inflow quality and the MIC. Correlations probably are weak because the MIC is influenced by the inflow water quality and the capability of each individual BMP site to reduce inflow concentrations.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145037","issn":"2328-0328","collaboration":"Prepared in cooperation with the U.S. Department of Transportation Federal Highway Administration Office of Project Development and Environmental Review","usgsCitation":"Granato, G., 2014, Statistics for stochastic modeling of volume reduction, hydrograph extension, and water-quality treatment by structural stormwater runoff best management practices (BMPs): U.S. Geological Survey Scientific Investigations Report 2014-5037, Report: vii, 37 p.; Digital media, https://doi.org/10.3133/sir20145037.","productDescription":"Report: vii, 37 p.; Digital media","numberOfPages":"50","onlineOnly":"Y","ipdsId":"IP-053232","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":285854,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145037.jpg"},{"id":285853,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5037/sir2014-5037.zip"},{"id":285851,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5037/pdf/sir2014-5037.pdf"},{"id":284444,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5037/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517065e4b05569d805a3cf","contributors":{"authors":[{"text":"Granato, Gregory E. 0000-0002-2561-9913 ggranato@usgs.gov","orcid":"https://orcid.org/0000-0002-2561-9913","contributorId":1692,"corporation":false,"usgs":true,"family":"Granato","given":"Gregory E.","email":"ggranato@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":false,"id":491974,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70100897,"text":"70100897 - 2014 - Serologic evidence of influenza A(H1N1)pdm09 virus in northern sea otters","interactions":[],"lastModifiedDate":"2018-03-23T14:17:35","indexId":"70100897","displayToPublicDate":"2014-04-07T14:13:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1493,"text":"Emerging Infectious Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Serologic evidence of influenza A(H1N1)pdm09 virus in northern sea otters","docAbstract":"

Sporadic epizootics of pneumonia among marine mammals have been associated with multiple animal-origin influenza A virus subtypes (1–6); seals are the only known nonhuman host for influenza B viruses (7). Recently, we reported serologic evidence of influenza A virus infection in free-ranging northern sea otters (Enhydra lutris kenyoni) captured off the coast of Washington, USA, in August 2011 (8). To investigate further which influenza A virus subtype infected these otters, we tested serum samples from these otters by ELISA for antibody-binding activity against 12 recombinant hemagglutinins (rHAs) from 7 influenza A hemagglutinin (HA) subtypes and 2 lineages of influenza B virus (Technical Appendix Table 1). Estimated ages for the otters were 2–19 years (Technical Appendix Table 2); we also tested archived serum samples from sea otters of similar ages collected from a study conducted during 2001–2002 along the Washington coast (9).

","language":"English","publisher":"Centers for Disease Control and Prevention","doi":"10.3201/eid2005.131890","usgsCitation":"Li, Z., Ip, S., Frost, J.F., White, C.L., Murray, M., Carney, P.J., Sun, X., Stevens, J., Levine, M.Z., and Katz, J.M., 2014, Serologic evidence of influenza A(H1N1)pdm09 virus in northern sea otters: Emerging Infectious Diseases, v. 20, no. 5, https://doi.org/10.3201/eid2005.131890.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053184","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":473064,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3201/eid2005.131890","text":"Publisher Index Page"},{"id":285845,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":285844,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3201/eid2005.131890"}],"country":"United 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This is a report about the geologic characteristics of five storage assessment units (SAUs) within the Denver Basin of Colorado, Wyoming, and Nebraska. These SAUs are Cretaceous in age and include (1) the Plainview and Lytle Formations, (2) the Muddy Sandstone, (3) the Greenhorn Limestone, (4) the Niobrara Formation and Codell Sandstone, and (5) the Terry and Hygiene Sandstone Members. The described characteristics, as specified in the methodology, affect the potential carbon dioxide storage resource in the SAUs. The specific geologic and petrophysical properties of interest include depth to the top of the storage formation, average thickness, net-porous thickness, porosity, permeability, groundwater quality, and the area of structural reservoir traps. Descriptions of the SAU boundaries and the overlying sealing units are also included. Assessment results are not contained in this report; however, the geologic information included here will be used to calculate a statistical Monte Carlo-based distribution of potential storage volume in the SAUs.

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In addition, ΣPCBs were determined both in the somatic tissue and in the gonads for a randomly selected subset of five females and five males. Mean ΣPCBs for females and males were 2.89 and 3.76 ng/g, respectively. Thus, males were 30 % greater in ΣPCB than females. Based on ΣPCB determinations for somatic tissue and gonads, ΣPCBs of females and males would be expected to decrease by 18 % and increase by 6 %, respectively, immediately after spawning due to release of gametes. Results from a previous study in eastern Lake Erie indicated that males were 28 and 71 % greater in ΣPCB than females from populations of younger (ages 6-13) and older (ages 14-17) burbot, respectively. Thus, although younger burbot from Lake Erie were about 50 times greater in ΣPCB than Great Slave Lake burbot, the relative difference in ΣPCBs between the sexes was remarkably similar across both populations. Our results supported the contention that the widening of the difference in ΣPCBs between the sexes in older burbot from Lake Erie was attributable to a “hot spot” effect operating on older burbot, as Lake Erie has received PCB point source loadings. Our results also supported the contention that male fish expend energy at a rate between 15 and 30 % greater than that of females. Eventually, these results will be useful in developing sex-specific bioenergetics models for fish.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Archives of Environmental Contamination and Toxicology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s00244-014-0015-9","usgsCitation":"Madenjian, C.P., Stapanian, M.A., Cott, P.A., Rediske, R.R., and O'Keefe, J., 2014, Polychlorinated biphenyl concentrations of burbot Lota lota from Great Slave Lake are very low but vary by sex: Archives of Environmental Contamination and Toxicology, v. 66, no. 4, p. 529-537, https://doi.org/10.1007/s00244-014-0015-9.","productDescription":"9 p.","startPage":"529","endPage":"537","ipdsId":"IP-052858","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":285779,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":285775,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s00244-014-0015-9"}],"country":"Canada","otherGeospatial":"Great Slave Lake;Northwest Territories","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -116.8045,60.828 ], [ -116.8045,62.9586 ], [ -108.8961,62.9586 ], [ -108.8961,60.828 ], [ -116.8045,60.828 ] ] ] } } ] }","volume":"66","issue":"4","noUsgsAuthors":false,"publicationDate":"2014-03-15","publicationStatus":"PW","scienceBaseUri":"5351705ae4b05569d805a364","contributors":{"authors":[{"text":"Madenjian, Charles P. 0000-0002-0326-164X cmadenjian@usgs.gov","orcid":"https://orcid.org/0000-0002-0326-164X","contributorId":2200,"corporation":false,"usgs":true,"family":"Madenjian","given":"Charles","email":"cmadenjian@usgs.gov","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":492442,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stapanian, Martin A. 0000-0001-8173-4273 mstapanian@usgs.gov","orcid":"https://orcid.org/0000-0001-8173-4273","contributorId":3425,"corporation":false,"usgs":true,"family":"Stapanian","given":"Martin","email":"mstapanian@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":492443,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cott, Peter A.","contributorId":64160,"corporation":false,"usgs":true,"family":"Cott","given":"Peter","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":492444,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rediske, Richard R.","contributorId":79053,"corporation":false,"usgs":true,"family":"Rediske","given":"Richard","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":492445,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"O'Keefe, James P.","contributorId":99499,"corporation":false,"usgs":true,"family":"O'Keefe","given":"James P.","affiliations":[],"preferred":false,"id":492446,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70101024,"text":"70101024 - 2014 - Blood lead concentrations in Alaskan tundra swans: linking breeding and wintering areas with satellite telemetry","interactions":[],"lastModifiedDate":"2018-09-14T15:53:03","indexId":"70101024","displayToPublicDate":"2014-04-07T10:55:47","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1479,"text":"Ecotoxicology","active":true,"publicationSubtype":{"id":10}},"title":"Blood lead concentrations in Alaskan tundra swans: linking breeding and wintering areas with satellite telemetry","docAbstract":"Tundra swans (Cygnus columbianus) like many waterfowl species are susceptible to lead (Pb) poisoning, and Pb-induced mortality has been reported from many areas of their wintering range. Little is known however about Pb levels throughout the annual cycle of tundra swans, especially during summer when birds are on remote northern breeding areas where they are less likely to be exposed to anthropogenic sources of Pb. Our objective was to document summer Pb levels in tundra swans throughout their breeding range in Alaska to determine if there were population-specific differences in blood Pb concentrations that might pose a threat to swans and to humans that may consume them. We measured blood Pb concentrations in tundra swans at five locations in Alaska, representing birds that winter in both the Pacific Flyway and Atlantic Flyway. We also marked swans at each location with satellite transmitters and coded neck bands, to identify staging and wintering sites and determine if winter site use correlated with summer Pb concentrations. Blood Pb levels were generally low ( < 0.2 μg/ml) in swans across all breeding areas. Pb levels were lower in cygnets than adults, suggesting that swans were likely exposed to Pb on wintering areas or on return migration to Alaska, rather than on the summer breeding grounds. Blood Pb levels varied significantly across the five breeding areas, with highest concentrations in birds on the North Slope of Alaska (wintering in the Atlantic Flyway), and lowest in birds from the lower Alaska Peninsula that rarely migrate south for winter.","language":"English","publisher":"Springer","doi":"10.1007/s10646-014-1192-z","usgsCitation":"Ely, C.R., and Franson, C., 2014, Blood lead concentrations in Alaskan tundra swans: linking breeding and wintering areas with satellite telemetry: Ecotoxicology, v. 23, no. 3, p. 349-356, https://doi.org/10.1007/s10646-014-1192-z.","productDescription":"8 p.","startPage":"349","endPage":"356","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053240","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":285950,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":285949,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10646-014-1192-z"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -141.240234375,\n 69.7181066990676\n ],\n [\n -156.09375,\n 71.41317683396566\n ],\n [\n -166.55273437499997,\n 68.75231494434473\n ],\n [\n -168.57421875,\n 65.47650756256367\n ],\n [\n -165.41015625,\n 59.62332522313024\n ],\n [\n -159.345703125,\n 57.562995459387146\n ],\n [\n -167.16796875,\n 54.36775852406841\n ],\n [\n -177.890625,\n 52.482780222078205\n ],\n [\n -187.3828125,\n 53.54030739150022\n ],\n [\n -187.998046875,\n 52.429222277955134\n ],\n [\n -177.275390625,\n 51.01375465718821\n ],\n [\n -166.904296875,\n 52.802761415419674\n ],\n [\n -161.279296875,\n 54.77534585936447\n ],\n [\n -151.611328125,\n 56.84897198026975\n ],\n [\n -150.99609375,\n 58.768200159239576\n ],\n [\n -146.42578125,\n 59.84481485969105\n ],\n [\n -140.9765625,\n 59.57885104663186\n ],\n [\n -141.240234375,\n 69.7181066990676\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"23","issue":"3","noUsgsAuthors":false,"publicationDate":"2014-01-28","publicationStatus":"PW","scienceBaseUri":"53517029e4b05569d805a17b","contributors":{"authors":[{"text":"Ely, Craig R. 0000-0003-4262-0892 cely@usgs.gov","orcid":"https://orcid.org/0000-0003-4262-0892","contributorId":3214,"corporation":false,"usgs":true,"family":"Ely","given":"Craig","email":"cely@usgs.gov","middleInitial":"R.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":492546,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Franson, Christian 0000-0002-0251-4238","orcid":"https://orcid.org/0000-0002-0251-4238","contributorId":58941,"corporation":false,"usgs":true,"family":"Franson","given":"Christian","affiliations":[],"preferred":false,"id":492547,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}