{"pageNumber":"378","pageRowStart":"9425","pageSize":"25","recordCount":46619,"records":[{"id":70200519,"text":"70200519 - 2017 - Developing an effective Agassiz's Desert Tortoise monitoring program: Final report to the Coachella Valley Conservation Commission","interactions":[],"lastModifiedDate":"2018-10-23T14:57:38","indexId":"70200519","displayToPublicDate":"2017-05-01T14:57:19","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Developing an effective Agassiz's Desert Tortoise monitoring program: Final report to the Coachella Valley Conservation Commission","docAbstract":"<p>Agassiz’s desert tortoise (Gopherus agassizii) is a conservation-reliant species with populations north and west of the Colorado River protected as threatened under the Endangered Species Act (Averill-Murray et al. 2012). Since it was listed under this category in 1990, a great deal has been learned about the natural history of the species, and it is now one of the best-studied turtles in the United States (Lovich and Ennen 2013). However, the accumulated body of scientific data available for the species has not yet been translated into recovery or delisting of the species. Successful conservation of any species requires knowledge of their natural history and how vital rates affect their ability to maintain stable populations in the face of natural and anthropogenic stresses. </p><p>Agassiz’s desert tortoises occur from southwestern Utah to near the Mexican border in California – a distance of over 450 km – but population densities vary greatly across this immense landscape (U.S. Fish and Wildlife Service 2015). Tortoises occur in the Sonoran Desert of California, including the eastern and western ends of the Coachella Valley, where it is one of 27 species covered under the Coachella Valley Multiple Species Habitat Conservation Plan and Natural Community Conservation Plan (CVMSHCP/NCCP). The southern portion of Joshua Tree National Park (JTNP) lies within this 1.1 million acre planning area, and was predicted to be an area of low-density tortoise populations using habitat suitability modeling (Barrows 2011). JTNP is near the southern distributional limit of G. agassizii, yet very little has been published regarding the ecology of tortoises in the Sonoran Desert of California.</p><p>Reproductive output is an important gross measure of the ability of a population to persist. When integrated with data on fertility and survivorship, this information forms a foundation for assessing population status and formulating effective management strategies (e.g., Congdon et al. 1993, 1994), especially for imperiled species. One aspect of the biology of G. agassizii that has been particularly well-studied is reproductive output. However, most of what we know about this topic comes from research in the Mojave Desert portion of the species’ range (Ernst and Lovich 2009). Comparatively little has been published on the reproductive ecology of populations living in the Sonoran Desert ecosystem of California. Publications by Lovich et al. (1999, 2011, 2012, 2014, 2015) constitute the main body of literature on desert tortoise reproductive ecology in the Sonoran Desert of California, with one study population located at the western end of the CVMSHCP/NCCP area. Collecting data on Agassiz’s desert tortoise ecology in the Sonoran Desert ecosystem is important due to significant differences between the two adjacent desert ecosystems, especially the timing and amounts of annual precipitation, and their potential effects on reproductive output (e.g., Lovich et al. 5 2015). There are also differences in the vulnerability of tortoises to the effects of a warming, drying climate between the two deserts (Barrows 2011; Zylstra et al. 2012). </p><p>The overall goal of this study was to collect data on demography, reproductive output, and genetic affinities at a study site in the Sonoran Desert portion of JTNP in the eastern end of the CVMSHCP/NCCP area. Specific objectives included: 1) Collect data to establish baselines on tortoise populations and/or their habitat suitability in core habitat within the CVNCCP area, including biotic and abiotic variables affecting persistence of tortoise populations; 2) Compare and contrast with data collected on desert tortoises at USGS/BLM study site near Palm Springs over 16 years; 3) Support long-term modeling efforts needed to determine tortoise population viability; 4) Refine modeled relationships with identified threats such as fire, invasive species and climate change; and 5) Prioritize adaptive management needs for the desert tortoise in and beyond the CVNCCP area. The data from this study will aid in determining baseline estimates of the desert tortoise population size within the planning area as well as establish a marked population of Agassiz’s desert tortoises for future monitoring. Data will be integrated with habitat modeling in order to refine model output. Genetic data will be collected on both the north and south sides of Interstate 10 to determine the potential effects of habitat fragmentation and genetic mixing. Analyses are ongoing and results beyond those presented in this report will be published in peer-reviewed scientific journals following inclusion of additional data collected on the south side of Shavers Valley in 2017-2018. </p>","language":"English","publisher":"Coachella Valley Conservation Commission","usgsCitation":"Lovich, J.E., and Puffer, S., 2017, Developing an effective Agassiz's Desert Tortoise monitoring program: Final report to the Coachella Valley Conservation Commission, 26 p.","productDescription":"26 p.","ipdsId":"IP-088374","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":358690,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":358644,"type":{"id":11,"text":"Document"},"url":"https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=152890&inline"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10ac2ce4b034bf6a7e6966","contributors":{"authors":[{"text":"Lovich, Jeffrey E. 0000-0002-7789-2831 jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":749275,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Puffer, Shellie R. 0000-0003-4957-0963","orcid":"https://orcid.org/0000-0003-4957-0963","contributorId":193099,"corporation":false,"usgs":true,"family":"Puffer","given":"Shellie R.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":749276,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70261470,"text":"70261470 - 2017 - Annual review 2016: Exploration review","interactions":[],"lastModifiedDate":"2024-12-11T16:58:29.035525","indexId":"70261470","displayToPublicDate":"2017-05-01T10:56:34","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2755,"text":"Mining Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Annual review 2016: Exploration review","docAbstract":"This summary of international mineral exploration activities for the year 2016 draws upon information from industry sources, published literature, SNL Metals & Mining (SNL), an offering of S&P Global Market Intelligence (New York, NY), and specialists in the U.S. Geological Survey (USGS) National Minerals Information Center. Three types of information are reported and analyzed in this annual review of international exploration: 1) budgetary statistics expressed in U.S. dollars provided by SNL; 2) regional and site-specific exploration activities that took place in 2016 as compiled by the USGS and 3) regional events and legislation that affected exploration activities including economic, social and political conditions, which were derived from published sources and discussions with USGS and industry specialists. Commodity and regional compilations are presented in this summary. Because multiple sources were used to develop commodity and regional compilations, statistics may vary depending on the source and type of data that are being reported.","language":"English","publisher":"Society for Mining, Metallurgy, & Exploration","usgsCitation":"Karl, N.A., and Wilburn, D.R., 2017, Annual review 2016: Exploration review: Mining Engineering, v. 69, no. 5, p. 28-49.","productDescription":"22 p.","startPage":"28","endPage":"49","ipdsId":"IP-085928","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":464992,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"http://me.smenet.org/abstract.cfm?preview=1&articleID=7513&page=28","linkFileType":{"id":5,"text":"html"}},{"id":465021,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"69","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Karl, Nick A 0000-0003-2858-2498","orcid":"https://orcid.org/0000-0003-2858-2498","contributorId":246006,"corporation":false,"usgs":true,"family":"Karl","given":"Nick","email":"","middleInitial":"A","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":920667,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilburn, David R. 0000-0002-5371-7617 wilburn@usgs.gov","orcid":"https://orcid.org/0000-0002-5371-7617","contributorId":1755,"corporation":false,"usgs":true,"family":"Wilburn","given":"David","email":"wilburn@usgs.gov","middleInitial":"R.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":920668,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70189333,"text":"70189333 - 2017 - Geomorphology, denudation rates, and stream channel profiles reveal patterns of mountain building adjacent to the San Andreas fault in northern California, USA","interactions":[],"lastModifiedDate":"2017-07-11T13:22:49","indexId":"70189333","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1723,"text":"GSA Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Geomorphology, denudation rates, and stream channel profiles reveal patterns of mountain building adjacent to the San Andreas fault in northern California, USA","docAbstract":"<p><span>Relative horizontal motion along strike-slip faults can build mountains when motion is oblique to the trend of the strike-slip boundary. The resulting contraction and uplift pose off-fault seismic hazards, which are often difficult to detect because of the poor vertical resolution of satellite geodesy and difficulty of locating offset datable landforms in active mountain ranges. Sparse geomorphic markers, topographic analyses, and measurement of denudation allow us to map spatiotemporal patterns of uplift along the northern San Andreas fault. Between Jenner and Mendocino, California, emergent marine terraces found southwest of the San Andreas fault record late Pleistocene uplift rates between 0.20 and 0.45 mm yr</span><sup>–1</sup><span><span>&nbsp;</span>along much of the coast. However, on the northeast side of the San Andreas fault, a zone of rapid uplift (0.6–1.0 mm yr</span><sup>–1</sup><span>) exists adjacent to the San Andreas fault, but rates decay northeastward as the coast becomes more distant from the San Andreas fault. A newly dated 4.5 Ma shallow-marine deposit located at ∼500 m above sea level (masl) adjacent to the San Andreas fault is warped down to just 150 masl 15 km northeast of the San Andreas fault, and it is exposed at just 60–110 masl to the west of the fault. Landscape denudation rates calculated from abundance of cosmogenic radionuclides in fluvial sediment northeast of, and adjacent to, the San Andreas fault are 0.16–0.29 mm yr</span><sup>–1</sup><span>, but they are only 0.03–0.07 mm yr</span><sup>–1</sup><span><span>&nbsp;</span>west of the fault. Basin-average channel steepness and the denudation rates can be used to infer the erosive properties of the underlying bedrock. Calibrated erosion rates can then be estimated across the entire landscape using the spatial distribution of channel steepness with these erosive properties. The lower-elevation areas of this landscape that show high channel steepness (and hence calibrated erosion rate) are distinct from higher-elevation areas with systematically lower channel steepness and denudation rates. These two areas do not appear to be coincident with lithologic contacts. Assuming that changes in rock uplift rates are manifest in channel steepness values as an upstream-propagating kinematic wave that separates high and low channel steepness values, the distance that this transition has migrated vertically provides an estimate of the timing of rock uplift rate increase. This analysis suggests that rock uplift rates along the coast changed from 0.3 to 0.75 mm yr</span><sup>–1</sup><span><span>&nbsp;</span>between 450 and 350 ka. This zone of recent, relatively rapid crustal deformation along the plate boundary may be a result of the impingement of relatively strong crust underlying the Gualala block into the thinner, weaker oceanic crust left at the western margin of the North American plate by the westward migration of the subduction zone prior to establishment of the current transform plate boundary. The warped Pliocene marine deposits and the presence of a topographic ridge support the patterns indicated by the channel steepness analyses, and further indicate that the zone of rapid uplift may herald elevated off-fault seismic hazard if this uplift is created by periodic stick-slip motion on contractional structures.</span></p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/B31551.1","usgsCitation":"DeLong, S.B., Hilley, G.E., Prentice, C.S., Crosby, C.J., and Yokelson, I.N., 2017, Geomorphology, denudation rates, and stream channel profiles reveal patterns of mountain building adjacent to the San Andreas fault in northern California, USA: GSA Bulletin, v. 129, no. 5-6, p. 732-749, https://doi.org/10.1130/B31551.1.","productDescription":"18 p.","startPage":"732","endPage":"749","ipdsId":"IP-069660","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":343577,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Andreas fault","volume":"129","issue":"5-6","noUsgsAuthors":false,"publicationDate":"2017-01-27","publicationStatus":"PW","scienceBaseUri":"5965b1efe4b0d1f9f05b37cc","contributors":{"authors":[{"text":"DeLong, Stephen B. 0000-0002-0945-2172 sdelong@usgs.gov","orcid":"https://orcid.org/0000-0002-0945-2172","contributorId":5240,"corporation":false,"usgs":true,"family":"DeLong","given":"Stephen","email":"sdelong@usgs.gov","middleInitial":"B.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":704204,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hilley, George E.","contributorId":85484,"corporation":false,"usgs":true,"family":"Hilley","given":"George","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":704205,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prentice, Carol S. 0000-0003-3732-3551 cprentice@usgs.gov","orcid":"https://orcid.org/0000-0003-3732-3551","contributorId":2676,"corporation":false,"usgs":true,"family":"Prentice","given":"Carol","email":"cprentice@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":704206,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crosby, Christopher J. 0000-0003-2522-4193","orcid":"https://orcid.org/0000-0003-2522-4193","contributorId":68415,"corporation":false,"usgs":true,"family":"Crosby","given":"Christopher","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":704207,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yokelson, Intan N.","contributorId":194456,"corporation":false,"usgs":false,"family":"Yokelson","given":"Intan","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":704208,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70193456,"text":"70193456 - 2017 - Fall and winter survival of brook trout and brown trout in a north-central Pennsylvania watershed","interactions":[],"lastModifiedDate":"2017-11-10T11:15:39","indexId":"70193456","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Fall and winter survival of brook trout and brown trout in a north-central Pennsylvania watershed","docAbstract":"<p>Stream-dwelling salmonids that spawn in the fall generally experience their lowest survival during the fall and winter due to behavioral changes associated with spawning and energetic deficiencies during this time of year. We used data from Brook Trout <i>Salvelinus fontinalis</i> and Brown Trout <i>Salmo trutta</i> implanted with radio transmitters in tributaries of the Hunts Run watershed of north-central Pennsylvania to estimate survival from the fall into the winter seasons (September 2012–February 2013). We examined the effects that individual-level covariates (trout species, size, and movement rates) and stream-level covariates (individual stream and cumulative drainage area of a stream) have on survival. Brook Trout experienced significantly lower survival than Brown Trout, especially in the early fall during their peak spawning period. Besides a significant species effect, none of the other covariates examined influenced survival for either species. A difference in life history between these species, with Brook Trout having a shorter life expectancy than Brown Trout, is likely the primary reason for the lower survival of Brook Trout. However, Brook Trout also spawn earlier in the fall than Brown Trout and low flows during Brook Trout spawning may have resulted in a greater risk of predation for Brook Trout compared with Brown Trout, thereby also contributing to the observed differences in survival between these species. Our estimates of survival can aid parameterization of future population models for Brook Trout and Brown Trout through the spawning season and into winter.</p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00028487.2017.1305987","usgsCitation":"Sweka, J.A., Davis, L.A., and Wagner, T., 2017, Fall and winter survival of brook trout and brown trout in a north-central Pennsylvania watershed: Transactions of the American Fisheries Society, v. 146, no. 4, p. 744-752, https://doi.org/10.1080/00028487.2017.1305987.","productDescription":"9 p.","startPage":"744","endPage":"752","ipdsId":"IP-079502","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":348571,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Hunts Run watershed","volume":"146","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-26","publicationStatus":"PW","scienceBaseUri":"5a06c8cde4b09af898c86123","contributors":{"authors":[{"text":"Sweka, John A.","contributorId":198858,"corporation":false,"usgs":false,"family":"Sweka","given":"John","email":"","middleInitial":"A.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":719128,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davis, Lori A.","contributorId":187762,"corporation":false,"usgs":false,"family":"Davis","given":"Lori","email":"","middleInitial":"A.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":721572,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":721573,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70192458,"text":"70192458 - 2017 - Global Positioning System data collection, processing, and analysis conducted by the U.S. Geological Survey Earthquake Hazards Program","interactions":[],"lastModifiedDate":"2017-10-26T13:46:25","indexId":"70192458","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Global Positioning System data collection, processing, and analysis conducted by the U.S. Geological Survey Earthquake Hazards Program","docAbstract":"<p><span>The U.S. Geological Survey Earthquake Science Center collects and processes Global Positioning System (GPS) data throughout the western United States to measure crustal deformation related to earthquakes and tectonic processes as part of a long‐term program of research and monitoring. Here, we outline data collection procedures and present the GPS dataset built through repeated temporary deployments since 1992. This dataset consists of observations at ∼1950 locations. In addition, this article details our data processing and analysis procedures, which consist of the following. We process the raw data collected through temporary deployments, in addition to data from continuously operating western U.S. GPS stations operated by multiple agencies, using the GIPSY software package to obtain position time series. Subsequently, we align the positions to a common reference frame, determine the optimal parameters for a temporally correlated noise model, and apply this noise model when carrying out time‐series analysis to derive deformation measures, including constant interseismic velocities, coseismic offsets, and transient postseismic motion.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220160204","usgsCitation":"Murray, J.R., and Svarc, J.L., 2017, Global Positioning System data collection, processing, and analysis conducted by the U.S. Geological Survey Earthquake Hazards Program: Seismological Research Letters, v. 88, no. 3, p. 916-925, https://doi.org/10.1785/0220160204.","productDescription":"10 p.","startPage":"916","endPage":"925","ipdsId":"IP-081230","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":347479,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"88","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-01","publicationStatus":"PW","scienceBaseUri":"5a07e8f7e4b09af898c8cbdd","contributors":{"authors":[{"text":"Murray, Jessica R. 0000-0002-6144-1681 jrmurray@usgs.gov","orcid":"https://orcid.org/0000-0002-6144-1681","contributorId":2759,"corporation":false,"usgs":true,"family":"Murray","given":"Jessica","email":"jrmurray@usgs.gov","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":715955,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Svarc, Jerry L. 0000-0002-2802-4528 jsvarc@usgs.gov","orcid":"https://orcid.org/0000-0002-2802-4528","contributorId":2413,"corporation":false,"usgs":true,"family":"Svarc","given":"Jerry","email":"jsvarc@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":715956,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70192626,"text":"70192626 - 2017 - A dynamic spatio-temporal model for spatial data","interactions":[],"lastModifiedDate":"2018-01-03T15:57:04","indexId":"70192626","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5548,"text":"Spatial Statistics","active":true,"publicationSubtype":{"id":10}},"title":"A dynamic spatio-temporal model for spatial data","docAbstract":"<p><span>Analyzing spatial data often requires modeling dependencies created by a dynamic spatio-temporal data generating process. In many applications, a generalized linear mixed model (GLMM) is used with a random effect to account for spatial dependence and to provide optimal spatial predictions. Location-specific covariates are often included as fixed effects in a GLMM and may be collinear with the spatial random effect, which can negatively affect inference. We propose a dynamic approach to account for spatial dependence that incorporates scientific knowledge of the spatio-temporal data generating process. Our approach relies on a dynamic spatio-temporal model that explicitly incorporates location-specific covariates. We illustrate our approach with a spatially varying ecological diffusion model implemented using a computationally efficient homogenization technique. We apply our model to understand individual-level and location-specific risk factors associated with chronic wasting disease in white-tailed deer from Wisconsin, USA and estimate the location the disease was first introduced. We compare our approach to several existing methods that are commonly used in spatial statistics. Our spatio-temporal approach resulted in a higher predictive accuracy when compared to methods based on optimal spatial prediction, obviated confounding among the spatially indexed covariates and the spatial random effect, and provided additional information that will be important for containing disease outbreaks.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.spasta.2017.02.005","usgsCitation":"Hefley, T.J., Hooten, M., Hanks, E.M., Russell, R., and Walsh, D.P., 2017, A dynamic spatio-temporal model for spatial data: Spatial Statistics, v. 20, p. 206-220, https://doi.org/10.1016/j.spasta.2017.02.005.","productDescription":"15 p.","startPage":"206","endPage":"220","ipdsId":"IP-079545","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":461613,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.spasta.2017.02.005","text":"Publisher Index Page"},{"id":348561,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","volume":"20","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a06c8cee4b09af898c8612d","contributors":{"authors":[{"text":"Hefley, Trevor J.","contributorId":147146,"corporation":false,"usgs":false,"family":"Hefley","given":"Trevor","email":"","middleInitial":"J.","affiliations":[{"id":16796,"text":"Dept Fish, Wildlife & Cons Biol, Colorado St Univ, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":716578,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":716576,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hanks, Ephraim M.","contributorId":178093,"corporation":false,"usgs":false,"family":"Hanks","given":"Ephraim","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":716579,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Russell, Robin 0000-0001-8726-7303 rerussell@usgs.gov","orcid":"https://orcid.org/0000-0001-8726-7303","contributorId":178094,"corporation":false,"usgs":true,"family":"Russell","given":"Robin","email":"rerussell@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":716577,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walsh, Daniel P. 0000-0002-7772-2445 dwalsh@usgs.gov","orcid":"https://orcid.org/0000-0002-7772-2445","contributorId":4758,"corporation":false,"usgs":true,"family":"Walsh","given":"Daniel","email":"dwalsh@usgs.gov","middleInitial":"P.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":716580,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70192811,"text":"70192811 - 2017 - Cosmogenic nuclide age estimate for Laurentide Ice Sheet recession from the terminal moraine, New Jersey, USA, and constraints on latest Pleistocene ice sheet history","interactions":[],"lastModifiedDate":"2017-11-13T13:25:46","indexId":"70192811","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3218,"text":"Quaternary Research","active":true,"publicationSubtype":{"id":10}},"title":"Cosmogenic nuclide age estimate for Laurentide Ice Sheet recession from the terminal moraine, New Jersey, USA, and constraints on latest Pleistocene ice sheet history","docAbstract":"<p>The time at which the Laurentide Ice Sheet reached its maximum extent and subsequently retreated from its terminal moraine in New Jersey has been constrained by bracketing radiocarbon ages on preglacial and postglacial sediments. Here, we present measurements of in situ produced <span class=\"sup\">10</span>Be and <span class=\"sup\">26</span>Al in 16 quartz-bearing samples collected from bedrock outcrops and glacial erratics just north of the terminal moraine in north-central New Jersey; as such, our ages represent a minimum limit on the timing of ice recession from the moraine. The data set includes field and laboratory replicates, as well as replication of the entire data set five years after initial measurement. We find that recession of the Laurentide Ice Sheet from the terminal moraine in New Jersey began before 25.2±2.1 ka (<span class=\"sup\">10</span>Be, n=16, average, 1 standard deviation). This cosmogenic nuclide exposure age is consistent with existing limiting radiocarbon ages in the study area and cosmogenic nuclide exposure ages from the terminal moraine on Martha’s Vineyard ~300 km to the northeast. The age we propose for Laurentide Ice Sheet retreat from the New Jersey terminal position is broadly consistent with regional and global climate records of the last glacial maximum termination and records of fluvial incision.</p>","language":"English","publisher":"Cambridge University Press","doi":"10.1017/qua.2017.11","usgsCitation":"Corbett, L.B., Bierman, P., Stone, B.D., Caffee, M.W., and Larsen, P.L., 2017, Cosmogenic nuclide age estimate for Laurentide Ice Sheet recession from the terminal moraine, New Jersey, USA, and constraints on latest Pleistocene ice sheet history: Quaternary Research, v. 87, no. 3, p. 482-498, https://doi.org/10.1017/qua.2017.11.","productDescription":"17 p.","startPage":"482","endPage":"498","ipdsId":"IP-077896","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":348702,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey","volume":"87","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-18","publicationStatus":"PW","scienceBaseUri":"5a60fbd6e4b06e28e9c236d3","contributors":{"authors":[{"text":"Corbett, Lee B.","contributorId":152123,"corporation":false,"usgs":false,"family":"Corbett","given":"Lee","email":"","middleInitial":"B.","affiliations":[{"id":17809,"text":"University of Vermont, Burlington","active":true,"usgs":false}],"preferred":false,"id":717037,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bierman, Paul R.","contributorId":198743,"corporation":false,"usgs":false,"family":"Bierman","given":"Paul R.","affiliations":[{"id":17809,"text":"University of Vermont, Burlington","active":true,"usgs":false}],"preferred":false,"id":717038,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stone, Byron D. 0000-0001-6092-0798 bdstone@usgs.gov","orcid":"https://orcid.org/0000-0001-6092-0798","contributorId":1702,"corporation":false,"usgs":true,"family":"Stone","given":"Byron","email":"bdstone@usgs.gov","middleInitial":"D.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":717036,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Caffee, Marc W. 0000-0002-6846-8967","orcid":"https://orcid.org/0000-0002-6846-8967","contributorId":193417,"corporation":false,"usgs":false,"family":"Caffee","given":"Marc","email":"","middleInitial":"W.","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":717039,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Larsen, Patrick L.","contributorId":198744,"corporation":false,"usgs":false,"family":"Larsen","given":"Patrick","email":"","middleInitial":"L.","affiliations":[{"id":17809,"text":"University of Vermont, Burlington","active":true,"usgs":false}],"preferred":false,"id":717040,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70192141,"text":"70192141 - 2017 - Reconstructing a herbivore’s diet using a novel rbcL DNA mini-barcode for plants","interactions":[],"lastModifiedDate":"2018-03-29T13:32:36","indexId":"70192141","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5538,"text":"AoB PLANTS","active":true,"publicationSubtype":{"id":10}},"title":"Reconstructing a herbivore’s diet using a novel rbcL DNA mini-barcode for plants","docAbstract":"<p><span>Next Generation Sequencing and the application of metagenomic analyses can be used to answer questions about animal diet choice and study the consequences of selective foraging by herbivores. The quantification of herbivore diet choice with respect to native versus exotic plant species is particularly relevant given concerns of invasive species establishment and their effects on ecosystems. While increased abundance of white-tailed deer (</span><i>Odocoileus virginianus</i><span>) appears to correlate with increased incidence of invasive plant species, data supporting a causal link is scarce. We used a metabarcoding approach (PCR amplicons of the plant<span>&nbsp;</span></span><i>rbc</i><span>L gene) to survey the diet of white-tailed deer (fecal samples), from a forested site in Warren County, Virginia with a comprehensive plant species inventory and corresponding reference collection of plant barcode and chloroplast sequences. We sampled fecal pellet piles and extracted DNA from 12 individual deer in October 2014. These samples were compared to a reference DNA library of plant species collected within the study area. For 72 % of the amplicons, we were able to assign taxonomy at the species level, which provides for the first time—sufficient taxonomic resolution to quantify the relative frequency at which native and exotic plant species are being consumed by white-tailed deer. For each of the 12 individual deer we collected three subsamples from the same fecal sample, resulting in sequencing 36 total samples. Using Qiime, we quantified the plant DNA found in all 36 samples, and found that variance within samples was less than variance between samples (</span><i>F</i><span> = 1.73,<span>&nbsp;</span></span><i>P</i><span> = 0.004), indicating additional subsamples may not be necessary. Species level diversity ranged from 60 to 93 OTUs per individual and nearly 70 % of all plant sequences recovered were from native plant species. The number of species detected did reduce significantly (range 4–12) when we excluded species whose OTU composed &lt;1 % of each sample’s total. When compared to the abundance of native and non-natives plants inventoried in the local community, our results support the observation that white-tailed deer have strong foraging preferences, but these preferences were not consistent for species in either class. Deer forage behaviour may favour some exotic species, but not all.</span></p>","language":"English","publisher":"Oxford University Press","doi":"10.1093/aobpla/plx015","usgsCitation":"Erickson, D.L., Reed, E., Ramachandran, P., Bourg, N., McShea, W.J., and Ottesen, A., 2017, Reconstructing a herbivore’s diet using a novel rbcL DNA mini-barcode for plants: AoB PLANTS, v. 9, no. 3, p. 1-17, https://doi.org/10.1093/aobpla/plx015.","productDescription":"Article plx015; 17 p.","startPage":"1","endPage":"17","ipdsId":"IP-084958","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":469892,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/aobpla/plx015","text":"Publisher Index Page"},{"id":352162,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-21","publicationStatus":"PW","scienceBaseUri":"5afee886e4b0da30c1bfc464","contributors":{"authors":[{"text":"Erickson, David L.","contributorId":197853,"corporation":false,"usgs":false,"family":"Erickson","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":714429,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reed, Elizabeth","contributorId":197854,"corporation":false,"usgs":false,"family":"Reed","given":"Elizabeth","email":"","affiliations":[],"preferred":false,"id":714430,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramachandran, Padmini","contributorId":197855,"corporation":false,"usgs":false,"family":"Ramachandran","given":"Padmini","email":"","affiliations":[],"preferred":false,"id":714431,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bourg, Norman 0000-0002-7443-1992 nbourg@usgs.gov","orcid":"https://orcid.org/0000-0002-7443-1992","contributorId":197809,"corporation":false,"usgs":true,"family":"Bourg","given":"Norman","email":"nbourg@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":714428,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McShea, William J.","contributorId":197834,"corporation":false,"usgs":false,"family":"McShea","given":"William","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":714432,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ottesen, Andrea","contributorId":197856,"corporation":false,"usgs":false,"family":"Ottesen","given":"Andrea","email":"","affiliations":[],"preferred":false,"id":714433,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70193454,"text":"70193454 - 2017 - Creating multithemed ecological regions for macroscale ecology: Testing a flexible, repeatable, and accessible clustering method","interactions":[],"lastModifiedDate":"2017-11-10T15:02:08","indexId":"70193454","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Creating multithemed ecological regions for macroscale ecology: Testing a flexible, repeatable, and accessible clustering method","docAbstract":"<p><span>Understanding broad-scale ecological patterns and processes often involves accounting for regional-scale heterogeneity. A common way to do so is to include ecological regions in sampling schemes and empirical models. However, most existing ecological regions were developed for specific purposes, using a limited set of geospatial features and irreproducible methods. Our study purpose was to: (1) describe a method that takes advantage of recent computational advances and increased availability of regional and global data sets to create customizable and reproducible ecological regions, (2) make this algorithm available for use and modification by others studying different ecosystems, variables of interest, study extents, and macroscale ecology research questions, and (3) demonstrate the power of this approach for the research question—How well do these regions capture regional-scale variation in lake water quality? To achieve our purpose we: (1) used a spatially constrained spectral clustering algorithm that balances geospatial homogeneity and region contiguity to create ecological regions using multiple terrestrial, climatic, and freshwater geospatial data for 17 northeastern U.S. states (~1,800,000&nbsp;km</span><sup>2</sup><span>); (2)&nbsp;identified which of the 52 geospatial features were most influential in creating the resulting 100 regions; and (3) tested the ability of these ecological regions to capture regional variation in water nutrients and clarity for ~6,000 lakes. We found that: (1) a combination of terrestrial, climatic, and freshwater geospatial features influenced region creation, suggesting that the oft-ignored freshwater landscape provides novel information on landscape variability not captured by traditionally used climate and terrestrial metrics; and (2) the delineated regions captured macroscale heterogeneity in ecosystem properties not included in region delineation—approximately 40% of the variation in total phosphorus and water clarity among lakes was at the regional scale. Our results demonstrate the usefulness of this method for creating customizable and reproducible regions for research and management applications.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.2884","usgsCitation":"Cheruvelil, K.S., Yuan, S., Webster, K.E., Tan, P., Lapierre, J., Collins, S.M., Fergus, C.E., Scott, C.E., Norton Henry, E., Soranno, P.A., Filstrup, C.T., and Wagner, T., 2017, Creating multithemed ecological regions for macroscale ecology: Testing a flexible, repeatable, and accessible clustering method: Ecology and Evolution, v. 7, no. 9, p. 3046-3058, https://doi.org/10.1002/ece3.2884.","productDescription":"13 p.","startPage":"3046","endPage":"3058","ipdsId":"IP-078752","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":469896,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.2884","text":"Publisher Index Page"},{"id":348589,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -97.734375,\n              35.96022296929667\n            ],\n            [\n              -66.62109375,\n              35.96022296929667\n            ],\n            [\n              -66.62109375,\n              49.03786794532644\n            ],\n            [\n              -97.734375,\n              49.03786794532644\n            ],\n            [\n              -97.734375,\n              35.96022296929667\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"7","issue":"9","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-26","publicationStatus":"PW","scienceBaseUri":"5a06c8cee4b09af898c8612a","contributors":{"authors":[{"text":"Cheruvelil, Kendra Spence","contributorId":150607,"corporation":false,"usgs":false,"family":"Cheruvelil","given":"Kendra","email":"","middleInitial":"Spence","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":721616,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yuan, Shuai","contributorId":172187,"corporation":false,"usgs":false,"family":"Yuan","given":"Shuai","affiliations":[],"preferred":false,"id":721617,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Webster, Katherine E.","contributorId":147903,"corporation":false,"usgs":false,"family":"Webster","given":"Katherine","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":721618,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tan, Pang-Ning","contributorId":172193,"corporation":false,"usgs":false,"family":"Tan","given":"Pang-Ning","affiliations":[],"preferred":false,"id":721619,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lapierre, Jean-Francois","contributorId":172182,"corporation":false,"usgs":false,"family":"Lapierre","given":"Jean-Francois","email":"","affiliations":[],"preferred":false,"id":721620,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Collins, Sarah M.","contributorId":172181,"corporation":false,"usgs":false,"family":"Collins","given":"Sarah","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":721621,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fergus, C. Emi","contributorId":150608,"corporation":false,"usgs":false,"family":"Fergus","given":"C.","email":"","middleInitial":"Emi","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":721622,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Scott, Caren E.","contributorId":172184,"corporation":false,"usgs":false,"family":"Scott","given":"Caren","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":721623,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Norton Henry, Emily","contributorId":200254,"corporation":false,"usgs":false,"family":"Norton Henry","given":"Emily","email":"","affiliations":[],"preferred":false,"id":721624,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Soranno, Patricia A.","contributorId":172104,"corporation":false,"usgs":false,"family":"Soranno","given":"Patricia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":721625,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Filstrup, Christopher T.","contributorId":169032,"corporation":false,"usgs":false,"family":"Filstrup","given":"Christopher","email":"","middleInitial":"T.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":721626,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":719125,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70192624,"text":"70192624 - 2017 - Do we need demographic data to forecast plant population dynamics?","interactions":[],"lastModifiedDate":"2017-11-10T10:59:58","indexId":"70192624","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Do we need demographic data to forecast plant population dynamics?","docAbstract":"<ol id=\"mee312686-list-0001\" class=\"o-list--numbered o-list--paragraph\"><li>Rapid environmental change has generated growing interest in forecasts of future population trajectories. Traditional population models built with detailed demographic observations from one study site can address the impacts of environmental change at particular locations, but are difficult to scale up to the landscape and regional scales relevant to management decisions. An alternative is to build models using population-level data that are much easier to collect over broad spatial scales than individual-level data. However, it is unknown whether models built using population-level data adequately capture the effects of density-dependence and environmental forcing that are necessary to generate skillful forecasts.</li><li>Here, we test the consequences of aggregating individual responses when forecasting the population states (percent cover) and trajectories of four perennial grass species in a semi-arid grassland in Montana, USA. We parameterized two population models for each species, one based on individual-level data (survival, growth and recruitment) and one on population-level data (percent cover), and compared their forecasting accuracy and forecast horizons with and without the inclusion of climate covariates. For both models, we used Bayesian ridge regression to weight the influence of climate covariates for optimal prediction.</li><li>In the absence of climate effects, we found no significant difference between the forecast accuracy of models based on individual-level data and models based on population-level data. Climate effects were weak, but increased forecast accuracy for two species. Increases in accuracy with climate covariates were similar between model types.</li><li>In our case study, percent cover models generated forecasts as accurate as those from a demographic model. For the goal of forecasting, models based on aggregated individual-level data may offer a practical alternative to data-intensive demographic models. Long time series of percent cover data already exist for many plant species. Modelers should exploit these data to predict the impacts of environmental change.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/2041-210X.12686","usgsCitation":"Tredennick, A.T., Hooten, M., and Adler, P.B., 2017, Do we need demographic data to forecast plant population dynamics?: Methods in Ecology and Evolution, v. 8, no. 5, p. 541-551, https://doi.org/10.1111/2041-210X.12686.","productDescription":"11 p.","startPage":"541","endPage":"551","ipdsId":"IP-076546","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":469886,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.12686","text":"Publisher Index Page"},{"id":348564,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-28","publicationStatus":"PW","scienceBaseUri":"5a06c8cfe4b09af898c86131","contributors":{"authors":[{"text":"Tredennick, Andrew T.","contributorId":152688,"corporation":false,"usgs":false,"family":"Tredennick","given":"Andrew","email":"","middleInitial":"T.","affiliations":[{"id":18962,"text":"Dept. of Wildland Resources and the Ecology Center, Utah State University, Logan, UT","active":true,"usgs":false}],"preferred":false,"id":721549,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":716574,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adler, Peter B.","contributorId":64789,"corporation":false,"usgs":false,"family":"Adler","given":"Peter","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":721550,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70191331,"text":"70191331 - 2017 - The Partners in Flight handbook on species assessment Version 2017","interactions":[],"lastModifiedDate":"2017-10-05T15:58:15","indexId":"70191331","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"The Partners in Flight handbook on species assessment Version 2017","docAbstract":"Partners in Flight (PIF) is a cooperative venture of federal, state, provincial, and territorial agencies, industry, non-governmental organizations, researchers, and many others whose common goal is the conservation of North American birds (www.partnersinflight.org). While PIF has focused primarily on landbirds, it works in conjunction with other bird partners to promote coordinated conservation of all birds.\n\nPIF follows an iterative, adaptive planning approach that develops a sound scientific basis for decision-making and a logical process for setting, implementing, and evaluating conservation objectives (Pashley et al. 2000, Rich et al. 2004, Berlanga et al. 2010). The steps include:\n\n1. Assessing conservation vulnerability of all bird species;\n2. Identifying species most in need of conservation attention at continental and regional scales;\n3. Setting of numerical population objectives for species of continental and regional importance;\n4. Identifying conservation needs and recommended actions for species and habitats of importance;\n5. Implementing strategies for meeting species and habitat objectives at continental and regional scales;\n6. Evaluating success, making revisions, and setting new objectives for the future.\n\nThe 2017 PIF Handbook on Species Assessment (2017 PIF Handbook) documents assessment rules and scores used in the Partners in Flight Landbird Conservation Plan: 2016 Revision for Canada and Continental United States (Rosenberg et al. 2016) and The State of North America’s Birds 2016 (NABCI 2016). It updates previous versions of the handbook (Panjabi et al. 2012, 2005, 2001) developed to accompany other PIF applications including Saving Our Shared Birds: Partners in Flight Tri-National Vision for Landbird Conservation (Berlanga et al. 2010) and the North American Landbird Conservation Plan (Rich et al. 2004). All current and past scores, data sources, and other related information are contained in databases hosted by the Bird Conservancy of the Rockies. Scores can be viewed online and downloaded as excel files, including archived versions (http://pif.birdconservancy.org/acad). The current accompanying Avian Conservation Assessment Database (ACAD) holds assessment scores and data for all 1585 native and 18 well-established non-native bird species found in mainland North America south to Panama plus adjacent islands and oceans. The taxonomy follows the American Ornithological Society’s 7th Edition Checklist of North and Middle American Birds, including updates though the 57th supplement, published in 2016 (http://checklist.aou.org/). The ACAD builds on archived PIF databases that hosted only data on the 882 landbirds native to Canada, USA and Mexico.\n\nThis handbook is presented in two principal sections. Part I details the factors and scoring used by PIF to assess the vulnerability of species at continental and regional scales (i.e. step 1 of the planning approach above). Each assessment factor is based on biological criteria that evaluate distinct components of vulnerability throughout the life cycle of each species across its range. Part II describes the process of how the factors and the corresponding scores can be combined to highlight conservation needs (i.e. step 2 of the planning approach above). Both the scores and the process have evolved over time (Hunter et al. 1992, Carter et al. 2000, Panjabi et al. 2001, 2005, 2012) and continue to be updated in response to external review (Beissinger et al. 2000), broad partner expertise, and the emergence of new data and analytical tools.","language":"English","publisher":"Partners in Flight","usgsCitation":"Panjabi, A.O., Blancher, P.J., Easton, W.E., Stanton, J.C., Demarest, D.W., Dettmers, R., Rosenberg, K.V., and Partners in Flight Science Committee, 2017, The Partners in Flight handbook on species assessment Version 2017, 43 p.","productDescription":"43 p.","ipdsId":"IP-086026","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":346439,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":346389,"type":{"id":15,"text":"Index Page"},"url":"https://pif.birdconservancy.org/ACAD/"}],"publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59d744a3e4b05fe04cc7e324","contributors":{"authors":[{"text":"Panjabi, Arvind O.","contributorId":169967,"corporation":false,"usgs":false,"family":"Panjabi","given":"Arvind","email":"","middleInitial":"O.","affiliations":[{"id":25644,"text":"Bird Conservancy of the Rockies","active":true,"usgs":false}],"preferred":false,"id":711964,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blancher, Peter J.","contributorId":175182,"corporation":false,"usgs":false,"family":"Blancher","given":"Peter","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":711965,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Easton, Wendy E.","contributorId":175185,"corporation":false,"usgs":false,"family":"Easton","given":"Wendy","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":711966,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stanton, Jessica C. 0000-0002-6225-3703 jcstanton@usgs.gov","orcid":"https://orcid.org/0000-0002-6225-3703","contributorId":5634,"corporation":false,"usgs":true,"family":"Stanton","given":"Jessica","email":"jcstanton@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":711963,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Demarest, Dean W.","contributorId":175184,"corporation":false,"usgs":false,"family":"Demarest","given":"Dean","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":712043,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dettmers, Randy","contributorId":196926,"corporation":false,"usgs":false,"family":"Dettmers","given":"Randy","email":"","affiliations":[],"preferred":false,"id":711967,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rosenberg, Kenneth V.","contributorId":171463,"corporation":false,"usgs":false,"family":"Rosenberg","given":"Kenneth","email":"","middleInitial":"V.","affiliations":[{"id":27615,"text":"Cornell Lab of Ornithology, Conservation Science Program","active":true,"usgs":false}],"preferred":false,"id":711968,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Partners in Flight Science Committee","contributorId":196951,"corporation":true,"usgs":false,"organization":"Partners in Flight Science Committee","id":711969,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70179386,"text":"70179386 - 2017 - Divergence and gene flow in the globally distributed blue-winged ducks","interactions":[],"lastModifiedDate":"2017-06-07T10:39:02","indexId":"70179386","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2190,"text":"Journal of Avian Biology","active":true,"publicationSubtype":{"id":10}},"title":"Divergence and gene flow in the globally distributed blue-winged ducks","docAbstract":"The ability to disperse over long distances can result in a high propensity for colonizing new geographic regions, including uninhabited continents, and lead to lineage diversification via allopatric speciation. However, high vagility can also result in gene flow between otherwise allopatric populations, and in some cases, parapatric or divergence-with-gene-flow models might be more applicable to widely distributed lineages. Here, we use five nuclear introns and the mitochondrial control region along with Bayesian models of isolation with migration to examine divergence, gene flow, and phylogenetic relationships within a cosmopolitan lineage comprising six species, the blue-winged ducks (genus Anas), which inhabit all continents except Antarctica. We found two primary sub-lineages, the globally-distributed shoveler group and the New World blue-winged/cinnamon teal group. The blue-winged/cinnamon sub-lineage is composed of sister taxa from North America and South America, and taxa with parapatric distributions are characterized by low to moderate levels of gene flow. In contrast, our data support strict allopatry for most comparisons within the shovelers. However, we found evidence of gene flow from the migratory, Holarctic northern shoveler (A. clypeata) and the more sedentary, African Cape shoveler (A. smithii) into the Australasian shoveler (A. rhynchotis), although we could not reject strict allopatry. Given the diverse mechanisms of speciation within this complex, the shovelers and blue-winged/cinnamon teals can serve as an effective model system for examining how the genome diverges under different evolutionary processes and how genetic variation is partitioned among highly dispersive taxa.","language":"English","publisher":"Wiley","doi":"10.1111/jav.00998","usgsCitation":"Nelson, J., Wilson, R.E., McCracken, K.G., Cumming, G., Joseph, L., Guay, P., and Peters, J., 2017, Divergence and gene flow in the globally distributed blue-winged ducks: Journal of Avian Biology, v. 48, no. 5, p. 640-649, https://doi.org/10.1111/jav.00998.","productDescription":"10 p.","startPage":"640","endPage":"649","ipdsId":"IP-071068","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":502591,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/journal_contribution/Divergence_and_gene_flow_in_the_globally_distributed_blue-winged_ducks/20599113","text":"External Repository"},{"id":438356,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7T72FK7","text":"USGS data release","linkHelpText":"Specimen and Genetic Information for Phylogeny of Blue-winged Ducks (Anas spp.), 2001-2011"},{"id":332672,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"48","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-21","publicationStatus":"PW","scienceBaseUri":"586781f7e4b0cd2dabe7c715","contributors":{"authors":[{"text":"Nelson, Joel","contributorId":177777,"corporation":false,"usgs":false,"family":"Nelson","given":"Joel","email":"","affiliations":[],"preferred":false,"id":657014,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, Robert E. 0000-0003-1800-0183 rewilson@usgs.gov","orcid":"https://orcid.org/0000-0003-1800-0183","contributorId":5718,"corporation":false,"usgs":true,"family":"Wilson","given":"Robert","email":"rewilson@usgs.gov","middleInitial":"E.","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":657013,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCracken, Kevin G.","contributorId":72309,"corporation":false,"usgs":false,"family":"McCracken","given":"Kevin","email":"","middleInitial":"G.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":657015,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cumming, Graeme","contributorId":177778,"corporation":false,"usgs":false,"family":"Cumming","given":"Graeme","affiliations":[],"preferred":false,"id":657016,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Joseph, Leo","contributorId":173726,"corporation":false,"usgs":false,"family":"Joseph","given":"Leo","affiliations":[],"preferred":false,"id":657017,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Guay, Patrick-Jean","contributorId":177779,"corporation":false,"usgs":false,"family":"Guay","given":"Patrick-Jean","email":"","affiliations":[],"preferred":false,"id":657018,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Peters, Jeffrey","contributorId":177780,"corporation":false,"usgs":false,"family":"Peters","given":"Jeffrey","email":"","affiliations":[],"preferred":false,"id":657019,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70187357,"text":"70187357 - 2017 - Spatiotemporal variability of snow depletion curves derived from SNODAS for the conterminous United States, 2004-2013","interactions":[],"lastModifiedDate":"2017-06-07T10:16:29","indexId":"70187357","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Spatiotemporal variability of snow depletion curves derived from SNODAS for the conterminous United States, 2004-2013","docAbstract":"<p><span>Assessment of water resources at a national scale is critical for understanding their vulnerability to future change in policy and climate. Representation of the spatiotemporal variability in snowmelt processes in continental-scale hydrologic models is critical for assessment of water resource response to continued climate change. Continental-extent hydrologic models such as the U.S. Geological Survey National Hydrologic Model (NHM) represent snowmelt processes through the application of snow depletion curves (SDCs). SDCs relate normalized snow water equivalent (SWE) to normalized snow covered area (SCA) over a snowmelt season for a given modeling unit. SDCs were derived using output from the operational Snow Data Assimilation System (SNODAS) snow model as daily 1-km gridded SWE over the conterminous United States. Daily SNODAS output were aggregated to a predefined watershed-scale geospatial fabric and used to also calculate SCA from October 1, 2004 to September 30, 2013. The spatiotemporal variability in SNODAS output at the watershed scale was evaluated through the spatial distribution of the median and standard deviation for the time period. Representative SDCs for each watershed-scale modeling unit over the conterminous United States (</span><i>n</i><span>&nbsp;=&nbsp;54,104) were selected using a consistent methodology and used to create categories of snowmelt based on SDC shape. The relation of SDC categories to the topographic and climatic variables allow for national-scale categorization of snowmelt processes.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12520","usgsCitation":"Driscoll, J.M., Hay, L.E., and Bock, A.R., 2017, Spatiotemporal variability of snow depletion curves derived from SNODAS for the conterminous United States, 2004-2013: Journal of the American Water Resources Association, v. 53, no. 3, p. 655-666, https://doi.org/10.1111/1752-1688.12520.","productDescription":"12 p.","startPage":"655","endPage":"666","ipdsId":"IP-079682","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":340646,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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 \"}}]}\n","volume":"53","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-13","publicationStatus":"PW","scienceBaseUri":"59084922e4b0fc4e448ffd3e","contributors":{"authors":[{"text":"Driscoll, Jessica M. 0000-0003-3097-9603 jdriscoll@usgs.gov","orcid":"https://orcid.org/0000-0003-3097-9603","contributorId":167585,"corporation":false,"usgs":true,"family":"Driscoll","given":"Jessica","email":"jdriscoll@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":693604,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hay, Lauren E. 0000-0003-3763-4595 lhay@usgs.gov","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":1287,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","email":"lhay@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":693605,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bock, Andrew R. 0000-0001-7222-6613 abock@usgs.gov","orcid":"https://orcid.org/0000-0001-7222-6613","contributorId":4580,"corporation":false,"usgs":true,"family":"Bock","given":"Andrew","email":"abock@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":693606,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70188091,"text":"70188091 - 2017 - Stable isotope analyses of oxygen (18O:17O:16O) and chlorine (37Cl:35Cl) in perchlorate: reference materials, calibrations, methods, and interferences","interactions":[],"lastModifiedDate":"2017-05-31T12:36:37","indexId":"70188091","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3233,"text":"Rapid Communications in Mass Spectrometry","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Stable isotope analyses of oxygen (<sup>18</sup>O:<sup>17</sup>O:<sup>16</sup>O) and chlorine (<sup>37</sup>Cl:<sup>35</sup>Cl) in perchlorate: reference materials, calibrations, methods, and interferences","title":"Stable isotope analyses of oxygen (18O:17O:16O) and chlorine (37Cl:35Cl) in perchlorate: reference materials, calibrations, methods, and interferences","docAbstract":"<p><strong>Rationale</strong></p><p>Perchlorate (ClO<sub>4</sub><sup>−</sup>) is a common trace constituent of water, soils, and plants; it has both natural and synthetic sources and is subject to biodegradation. The stable isotope ratios of Cl and O provide three independent quantities for ClO<sub>4</sub><sup>−</sup> source attribution and natural attenuation studies: δ<sup>37</sup>Cl, δ<sup>18</sup>O, and δ<sup>17</sup>O (or Δ<sup>17</sup>O or <sup>17</sup>Δ) values. Documented reference materials, calibration schemes, methods, and interferences will improve the reliability of such studies.</p><p><strong>Methods</strong></p><p>Three large batches of KClO<sub>4</sub> with contrasting isotopic compositions were synthesized and analyzed against VSMOW-SLAP, atmospheric O<sub>2</sub>, and international nitrate and chloride reference materials. Three analytical methods were tested for O isotopes: conversion of ClO<sub>4</sub><sup>−</sup> to CO for continuous-flow IRMS (CO-CFIRMS), decomposition to O<sub>2</sub> for dual-inlet IRMS (O2-DIIRMS), and decomposition to O<sub>2</sub> with molecular-sieve trap (O2-DIIRMS+T). For Cl isotopes, KCl produced by thermal decomposition of KClO<sub>4</sub> was reprecipitated as AgCl and converted into CH<sub>3</sub>Cl for DIIRMS.</p><p><strong>Results</strong></p><p>KClO<sub>4</sub> isotopic reference materials (USGS37, USGS38, USGS39) represent a wide range of Cl and O isotopic compositions, including non-mass-dependent O isotopic variation. Isotopic fractionation and exchange can affect O isotope analyses of ClO<sub>4</sub><sup>−</sup> depending on the decomposition method. Routine analyses can be adjusted for such effects by normalization, using reference materials prepared and analyzed as samples. Analytical errors caused by SO<sub>4</sub><sup>2</sup><sup>−</sup>, NO<sub>3</sub><sup>−</sup>, ReO<sub>4</sub><sup>2</sup><sup>−</sup>, and C-bearing contaminants include isotope mixing and fractionation effects on CO and O<sub>2</sub>, plus direct interference from CO<sub>2</sub> in the mass spectrometer. The results highlight the importance of effective purification of ClO<sub>4</sub><sup>−</sup> from environmental samples.</p><p><strong>Conclusions</strong></p><p>KClO<sub>4</sub> reference materials are available for testing methods and calibrating isotopic data for ClO<sub>4</sub><sup>−</sup> and other substances with widely varying Cl or O isotopic compositions. Current ClO<sub>4</sub><sup>−</sup>extraction, purification, and analysis techniques provide relative isotope-ratio measurements with uncertainties much smaller than the range of values in environmental ClO<sub>4</sub><sup>−</sup>, permitting isotopic evaluation of environmental ClO<sub>4</sub><sup>−</sup> sources and natural attenuation.</p>","language":"English","publisher":"Wiley","doi":"10.1002/rcm.7751","usgsCitation":"Bohlke, J., Mroczkowski, S.J., Sturchio, N.C., Heraty, L.J., Richman, K.W., Sullivan, D.B., Griffith, K.N., Gu, B., and Hatzinger, P., 2017, Stable isotope analyses of oxygen (18O:17O:16O) and chlorine (37Cl:35Cl) in perchlorate: reference materials, calibrations, methods, and interferences: Rapid Communications in Mass Spectrometry, v. 31, no. 1, p. 85-110, https://doi.org/10.1002/rcm.7751.","productDescription":"26 p.","startPage":"85","endPage":"110","ipdsId":"IP-079870","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":341925,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-12","publicationStatus":"PW","scienceBaseUri":"592fd63de4b0e9bd0ea896e9","contributors":{"authors":[{"text":"Bohlke, J.K. 0000-0001-5693-6455 jkbohlke@usgs.gov","orcid":"https://orcid.org/0000-0001-5693-6455","contributorId":191103,"corporation":false,"usgs":true,"family":"Bohlke","given":"J.K.","email":"jkbohlke@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":696640,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mroczkowski, Stanley J. 0000-0001-8026-6025 smroczko@usgs.gov","orcid":"https://orcid.org/0000-0001-8026-6025","contributorId":2628,"corporation":false,"usgs":true,"family":"Mroczkowski","given":"Stanley","email":"smroczko@usgs.gov","middleInitial":"J.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":696641,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sturchio, Neil C.","contributorId":149375,"corporation":false,"usgs":false,"family":"Sturchio","given":"Neil","email":"","middleInitial":"C.","affiliations":[{"id":15289,"text":"University of Illinois, Ven Te Chow Hydrosystems Laboratory","active":true,"usgs":false}],"preferred":false,"id":696642,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Heraty, Linnea J.","contributorId":192520,"corporation":false,"usgs":false,"family":"Heraty","given":"Linnea","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":696643,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Richman, Kent W.","contributorId":192519,"corporation":false,"usgs":false,"family":"Richman","given":"Kent","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":696644,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sullivan, Donald B.","contributorId":192517,"corporation":false,"usgs":false,"family":"Sullivan","given":"Donald","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":696645,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Griffith, Kris N.","contributorId":192518,"corporation":false,"usgs":false,"family":"Griffith","given":"Kris","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":696646,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gu, Baohua","contributorId":15504,"corporation":false,"usgs":true,"family":"Gu","given":"Baohua","affiliations":[],"preferred":false,"id":696648,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hatzinger, Paul B.","contributorId":43204,"corporation":false,"usgs":true,"family":"Hatzinger","given":"Paul B.","affiliations":[],"preferred":false,"id":696647,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70193740,"text":"70193740 - 2017 - Automatic mapping of the base of aquifer — A case study from Morrill, Nebraska","interactions":[],"lastModifiedDate":"2017-11-06T11:01:35","indexId":"70193740","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3906,"text":"Interpretation","active":true,"publicationSubtype":{"id":10}},"title":"Automatic mapping of the base of aquifer — A case study from Morrill, Nebraska","docAbstract":"<p><span>When a geologist sets up a geologic model, various types of disparate information may be available, such as exposures, boreholes, and (or) geophysical data. In recent years, the amount of geophysical data available has been increasing, a trend that is only expected to continue. It is nontrivial (and often, in practice, impossible) for the geologist to take all the details of the geophysical data into account when setting up a geologic model. We have developed an approach that allows for the objective quantification of information from geophysical data and borehole observations in a way that is easy to integrate in the geologic modeling process. This will allow the geologist to make a geologic interpretation that is consistent with the geophysical information at hand. We have determined that automated interpretation of geologic layer boundaries using information from boreholes and geophysical data alone can provide a good geologic layer model, even before manual interpretation has begun. The workflow is implemented on a set of boreholes and airborne electromagnetic (AEM) data from Morrill, Nebraska. From the borehole logs, information about the depth to the base of aquifer (BOA) is extracted and used together with the AEM data to map a surface that represents this geologic contact. Finally, a comparison between our automated approach and a previous manual mapping of the BOA in the region validates the quality of the proposed method and suggests that this workflow will allow a much faster and objective geologic modeling process that is consistent with the available data.</span><br></p>","language":"English","publisher":"Society of Exploration Geophysicists","doi":"10.1190/INT-2016-0195.1","usgsCitation":"Gulbrandsen, M.L., Ball, L.B., Minsley, B.J., and Hansen, T.M., 2017, Automatic mapping of the base of aquifer — A case study from Morrill, Nebraska: Interpretation, v. 5, no. 2, p. T231-T241, https://doi.org/10.1190/INT-2016-0195.1.","productDescription":"11 p.","startPage":"T231","endPage":"T241","ipdsId":"IP-081039","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":348252,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","city":"Morrill","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -104.05975341796875,\n              41.9167\n            ],\n            [\n              -103.8333,\n              41.9167\n            ],\n            [\n              -103.8333,\n              42.1667\n            ],\n            [\n              -104.05975341796875,\n              42.1667\n            ],\n            [\n              -104.05975341796875,\n              41.9167\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"5","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a07e8f7e4b09af898c8cbd9","contributors":{"authors":[{"text":"Gulbrandsen, Mats Lundh","contributorId":199734,"corporation":false,"usgs":false,"family":"Gulbrandsen","given":"Mats","email":"","middleInitial":"Lundh","affiliations":[{"id":27198,"text":"Niels Bohr Institute, University of Copenhagen","active":true,"usgs":false}],"preferred":false,"id":720136,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ball, Lyndsay B. 0000-0002-6356-4693 lbball@usgs.gov","orcid":"https://orcid.org/0000-0002-6356-4693","contributorId":1138,"corporation":false,"usgs":true,"family":"Ball","given":"Lyndsay","email":"lbball@usgs.gov","middleInitial":"B.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":720135,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Minsley, Burke J. 0000-0003-1689-1306 bminsley@usgs.gov","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":697,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","email":"bminsley@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":720137,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hansen, Thomas Mejer","contributorId":199735,"corporation":false,"usgs":false,"family":"Hansen","given":"Thomas","email":"","middleInitial":"Mejer","affiliations":[{"id":27198,"text":"Niels Bohr Institute, University of Copenhagen","active":true,"usgs":false}],"preferred":false,"id":720138,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70187141,"text":"ofr20171029 - 2017 - Guidelines for preparation of State water-use estimates for 2015","interactions":[],"lastModifiedDate":"2017-05-02T08:59:14","indexId":"ofr20171029","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1029","title":"Guidelines for preparation of State water-use estimates for 2015","docAbstract":"<p>The U.S. Geological Survey (USGS) has estimated the use of water in the United States at 5-year intervals since 1950. This report describes the water-use categories and data elements used for the national water-use compilation conducted as part of the USGS National Water-Use Science Project. The report identifies sources of water-use information, provides standard methods and techniques for estimating water use at the county level, and outlines steps for preparing documentation for the United States, the District of Columbia, Puerto Rico, and the U.S. Virgin Islands.</p><p>As part of this USGS program to document water use on a national scale, estimates of water withdrawals for the categories of public supply, self-supplied domestic, industrial, irrigation, and thermoelectric power are prepared for each county in each State, District, or territory by using the guidelines in this report. County estimates of water withdrawals for aquaculture, livestock, and mining are prepared for each State by using a county-based national model, although water-use programs in each State or Water Science Center have the option of producing independent county estimates of water withdrawals for these categories. Estimates of water withdrawals and consumptive use for thermoelectric power will be aggregated to the county level for each State by the national project; additionally, irrigation consumptive use at the county level will also be provided, although study chiefs in each State have the option of producing independent county estimates of water withdrawals and consumptive use for these categories.</p><p>Estimates of deliveries of water from public supplies for domestic use by county also will be prepared for each State. As a result, total domestic water use can be determined for each State by combining self-supplied domestic withdrawals and public-supplied domestic deliveries. Fresh groundwater and surface-water estimates will be prepared for all categories of use, and saline groundwater and surface-water estimates by county will be prepared for the categories of public supply, industrial, mining, and thermoelectric power. Power production for thermoelectric power and irrigated acres by irrigation system type will be compiled. If data are available, reclaimed-wastewater use will be compiled for the public-supply, industrial, mining, thermoelectric-power, and irrigation categories.</p><p>Optional water-use categories are commercial, hydroelectric power, and wastewater treatment. Optional data elements are public-supply deliveries to commercial, industrial, and thermoelectric-power users; consumptive use (for categories other than thermoelectric power and irrigation); irrigation conveyance loss; and number of facilities. Aggregation of water-use data by stream basin (eight-digit hydrologic unit code) and principal aquifers also is optional.</p><p>Water-use data compiled by the States will be stored in the USGS Aggregate Water-Use Data System (AWUDS). This database is a comprehensive aggregated database designed to store mandatory and optional data elements. AWUDS contains several routines that can be used for quality assurance and quality control of the data, and AWUDS produces tables of water-use data from the previous compilations.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171029","collaboration":"National Water-Use Science Project","usgsCitation":"Bradley, M.W., comp., 2017, Guidelines for preparation of State water-use estimates for 2015: U.S. Geological Survey Open-File Report 2017–1029, 54 p., https://doi.org/10.3133/ofr20171029.","productDescription":"viii, 54 p.","numberOfPages":"66","onlineOnly":"Y","ipdsId":"IP-078880","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":340450,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1029/coverthb2.jpg"},{"id":340259,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1029/ofr20171029.pdf","text":"Report","size":"719 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1029"},{"id":340258,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1029/coverthb.jpg"}],"contact":"<p>Director, Lower Mississippi-Gulf Water Science Center—Tennessee <br>640 Grassmere&nbsp;Park<br>Suite 100<br>Nashville, TN 37211</p><p><a href=\"https://tn.water.usgs.gov/\" data-mce-href=\"https://tn.water.usgs.gov/\">https://tn.water.usgs.gov</a>/</p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Water-Use Compilation Requirements<br></li><li>Compilation Methods<br></li><li>Public Supply<br></li><li>Self-Supplied Domestic<br></li><li>Commercial<br></li><li>Industrial<br></li><li>Thermoelectric Power<br></li><li>Mining<br></li><li>Livestock<br></li><li>Aquaculture<br></li><li>Irrigation<br></li><li>Hydroelectric Power<br></li><li>Wastewater Treatment<br></li><li>Reservoir Evaporation<br></li><li>References<br></li><li>Glossary<br></li><li>Appendix 1. Coding Forms for the Compilation of Water-Use Data<br></li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2017-05-01","noUsgsAuthors":false,"publicationDate":"2017-05-01","publicationStatus":"PW","scienceBaseUri":"59084922e4b0fc4e448ffd40","contributors":{"compilers":[{"text":"Bradley, Mike 0000-0002-2979-265X mbradley@usgs.gov","orcid":"https://orcid.org/0000-0002-2979-265X","contributorId":582,"corporation":false,"usgs":true,"family":"Bradley","given":"Mike","email":"mbradley@usgs.gov","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":692793,"contributorType":{"id":3,"text":"Compilers"},"rank":1}]}}
,{"id":70195117,"text":"70195117 - 2017 - Advancing coastal ocean modelling, analysis, and prediction for the US Integrated Ocean Observing System","interactions":[],"lastModifiedDate":"2021-10-26T15:52:22.76388","indexId":"70195117","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5621,"text":"Journal of Operational Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Advancing coastal ocean modelling, analysis, and prediction for the US Integrated Ocean Observing System","docAbstract":"<p><span>This paper outlines strategies that would advance coastal ocean modelling, analysis and prediction as a complement to the observing and data management activities of the coastal components of the US Integrated Ocean Observing System (IOOS®) and the Global Ocean Observing System (GOOS). The views presented are the consensus of a group of US-based researchers with a cross-section of coastal oceanography and ocean modelling expertise and community representation drawn from Regional and US Federal partners in IOOS. Priorities for research and development are suggested that would enhance the value of IOOS observations through model-based synthesis, deliver better model-based information products, and assist the design, evaluation, and operation of the observing system itself. The proposed priorities are: model coupling, data assimilation, nearshore processes, cyberinfrastructure and model skill assessment, modelling for observing system design, evaluation and operation, ensemble prediction, and fast predictors. Approaches are suggested to accomplish substantial progress in a 3–8-year timeframe. In addition, the group proposes steps to promote collaboration between research and operations groups in Regional Associations, US Federal Agencies, and the international ocean research community in general that would foster coordination on scientific and technical issues, and strengthen federal–academic partnerships benefiting IOOS stakeholders and end users.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/1755876X.2017.1322026","usgsCitation":"Wilkin, J.L., Rosenfeld, L., Allen, A., Baltes, R., Baptista, A., He, R., Hogan, P., Kurapov, A., Mehra, A., Quintrell, J., Schwab, D., Signell, R.P., and Smith, J., 2017, Advancing coastal ocean modelling, analysis, and prediction for the US Integrated Ocean Observing System: Journal of Operational Oceanography, v. 10, no. 2, p. 115-126, https://doi.org/10.1080/1755876X.2017.1322026.","productDescription":"12 p.","startPage":"115","endPage":"126","ipdsId":"IP-086129","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469897,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/1755876x.2017.1322026","text":"Publisher Index Page"},{"id":351300,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"2","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-20","publicationStatus":"PW","scienceBaseUri":"5a7c1e7ce4b00f54eb229351","contributors":{"authors":[{"text":"Wilkin, John L. 0000-0002-5444-9466","orcid":"https://orcid.org/0000-0002-5444-9466","contributorId":28872,"corporation":false,"usgs":true,"family":"Wilkin","given":"John","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":727018,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosenfeld, Leslie 0000-0002-0768-819X","orcid":"https://orcid.org/0000-0002-0768-819X","contributorId":140915,"corporation":false,"usgs":false,"family":"Rosenfeld","given":"Leslie","email":"","affiliations":[{"id":13614,"text":"Naval Postgraduate School, Monterey, CA","active":true,"usgs":false}],"preferred":false,"id":727019,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, Arthur 0000-0002-6061-9396","orcid":"https://orcid.org/0000-0002-6061-9396","contributorId":70870,"corporation":false,"usgs":true,"family":"Allen","given":"Arthur","email":"","affiliations":[],"preferred":false,"id":727020,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baltes, Rebecca 0000-0003-3121-1495","orcid":"https://orcid.org/0000-0003-3121-1495","contributorId":201818,"corporation":false,"usgs":false,"family":"Baltes","given":"Rebecca","email":"","affiliations":[{"id":36259,"text":"U.S. IOOS Program Office","active":true,"usgs":false}],"preferred":false,"id":727021,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baptista, Antonio 0000-0002-7641-5937","orcid":"https://orcid.org/0000-0002-7641-5937","contributorId":202188,"corporation":false,"usgs":false,"family":"Baptista","given":"Antonio","email":"","affiliations":[],"preferred":false,"id":727022,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"He, Ruoying","contributorId":68029,"corporation":false,"usgs":true,"family":"He","given":"Ruoying","affiliations":[],"preferred":false,"id":727773,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hogan, Patrick 0000-0001-5931-3675","orcid":"https://orcid.org/0000-0001-5931-3675","contributorId":201819,"corporation":false,"usgs":false,"family":"Hogan","given":"Patrick","email":"","affiliations":[{"id":36260,"text":"U.S. Naval Research Laboratory and GCOOS","active":true,"usgs":false}],"preferred":false,"id":727024,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kurapov, Alexander","contributorId":201820,"corporation":false,"usgs":false,"family":"Kurapov","given":"Alexander","email":"","affiliations":[{"id":36261,"text":"Oregon State University and NANOOS","active":true,"usgs":false}],"preferred":false,"id":727025,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mehra, Avichal","contributorId":201821,"corporation":false,"usgs":false,"family":"Mehra","given":"Avichal","email":"","affiliations":[{"id":36262,"text":"NOAA National Centers for Environmental Prediction","active":true,"usgs":false}],"preferred":false,"id":727026,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Quintrell, Josie","contributorId":201822,"corporation":false,"usgs":false,"family":"Quintrell","given":"Josie","email":"","affiliations":[{"id":36263,"text":"IOOS Association","active":true,"usgs":false}],"preferred":false,"id":727027,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Schwab, David","contributorId":202190,"corporation":false,"usgs":false,"family":"Schwab","given":"David","affiliations":[],"preferred":false,"id":727028,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Signell, Richard P. 0000-0003-0682-9613 rsignell@usgs.gov","orcid":"https://orcid.org/0000-0003-0682-9613","contributorId":140906,"corporation":false,"usgs":true,"family":"Signell","given":"Richard","email":"rsignell@usgs.gov","middleInitial":"P.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":727017,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Smith, Jane","contributorId":202191,"corporation":false,"usgs":false,"family":"Smith","given":"Jane","affiliations":[],"preferred":false,"id":727029,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70195433,"text":"70195433 - 2017 - Neutron scattering measurements of carbon dioxide adsorption in pores within the Marcellus Shale: Implications for sequestration","interactions":[],"lastModifiedDate":"2018-04-02T10:03:30","indexId":"70195433","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Neutron scattering measurements of carbon dioxide adsorption in pores within the Marcellus Shale: Implications for sequestration","docAbstract":"<p><span>Shale is an increasingly viable source of natural gas and a potential candidate for geologic CO</span><sub>2</sub><span>sequestration. Understanding the gas adsorption behavior on shale is necessary for the design of optimal gas recovery and sequestration projects. In the present study neutron diffraction and small-angle neutron scattering measurements of adsorbed CO</span><sub>2</sub><span><span>&nbsp;</span>in Marcellus Shale samples were conducted on the Near and InterMediate Range Order Diffractometer (NIMROD) at the ISIS Pulsed Neutron and Muon Source, STFC Rutherford Appleton Laboratory along an adsorption isotherm of 22 °C and pressures of 25 and 40 bar. Additional measurements were conducted at approximately 22 and 60 °C at the same pressures on the General-Purpose Small-Angle Neutron Scattering (GP-SANS) instrument at Oak Ridge National Laboratory. The structures investigated (pores) for CO</span><sub>2</sub><span><span>&nbsp;</span>adsorption range in size from Å level to ∼50 nm. The results indicate that, using the conditions investigated densification or condensation effects occurred in all accessible pores. The data suggest that at 22 °C the CO</span><sub>2</sub><span><span>&nbsp;</span>has liquid-like properties when confined in pores of around 1 nm radius at pressures as low as 25 bar. Many of the 2.5 nm pores, 70% of 2 nm pores, most of the &lt;1 nm pores, and all pores &lt;0.25 nm, are inaccessible or closed to CO</span><sub>2</sub><span>, suggesting that despite the vast numbers of micropores in shale, the micropores will be unavailable for storage for geologic CO</span><sub>2</sub><span><span>&nbsp;</span>sequestration.</span></p>","language":"English","publisher":"ACS","doi":"10.1021/acs.est.6b05707","usgsCitation":"Stefanopoulos, K.L., Youngs, T.G., Sakurovs, R., Ruppert, L.F., Bahadur, J., and Melnichenko, Y.B., 2017, Neutron scattering measurements of carbon dioxide adsorption in pores within the Marcellus Shale: Implications for sequestration: Environmental Science & Technology, v. 51, no. 11, p. 6515-6521, https://doi.org/10.1021/acs.est.6b05707.","productDescription":"7 p.","startPage":"6515","endPage":"6521","ipdsId":"IP-081182","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":469890,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1356718","text":"Publisher Index Page"},{"id":352996,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"11","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-12","publicationStatus":"PW","scienceBaseUri":"5afee886e4b0da30c1bfc462","contributors":{"authors":[{"text":"Stefanopoulos, Konstantinos L.","contributorId":202501,"corporation":false,"usgs":false,"family":"Stefanopoulos","given":"Konstantinos","email":"","middleInitial":"L.","affiliations":[{"id":36464,"text":"Institute of Nanoscience and Nanotechnology, NCSR “Demokritos”, Greece","active":true,"usgs":false}],"preferred":false,"id":728583,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Youngs, Tristan G. A.","contributorId":202502,"corporation":false,"usgs":false,"family":"Youngs","given":"Tristan","email":"","middleInitial":"G. A.","affiliations":[{"id":36465,"text":"Disordered Materials Group (ISIS), STFC Rutherford Appleton Laboratory, U.K.","active":true,"usgs":false}],"preferred":false,"id":728584,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sakurovs, Richard 0000-0003-0967-6560","orcid":"https://orcid.org/0000-0003-0967-6560","contributorId":196194,"corporation":false,"usgs":false,"family":"Sakurovs","given":"Richard","email":"","affiliations":[],"preferred":false,"id":728585,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ruppert, Leslie F. 0000-0002-7453-1061 lruppert@usgs.gov","orcid":"https://orcid.org/0000-0002-7453-1061","contributorId":660,"corporation":false,"usgs":true,"family":"Ruppert","given":"Leslie","email":"lruppert@usgs.gov","middleInitial":"F.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":728582,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bahadur, Jitendra","contributorId":202499,"corporation":false,"usgs":false,"family":"Bahadur","given":"Jitendra","email":"","affiliations":[{"id":36462,"text":"Bhabha Atomic Research Centre","active":true,"usgs":false}],"preferred":false,"id":728586,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Melnichenko, Yuri B.","contributorId":196197,"corporation":false,"usgs":false,"family":"Melnichenko","given":"Yuri","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":728587,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70192769,"text":"70192769 - 2017 - Distribution and abundance of Millicoma Dace in the Coos River Basin, Oregon","interactions":[],"lastModifiedDate":"2017-11-10T10:13:48","indexId":"70192769","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2901,"text":"Northwestern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Distribution and abundance of Millicoma Dace in the Coos River Basin, Oregon","docAbstract":"<p><span>The Millicoma Dace&nbsp;</span><i><i>Rhinichthys cataractae</i></i><span><span>&nbsp;</span>is a form of Longnose Dace endemic to the Coos River drainage in southwestern Oregon. Sparse species records in the Oregon State University Ichthyology Collection and database and infrequent recent encounters prompted surveys to assess the current status and distribution of the species. In 2014, we surveyed locations that had historically supported Millicoma Dace using backpack electrofishing to describe their current distribution and abundance at these locations. In 2015, we extended these surveys further upstream in the South Coos River basin, outside of the documented historical range. We used an N-mixture model to estimate abundance and capture probability for Millicoma Dace at each sampling location. We evaluated the effects of habitat covariates on both capture probability and abundance at each sample site. We found Millicoma Dace were widespread throughout their historical range and in the South Coos River sites outside of their documented historical range. We only found Millicoma Dace associated with native fishes; we did not collect any nonnative fish during our surveys. We collected Millicoma Dace exclusively from swift-water habitats, which were relatively uncommon in the basin, and found them typically associated with cobble or boulder substrates. Millicoma Dace were most abundant in the South Fork Coos and West Fork Millicoma River subbasins. We estimated capture probabilities for Millicoma Dace ranging from 9% when substrate was dominated by bedrock to 28% when substrate was dominated by cobble or gravel. Abundance estimates ranged from 1 to 560 dace per sampling location with a total estimated abundance (sum of site estimates) of over 3200 dace for the sites we sampled.</span></p>","language":"English","publisher":"Society for Northwestern Vertebrate Biology","doi":"10.1898/NWN16-15.1","usgsCitation":"Scheerer, P.D., Peterson, J., and Clements, S., 2017, Distribution and abundance of Millicoma Dace in the Coos River Basin, Oregon: Northwestern Naturalist, v. 98, no. 1, p. 39-47, https://doi.org/10.1898/NWN16-15.1.","productDescription":"9 p.","startPage":"39","endPage":"47","ipdsId":"IP-078974","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":348439,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Coos River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -124.46411132812499,\n              43.00866413845207\n            ],\n            [\n              -122.90954589843749,\n              43.00866413845207\n            ],\n            [\n              -122.90954589843749,\n              43.95328204198018\n            ],\n            [\n              -124.46411132812499,\n              43.95328204198018\n            ],\n            [\n              -124.46411132812499,\n              43.00866413845207\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"98","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a0425b9e4b0dc0b45b45381","contributors":{"authors":[{"text":"Scheerer, Paul D.","contributorId":171713,"corporation":false,"usgs":false,"family":"Scheerer","given":"Paul","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":721120,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peterson, James T. 0000-0002-7709-8590 james_peterson@usgs.gov","orcid":"https://orcid.org/0000-0002-7709-8590","contributorId":2111,"corporation":false,"usgs":true,"family":"Peterson","given":"James","email":"james_peterson@usgs.gov","middleInitial":"T.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":716870,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clements, Shaun","contributorId":171685,"corporation":false,"usgs":false,"family":"Clements","given":"Shaun","email":"","affiliations":[],"preferred":false,"id":721121,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70192831,"text":"70192831 - 2017 - A report on upgraded seismic monitoring stations in Myanmar: Station performance and site response","interactions":[],"lastModifiedDate":"2017-10-30T16:33:18","indexId":"70192831","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"A report on upgraded seismic monitoring stations in Myanmar: Station performance and site response","docAbstract":"<p><span>Myanmar is in a tectonically complex region between the eastern edge of the Himalayan collision zone and the northern end of the Sunda megathrust. Until recently, earthquake monitoring and research efforts have been hampered by a lack of modern instrumentation and communication infrastructure. In January 2016, a major upgrade of the Myanmar National Seismic Network (MNSN; network code MM) was undertaken to improve earthquake monitoring capability. We installed five permanent broadband and strong‐motion seismic stations and real‐time data telemetry using newly improved cellular networks. Data are telemetered to the MNSN hub in Nay Pyi Taw and archived at the Incorporated Research Institutions for Seismology Data Management Center. We analyzed station noise characteristics and site response using noise and events recorded over the first six months of station operation. Background noise characteristics vary across the array, but indicate that the new stations are performing well. MM stations recorded more than 20 earthquakes of&nbsp;</span><i>M</i><span>≥4.5 within Myanmar and its immediate surroundings, including an<span>&nbsp;</span></span><i>M</i><span>&nbsp;6.8 earthquake located northwest of Mandalay on 13 April 2016 and the<span>&nbsp;</span></span><i>M</i><sub>w</sub><span>&nbsp;6.8 Chauk event on 24 August 2016. We use this new dataset to calculate horizontal‐to‐vertical spectral ratios, which provide a preliminary characterization of site response of the upgraded MM stations.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220160168","usgsCitation":"Thiam, H.N., Min Htwe, Y.M., Kyaw, T.L., Tun, P.P., Min, Z., Htwe, S.H., Aung, T.M., Lin, K.K., Aung, M.M., De Cristofaro, J., Franke, M., Radman, S., Lepiten, E., Wolin, E., and Hough, S.E., 2017, A report on upgraded seismic monitoring stations in Myanmar: Station performance and site response: Seismological Research Letters, v. 88, no. 3, p. 926-934, https://doi.org/10.1785/0220160168.","productDescription":"9 p.","startPage":"926","endPage":"934","ipdsId":"IP-084392","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":347753,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Myanmar","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[99.54331,20.1866],[98.95968,19.75298],[98.25372,19.7082],[97.79778,18.62708],[97.3759,18.44544],[97.85912,17.56795],[98.49376,16.83784],[98.90335,16.17782],[98.53738,15.3085],[98.19207,15.1237],[98.43082,14.62203],[99.09776,13.8275],[99.21201,13.26929],[99.19635,12.80475],[99.58729,11.89276],[99.03812,10.96055],[98.55355,9.93296],[98.45717,10.67527],[98.76455,11.44129],[98.42834,12.03299],[98.50957,13.12238],[98.1036,13.64046],[97.77773,14.83729],[97.59707,16.10057],[97.16454,16.92873],[96.50577,16.42724],[95.36935,15.71439],[94.8084,15.80345],[94.1888,16.03794],[94.53349,17.27724],[94.32482,18.21351],[93.54099,19.36649],[93.66325,19.72696],[93.07828,19.85514],[92.36855,20.67088],[92.30323,21.47549],[92.65226,21.32405],[92.67272,22.04124],[93.16613,22.27846],[93.06029,22.70311],[93.28633,23.04366],[93.32519,24.07856],[94.10674,23.85074],[94.55266,24.67524],[94.60325,25.1625],[95.15515,26.00131],[95.12477,26.57357],[96.41937,27.26459],[97.134,27.08377],[97.05199,27.69906],[97.40256,27.88254],[97.32711,28.26158],[97.91199,28.33595],[98.24623,27.74722],[98.68269,27.50881],[98.71209,26.74354],[98.67184,25.9187],[97.72461,25.08364],[97.60472,23.8974],[98.66026,24.06329],[98.89875,23.14272],[99.53199,22.94904],[99.2409,22.11831],[99.98349,21.74294],[100.41654,21.55884],[101.15003,21.84998],[101.18001,21.43657],[100.3291,20.78612],[100.11599,20.41785],[99.54331,20.1866]]]},\"properties\":{\"name\":\"Myanmar\"}}]}","volume":"88","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-22","publicationStatus":"PW","scienceBaseUri":"59f83a37e4b063d5d30980e1","contributors":{"authors":[{"text":"Thiam, Hrin Nei","contributorId":198766,"corporation":false,"usgs":false,"family":"Thiam","given":"Hrin","email":"","middleInitial":"Nei","affiliations":[],"preferred":false,"id":717099,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Min Htwe, Yin Myo","contributorId":198767,"corporation":false,"usgs":false,"family":"Min Htwe","given":"Yin","email":"","middleInitial":"Myo","affiliations":[],"preferred":false,"id":717100,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kyaw, Tun Lin","contributorId":198768,"corporation":false,"usgs":false,"family":"Kyaw","given":"Tun","email":"","middleInitial":"Lin","affiliations":[],"preferred":false,"id":717101,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tun, Pa Pa","contributorId":198769,"corporation":false,"usgs":false,"family":"Tun","given":"Pa","email":"","middleInitial":"Pa","affiliations":[],"preferred":false,"id":717102,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Min, Zaw","contributorId":198770,"corporation":false,"usgs":false,"family":"Min","given":"Zaw","email":"","affiliations":[],"preferred":false,"id":717103,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Htwe, Sun Hninn","contributorId":198771,"corporation":false,"usgs":false,"family":"Htwe","given":"Sun","email":"","middleInitial":"Hninn","affiliations":[],"preferred":false,"id":717104,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Aung, Tin Myo","contributorId":198772,"corporation":false,"usgs":false,"family":"Aung","given":"Tin","email":"","middleInitial":"Myo","affiliations":[],"preferred":false,"id":717105,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lin, Kyaw Kyaw","contributorId":198773,"corporation":false,"usgs":false,"family":"Lin","given":"Kyaw","email":"","middleInitial":"Kyaw","affiliations":[],"preferred":false,"id":717106,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Aung, Myat Min","contributorId":198774,"corporation":false,"usgs":false,"family":"Aung","given":"Myat","email":"","middleInitial":"Min","affiliations":[],"preferred":false,"id":717107,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"De Cristofaro, Jason 0000-0001-8179-2393 jdecristofaro@usgs.gov","orcid":"https://orcid.org/0000-0001-8179-2393","contributorId":198779,"corporation":false,"usgs":true,"family":"De Cristofaro","given":"Jason","email":"jdecristofaro@usgs.gov","affiliations":[],"preferred":true,"id":717112,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Franke, Mathias","contributorId":198775,"corporation":false,"usgs":false,"family":"Franke","given":"Mathias","email":"","affiliations":[],"preferred":false,"id":717108,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Radman, Stefan","contributorId":198776,"corporation":false,"usgs":false,"family":"Radman","given":"Stefan","email":"","affiliations":[],"preferred":false,"id":717109,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Lepiten, Elouie","contributorId":198777,"corporation":false,"usgs":false,"family":"Lepiten","given":"Elouie","email":"","affiliations":[],"preferred":false,"id":717110,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Wolin, Emily 0000-0003-1610-1191 ewolin@usgs.gov","orcid":"https://orcid.org/0000-0003-1610-1191","contributorId":198778,"corporation":false,"usgs":true,"family":"Wolin","given":"Emily","email":"ewolin@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":717111,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Hough, Susan E. 0000-0002-5980-2986 hough@usgs.gov","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":587,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"hough@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":717098,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}}
,{"id":70191452,"text":"70191452 - 2017 - Migratory behavior of adult sea lamprey and cumulative passage performance through four fishways","interactions":[],"lastModifiedDate":"2017-10-13T11:30:42","indexId":"70191452","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","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":"Migratory behavior of adult sea lamprey and cumulative passage performance through four fishways","docAbstract":"<p><span>This article describes a study of PIT-tagged sea lamprey (</span><i>Petromyzon marinus</i><span>) ascending four fishways comprising three designs at two dams on the Connecticut River, USA. Migration between dams was rapid (median migration rate = 23 km·day</span><sup>−1</sup><span>). Movement through the fishways was much slower, however (median = 0.02–0.33 km·day</span><sup>−1</sup><span>). Overall delay at dams was substantial (median = 13.6–14.6 days); many fish failed to pass (percent passage ranged from 29% to 55%, depending on fishway), and repeated passage attempts compounded delay for both passers and failers. Cox regression revealed that fishway entry rates were influenced by flow, temperature, and diel cycle, with most lampreys entering at night and at elevated flows, but with no apparent effect of sex or length. Overall delay was influenced by slow movement through the fishways, but repeated failures were the primary factor determining delay. These data suggest that although some lamprey were able to pass fishways, they did so with difficulty, and delays incurred as they attempted to pass may act to limit their distribution within their native range.</span></p>","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2016-0089","issn":"0706-652X","usgsCitation":"Castro-Santos, T.R., Shi, X., and Haro, A., 2017, Migratory behavior of adult sea lamprey and cumulative passage performance through four fishways: Canadian Journal of Fisheries and Aquatic Sciences, v. 5, no. 74, p. 790-800, https://doi.org/10.1139/cjfas-2016-0089.","productDescription":"11 p.","startPage":"790","endPage":"800","ipdsId":"IP-060899","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":469877,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/75797","text":"External Repository"},{"id":346579,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"74","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59e1d099e4b05fe04cd117b4","contributors":{"authors":[{"text":"Castro-Santos, Theodore R. 0000-0003-2575-9120 tcastrosantos@usgs.gov","orcid":"https://orcid.org/0000-0003-2575-9120","contributorId":3321,"corporation":false,"usgs":true,"family":"Castro-Santos","given":"Theodore","email":"tcastrosantos@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":712332,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shi, Xiaotao","contributorId":197033,"corporation":false,"usgs":false,"family":"Shi","given":"Xiaotao","email":"","affiliations":[],"preferred":false,"id":712333,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haro, Alexander 0000-0002-7188-9172 aharo@usgs.gov","orcid":"https://orcid.org/0000-0002-7188-9172","contributorId":139198,"corporation":false,"usgs":true,"family":"Haro","given":"Alexander","email":"aharo@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":712334,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70191602,"text":"70191602 - 2017 - A paleoseismic transect across the northwestern Basin and Range Province, northwestern Nevada and northeastern California, USA","interactions":[],"lastModifiedDate":"2017-10-25T10:58:43","indexId":"70191602","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"A paleoseismic transect across the northwestern Basin and Range Province, northwestern Nevada and northeastern California, USA","docAbstract":"<p><span>We use new and existing data to compile a record of ∼18 latest Quaternary large-magnitude surface-rupturing earthquakes on 7 fault zones in the northwestern Basin and Range Province of northwestern Nevada and northeastern California. The most recent earthquake on all faults postdates the ca. 18–15 ka last glacial highstand of pluvial Lake Lahontan and other pluvial lakes in the region. These lacustrine data provide a window in which we calculate latest Quaternary vertical slip rates and compare them with rates of modern deformation in a global positioning system (GPS) transect spanning the region. Average vertical slip rates on these fault zones range from 0.1 to 0.8 mm/yr and total ∼2 mm/yr across a 265-km-wide transect from near Paradise Valley, Nevada, to the Warner Mountains in California. We converted vertical slip rates to horizontal extension rates using fault dips of 30°–60°, and then compared the extension rates to GPS-derived rates of modern (last 7–9 yr) deformation. Our preferred fault dip values (45°–55°) yield estimated long-term extension rates (1.3–1.9 mm/yr) that underestimate our modern rate (2.4 mm/yr) by ∼21%–46%. The most likely sources of this underestimate are geologically unrecognizable deformation from moderate-sized earthquakes and unaccounted-for coseismic off-fault deformation from large surface-rupturing earthquakes. However, fault dip values of ≤40° yield long-term rates comparable to or greater than modern rates, so an alternative explanation is that fault dips are closer to 40° than our preferred values. We speculate that the large component of right-lateral shear apparent in the GPS signal is partitioned on faults with primary strike-slip displacement, such as the Long Valley fault zone, and as not easily detected oblique slip on favorably oriented normal faults in the region.</span></p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES01380.1","usgsCitation":"Personius, S., Briggs, R.W., Maharrey, J.Z., Angster, S.J., and Mahan, S.A., 2017, A paleoseismic transect across the northwestern Basin and Range Province, northwestern Nevada and northeastern California, USA: Geosphere, v. 13, no. 3, p. 782-810, https://doi.org/10.1130/GES01380.1.","productDescription":"29 p.","startPage":"782","endPage":"810","ipdsId":"IP-082995","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":469881,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges01380.1","text":"Publisher Index Page"},{"id":347328,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Basin and Range Province","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -121,\n              41\n            ],\n            [\n              -117.25,\n              41\n            ],\n            [\n              -117.25,\n              42\n            ],\n            [\n              -121,\n              42\n            ],\n            [\n              -121,\n              41\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"13","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-10","publicationStatus":"PW","scienceBaseUri":"59f1a2a5e4b0220bbd9d9f58","contributors":{"authors":[{"text":"Personius, Stephen 0000-0001-8347-7370 personius@usgs.gov","orcid":"https://orcid.org/0000-0001-8347-7370","contributorId":150055,"corporation":false,"usgs":true,"family":"Personius","given":"Stephen","email":"personius@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":712838,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Briggs, Richard W. 0000-0001-8108-0046 rbriggs@usgs.gov","orcid":"https://orcid.org/0000-0001-8108-0046","contributorId":139002,"corporation":false,"usgs":true,"family":"Briggs","given":"Richard","email":"rbriggs@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":712839,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maharrey, J. Zebulon","contributorId":20625,"corporation":false,"usgs":true,"family":"Maharrey","given":"J.","email":"","middleInitial":"Zebulon","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":712840,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Angster, Stephen J. 0000-0001-9250-8415 sangster@usgs.gov","orcid":"https://orcid.org/0000-0001-9250-8415","contributorId":3885,"corporation":false,"usgs":true,"family":"Angster","given":"Stephen","email":"sangster@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":712841,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mahan, Shannon A. 0000-0001-5214-7774 smahan@usgs.gov","orcid":"https://orcid.org/0000-0001-5214-7774","contributorId":147159,"corporation":false,"usgs":true,"family":"Mahan","given":"Shannon","email":"smahan@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":712842,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70191541,"text":"70191541 - 2017 - Coal-tar-based pavement sealants—a potent source of PAHs","interactions":[],"lastModifiedDate":"2017-10-17T11:03:27","indexId":"70191541","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2593,"text":"Lakeline","active":true,"publicationSubtype":{"id":10}},"title":"Coal-tar-based pavement sealants—a potent source of PAHs","docAbstract":"<p>P avement sealants are applied to the asphalt pavement of many parking lots, driveways, and even playgrounds in North America (Figure 1), where, when first applied, they render the pavement glossy black and looking like new. Sealant products used commercially in the central, eastern, and northern United States typically are coal-tarbased, whereas those used in the western United States typically are asphalt-based. Although the products look similar, they are chemically different. Coal-tarbased pavement sealants typically are 25-35 percent (by weight) coal tar or coal-tar pitch, materials that are known human carcinogens and that contain high concentrations of polycyclic aromatic hydrocarbons (PAHs) and related chemicals (unless otherwise noted, all Figure 1. Pavement sealant is commonly used to seal parking lots, playgrounds, and driveways throughout the United States. Sealants used in the central, northern, eastern, and southern United States typically contain coal tar or coal-tar pitch, both of which are known human carcinogens. Photos by the U.S. Geological Survey. data in this article are from Mahler et al. 2012 and references therein). </p>","language":"English","publisher":"North American Lake Management Society","usgsCitation":"Mahler, B., and Van Metre, P., 2017, Coal-tar-based pavement sealants—a potent source of PAHs: Lakeline, v. 37, no. 1, p. 13-18.","productDescription":"6 p.","startPage":"13","endPage":"18","ipdsId":"IP-082495","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":346679,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":346647,"type":{"id":15,"text":"Index Page"},"url":"https://www.nalms.org/lakeline-magazine/"}],"volume":"37","issue":"1","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59e71691e4b05fe04cd331a9","contributors":{"authors":[{"text":"Mahler, Barbara 0000-0002-9150-9552 bjmahler@usgs.gov","orcid":"https://orcid.org/0000-0002-9150-9552","contributorId":1249,"corporation":false,"usgs":true,"family":"Mahler","given":"Barbara","email":"bjmahler@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":712708,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Metre, Peter C. 0000-0001-7564-9814 pcvanmet@usgs.gov","orcid":"https://orcid.org/0000-0001-7564-9814","contributorId":172246,"corporation":false,"usgs":true,"family":"Van Metre","given":"Peter C.","email":"pcvanmet@usgs.gov","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":712709,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70192057,"text":"70192057 - 2017 - Matching watershed and otolith chemistry to establish natal origin of an endangered desert lake sucker","interactions":[],"lastModifiedDate":"2017-10-19T15:58:32","indexId":"70192057","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Matching watershed and otolith chemistry to establish natal origin of an endangered desert lake sucker","docAbstract":"<p><span>Stream habitat restoration and supplemental stocking of hatchery-reared fish have increasingly become key components of recovery plans for imperiled freshwater fish; however, determining when to discontinue stocking efforts, prioritizing restoration areas, and evaluating restoration success present a conservation challenge. In this study, we demonstrate that otolith microchemistry is an effective tool for establishing natal origin of the June Sucker&nbsp;</span><i>Chasmistes liorus</i><span>, an imperiled potamodromous fish. This approach allows us to determine whether a fish is of wild or hatchery origin in order to assess whether habitat restoration enhances recruitment and to further identify areas of critical habitat. Our specific objectives were to (1) quantify and characterize chemical variation among three main spawning tributaries; (2) understand the relationship between otolith microchemistry and tributary chemistry; and (3) develop and validate a classification model to identify stream origin using otolith microchemistry data. We quantified molar ratios of Sr:Ca, Ba:Ca, and Mg:Ca for water and otolith chemistry from three main tributaries to Utah Lake, Utah, during the summer of 2013. Water chemistry (log</span><sub><i>e</i></sub><span><span>&nbsp;</span>transformed Sr:Ca, Ba:Ca, and Mg:Ca ratios) differed significantly across all three spawning tributaries. We determined that Ba:Ca and Sr:Ca ratios were the most important variables driving our classification models, and we observed a strong linear relationship between water and otolith values for Sr:Ca and Ba:Ca but not for Mg:Ca. Classification models derived from otolith element : Ca signatures accurately sorted individuals to their experimental tributary of origin (classification tree: 89% accuracy; random forest model: 91% accuracy) and determined wild versus hatchery origin with 100% accuracy. Overall, this study aids in evaluating the effectiveness of restoration, tracking progress toward recovery, and prioritizing future restoration plans for fishes of conservation concern. Our results have further application, such as identifying subpopulations that provide the greatest reproductive contribution to a metapopulation or finding the reproductive area and origin of invasive fishes.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00028487.2017.1301994","usgsCitation":"Strohm, D.D., Budy, P., and Crowl, T.A., 2017, Matching watershed and otolith chemistry to establish natal origin of an endangered desert lake sucker: Transactions of the American Fisheries Society, v. 146, no. 4, p. 732-743, https://doi.org/10.1080/00028487.2017.1301994.","productDescription":"12 p.","startPage":"732","endPage":"743","ipdsId":"IP-069787","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":469888,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1080/00028487.2017.1301994","text":"External Repository"},{"id":347006,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Utah Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.75704956054688,\n              40.158410030219486\n            ],\n            [\n              -111.65061950683594,\n              40.158410030219486\n            ],\n            [\n              -111.65061950683594,\n              40.247039698452085\n            ],\n            [\n              -111.75704956054688,\n              40.247039698452085\n            ],\n            [\n              -111.75704956054688,\n              40.158410030219486\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"146","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-22","publicationStatus":"PW","scienceBaseUri":"59e9b995e4b05fe04cd65c92","contributors":{"authors":[{"text":"Strohm, Deanna D.","contributorId":197742,"corporation":false,"usgs":false,"family":"Strohm","given":"Deanna","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":714188,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Budy, Phaedra E. 0000-0002-9918-1678 pbudy@usgs.gov","orcid":"https://orcid.org/0000-0002-9918-1678","contributorId":140028,"corporation":false,"usgs":true,"family":"Budy","given":"Phaedra","email":"pbudy@usgs.gov","middleInitial":"E.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":714031,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crowl, Todd A.","contributorId":197743,"corporation":false,"usgs":false,"family":"Crowl","given":"Todd","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":714189,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70191275,"text":"70191275 - 2017 - National Park Service Vegetation Mapping Inventory Program: Appalachian National Scenic Trail vegetation mapping project","interactions":[],"lastModifiedDate":"2017-10-03T11:47:48","indexId":"70191275","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":53,"text":"Natural Resource Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"NPS/NETN/NRR—2017/1437","title":"National Park Service Vegetation Mapping Inventory Program: Appalachian National Scenic Trail vegetation mapping project","docAbstract":"<p><span>The National Park Service (NPS) Vegetation Mapping Inventory (VMI) Program classifies, describes, and maps existing vegetation of national park units for the NPS Natural Resource Inventory and Monitoring (I&amp;M) Program. The NPS VMI Program is managed by the NPS I&amp;M Division and provides baseline vegetation information to the NPS Natural Resource I&amp;M Program. The U.S. Geological Survey Upper Midwest Environmental Sciences Center, NatureServe, NPS Northeast Temperate Network, and NPS Appalachian National Scenic Trail (APPA) have completed vegetation classification and mapping of APPA for the NPS VMI Program.</span><br><br><span>Mappers, ecologists, and botanists collaborated to affirm vegetation types within the U.S. National Vegetation Classification (USNVC) of APPA and to determine how best to map the vegetation types by using aerial imagery. Analyses of data from 1,618 vegetation plots were used to describe USNVC associations of APPA. Data from 289 verification sites were collected to test the field key to vegetation associations and the application of vegetation associations to a sample set of map polygons. Data from 269 validation sites were collected to assess vegetation mapping prior to submitting the vegetation map for accuracy assessment (AA). Data from 3,265 AA sites were collected, of which 3,204 were used to test accuracy of the vegetation map layer. The collective of these datasets affirmed 280 USNVC associations for the APPA vegetation mapping project.</span><br><br><span>To map the vegetation and land cover of APPA, 169 map classes were developed. The 169 map classes consist of 150 that represent natural (including ruderal) vegetation types in the USNVC, 11 that represent cultural (agricultural and developed) vegetation types in the USNVC, 5 that represent natural landscapes with catastrophic disturbance or some other modification to natural vegetation preventing accurate classification in the USNVC, and 3 that represent nonvegetated water (non-USNVC). Features were interpreted from viewing 4-band digital aerial imagery using digital onscreen three-dimensional stereoscopic workflow systems in geographic information systems (GIS). (Digital aerial imagery was collected each fall during 2009–11 to capture leaf-phenology change of hardwood trees across the latitudinal range of APPA.) The interpreted data were digitally and spatially referenced, thus making the spatial-database layers usable in GIS. Polygon units were mapped to either a 0.5-hectare (ha) or 0.25-ha minimum mapping unit, depending on vegetation type or scenario; however, polygon units were mapped to 0.1 ha for alpine vegetation.</span><br><br><span>A geodatabase containing various feature-class layers and tables provide locations and support data to USNVC vegetation types (vegetation map layer), vegetation plots, verification sites, validation sites, AA sites, project boundary extent and zones, and aerial image centers and flight lines. The feature-class layer and related tables of the vegetation map layer provide 30,395 polygons of detailed attribute data covering 110,919.7 ha, with an average polygon size of 3.6 ha; the vegetation map coincides closely with the administrative boundary for APPA.</span><br><br><span>Summary reports generated from the vegetation map layer of the map classes representing USNVC natural (including ruderal) vegetation types apply to 28,242 polygons (92.9% of polygons) and cover 106,413.0 ha (95.9%) of the map extent for APPA. The map layer indicates APPA to be 92.4% forest and woodland (102,480.8 ha), 1.7% shrubland (1866.3 ha), and 1.8% herbaceous cover (2,065.9 ha). Map classes representing park-special vegetation (undefined in the USNVC) apply to 58 polygons (0.2% of polygons) and cover 404.3 ha (0.4%) of the map extent. Map classes representing USNVC cultural types apply to 1,777 polygons (5.8% of polygons) and cover 2,516.3 ha (2.3%) of the map extent. Map classes representing nonvegetated water (non-USNVC) apply to 332 polygons (1.1% of polygons) and cover 1,586.2 ha (1.4%) of the map extent.</span></p>","language":"English","publisher":"National Park Service","publisherLocation":"Fort Collins, CO","usgsCitation":"Hop, K.D., Strassman, A.C., Hall, M., Menard, S., Largay, E., Sattler, S., Hoy, E.E., Ruhser, J., Hlavacek, E., and Dieck, J., 2017, National Park Service Vegetation Mapping Inventory Program: Appalachian National Scenic Trail vegetation mapping project: Natural Resource Report NPS/NETN/NRR—2017/1437, 1620 p.","productDescription":"1620 p.","ipdsId":"IP-082135","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":346348,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":346344,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/DataStore/Reference/Profile/2240273"}],"country":"United States","otherGeospatial":"Appalachian National Scenic Trail","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59d4a1a9e4b05fe04cc4e0fb","contributors":{"authors":[{"text":"Hop, Kevin D. 0000-0002-9928-4773 khop@usgs.gov","orcid":"https://orcid.org/0000-0002-9928-4773","contributorId":1438,"corporation":false,"usgs":true,"family":"Hop","given":"Kevin","email":"khop@usgs.gov","middleInitial":"D.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":711818,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Strassman, Andrew C. 0000-0002-9792-7181 astrassman@usgs.gov","orcid":"https://orcid.org/0000-0002-9792-7181","contributorId":4575,"corporation":false,"usgs":true,"family":"Strassman","given":"Andrew","email":"astrassman@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":711819,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hall, Mark","contributorId":196864,"corporation":false,"usgs":false,"family":"Hall","given":"Mark","email":"","affiliations":[],"preferred":false,"id":711820,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Menard, Shannon","contributorId":167864,"corporation":false,"usgs":false,"family":"Menard","given":"Shannon","email":"","affiliations":[{"id":17658,"text":"NatureServe","active":true,"usgs":false}],"preferred":false,"id":711821,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Largay, Ery","contributorId":196865,"corporation":false,"usgs":false,"family":"Largay","given":"Ery","email":"","affiliations":[],"preferred":false,"id":711822,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sattler, Stephanie 0000-0003-4417-2480 ssattler@usgs.gov","orcid":"https://orcid.org/0000-0003-4417-2480","contributorId":191016,"corporation":false,"usgs":true,"family":"Sattler","given":"Stephanie","email":"ssattler@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":711823,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hoy, Erin E. 0000-0002-2853-3242 ehoy@usgs.gov","orcid":"https://orcid.org/0000-0002-2853-3242","contributorId":4523,"corporation":false,"usgs":true,"family":"Hoy","given":"Erin","email":"ehoy@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":711824,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ruhser, Janis 0000-0001-9987-2578 jruhser@usgs.gov","orcid":"https://orcid.org/0000-0001-9987-2578","contributorId":149646,"corporation":false,"usgs":true,"family":"Ruhser","given":"Janis","email":"jruhser@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":711825,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hlavacek, Enrika 0000-0002-9872-2305 ehlavacek@usgs.gov","orcid":"https://orcid.org/0000-0002-9872-2305","contributorId":149114,"corporation":false,"usgs":true,"family":"Hlavacek","given":"Enrika","email":"ehlavacek@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":711826,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Dieck, Jennifer 0000-0002-4388-4534 jdieck@usgs.gov","orcid":"https://orcid.org/0000-0002-4388-4534","contributorId":149647,"corporation":false,"usgs":true,"family":"Dieck","given":"Jennifer","email":"jdieck@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":711827,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
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