We present numeric grids containing estimates of the thickness of unconsolidated sediments and depth to the pre-Cenozoic
basement for the western United States. Values for these grids were combined and integrated from previous studies or derived
directly from gravity analyses. The grids are provided with 1-kilometer grid-node spacing in ScienceBase (https://www.sciencebase.gov).
These layers may be updated as results from new studies become available.
Director, Geology, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
Box 25046, MS 973
Denver, CO 80225
Little is known about populations of Stonecat Noturus flavus, especially in the northeastern United States, where they are at the edge of their range. In Lake Champlain tributaries, Stonecats are listed as endangered in Vermont but not in New York. Here we describe the growth of Stonecats in two tributaries to Lake Champlain, one in Vermont (LaPlatte River), which was our primary interest, and one in New York (Great Chazy River), with von Bertalanffy growth models fit to lengths at the times of marking and recapture and to observed length and age data. We also compared growth of Stonecats in these waters to results from other locations near the middle of their distribution. Stonecats in the Great Chazy River were larger at ages 1–3, but similar in size for ages 4 and 5, than Stonecats from the LaPlatte River. Stonecats in Lake Champlain tributaries were generally larger at age than those from the middle of their range, except for those from Lake Erie. From our mean length‐at‐age results and previous literature estimates of length at maturity for Stonecats, it appears that Stonecats in Lake Champlain reach maturity by age 3, though future research that directly estimates age at maturity would be more informative. These results will help managers assess the effect of various environmental and human stressors that Stonecats have experienced in the Lake Champlain basin in recent years. Furthermore, our results expand the literature, which lacks information about growth of this species. Finally, our mark–recapture approach to estimating growth of Stonecats can be applied to other species, especially where data are limited because of their status, and in other systems.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10230","usgsCitation":"Puchala, E., Parrish, D.L., and Ogle, D.H., 2018, Size and age of Stonecats in Lake Champlain; Estimating growth at the margin of their range to aid in population management: North American Journal of Fisheries Management, v. 38, no. 6, p. 1316-1323, https://doi.org/10.1002/nafm.10230.","productDescription":"8 p.","startPage":"1316","endPage":"1323","ipdsId":"IP-097102","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":380303,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York, Vermont","otherGeospatial":"Great Chazy River, La Platte River, Lake Champlain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n 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Vermont","active":true,"usgs":false}],"preferred":false,"id":804383,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parrish, Donna L. 0000-0001-9693-6329 dparrish@usgs.gov","orcid":"https://orcid.org/0000-0001-9693-6329","contributorId":138661,"corporation":false,"usgs":true,"family":"Parrish","given":"Donna","email":"dparrish@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":804382,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ogle, Derek H.","contributorId":73967,"corporation":false,"usgs":true,"family":"Ogle","given":"Derek","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":804388,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70227781,"text":"70227781 - 2018 - Integrating physiological stress into the movement ecology of migratory ungulates: A spatial analysis with mule deer","interactions":[],"lastModifiedDate":"2022-01-31T16:45:58.555732","indexId":"70227781","displayToPublicDate":"2018-09-28T10:30:35","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3919,"text":"Conservation Physiology","onlineIssn":"2051-1434","active":true,"publicationSubtype":{"id":10}},"title":"Integrating physiological stress into the movement ecology of migratory ungulates: A spatial analysis with mule deer","docAbstract":"Rapid climate and human land-use change may limit the ability of long-distance migratory herbivores to optimally track or “surf” high-quality forage during spring green-up. Understanding how anthropogenic and environmental stressors influence migratory movements is of critical importance because of their potential to cause a mismatch between the timing of animal movements and the emergence of high-quality forage. We measured stress hormones (fecal glucocorticoid metabolites; FGMs) to test hypotheses about the effects of high-quality forage tracking, human land use, and use of stopover sites on the physiological state of individuals along a migratory route. We collected and analyzed FGM concentrations from 399 mule deer (Odocoileus hemionus) samples obtained along a 241 km migratory route in western Wyoming, USA, during spring 2015 and 2016. In support of a fitness benefit hypothesis, individuals occupying areas closer to peak forage quality had decreased FGM levels. Specifically, for every 10-day interval closer to peak forage quality, we observed a 7% decrease in FGMs. Additionally, we observed support for both an additive anthropogenic stress hypothesis and a hypothesis that stopovers act as physiological refugia, wherein individuals sampled far from stopover sites exhibited 341% higher FGM levels if in areas of low landscape integrity compared to areas of high landscape integrity. Overall, our findings indicate that the physiological state of mule deer during migration is influenced by both anthropogenic disturbances and their ability to track high-quality forage. The availability of stopovers, however, modulates physiological responses to those stressors. Thus, our results support a recent call for the prioritization of stopover locations and connectivity between those locations in conservation planning for migratory large herbivores.","language":"English","publisher":"Oxford University Press","doi":"10.1093/conphys/coy054","usgsCitation":"Jachowski, D., Kauffman, M., Jesmer, B.R., Sawyer, H., and Millspaugh, J., 2018, Integrating physiological stress into the movement ecology of migratory ungulates: A spatial analysis with mule deer: Conservation Physiology, v. 6, no. 1, p. 1-12, https://doi.org/10.1093/conphys/coy054.","productDescription":"coy054, 12 p.","startPage":"1","endPage":"12","ipdsId":"IP-092704","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":468360,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/conphys/coy054","text":"Publisher Index Page"},{"id":395156,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Wyoming","otherGeospatial":"Big Sandy River, Finger Lakes, Fremont Lake, Green River Valley, Hoback Basin, Red Desert, Wind River Mountain Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.05303955078125,\n 41.66470503009207\n ],\n [\n -108.71520996093749,\n 41.693424216151314\n ],\n [\n -108.97338867187499,\n 42.52069952914966\n ],\n [\n -109.57489013671875,\n 42.85583308674893\n ],\n [\n -109.68475341796875,\n 42.93430692117159\n ],\n [\n -109.786376953125,\n 43.014689161895184\n ],\n [\n -109.88800048828125,\n 43.10298826174054\n ],\n [\n -109.84405517578125,\n 43.48680489735277\n ],\n [\n -110.830078125,\n 43.369119087738554\n ],\n [\n -110.78338623046875,\n 43.08694333811321\n ],\n [\n -110.093994140625,\n 42.97250158602597\n ],\n [\n -110.05279541015625,\n 42.81555136172695\n ],\n [\n -109.7039794921875,\n 42.75104599038353\n ],\n [\n -109.23431396484375,\n 42.18986405028881\n ],\n [\n -109.20135498046875,\n 41.68316883525891\n ],\n [\n -109.05303955078125,\n 41.66470503009207\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","issue":"1","noUsgsAuthors":false,"publicationDate":"2018-09-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Jachowski, David S.","contributorId":228814,"corporation":false,"usgs":false,"family":"Jachowski","given":"David S.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":832213,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":202921,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":832214,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jesmer, Brett R.","contributorId":200192,"corporation":false,"usgs":false,"family":"Jesmer","given":"Brett","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":832215,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sawyer, Hall","contributorId":39930,"corporation":false,"usgs":false,"family":"Sawyer","given":"Hall","affiliations":[],"preferred":false,"id":832216,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Millspaugh, Joshua J.","contributorId":11141,"corporation":false,"usgs":false,"family":"Millspaugh","given":"Joshua J.","affiliations":[],"preferred":false,"id":832217,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70210081,"text":"70210081 - 2018 - The San Andreas Fault System--Complexities along a major transform fault system and relation to earthquake hazards","interactions":[],"lastModifiedDate":"2020-05-13T14:33:48.440524","indexId":"70210081","displayToPublicDate":"2018-09-28T09:30:00","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"10","title":"The San Andreas Fault System--Complexities along a major transform fault system and relation to earthquake hazards","docAbstract":"The San Andreas Fault System is a 1300-km-long transform boundary that accommodates motion between the North American and Pacific Plates. New technologies and data reveal rich details about the present configuration of faults, distribution of strain and associated seismic hazard on this complex network of faults. This contribution provides a brief summary of the geologic history of the San Andreas Fault System, followed by an introduction to recent research that has changed understanding of the hazards along the main faults. Organized by region, we highlight a selection of recent research using new geodetic techniques, improved topographic data, advanced geochronologic methods, and high-resolution geophysics. The contribution ends with a review of the historic earthquakes on the San Andreas and San Jacinto Faults, comparing these to past ruptures interpreted from paleoseismic studies.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Transform plate boundaries and fracture zones","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-812064-4.00010-4","usgsCitation":"Scharer, K., and Streig, A., 2018, The San Andreas Fault System--Complexities along a major transform fault system and relation to earthquake hazards, chap. 10 of Transform plate boundaries and fracture zones, p. 249-269, https://doi.org/10.1016/B978-0-12-812064-4.00010-4.","productDescription":"21 p.","startPage":"249","endPage":"269","ipdsId":"IP-093013","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":374754,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Andreas Fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.14672851562499,\n 34.34343606848294\n ],\n [\n -115.9442138671875,\n 34.34343606848294\n ],\n [\n -115.9442138671875,\n 35.43381992014202\n ],\n [\n -119.14672851562499,\n 35.43381992014202\n ],\n [\n -119.14672851562499,\n 34.34343606848294\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Scharer, Katherine M. 0000-0003-2811-2496","orcid":"https://orcid.org/0000-0003-2811-2496","contributorId":217361,"corporation":false,"usgs":true,"family":"Scharer","given":"Katherine M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":789032,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Streig, Ashley","contributorId":189716,"corporation":false,"usgs":false,"family":"Streig","given":"Ashley","affiliations":[],"preferred":false,"id":789033,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70198296,"text":"sir20185102 - 2018 - Groundwater contributions to excessive algal growth in the East Fork Carson River, Carson Valley, west-central Nevada, 2010 and 2012","interactions":[],"lastModifiedDate":"2018-09-28T16:55:22","indexId":"sir20185102","displayToPublicDate":"2018-09-28T09:17:05","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5102","title":"Groundwater contributions to excessive algal growth in the East Fork Carson River, Carson Valley, west-central Nevada, 2010 and 2012","docAbstract":"Excessive algal growth and low dissolved oxygen concentrations were observed during low streamflow conditions during summer months along a 5,800-foot reach of the East Fork Carson River in Carson Valley, west-central Nevada. Algal growth from nutrient enrichment of a stream reduces aquatic diversity, threatens fish ecology and stream health, and can be a recreational nuisance. In response to concerns that groundwater discharging to the 5,800-foot reach of the East Fork Carson River may be a source of nutrients to the stream, the U.S. Geological Survey, in cooperation with the Carson Water Subconservancy District and the Nevada Division of Environmental Protection, conducted studies during the summers of 2010 and 2012 to gain an improved understanding of the contributions of nutrients to the stream from groundwater, characterize algal conditions and algal effects on water quality, assess potential sources of nitrate in groundwater discharging to the stream, and evaluate nitrate reduction in groundwater from denitrification.
A reconnaissance study in the summer of 2010 along the 5,800-foot study reach located a subreach with clear evidence of nutrient-rich groundwater discharging to the stream. At the subreach, nitrate plus nitrite (referred to hereafter as nitrate) concentrations in groundwater discharging to the stream were high (average 2.75 milligrams per liter as nitrogen) along the right bank. The stream at this location had the highest stream nitrate concentrations (average 0.056 milligrams per liter as nitrogen) compared to other locations upstream and downstream of the subreach. As a result, the 2012 study focused on a 405-foot subreach of the East Fork Carson River centered where results from the 2010 study found the highest stream and groundwater concentrations of nitrate, as well as the greatest observed contributions of groundwater discharge to the stream.
Groundwater nutrient concentrations were much higher than stream nutrient concentrations during the summer of 2012 during low streamflow conditions at the 405-foot subreach of the East Fork Carson River. Average groundwater nitrate and orthophosphate concentrations along the right bank of the 405‑foot subreach were 9 and 12 times higher, respectively, than in the stream at this subreach. Groundwater discharge rates to the study reach based on different methods varied from 0.09 to 1.2 cubic feet per second per mile. Estimated groundwater discharge rates to the right bank of the study subreach were used to calculate groundwater nutrient load estimates to the subreach right bank, which were found to be low when compared to stream nutrient loads.
Elevated algal biomass levels above nuisance thresholds were observed during the summers of 2010 and 2012. The study reach was characterized as mesotrophic-eutrophic during the 2010 study and eutrophic during the 2012 study. The presence of algae caused daily dissolved oxygen and pH fluctuations in the stream, resulting in exceedances of the State of Nevada water-quality standards owing to low dissolved oxygen concentrations and high pH concentrations, although the standards might not have been applicable during 2012 because of extremely low streamflow.
The addition of nutrients to the stream from the constant supply in groundwater discharge sustains the growth of algae during low streamflow conditions. In the summer when streamflow is low or very low, nutrient-rich groundwater discharge enters the stream through the sediment-water interface at the streambed. Because the attached algae is thick and stream velocity is low, the nutrient-rich water pools at the sediment-water interface. Higher nutrient concentrations at the streambed create a favorable microenvironment for algae attached to the substrate to consume available nutrients from the groundwater before the groundwater mixes with overlying stream water.
The source of nitrate in groundwater in this subreach is anthropogenic because nitrate concentrations are greater than background groundwater nitrate concentrations in Douglas County, high groundwater nitrate concentrations are only found at the right bank of the stream near a housing development, and organic wastewater compounds indicative of human-derived sources were also detected in groundwater wells on the right bank of the stream. Nitrogen and oxygen isotope concentrations of nitrate in shallow groundwater were used to determine the specific source of the nitrate, but the isotopic values indicated denitrification was occurring. Further investigation is needed to determine the specific anthropogenic source of the nitrate in the groundwater because the denitrification present in all samples obscures the original source of nitrogen.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185102","collaboration":"Prepared in cooperation with the Carson Water Subconservancy District and Nevada Division of Environmental Protection","usgsCitation":"Alvarez, N.L., Pahl, R.A, and Rosen, M.R., 2018, Groundwater contributions to excessive algal growth in the East Fork Carson River, Carson Valley, west-central Nevada, 2010 and 2012: U.S. Geological Survey Scientific Investigations Report 2018–5102, 94 p., https://doi.org/10.3133/sir20185102.","productDescription":"Report: xii, 94 p.; Data release","numberOfPages":"110","onlineOnly":"Y","ipdsId":"IP-045681","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":357719,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5102/coverthb.jpg"},{"id":357720,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5102/sir20185102.pdf","text":"Report","size":"5.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5102"},{"id":357725,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7C53K4Q","linkHelpText":"Supplemental data for groundwater contributions to excessive algal growth in the East Fork Carson River, Carson Valley, west-central Nevada, 2010 and 2012"}],"country":"United States","state":"Nevada","otherGeospatial":"East Fork Carson River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.7989,\n 38.94\n ],\n [\n -119.7714,\n 38.94\n ],\n [\n -119.7714,\n 38.97\n ],\n [\n -119.7989,\n 38.97\n ],\n [\n -119.7989,\n 38.94\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Rd.
Carson City, NV 89701
Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean resources of 1.1 billion barrels of oil and 793 billion cubic feet of gas in the Putumayo-Oriente-Marañón Basin Province of Colombia, Ecuador, and Perú.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183048","usgsCitation":"Schenk, C.J., Mercier, T.J., Pitman, J.K., Finn, T.M., Le, P.A., Gaswirth, S.B., Marra, K.R., and Leathers-Miller, H.M., 2018, Assessment of continuous oil and gas resources of the Putumayo- Oriente-Marañón Basin Province of Colombia, Ecuador, and Perú, 2018: U.S. Geological Survey Fact Sheet 2018–3048, 4 p., https://doi.org/10.3133/fs20183048.","productDescription":"4 p.","onlineOnly":"N","ipdsId":"IP-097191","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":357629,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3048/coverthb.jpg"},{"id":357630,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3048/fs20183048.pdf","text":"Report","size":"11.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018-3048"}],"country":"Colombia, Ecuador, Perú","otherGeospatial":"Putumayo-Oriente-Marañón Basin Province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.5,\n -7\n ],\n [\n -75,\n -7\n ],\n [\n -75,\n 2\n ],\n [\n -78.5,\n 2\n ],\n [\n -78.5,\n -7\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
Human impact, particularly land cover changes (e.g., agriculture, construction) increase erosion and sediment loading into streams. Benthic species are negatively affected by silt deposition that coats and embeds stream substrate. Given that riparian buffers are effective sediment filters, riparian restoration is increasingly implemented by conservation groups to protect stream habitats. Limited funding and a multitude of impaired streams warrant the need for cost-effective prioritization of potential restoration actions. We created a decision-support framework for conservation agencies and aquatic resource managers to prioritize riparian restoration efforts. Our framework integrates GIS data and field surveys into a statistical model to predict instream silt from estimates of upland soil loss and riparian filtration capacity. We focus specifically on prioritizing sites in upper sections of the Roanoke and Nottoway river basins (Virginia, US) based on observed records of Roanoke logperch (Percina rex), an imperiled sediment-sensitive species. Our statistical approach examines soil characteristics, land cover, precipitation, topography, and annual soil loss estimates from the empirically derived Revised Universal Soil Loss Equation, combined with land cover-based riparian filtration capacity as potential stream habitat predictors. We found riparian filtration capacity to be a significant predictor of silt cover, while precipitation was a significant predictor of embeddedness. Spatial scale was also a factor, in that spatial variance in silt cover and embeddedness was more accurately predicted at smaller spatial extents. Ultimately, our model can be used as a prioritization tool for mitigating high siltation areas, or for protecting low soil erosion areas.
","language":"English","publisher":"Springer","doi":"10.1007/s00267-018-1078-6","usgsCitation":"Scott, L.N., Villamagna, A.M., and Angermeier, P., 2018, A new modeling approach to prioritize riparian restoration to reduce sediment loading in two Virginia river basins: Environmental Management, v. 62, no. 4, p. 721-739, https://doi.org/10.1007/s00267-018-1078-6.","productDescription":"19 p.","startPage":"721","endPage":"739","ipdsId":"IP-090172","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468362,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10919/99269","text":"External Repository"},{"id":357850,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina, Virginia","volume":"62","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-16","publicationStatus":"PW","scienceBaseUri":"5bc02f87e4b0fc368eb5388b","contributors":{"authors":[{"text":"Scott, Lisa N.","contributorId":208250,"corporation":false,"usgs":false,"family":"Scott","given":"Lisa","email":"","middleInitial":"N.","affiliations":[{"id":35056,"text":"Plymouth State University","active":true,"usgs":false}],"preferred":false,"id":746534,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Villamagna, Amy M.","contributorId":201421,"corporation":false,"usgs":false,"family":"Villamagna","given":"Amy","email":"","middleInitial":"M.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":746535,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Angermeier, Paul L. 0000-0003-2864-170X","orcid":"https://orcid.org/0000-0003-2864-170X","contributorId":204519,"corporation":false,"usgs":true,"family":"Angermeier","given":"Paul L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":746533,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70199768,"text":"70199768 - 2018 - Diel fledging patterns among grassland passerines: Relative impacts of energetics and predation risk","interactions":[],"lastModifiedDate":"2018-09-27T14:23:05","indexId":"70199768","displayToPublicDate":"2018-09-27T14:22:54","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3544,"text":"The Auk","onlineIssn":"1938-4254","printIssn":"0004-8038","active":true,"publicationSubtype":{"id":10}},"title":"Diel fledging patterns among grassland passerines: Relative impacts of energetics and predation risk","docAbstract":"The time of day that nestlings fledge from a nest is thought to be shaped by predation risk and energetics. To minimize predation risk, fledging is predicted to start as early in the day as possible so that nestlings can maximize time outside the nest to find a safe place to stay before nightfall. Fledging times are predicted to be tightly grouped and to not be affected by the number of nestlings, given that all nestlings are responding to the same relative risk of predation. Conversely, energetic considerations predict that fledging time of day should vary so that nestlings can maximize energy intake before having to forage for themselves. However, data to evaluate the relative importance of these drivers in grassland birds are scarce because of the difficulty of observing nestlings as they fledge. We used nest surveillance video from 178 nests to evaluate how the initiation and duration of fledging varied among 7 grassland passerine species, as well as by the number of nestlings in the nest and fledging date. Fledging initiation varied most strongly by species, with some effects of date. Across species, the median start time of fledging was 4.55 hr after sunrise. Fledging before the solstice started ∼30 min earlier compared to fledging at or after the solstice. Fledging duration increased with number of nestlings in the nest and was spread over >1 day in 21% of nests. While our results primarily supported the hypothesis that fledging is motivated by energetic considerations, additional data on basic life history traits and behavior will be needed to fully understand how fledging grassland birds balance energetics against predation risk.
","language":"English","publisher":"American Ornithological Society","doi":"10.1642/AUK-17-213.1","usgsCitation":"Ribic, C., Ng, C., Koper, N., Ellison, K., Pietz, P., and Rugg, D.J., 2018, Diel fledging patterns among grassland passerines: Relative impacts of energetics and predation risk: The Auk, v. 135, no. 4, p. 1100-1112, https://doi.org/10.1642/AUK-17-213.1.","productDescription":"13 p.","startPage":"1100","endPage":"1112","ipdsId":"IP-090183","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468363,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.bioone.org/doi/10.1642/AUK-17-213.1","text":"External Repository"},{"id":357849,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"135","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02f87e4b0fc368eb5388d","contributors":{"authors":[{"text":"Ribic, Christine 0000-0003-2583-1778 caribic@usgs.gov","orcid":"https://orcid.org/0000-0003-2583-1778","contributorId":147952,"corporation":false,"usgs":true,"family":"Ribic","given":"Christine","email":"caribic@usgs.gov","affiliations":[{"id":5068,"text":"Midwest Regional Director's Office","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":746536,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ng, Christoph","contributorId":208253,"corporation":false,"usgs":false,"family":"Ng","given":"Christoph","affiliations":[{"id":16603,"text":"University of Manitoba","active":true,"usgs":false}],"preferred":false,"id":746538,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koper, Nicola","contributorId":208255,"corporation":false,"usgs":false,"family":"Koper","given":"Nicola","email":"","affiliations":[],"preferred":false,"id":746541,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ellison, Kevin","contributorId":208254,"corporation":false,"usgs":false,"family":"Ellison","given":"Kevin","affiliations":[{"id":37767,"text":"World Wildlife Fund","active":true,"usgs":false}],"preferred":false,"id":746539,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pietz, Pamela J. ppietz@usgs.gov","contributorId":2382,"corporation":false,"usgs":true,"family":"Pietz","given":"Pamela J.","email":"ppietz@usgs.gov","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":746537,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rugg, David J.","contributorId":171931,"corporation":false,"usgs":false,"family":"Rugg","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":746540,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70199765,"text":"70199765 - 2018 - Sensor suite: The Albuquerque Seismological Laboratory Instrumentation Testing Suite","interactions":[],"lastModifiedDate":"2018-11-14T09:11:54","indexId":"70199765","displayToPublicDate":"2018-09-27T14:20:11","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Sensor suite: The Albuquerque Seismological Laboratory Instrumentation Testing Suite","docAbstract":"To standardize parameters used in seismometer testing and calibration and to make these algorithms accessible to the seismological community, we have developed a new seismometer testing software package called Albuquerque Seismological Laboratory (ASL) Sensor Test Suite. This software is written in Java and makes use of Seismological Exchange for Earthquake Data (SEED) format. Our goal is not to be all‐inclusive but instead to focus on a few of the instrumentation tests we view as critical when verifying a sensor’s performance. The tests include self‐noise, relative azimuth, relative gain, and estimation of the poles and zeros. For the self‐noise and the relative azimuth, we also include three‐component versions of these tests to allow for the case of sensors with potentially different orientations (e.g., boreholes). The software has been made available on GitHub with the hope that it will be useful for other seismologists who need to quickly verify various sensor parameters without having to write their own versions of the algorithms. Furthermore, by using a common platform and processing algorithms, it becomes possible to compare results among different tests with similar processing methods being used for both.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220180174","usgsCitation":"Kearns, A., Ringler, A.T., Holland, J., Storm, T., Wilson, D.C., and Anthony, R.E., 2018, Sensor suite: The Albuquerque Seismological Laboratory Instrumentation Testing Suite: Seismological Research Letters, v. 89, no. 6, p. 2374-2385, https://doi.org/10.1785/0220180174.","productDescription":"12 p.","startPage":"2374","endPage":"2385","ipdsId":"IP-100486","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":437738,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XXBOVR","text":"USGS data release","linkHelpText":"ASL Sensor Test Suite"},{"id":357847,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"89","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-12","publicationStatus":"PW","scienceBaseUri":"5bc02f87e4b0fc368eb5388f","contributors":{"authors":[{"text":"Kearns, A.","contributorId":208247,"corporation":false,"usgs":false,"family":"Kearns","given":"A.","email":"","affiliations":[{"id":37766,"text":"KBRwyle Technology Solutions Incorporated","active":true,"usgs":false}],"preferred":false,"id":746524,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ringler, Adam T. 0000-0002-9839-4188 aringler@usgs.gov","orcid":"https://orcid.org/0000-0002-9839-4188","contributorId":145576,"corporation":false,"usgs":true,"family":"Ringler","given":"Adam","email":"aringler@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":746525,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holland, James 0000-0002-6973-9722 jholland@usgs.gov","orcid":"https://orcid.org/0000-0002-6973-9722","contributorId":208248,"corporation":false,"usgs":true,"family":"Holland","given":"James","email":"jholland@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":746526,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Storm, Tyler 0000-0002-6787-9545 tstorm@usgs.gov","orcid":"https://orcid.org/0000-0002-6787-9545","contributorId":152165,"corporation":false,"usgs":true,"family":"Storm","given":"Tyler","email":"tstorm@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":746527,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wilson, David C. 0000-0003-2582-5159 dwilson@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-5159","contributorId":145580,"corporation":false,"usgs":true,"family":"Wilson","given":"David","email":"dwilson@usgs.gov","middleInitial":"C.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":746528,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Anthony, Robert 0000-0001-7089-8846 reanthony@usgs.gov","orcid":"https://orcid.org/0000-0001-7089-8846","contributorId":202829,"corporation":false,"usgs":true,"family":"Anthony","given":"Robert","email":"reanthony@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":746529,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70199746,"text":"70199746 - 2018 - Effects of leg flags on nest survival of four species of Arctic‐breeding shorebirds","interactions":[],"lastModifiedDate":"2018-09-27T14:17:35","indexId":"70199746","displayToPublicDate":"2018-09-27T14:17:31","publicationYear":"2018","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":"Effects of leg flags on nest survival of four species of Arctic‐breeding shorebirds","docAbstract":"Marking wild birds is an integral part of many field studies. However, if marks affect the vital rates or behavior of marked individuals, any conclusions reached by a study might be biased relative to the general population. Leg bands have rarely been found to have negative effects on birds and are frequently used to mark individuals. Leg flags, which are larger, heavier, and might produce more drag than bands, are commonly used on shorebirds and can help improve resighting rates. However, no one to date has assessed the possible effects of leg flags on the demographic performance of shorebirds. At seven sites in Arctic Alaska and western Canada, we marked individuals and monitored nest survival of four species of Arctic‐breeding shorebirds, including Semipalmated Sandpipers (Calidris pusilla), Western Sandpipers (C. mauri), Red‐necked Phalaropes (Phalaropus lobatus), and Red Phalaropes (P. fulicarius). We used a daily nest survival model in a Bayesian framework to test for effects of leg flags, relative to birds with only bands, on daily survival rates of 1952 nests. We found no evidence of a difference in nest survival between birds with flags and those with only bands. Our results suggest, therefore, that leg flags have little effect on the nest success of Arctic‐breeding sandpipers and phalaropes. Additional studies are needed, however, to evaluate the possible effects of flags on shorebirds that use other habitats and on survival rates of adults and chicks.
","language":"English","publisher":"Wiley","doi":"10.1111/jofo.12264","usgsCitation":"Weiser, E.L., Lanctot, R., Brown, S.C., Gates, H.R., Bentzen, R.L., Boldenow, M.L., Cunningham, J.A., Doll, A.C., Donnelly, T., English, W.B., Franks, S.E., Grond, K., Herzog, P., Hill, B.L., Kendall, S.J., Kwon, E., Lank, D.B., Liebezeit, J.R., Rausch, J., Saalfeld, S.T., Taylor, A.R., Ward, D.H., Wood, P., and Sandercock, B.K., 2018, Effects of leg flags on nest survival of four species of Arctic‐breeding shorebirds: Journal of Field Ornithology, v. 89, no. 3, p. 287-297, https://doi.org/10.1111/jofo.12264.","productDescription":"11 p.","startPage":"287","endPage":"297","ipdsId":"IP-098142","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":468364,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/jofo.12264","text":"External Repository"},{"id":357846,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"89","issue":"3","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-23","publicationStatus":"PW","scienceBaseUri":"5bc02f88e4b0fc368eb53891","contributors":{"authors":[{"text":"Weiser, Emily L. 0000-0003-1598-659X","orcid":"https://orcid.org/0000-0003-1598-659X","contributorId":206605,"corporation":false,"usgs":true,"family":"Weiser","given":"Emily","email":"","middleInitial":"L.","affiliations":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"preferred":true,"id":746438,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lanctot, Richard B.","contributorId":77879,"corporation":false,"usgs":false,"family":"Lanctot","given":"Richard B.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":746439,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Stephen C. 0000-0002-0421-1660","orcid":"https://orcid.org/0000-0002-0421-1660","contributorId":208214,"corporation":false,"usgs":false,"family":"Brown","given":"Stephen","email":"","middleInitial":"C.","affiliations":[{"id":37764,"text":"Shorebird Recovery Program","active":true,"usgs":false}],"preferred":false,"id":746440,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gates, H. River","contributorId":138969,"corporation":false,"usgs":false,"family":"Gates","given":"H.","email":"","middleInitial":"River","affiliations":[{"id":12600,"text":"ABR, Inc. – Environmental Research and Services","active":true,"usgs":false}],"preferred":false,"id":746441,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bentzen, Rebecca L.","contributorId":208215,"corporation":false,"usgs":false,"family":"Bentzen","given":"Rebecca","email":"","middleInitial":"L.","affiliations":[{"id":13272,"text":"Wildlife Conservation Society","active":true,"usgs":false}],"preferred":false,"id":746442,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boldenow, Megan L.","contributorId":203662,"corporation":false,"usgs":false,"family":"Boldenow","given":"Megan","email":"","middleInitial":"L.","affiliations":[{"id":36677,"text":"Department of Biology and Wildlife, University of Alaska 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R.","contributorId":127693,"corporation":false,"usgs":false,"family":"Liebezeit","given":"Joseph","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":746455,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Rausch, Jennie","contributorId":208222,"corporation":false,"usgs":false,"family":"Rausch","given":"Jennie","email":"","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":746456,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Saalfeld, Sarah T.","contributorId":208223,"corporation":false,"usgs":false,"family":"Saalfeld","given":"Sarah","email":"","middleInitial":"T.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":746457,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Taylor, Audrey R.","contributorId":10396,"corporation":false,"usgs":false,"family":"Taylor","given":"Audrey","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":746458,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Ward, David H. 0000-0002-5242-2526 dward@usgs.gov","orcid":"https://orcid.org/0000-0002-5242-2526","contributorId":3247,"corporation":false,"usgs":true,"family":"Ward","given":"David","email":"dward@usgs.gov","middleInitial":"H.","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":746459,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Wood, Paul F.","contributorId":203707,"corporation":false,"usgs":false,"family":"Wood","given":"Paul F.","affiliations":[],"preferred":false,"id":746460,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Sandercock, Brett K.","contributorId":208224,"corporation":false,"usgs":false,"family":"Sandercock","given":"Brett","email":"","middleInitial":"K.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":746461,"contributorType":{"id":1,"text":"Authors"},"rank":24}]}} ,{"id":70199747,"text":"70199747 - 2018 - Effects of urban stormwater and iron‐enhanced sand filtration on Daphnia magna and Pimephales promelas","interactions":[],"lastModifiedDate":"2018-09-27T14:12:16","indexId":"70199747","displayToPublicDate":"2018-09-27T14:12:11","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Effects of urban stormwater and iron‐enhanced sand filtration on Daphnia magna and Pimephales promelas","title":"Effects of urban stormwater and iron‐enhanced sand filtration on Daphnia magna and Pimephales promelas","docAbstract":"Urban stormwater is an important but incompletely characterized contributor to surface‐water toxicity. The present study used 5 bioassays of 2 model organisms (Daphnia magnaand fathead minnow, Pimephales promelas) to investigate stormwater toxicity and mitigation by full‐scale iron‐enhanced sand filters (IESFs). Stormwater samples were collected from major stormwater conveyances and full‐scale IESFs during 4 seasonal events (winter snowmelt and spring, early summer, and late summer rainfalls) and analyzed for a diverse range of contaminants of emerging concern including pharmaceuticals, personal care products, industrial chemicals, and pesticides. Concurrently, stormwater samples were collected for toxicity testing. Seasonality appeared more influential and consistent than site type for most bioassays. Typically, biological consequences were least in early summer and greatest in late summer and winter. In contrast with the unimproved and occasionally reduced biological outcomes in IESF‐treated and late summer samples, water chemistry indicated that numbers and total concentrations of detected organic chemicals, metals, and nutrients were reduced in late summer and in IESF‐treated stormwater samples. Some potent toxicants showed more specific seasonality (e.g., high concentrations of polycyclic aromatic hydrocarbons and industrial compounds in winter, pesticides in early summer and spring, flame retardants in late summer), which may have influenced outcomes. Potential explanations for insignificant or unexpected stormwater treatment outcomes include confounding effects of complex stormwater matrices, IESF nutrient removal, and, less likely, unmonitored toxicants.
","language":"English","publisher":"Society of Environmental Toxicology and Chemistry","doi":"10.1002/etc.4227","usgsCitation":"Westerhoff, B.M., Fairbairn, D.J., Ferrey, M.L., Matilla, A., Kunkel, J., Elliott, S.M., Kiesling, R.L., Woodruff, D., and Schoenfuss, H.L., 2018, Effects of urban stormwater and iron‐enhanced sand filtration on Daphnia magna and Pimephales promelas: Environmental Toxicology and Chemistry, v. 37, no. 10, p. 2645-2659, https://doi.org/10.1002/etc.4227.","productDescription":"15 p.","startPage":"2645","endPage":"2659","ipdsId":"IP-095127","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":357842,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","issue":"10","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-05","publicationStatus":"PW","scienceBaseUri":"5bc02f88e4b0fc368eb53893","contributors":{"authors":[{"text":"Westerhoff, Benjamin M.","contributorId":208226,"corporation":false,"usgs":false,"family":"Westerhoff","given":"Benjamin","email":"","middleInitial":"M.","affiliations":[{"id":20306,"text":"St. Cloud State University","active":true,"usgs":false}],"preferred":false,"id":746463,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fairbairn, David J.","contributorId":207455,"corporation":false,"usgs":false,"family":"Fairbairn","given":"David","email":"","middleInitial":"J.","affiliations":[{"id":13330,"text":"Minnesota Pollution Control Agency","active":true,"usgs":false}],"preferred":false,"id":746464,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ferrey, Mark L.","contributorId":207457,"corporation":false,"usgs":false,"family":"Ferrey","given":"Mark","email":"","middleInitial":"L.","affiliations":[{"id":13330,"text":"Minnesota Pollution Control Agency","active":true,"usgs":false}],"preferred":false,"id":746465,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Matilla, Adriana","contributorId":208227,"corporation":false,"usgs":false,"family":"Matilla","given":"Adriana","email":"","affiliations":[{"id":20306,"text":"St. Cloud State University","active":true,"usgs":false}],"preferred":false,"id":746466,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kunkel, Jordan","contributorId":208228,"corporation":false,"usgs":false,"family":"Kunkel","given":"Jordan","email":"","affiliations":[{"id":20306,"text":"St. Cloud State University","active":true,"usgs":false}],"preferred":false,"id":746467,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Elliott, Sarah M. 0000-0002-1414-3024 selliott@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-3024","contributorId":1472,"corporation":false,"usgs":true,"family":"Elliott","given":"Sarah","email":"selliott@usgs.gov","middleInitial":"M.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":746462,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kiesling, Richard L. 0000-0002-3017-1826 kiesling@usgs.gov","orcid":"https://orcid.org/0000-0002-3017-1826","contributorId":1837,"corporation":false,"usgs":true,"family":"Kiesling","given":"Richard","email":"kiesling@usgs.gov","middleInitial":"L.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":746468,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Woodruff, Dustin","contributorId":208230,"corporation":false,"usgs":false,"family":"Woodruff","given":"Dustin","email":"","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":746469,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schoenfuss, Heiko L.","contributorId":76409,"corporation":false,"usgs":false,"family":"Schoenfuss","given":"Heiko","email":"","middleInitial":"L.","affiliations":[{"id":13317,"text":"Saint Cloud State University","active":true,"usgs":false}],"preferred":false,"id":746470,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70199755,"text":"70199755 - 2018 - Practical approaches to maximizing the resolution of sparker seismic reflection data","interactions":[],"lastModifiedDate":"2019-09-16T11:44:51","indexId":"70199755","displayToPublicDate":"2018-09-27T14:09:13","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2668,"text":"Marine Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Practical approaches to maximizing the resolution of sparker seismic reflection data","docAbstract":"Sparkers are a type of sound source widely used by the marine seismic community to provide high-resolution imagery of the shallow sub-bottom (i.e., < 1000 m). Although sparkers are relatively simple, inexpensive, and high-frequency (100–2500 Hz) sources, they have several potential pitfalls due to their complicated and unpredictable signature. In this study we quantify the source characteristics of several sparker systems and develop a suite of simple processing approaches for both single channel and multi-channel sparker data. In all cases, the results show improved vertical resolution and reflection coherency. Correcting for small static variations in multi-channel seismic (MCS) data is a critical first step to preserve the broad frequency content during stacking, and to reduce the shot-to-shot variability of outgoing and incoming signals. Application of predictive deconvolution to static-corrected, post-stack traces suppresses short-path multiples and restores the latent high-resolution reflection patterns. However, if shot-to-shot source signatures are recorded directly, pre-stack deterministic deconvolution followed by post-stack predictive deconvolution produces the most robust results. Processing sparker data without broadband techniques results in less confident or completely missed interpretations when compared to the broadband equivalent. If processed correctly, marine sparker data can provide exceptional sub-bottom imagery that rivals other more repeatable marine seismic sources (e.g., high-frequency air-guns).
","language":"English","publisher":"Springer","doi":"10.1007/s11001-018-9367-2","usgsCitation":"Kluesner, J.W., Brothers, D.S., Hart, P.E., Miller, N.C., and Hatcher, G.A., 2018, Practical approaches to maximizing the resolution of sparker seismic reflection data: Marine Geophysical Research, v. 40, no. 3, p. 279-301, https://doi.org/10.1007/s11001-018-9367-2.","productDescription":"12 p.","startPage":"279","endPage":"301","ipdsId":"IP-097450","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":437739,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7CV4FW6","text":"USGS data release","linkHelpText":"Minisparker and chirp seismic-reflection data of field activity 2014-645-FA collected in the outer Santa Barbara Channel, California, between 2014-11-12 to 2014-11-25 (ver. 2.0, March 2020)"},{"id":357841,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"40","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-20","publicationStatus":"PW","scienceBaseUri":"5bc02f88e4b0fc368eb53895","contributors":{"authors":[{"text":"Kluesner, Jared W. 0000-0003-1701-8832 jkluesner@usgs.gov","orcid":"https://orcid.org/0000-0003-1701-8832","contributorId":201261,"corporation":false,"usgs":true,"family":"Kluesner","given":"Jared","email":"jkluesner@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":746498,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brothers, Daniel S. 0000-0001-7702-157X dbrothers@usgs.gov","orcid":"https://orcid.org/0000-0001-7702-157X","contributorId":167089,"corporation":false,"usgs":true,"family":"Brothers","given":"Daniel","email":"dbrothers@usgs.gov","middleInitial":"S.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":746499,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hart, Patrick E. 0000-0002-5080-1426 hart@usgs.gov","orcid":"https://orcid.org/0000-0002-5080-1426","contributorId":2879,"corporation":false,"usgs":true,"family":"Hart","given":"Patrick","email":"hart@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":746500,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Nathaniel C. 0000-0003-3271-2929 ncmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-3271-2929","contributorId":174592,"corporation":false,"usgs":true,"family":"Miller","given":"Nathaniel","email":"ncmiller@usgs.gov","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":746501,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hatcher, Gerry A. 0000-0001-7705-1509 ghatcher@usgs.gov","orcid":"https://orcid.org/0000-0001-7705-1509","contributorId":208239,"corporation":false,"usgs":true,"family":"Hatcher","given":"Gerry","email":"ghatcher@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":746502,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70198847,"text":"fs20183046 - 2018 - Williston Basin groundwater availability, United States and Canada","interactions":[],"lastModifiedDate":"2018-09-27T16:45:41","indexId":"fs20183046","displayToPublicDate":"2018-09-27T12:55:52","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-3046","title":"Williston Basin groundwater availability, United States and Canada","docAbstract":"The Williston Basin contains important oil and gas resources for the Nation. Freshwater supplies are limited in this semiarid area, and oil and gas development can require large volumes of freshwater. Groundwater is the primary source of water for many water users in the Williston Basin, so to better understand these resources, the U.S. Geological Survey (USGS) assessed the groundwater availability in this area. The final phase of this assessment included a computer model that simulates how groundwater flows in the aquifer systems and simulates how changes in water use and natural conditions may affect the water resources. These results provide a tool for land and water-resource managers to determine how water can be used for multiple purposes in the Williston Basin. For additional information about this assessment and more in-depth descriptions and results, see Long and others (2018).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183046","collaboration":"Water Availability and Use Science Program","usgsCitation":"Thamke, J.N., Long, A.J., and Davis, K.W., 2018, Williston Basin groundwater availability, United States and Canada: U.S. Geological Survey Fact Sheet 2018-3046, 4 p., https://doi.org/10.3133/fs20183046.","productDescription":"Report: 4 p.; Data Releases","onlineOnly":"N","ipdsId":"IP-098105","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":357815,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3046/fs20183046.pdf","text":"Report","size":"3.40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018–3046"},{"id":357816,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78P5ZDV","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water use data for hydraulic fracturing treatments in the Williston Basin, United States, 2000–2015"},{"id":357814,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3046/coverthb.jpg"},{"id":357817,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/pp1841","text":"Professional Paper 1841","size":"18.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1841","linkHelpText":"Groundwater availability of the Williston Basin, United States and Canada"},{"id":357818,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FACTT3","text":"USGS data release","description":"USGS Data Release","linkHelpText":"MODFLOW-NWT model of predictive simulations of groundwater response to selected scenarios in the Williston Basin, United States and Canada"}],"country":"Canada, United States","otherGeospatial":"Williston Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108,\n 44\n ],\n [\n -98,\n 44\n ],\n [\n -98,\n 51\n ],\n [\n -108,\n 51\n ],\n [\n -108,\n 44\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director , Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, Montana 59601
Outbreaks of plague, a flea‐vectored bacterial disease, occur periodically in prairie dog populations in the western United States. In order to understand the conditions that are conducive to plague outbreaks and potentially predict spatial and temporal variations in risk, it is important to understand the factors associated with flea abundance and distribution that may lead to plague outbreaks. We collected and identified 20,041 fleas from 6,542 individual prairie dogs of four different species over a 4‐year period along a latitudinal gradient from Texas to Montana. We assessed local climate and other factors associated with flea prevalence and abundance, as well as the incidence of plague outbreaks. Oropsylla hirsuta, a prairie dog specialist flea, and Pulex simulans, a generalist flea species, were the most common fleas found on our pairs. High elevation pairs in Wyoming and Utah had distinct flea communities compared with the rest of the study pairs. The incidence of prairie dogs with Yersinia pestis detections in fleas was low (n = 64 prairie dogs with positive fleas out of 5,024 samples from 4,218 individual prairie dogs). The results of our regression models indicate that many factors are associated with the presence of fleas. In general, flea abundance (number of fleas on hosts) is higher during plague outbreaks, lower when prairie dogs are more abundant, and reaches peak levels when climate and weather variables are at intermediate levels. Changing climate conditions will likely affect aspects of both flea and host communities, including population densities and species composition, which may lead to changes in plague dynamics. Our results support the hypothesis that local conditions, including host, vector, and environmental factors, influence the likelihood of plague outbreaks, and that predicting changes to plague dynamics under climate change scenarios will have to consider both host and vector responses to local factors.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.4390","usgsCitation":"Russell, R.E., Abbott, R.C., Tripp, D.W., and Rocke, T.E., 2018, Local factors associated with on‐host flea distributions on prairie dog colonies: Ecology and Evolution, v. 8, no. 17, p. 8951-8972, https://doi.org/10.1002/ece3.4390.","productDescription":"22 p.; Data Release","startPage":"8951","endPage":"8972","ipdsId":"IP-098871","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":460839,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.4390","text":"Publisher Index Page"},{"id":357829,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418306,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TM79CK"}],"volume":"8","issue":"17","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-14","publicationStatus":"PW","scienceBaseUri":"5bc02f88e4b0fc368eb53899","contributors":{"authors":[{"text":"Russell, Robin E. 0000-0001-8726-7303 rerussell@usgs.gov","orcid":"https://orcid.org/0000-0001-8726-7303","contributorId":3998,"corporation":false,"usgs":true,"family":"Russell","given":"Robin","email":"rerussell@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":746471,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Abbott, Rachel C. 0000-0003-4820-9295 rabbott@usgs.gov","orcid":"https://orcid.org/0000-0003-4820-9295","contributorId":1183,"corporation":false,"usgs":true,"family":"Abbott","given":"Rachel","email":"rabbott@usgs.gov","middleInitial":"C.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":746472,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tripp, Daniel W.","contributorId":17910,"corporation":false,"usgs":false,"family":"Tripp","given":"Daniel","email":"","middleInitial":"W.","affiliations":[{"id":13449,"text":"Colorado Division of Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":746473,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rocke, Tonie E. 0000-0003-3933-1563 trocke@usgs.gov","orcid":"https://orcid.org/0000-0003-3933-1563","contributorId":2665,"corporation":false,"usgs":true,"family":"Rocke","given":"Tonie","email":"trocke@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":746474,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70199749,"text":"70199749 - 2018 - Temperature regimes, growth, and food consumption for female and male adult walleye in Lake Huron and Lake Erie: a bioenergetics analysis","interactions":[],"lastModifiedDate":"2018-09-27T12:14:07","indexId":"70199749","displayToPublicDate":"2018-09-27T12:14:04","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Temperature regimes, growth, and food consumption for female and male adult walleye in Lake Huron and Lake Erie: a bioenergetics analysis","docAbstract":"Bioenergetics modeling was used to assess the relative importance of food availability and water temperature in determining walleye (Sander vitreus) growth. Temperature regimes experienced by both female and male adult walleye in three basins of Lake Huron and in Lake Erie were determined by use of surgically implanted temperature loggers and acoustic telemetry. Temperatures experienced by walleye were higher in Lake Erie than in Lake Huron. Walleye from Lake Erie grew at nearly double the rate of walleye from Lake Huron, and mass at age for adult females averaged about 50% greater than that for adult males in both lakes. Food consumption rate for an average adult walleye in Lake Erie was nearly twice as high as that in Lake Huron. Interbasin and interlake variability in temperature regimes accounted for a moderate degree of variability in walleye growth. We concluded that the driver for faster growth in Lake Erie compared with Lake Huron was higher food availability in Lake Erie compared with Lake Huron. The sex difference in temperature regimes explained 15% of the sex difference in Lake Erie walleye growth.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2017-0280","usgsCitation":"Madenjian, C.P., Hayden, T., Peat, T.B., Vandergoot, C., Fielder, D.G., Gorman, A.M., Pothoven, S.A., Dettmers, J.M., Cooke, S., Zhao, Y., and Krueger, C., 2018, Temperature regimes, growth, and food consumption for female and male adult walleye in Lake Huron and Lake Erie: a bioenergetics analysis: Canadian Journal of Fisheries and Aquatic Sciences, v. 75, no. 10, p. 1573-1586, https://doi.org/10.1139/cjfas-2017-0280.","productDescription":"14 p.","startPage":"1573","endPage":"1586","ipdsId":"IP-081676","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":460841,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2017-0280","text":"External Repository"},{"id":357828,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Erie, Lake Huron","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.88037109375,\n 41.31082388091818\n ],\n [\n -79.70581054687499,\n 41.31082388091818\n ],\n [\n -79.70581054687499,\n 46.118941506107056\n ],\n [\n -84.88037109375,\n 46.118941506107056\n ],\n [\n -84.88037109375,\n 41.31082388091818\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"75","issue":"10","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02f89e4b0fc368eb5389b","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":746475,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hayden, Todd A.","contributorId":205146,"corporation":false,"usgs":false,"family":"Hayden","given":"Todd A.","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":746484,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peat, Tyler B.","contributorId":208231,"corporation":false,"usgs":false,"family":"Peat","given":"Tyler","email":"","middleInitial":"B.","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":746476,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vandergoot, Christopher 0000-0003-4128-3329 cvandergoot@usgs.gov","orcid":"https://orcid.org/0000-0003-4128-3329","contributorId":178356,"corporation":false,"usgs":true,"family":"Vandergoot","given":"Christopher","email":"cvandergoot@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":746485,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fielder, David G.","contributorId":127528,"corporation":false,"usgs":false,"family":"Fielder","given":"David","email":"","middleInitial":"G.","affiliations":[{"id":6983,"text":"Michigan DNR","active":true,"usgs":false}],"preferred":false,"id":746477,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gorman, Ann Marie","contributorId":145525,"corporation":false,"usgs":false,"family":"Gorman","given":"Ann","email":"","middleInitial":"Marie","affiliations":[],"preferred":false,"id":746478,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pothoven, Steven A.","contributorId":92998,"corporation":false,"usgs":false,"family":"Pothoven","given":"Steven","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":746479,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dettmers, John M.","contributorId":191256,"corporation":false,"usgs":false,"family":"Dettmers","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":746480,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cooke, Steven J.","contributorId":56132,"corporation":false,"usgs":false,"family":"Cooke","given":"Steven J.","affiliations":[{"id":36574,"text":"Carleton University, Ottawa, Ontario","active":true,"usgs":false}],"preferred":false,"id":746481,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Zhao, Yingming","contributorId":205147,"corporation":false,"usgs":false,"family":"Zhao","given":"Yingming","email":"","affiliations":[{"id":37034,"text":"Ontario Ministry of Natural Resources and Forestry, Aquatic Research and Monitoring Section","active":true,"usgs":false}],"preferred":false,"id":746482,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Krueger, Charles C.","contributorId":67821,"corporation":false,"usgs":false,"family":"Krueger","given":"Charles C.","affiliations":[{"id":7019,"text":"Great Lakes Fishery Commission","active":true,"usgs":false}],"preferred":false,"id":746483,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70198657,"text":"ofr20181134 - 2018 - U.S. Geological Survey input-data forms for the assessment of the Upper Jurassic Bossier Formation, U.S. Gulf Coast, 2016","interactions":[],"lastModifiedDate":"2018-09-27T15:17:32","indexId":"ofr20181134","displayToPublicDate":"2018-09-27T11:30:00","publicationYear":"2018","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":"2018-1134","title":"U.S. Geological Survey input-data forms for the assessment of the Upper Jurassic Bossier Formation, U.S. Gulf Coast, 2016","docAbstract":"In 2016, the U.S. Geological Survey (USGS) completed an updated assessment of undiscovered, technically recoverable oil and gas resources in the Upper Jurassic Bossier Formation of the onshore U.S. Gulf Coast Province (Paxton and others, 2017). The Bossier Formation was assessed using both the standard continuous (unconventional) and conventional methodologies established by the USGS for three assessment units (AUs): (1) Bossier Eastern Shelf Sandstone Gas and Oil AU, (2) Bossier Western Shelf Sandstone Gas AU, and (3) Bossier Shale Continuous Gas AU. A fourth assessment unit, the Upper Jurassic Downdip Continuous Gas AU, was also defined but was not quantitatively assessed because of limited well data within the extent of the AU. The revised assessment resulted in total estimated mean resources of 2.9 billion barrels of oil, 108.6 trillion cubic feet of gas, and 1.1 billion barrels of natural gas liquids. The purpose of this report is to provide supplemental documentation of the input parameters used in the USGS 2016 Bossier Formation assessment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181134","usgsCitation":"Paxton, S.T., Pitman, J.K., Kinney, S.A., Gianoutsos, N.J., Pearson, O.N., Whidden, K.J., Dubiel, R.F., Schenk, C.J., Burke, L.A., Klett, T.R., Leathers-Miller, H.M., Mercier, T.J., Haines, S.S., Varela, B.A., Le, P.A., Finn, T.M., Gaswirth, S.B., Hawkins, S.J., Marra, K.R., and Tennyson, M.E., 2018, U.S. Geological Survey input-data forms for the assessment of the Upper Jurassic Bossier Formation, U.S. Gulf Coast, 2016: U.S. Geological Survey Open-File Report 2018–1134, 48 p., https://doi.org/10.3133/ofr20181134.","productDescription":"iii, 48 p.","onlineOnly":"Y","ipdsId":"IP-098783","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":357711,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1134/coverthb.jpg"},{"id":357712,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1134/ofr20181134.pdf","text":"Report","size":"960 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1134"}],"otherGeospatial":"Upper Jurassic Bossier Formation","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
The U.S. Geological Survey completed a geology-based assessment of undiscovered, technically recoverable oil and gas resources in the Haynesville and Bossier Formations of the onshore and State waters portion of the U.S. Gulf Coast region. Haynesville Formation conventional oil and gas production began in the late 1930s, whereas Bossier Formation production began in the early 1970s. Production of continuous gas resources from both formations began in 2006–7. Most of the current activity is focused on natural gas production from Haynesville and Bossier shales using horizontal wells and hydraulic fracturing. In 2016, the U.S. Geological Survey assessed technically recoverable mean resources of 4 billion barrels of oil and 304.4 trillion cubic feet of gas in the Haynesville and Bossier Formations of the onshore and State waters portion of the U.S. Gulf Coast region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181135","usgsCitation":"Paxton, S.T., 2018, Assessment of oil and gas resources in the Upper Jurassic Haynesville and Bossier Formations, U.S. Gulf Coast, 2016: U.S. Geological Survey Open-File Report 2018–1135, 13 p., https://doi.org/10.3133/ofr20181135.","productDescription":"ii, 13 p.","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-098785","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":357757,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1135/ofr20181135.pdf","text":"Report","size":"9.66 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1135"},{"id":357756,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1135/coverthb.jpg"}],"otherGeospatial":"Upper Jurassic Haynesville and Bossier Formations","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
In 2016, the U.S. Geological Survey (USGS) completed an updated assessment of undiscovered, technically recoverable oil and gas resources in the Upper Jurassic Haynesville Formation of the onshore U.S. Gulf Coast Province (Paxton and others, 2017). The Haynesville Formation was assessed using both the standard continuous (unconventional) and conventional methodologies established by the USGS for four assessment units (AUs): (1) Haynesville Western Shelf Carbonate Gas and Oil AU, (2) Haynesville Eastern Shelf Sandstone and Carbonate Oil and Gas AU, (3) Haynesville Shale Continuous Gas AU, and (4) Haynesville Shale Peripheral Continuous Gas AU. The revised assessment resulted in total estimated mean resources of 1.1 billion barrels of oil, 195.8 trillion cubic feet of gas, and 866 million barrels of natural gas liquids. The purpose of this report is to provide supplemental documentation of the input parameters used in the USGS 2016 Haynesville Formation assessment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181130","usgsCitation":"Paxton, S.T., Pitman, J.K., Kinney, S.A., Gianoutsos, N.J., Pearson, O.N., Whidden, K.J., Dubiel, R.F., Schenk, C.J., Burke, L.A., Klett, T.R., Leathers-Miller, H.M., Mercier, T.J., Haines, S.S., Varela, B.A., Le, P.A., Finn, T.M., Gaswirth, S.B., Hawkins, S.J., Marra, K.R., and Tennyson, M.E., 2018, U.S. Geological Survey input-data forms for the assessment of the Upper Jurassic Haynesville Formation, U.S. Gulf Coast, 2016: U.S. Geological Survey Open-File Report 2018–1130, 62 p., https://doi.org/10.3133/ofr20181130.","productDescription":"iii, 62 p.","onlineOnly":"Y","ipdsId":"IP-098784","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":357710,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1130/ofr20181130.pdf","text":"Report","size":"1.03 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1130"},{"id":357709,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1130/coverthb.jpg"}],"otherGeospatial":"Upper Jurassic Haynesville Formation","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
The Williston Basin of the Northern Great Plains is a sedimentary basin—a geologic bowl-like structure filled with layered sedimentary rocks dating as far back as the Paleozoic age. The basin, which is nationally important for the production of energy resources, spans Montana, North Dakota, and South Dakota in the United States, and Manitoba and Saskatchewan in Canada. The three uppermost principal aquifer systems are the glacial, lower Tertiary, and Upper Cretaceous aquifer systems. As deep as 3,000 feet (ft) at the center of the basin, these are the most accessible aquifer systems in the basin and are the primary sources of potable groundwater in much of this area. The glacial aquifer system consists of Quaternary-age unconsolidated till, silt, clay, outwash sand and gravel, and occasional cobbles and boulders. The lower Tertiary and Upper Cretaceous aquifer systems consist primarily of sandstone, siltstone, mudstone, shale, and coal.
As energy demands have increased in the basin, horizontal drilling and hydraulic-fracturing have been used (especially since 2005) to develop previously inaccessible formations—namely, the Bakken and Three Forks Formations. The basin has yielded a large supply of domestic oil and natural gas since the 1950s, but the technologies required to extract those materials use large amounts of freshwater. The increasing freshwater demands of energy production in the Williston Basin, in addition to population growth, have led to a need for new tools to assess groundwater resources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1841","collaboration":"Water Availability and Use Science Program","usgsCitation":"Long, A.J., Thamke, J.N., Davis, K.W., and Bartos, T.T., 2018, Groundwater availability of the Williston Basin, United States and Canada: U.S. Geological Survey Professional Paper 1841, 42 p., https://doi.org/10.3133/pp1841.","productDescription":"Report: viii, 42 p.; Data releases","onlineOnly":"Y","ipdsId":"IP-095100","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":357810,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78P5ZDV","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water use data for hydraulic fracturing treatments in the Williston Basin, United States, 2000–2015"},{"id":357812,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20183046","text":"Fact Sheet 2018–3046","description":"FS 2018-3046"},{"id":357811,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FACTT3","text":"USGS data release","description":"USGS Data Release","linkHelpText":"MODFLOW-NWT model of predictive simulations of groundwater response to selected scenarios in the Williston Basin, United States and Canada"},{"id":357808,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1841/coverthb.jpg"},{"id":357809,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1841/pp1841.pdf","text":"Report","size":"18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1841"}],"country":"Canada, United States","otherGeospatial":"Williston Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108,\n 44\n ],\n [\n -98,\n 44\n ],\n [\n -98,\n 51\n ],\n [\n -108,\n 51\n ],\n [\n -108,\n 44\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director , Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, Montana 59601
Variation in life‐history traits such as lifespan and lifetime reproductive output is thought to arise, in part, due to among‐individual differences in the underlying probabilities of survival and reproduction. However, the stochastic nature of demographic processes can also generate considerable variation in fitness‐related traits among otherwise‐identical individuals. An improved understanding of life‐history evolution and population dynamics therefore depends on evaluating the relative role of each of these processes. Here, we used a 33‐yr data set with reproductive histories for 1,274 female Weddell seals from Erebus Bay, Antarctica, to assess the strength of evidence for among‐individual heterogeneity in the probabilities of survival and reproduction, while accounting for multiple other sources of variation in vital rates. Our analysis used recent advances in Bayesian model selection techniques and diagnostics to directly compare model fit and predictive power between models that included individual effects on survival and reproduction to those that did not. We found strong evidence for costs of reproduction to both survival and future reproduction, with breeders having rates of survival and subsequent reproduction that were 3% and 6% lower than rates for non‐breeders. We detected age‐related changes in the rates of survival and reproduction, but the patterns differed for the two rates. Survival rates steadily declined from 0.92 at age 7 to 0.56 at the maximal age of 31 yr. In contrast, reproductive rates increased from 0.68 at age 7 to 0.79 at age 16 and then steadily declined to 0.37 for the oldest females. Models that included individual effects explained more variation in observed life histories and had better estimated predictive power than those that did not, indicating their importance in understanding sources of variation among individuals in life‐history traits. We found that among‐individual heterogeneity in survival was small relative to that for reproduction. Our study, which found patterns of variation in vital rates that are consistent with a series of predictions from life‐history theory, is the first to provide a thorough assessment of variation in important vital rates for a long‐lived, high‐latitude marine mammal while taking full advantage of recent developments in model evaluation.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.2481","usgsCitation":"Paterson, J.T., Rotella, J.J., Link, W.A., and Garrott, R.A., 2018, Variation in the vital rates of an Antarctic marine predator: the role of individual heterogeneity: Ecology, v. 99, no. 10, p. 2385-2396, https://doi.org/10.1002/ecy.2481.","productDescription":"12 p.","startPage":"2385","endPage":"2396","ipdsId":"IP-099409","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":460843,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecy.2481","text":"Publisher Index Page"},{"id":357774,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"99","issue":"10","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-12","publicationStatus":"PW","scienceBaseUri":"5bc02f8be4b0fc368eb538a9","contributors":{"authors":[{"text":"Paterson, J. Terrill","contributorId":206296,"corporation":false,"usgs":false,"family":"Paterson","given":"J.","email":"","middleInitial":"Terrill","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":740000,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rotella, Jay J.","contributorId":37271,"corporation":false,"usgs":false,"family":"Rotella","given":"Jay","email":"","middleInitial":"J.","affiliations":[{"id":5098,"text":"Department of Ecology, Montana State University","active":true,"usgs":false}],"preferred":false,"id":740001,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Link, William A. 0000-0002-9913-0256 wlink@usgs.gov","orcid":"https://orcid.org/0000-0002-9913-0256","contributorId":146920,"corporation":false,"usgs":true,"family":"Link","given":"William","email":"wlink@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":739999,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Garrott, Robert A.","contributorId":171537,"corporation":false,"usgs":false,"family":"Garrott","given":"Robert","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":740002,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70198476,"text":"70198476 - 2018 - Deciphering the dynamics of inorganic carbon export from intertidal salt marshes using high-frequency measurements","interactions":[],"lastModifiedDate":"2018-11-14T09:16:01","indexId":"70198476","displayToPublicDate":"2018-09-26T12:23:09","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2662,"text":"Marine Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Deciphering the dynamics of inorganic carbon export from intertidal salt marshes using high-frequency measurements","docAbstract":"The lateral export of carbon from coastal marshes via tidal exchange is a key component of the marsh carbon budget and coastal carbon cycles. However, the magnitude of this export has been difficult to accurately quantify due to complex tidal dynamics and seasonal cycling of carbon. In this study, we use in situ, high-frequency measurements of dissolved inorganic carbon (DIC) and water fluxes to estimate lateral DIC fluxes from a U.S. northeastern salt marsh. DIC was measured by a CHANnelized Optical Sensor (CHANOS) that provided an in situ concentration measurement at 15-min intervals, during periods in summer (July – August) and late fall (December). Seasonal changes in the marsh had strong effects on DIC concentrations, while tidally-driven water fluxes were the fundamental vehicle of marsh carbon export. Episodic events, such as groundwater discharge and mean sea water level changes, can impact DIC flux through altered DIC concentrations and water flow. Variability between individual tides within each season was comparable to mean variability between the two seasons. Estimated mean DIC fluxes based on a multiple linear regression (MLR) model of DIC concentrations and high-frequency water fluxes agreed reasonably well with those derived from CHANOS DIC measurements for both study periods, indicating that high-frequency, modeled DIC concentrations, coupled with continuous water flux measurements and a hydrodynamic model, provide a robust estimate of DIC flux. Additionally, an analysis of sampling strategies revealed that DIC fluxes calculated using conventional sampling frequencies (hourly to two-hourly) of a single tidal cycle are unlikely to capture a representative mean DIC flux compared to longer-term measurements across multiple tidal cycles with sampling frequency on the order of tens of minutes. This results from a disproportionately large amount of the net DIC flux occurring over a small number of tidal cycles, while most tides have a near-zero DIC export. Thus, high-frequency measurements (on the order of tens of minutes or better) over the time period of interest are necessary to accurately quantify tidal exports of carbon species from salt marshes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.marchem.2018.08.005","usgsCitation":"Chu, S.N., Wang, Z., Gonneea Eagle, M., Kroeger, K.D., and Ganju, N., 2018, Deciphering the dynamics of inorganic carbon export from intertidal salt marshes using high-frequency measurements: Marine Chemistry, v. 206, p. 7-18, https://doi.org/10.1016/j.marchem.2018.08.005.","productDescription":"12 p.","startPage":"7","endPage":"18","ipdsId":"IP-099810","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468365,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.marchem.2018.08.005","text":"Publisher Index Page"},{"id":357773,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"206","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02f8be4b0fc368eb538ab","contributors":{"authors":[{"text":"Chu, Sophie N.","contributorId":174603,"corporation":false,"usgs":false,"family":"Chu","given":"Sophie","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":741590,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wang, Zhaohui Aleck","contributorId":174589,"corporation":false,"usgs":false,"family":"Wang","given":"Zhaohui Aleck","affiliations":[{"id":13627,"text":"Woods Hole Oceanographic Institution, Woods Hole, MA","active":true,"usgs":false}],"preferred":false,"id":741591,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gonneea Eagle, Meagan 0000-0001-5072-2755 mgonneea@usgs.gov","orcid":"https://orcid.org/0000-0001-5072-2755","contributorId":174590,"corporation":false,"usgs":true,"family":"Gonneea Eagle","given":"Meagan","email":"mgonneea@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":741589,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kroeger, Kevin D. 0000-0002-4272-2349 kkroeger@usgs.gov","orcid":"https://orcid.org/0000-0002-4272-2349","contributorId":1603,"corporation":false,"usgs":true,"family":"Kroeger","given":"Kevin","email":"kkroeger@usgs.gov","middleInitial":"D.","affiliations":[{"id":41100,"text":"Coastal and Marine Hazards and Resources Program","active":true,"usgs":true}],"preferred":true,"id":741592,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":741593,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70199711,"text":"70199711 - 2018 - A causal partition of trait correlations: using graphical models to derive statistical models from theoretical language","interactions":[],"lastModifiedDate":"2018-09-26T11:05:12","indexId":"70199711","displayToPublicDate":"2018-09-26T11:05:04","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"A causal partition of trait correlations: using graphical models to derive statistical models from theoretical language","docAbstract":"Recent studies hypothesize various causes of species‐level trait covariation, namely size (e.g., metabolic theory of ecology and leaf economics spectrum), pace‐of‐life (e.g., slow‐to‐fast continuum; lifestyle continuum), evolutionary history (e.g., phylogenetic conservatism), and ecological conditions (e.g., stabilizing selection). Various methods have been used in attempts to partition trait correlation among these influences (e.g., univariate analysis, principal components analysis, and factor analysis). However, it is not clear that the implied causal structure assumed by these methods matches the hypothesized causal structure driving trait correlations, a situation that can potentially lead to biased estimates and incorrect partitioning among mechanisms. Here, we propose the application of graphical causal models (GCM) for across‐kingdom synthesis and to aid researchers in their selection of correct analytical strategies. Graphical causal models use causal diagrams (i.e., box‐and‐arrow graphs) to represent expert knowledge of the data‐generating processes to analytically investigate the possibility of identifying hypothesized causal associations. We developed a causal diagram that synthesizes prominent hypotheses of trait covariation. Using the causal diagram, we (1) derived a quantitative expression to partition trait covariance among its hypothesized causal elements (i.e., size, pace‐of‐life, evolutionary history, and ecological conditions) and (2) developed analytic strategies to attribute trait covariance among the hypothesized causal elements under real‐world data availability, namely unobserved variables (i.e., pace‐of‐life) and confounding variables (i.e., evolutionary history and ecological conditions). Finally, we tested each analytic strategy by simulating trait datasets and, after incorporating the data limitations, tested their ability to correctly partition trait covariance. The analytical strategies were able to correctly partition trait covariance into the hypothesized causal elements of size, pace‐of‐life, and the historical effects of evolutionary history and ecological conditions. We demonstrate the efficacy of these strategies by applying them to a widely used trait dataset. Overall, the application of GCM revealed that researchers have used inappropriate measures to represent their theoretical constructs and have relied on analytical strategies that violated their causal assumptions, likely resulting in biased estimates. We discuss how this mismatch between theoretical language and statistical methods is prevalent in species‐level, trait‐based research and call for future studies to address these limitations.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2422","usgsCitation":"Cronin, J.P., and Schoolmaster, D., 2018, A causal partition of trait correlations: using graphical models to derive statistical models from theoretical language: Ecosphere, v. 9, no. 9, p. 1-15, https://doi.org/10.1002/ecs2.2422.","productDescription":"e02422; 15 p.","startPage":"1","endPage":"15","ipdsId":"IP-066629","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":468366,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2422","text":"Publisher Index Page"},{"id":357754,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"9","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-17","publicationStatus":"PW","scienceBaseUri":"5bc02f8ce4b0fc368eb538b1","contributors":{"authors":[{"text":"Cronin, James P. 0000-0001-6791-5828 jcronin@usgs.gov","orcid":"https://orcid.org/0000-0001-6791-5828","contributorId":5834,"corporation":false,"usgs":true,"family":"Cronin","given":"James","email":"jcronin@usgs.gov","middleInitial":"P.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":746297,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schoolmaster, Donald 0000-0003-0910-4458 schoolmasterd@usgs.gov","orcid":"https://orcid.org/0000-0003-0910-4458","contributorId":156350,"corporation":false,"usgs":true,"family":"Schoolmaster","given":"Donald","email":"schoolmasterd@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":746298,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70259473,"text":"70259473 - 2018 - McGee Till—oldest glacial deposit in the Sierra Nevada, California— and Quaternary evolution of the rangefront escarpment","interactions":[],"lastModifiedDate":"2024-10-09T15:23:08.832201","indexId":"70259473","displayToPublicDate":"2018-09-26T10:16:53","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"McGee Till—oldest glacial deposit in the Sierra Nevada, California— and Quaternary evolution of the rangefront escarpment","docAbstract":"The McGee Till is an early Pleistocene glacial diamict as thick as 50 m, preserved over an area of 1.65 km2 on a relict low-relief Pliocene plateau that stands 900 m higher than mouths of its bounding canyons, on the rangefront of the Sierra Nevada. Although recognized 90 years ago as the oldest till in the Sierra, its age and relation to the next oldest Sierran till have remained uncertain, even controversial. This contribution seeks to clarify both. The McGee Till consists predominantly of grussy boulders and sandy-granular matrix derived largely from a distinctive Cretaceous granodiorite that walls McGee Creek canyon 4–8 km to the south. The till rests directly upon two different basaltic units that yield 40Ar/39Ar ages of 2.8 and 2.6 Ma and show little or no evidence of preglacial erosion. The basalts preserve a minimum of 165–255 m of relief on steep slopes that existed around the plateau margins at the time of their eruption. McGee Creek consists of two segments—a north-directed reach that confined the glacier that deposited the till and, now diverging at a right bend just upvalley from the till, a northeast-flowing reach that was incised later. The base of the McGee Till is at 3160 m elevation on the present-day rim of McGee Creek, 610 m above the bend. The base of the 130-ka Tahoe Till (MIS 6) is at 2550 m elevation directly downslope from the McGee Till and at 2300 m at the rangefront mouth of the canyon's northeast reach. The base of the 900–866 ka Sherwin Till (MIS 22) is at 2400 m at the nearby rangefront mouth of Rock Creek. As the canyons were cut to nearly modern depths before the Sherwin glaciation, the high-perched McGee Till is probably older than 2 Ma and possibly close in age to the 2.6 Ma basalt it overlies. Growth in rangefront relief since about 3.0–2.5 Ma owes to normal slip on the Hilton Creek and Round Valley Faults east of McGee Mountain as well as to the 767-ka collapse of Long Valley caldera to its north.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2018.08.008","usgsCitation":"Hildreth, W., Fierstein, J., and Calvert, A.T., 2018, McGee Till—oldest glacial deposit in the Sierra Nevada, California— and Quaternary evolution of the rangefront escarpment: Quaternary Science Reviews, v. 198, p. 242-265, https://doi.org/10.1016/j.quascirev.2018.08.008.","productDescription":"24 p.","startPage":"242","endPage":"265","ipdsId":"IP-097618","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":468367,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quascirev.2018.08.008","text":"Publisher Index Page"},{"id":462747,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"McGill Till","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.34178096223278,\n 37.90563417842898\n ],\n [\n -119.34178096223278,\n 37.462740515318\n ],\n [\n -118.32272088159911,\n 37.462740515318\n ],\n [\n -118.32272088159911,\n 37.90563417842898\n ],\n [\n -119.34178096223278,\n 37.90563417842898\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"198","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hildreth, Wes 0000-0002-7925-4251 hildreth@usgs.gov","orcid":"https://orcid.org/0000-0002-7925-4251","contributorId":2221,"corporation":false,"usgs":true,"family":"Hildreth","given":"Wes","email":"hildreth@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":915429,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fierstein, Judith E. 0000-0001-8024-1426","orcid":"https://orcid.org/0000-0001-8024-1426","contributorId":329988,"corporation":false,"usgs":true,"family":"Fierstein","given":"Judith E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":915430,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Calvert, Andrew T. 0000-0001-5237-2218 acalvert@usgs.gov","orcid":"https://orcid.org/0000-0001-5237-2218","contributorId":2694,"corporation":false,"usgs":true,"family":"Calvert","given":"Andrew","email":"acalvert@usgs.gov","middleInitial":"T.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":915431,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}