The Millicoma Dace Rhinichthys cataractae 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.
","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":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":"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 Chasmistes liorus, 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 (loge 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.
","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":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":"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 km2); (2) 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.
","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. 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The scaling methods that are investigated are based on: (1) ASCE/SEI 7–10 guidelines; (2) spectral acceleration at the fundamental (first mode) period of the structure, Sa(T1); (3) maximum incremental velocity, MIV; and (4) modal pushover analysis. A total of 720 shake-table tests of four small-scale nonlinear building frame specimens with different static and dynamic characteristics are conducted. The peak displacement demands from full suites of 36 near-fault ground-motion records as well as from smaller “unbiased” and “biased” design subsets (bins) of ground-motions are included. Out of the four scaling methods, ground-motions scaled to the median MIV of the ensemble resulted in the smallest dispersion in the peak roof and inter-story drift demands. Scaling based on MIValso provided the most accurate median demands as compared with the “benchmark” demands for structures with greater nonlinearity; however, this accuracy was reduced for structures exhibiting reduced nonlinearity. The modal pushover-based scaling (MPS) procedure was the only method to conservatively overestimate the median drift demands.
","language":"English","publisher":"Springer","doi":"10.1007/s10518-016-0052-z","usgsCitation":"O’Donnell, A.P., Kurama, Y.C., Kalkan, E., and Taflanidis, A.A., 2017, Experimental evaluation of four ground-motion scaling methods for dynamic response-history analysis of nonlinear structures: Bulletin of Earthquake Engineering, v. 15, no. 5, p. 1899-1924, https://doi.org/10.1007/s10518-016-0052-z.","productDescription":"26 p.","startPage":"1899","endPage":"1924","ipdsId":"IP-069003","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":347808,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-02","publicationStatus":"PW","scienceBaseUri":"59f98bb6e4b0531197af9fea","contributors":{"authors":[{"text":"O’Donnell, Andrew P.","contributorId":199049,"corporation":false,"usgs":false,"family":"O’Donnell","given":"Andrew","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":718026,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kurama, Yahya C.","contributorId":199050,"corporation":false,"usgs":false,"family":"Kurama","given":"Yahya","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":718027,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kalkan, Erol 0000-0002-9138-9407 ekalkan@usgs.gov","orcid":"https://orcid.org/0000-0002-9138-9407","contributorId":1218,"corporation":false,"usgs":true,"family":"Kalkan","given":"Erol","email":"ekalkan@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":718025,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Taflanidis, Alexandros A.","contributorId":199051,"corporation":false,"usgs":false,"family":"Taflanidis","given":"Alexandros","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":718028,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"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":"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.
","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 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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":70189491,"text":"70189491 - 2017 - Continued feeding on Diporeia by deepwater sculpin in Lake Huron","interactions":[],"lastModifiedDate":"2018-03-28T11:17:16","indexId":"70189491","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1528,"text":"Environmental Biology of Fishes","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Continued feeding on Diporeia by deepwater sculpin in Lake Huron","title":"Continued feeding on Diporeia by deepwater sculpin in Lake Huron","docAbstract":"Monitoring changes in diets of fish is essential to understanding how food web dynamics respond to changes in native prey abundances. In the Great Lakes, Diporeia, a benthic macroinvertebrate and primary food of native benthivores, declined following the introduction of invasive Dreissena mussels and these changes were reflected in fish diets. We examined the diets of deepwater sculpin Myoxocephalus thompsonii collected in bottom trawls during 2010–2014 in the main basin of Lake Huron, and compared these results to an earlier diet study (2003–2005) to assess if their diets have continued to change after a prolonged period of Dreissena mussel invasion and declined Diporeia densities. Diporeia, Mysis, Bythotrephes, and Chironomidae were consumed regularly and other diet items included ostracods, copepods, sphaerid clams, and fish eggs. The prey-specific index of relative importance calculated for each prey group indicated that Mysis importance increased at shallow (≤55 m) and mid (64–73 m) depths, while Diporeia importance increased offshore (≥82 m). The average number of Diporeia consumed per fish increased by 10.0% and Mysis decreased by 7.5%, while the frequency of occurrence of Diporeia and Mysis remained comparable between time periods. The weight of adult deepwater sculpin (80 mm and 100 mm TL bins) increased between time periods; however, the change in weight was only significant for the 80 mm TL group (p < 0.01). Given the historical importance of Diporeia in the Great Lakes, the examination of deepwater sculpin diets provides unique insight into the trophic dynamics of the benthic community in Lake Huron.
","language":"English","publisher":"Springer","doi":"10.1007/s10641-016-0568-8","usgsCitation":"Thompson, P., Roseman, E., Keeler, K.M., O’Brien, T.P., and Bowser, D., 2017, Continued feeding on Diporeia by deepwater sculpin in Lake Huron: Environmental Biology of Fishes, v. 100, no. 4, p. 407-419, https://doi.org/10.1007/s10641-016-0568-8.","productDescription":"13 p.","startPage":"407","endPage":"419","ipdsId":"IP-071146","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":344138,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7FX77MK","text":"Diets of Deepwater Sculpin collected from fall forage (2003-05 and 2010-14) in Lake Huron"},{"id":343825,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Lake Huron","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.847412109375,\n 42.79540065303723\n ],\n [\n -81.090087890625,\n 42.79540065303723\n ],\n [\n -81.090087890625,\n 46.46813299215554\n ],\n [\n -84.847412109375,\n 46.46813299215554\n ],\n [\n -84.847412109375,\n 42.79540065303723\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"100","issue":"4","noUsgsAuthors":false,"publicationDate":"2016-12-28","publicationStatus":"PW","scienceBaseUri":"5968869de4b0d1f9f05f5974","contributors":{"authors":[{"text":"Thompson, Patricia A. pathompson@usgs.gov","contributorId":5249,"corporation":false,"usgs":true,"family":"Thompson","given":"Patricia A.","email":"pathompson@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":704903,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roseman, Edward F. eroseman@usgs.gov","contributorId":534,"corporation":false,"usgs":true,"family":"Roseman","given":"Edward F.","email":"eroseman@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":704904,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keeler, Kevin M. 0000-0002-8118-0060 kkeeler@usgs.gov","orcid":"https://orcid.org/0000-0002-8118-0060","contributorId":4377,"corporation":false,"usgs":true,"family":"Keeler","given":"Kevin","email":"kkeeler@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":704905,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O’Brien, Timothy P. 0000-0003-4502-5204 tiobrien@usgs.gov","orcid":"https://orcid.org/0000-0003-4502-5204","contributorId":2662,"corporation":false,"usgs":true,"family":"O’Brien","given":"Timothy","email":"tiobrien@usgs.gov","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":704906,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bowser, Dustin dbowser@usgs.gov","contributorId":145563,"corporation":false,"usgs":true,"family":"Bowser","given":"Dustin","email":"dbowser@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":704907,"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":"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 (Odocoileus virginianus) 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 rbcL 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 (F = 1.73, P = 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 <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.
","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":70187423,"text":"70187423 - 2017 - Datasheet: Pseudogymnoascus destructans (white-nose syndrome fungus)","interactions":[],"lastModifiedDate":"2018-01-03T11:17:55","indexId":"70187423","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Datasheet: Pseudogymnoascus destructans (white-nose syndrome fungus)","docAbstract":"Pseudogymnoascus destructans is a psychrophilic (cold-loving) fungus that causes white-nose syndrome (WNS), an emerging disease of North American bats that has caused unprecedented population declines. The fungus is believed to have been introduced to North America from Europe or Asia (where it is present but does not cause significant mortality), but the full extent of its native range is unknown. The route of introduction is also unknown. In North America, hibernating bats become infected with P. destructans when body temperature decreases during winter torpor into the range permissive for growth of this fungus. Infected bats may develop visible fungal growth on the nose or wings, awaken more frequently from torpor, and experience a cascade of physiologic changes that result in weight loss, dehydration, electrolyte imbalances, and death. P. destructans persists in the environments of underground bat hibernation sites (hibernacula) and is believed to spread primarily by natural movements of infected bats. The first evidence of WNS in North America is from a photograph of a hibernating bat taken during winter of 2005-2006 in a hibernaculum near Albany, New York. P. destructans subsequently spread rapidly from the northeastern United States throughout much of the eastern portions of the United States and Canada, and most recently (as of May 2017) was detected in Washington State. It has killed millions of bats, threatening some species with regional extirpation and putting at risk the valuable environmental services that bats provide by eating harmful insects.","largerWorkTitle":"Invasive species compendium","language":"English","publisher":"Centre for Agriculture and Biosciences International","usgsCitation":"Blehert, D.S., and Lankau, E.W., 2017, Datasheet: Pseudogymnoascus destructans (white-nose syndrome fungus), chap. of Invasive species compendium, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-084223","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":340751,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":340748,"type":{"id":15,"text":"Index Page"},"url":"https://www.cabi.org/isc/datasheet/119002"}],"publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59099aaee4b0fc4e449157e8","contributors":{"authors":[{"text":"Blehert, David S. 0000-0002-1065-9760 dblehert@usgs.gov","orcid":"https://orcid.org/0000-0002-1065-9760","contributorId":140397,"corporation":false,"usgs":true,"family":"Blehert","given":"David","email":"dblehert@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":693988,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lankau, Emily W. 0000-0002-7094-7780 elankau@usgs.gov","orcid":"https://orcid.org/0000-0002-7094-7780","contributorId":175270,"corporation":false,"usgs":true,"family":"Lankau","given":"Emily","email":"elankau@usgs.gov","middleInitial":"W.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":693989,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"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 (18O:17O:16O) and chlorine (37Cl:35Cl) 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":"Rationale
Perchlorate (ClO4−) 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 ClO4− source attribution and natural attenuation studies: δ37Cl, δ18O, and δ17O (or Δ17O or 17Δ) values. Documented reference materials, calibration schemes, methods, and interferences will improve the reliability of such studies.
Methods
Three large batches of KClO4 with contrasting isotopic compositions were synthesized and analyzed against VSMOW-SLAP, atmospheric O2, and international nitrate and chloride reference materials. Three analytical methods were tested for O isotopes: conversion of ClO4− to CO for continuous-flow IRMS (CO-CFIRMS), decomposition to O2 for dual-inlet IRMS (O2-DIIRMS), and decomposition to O2 with molecular-sieve trap (O2-DIIRMS+T). For Cl isotopes, KCl produced by thermal decomposition of KClO4 was reprecipitated as AgCl and converted into CH3Cl for DIIRMS.
Results
KClO4 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 ClO4− 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 SO42−, NO3−, ReO42−, and C-bearing contaminants include isotope mixing and fractionation effects on CO and O2, plus direct interference from CO2 in the mass spectrometer. The results highlight the importance of effective purification of ClO4− from environmental samples.
Conclusions
KClO4 reference materials are available for testing methods and calibrating isotopic data for ClO4− and other substances with widely varying Cl or O isotopic compositions. Current ClO4−extraction, purification, and analysis techniques provide relative isotope-ratio measurements with uncertainties much smaller than the range of values in environmental ClO4−, permitting isotopic evaluation of environmental ClO4− sources and natural attenuation.
","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":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions 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":70190561,"text":"70190561 - 2017 - Drawing a line in the sand: Effectiveness of off-highway vehicle management in California's Sonoran desert","interactions":[],"lastModifiedDate":"2017-09-07T12:26:55","indexId":"70190561","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Drawing a line in the sand: Effectiveness of off-highway vehicle management in California's Sonoran desert","docAbstract":"Public land policies manage multiple uses while striving to protect vulnerable plant and wildlife habitats from degradation; yet the effectiveness of such policies are infrequently evaluated, particularly for remote landscapes that are difficult to monitor. We assessed the use and impacts of recreational vehicles on Mojave Desert washes (intermittent streams) in the Chemehuevi Desert Wildlife Management Area (DWMA) of southern California. Wash zones designated as open and closed to off-highway vehicle (OHV) activity were designed in part to protect Mojave desert tortoise (Gopherus agassizii) habitat while allowing recreation in designated areas. OHV tracks were monitored in washes located near access roads during winter and early spring holidays – when recreation is typically high – and at randomly dispersed locations away from roads. Washes near access roads had fewer vehicle tracks within closed than open zones; further away from roads, OHV tracks were infrequent and their occurrence was not different between wash designations. Washes were in better condition in closed zones following major holidays as indicated by less vegetation damage, presence of trash, and wash bank damage. Furthermore, the frequency of washes with live tortoises and their sign was marginally greater in closed than open wash zones. Collectively, these results suggest that low impacts to habitats in designated closed wash zones reflect public compliance with federal OHV policy and regulations in the Chemehuevi DWMA during our study. Future monitoring to contrast wash use and impacts during other seasons as well as in other DWMAs will elucidate spatial and temporal patterns of recreation in these important conservation areas.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2017.02.033","usgsCitation":"Custer, N., Defalco, L., Nussear, K.E., and Esque, T., 2017, Drawing a line in the sand: Effectiveness of off-highway vehicle management in California's Sonoran desert: Journal of Environmental Management, v. 193, p. 448-457, https://doi.org/10.1016/j.jenvman.2017.02.033.","productDescription":"10 p.","startPage":"448","endPage":"457","ipdsId":"IP-053017","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":469885,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2017.02.033","text":"Publisher Index Page"},{"id":345546,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sonoran Desert","volume":"193","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59b25b00e4b020cdf7db1fbb","contributors":{"authors":[{"text":"Custer, Nathan ncuster@usgs.gov","contributorId":5561,"corporation":false,"usgs":true,"family":"Custer","given":"Nathan","email":"ncuster@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":709811,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Defalco, Lesley A. ldefalco@usgs.gov","contributorId":138961,"corporation":false,"usgs":true,"family":"Defalco","given":"Lesley A.","email":"ldefalco@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":709812,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nussear, Kenneth E. knussear@usgs.gov","contributorId":2695,"corporation":false,"usgs":true,"family":"Nussear","given":"Kenneth","email":"knussear@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":709813,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Esque, Todd C. tesque@usgs.gov","contributorId":138964,"corporation":false,"usgs":true,"family":"Esque","given":"Todd C.","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":709814,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"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":"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&M) Program. The NPS VMI Program is managed by the NPS I&M Division and provides baseline vegetation information to the NPS Natural Resource I&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.
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.
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.
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.
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.
The aim of the study was to determine whether location and sex affected the age precision estimates between two southern, reservoir populations of paddlefish [Polyodon spathula (Walbaum, 1792)]. From 589 paddlefish collected in Grand Lake and Keystone Lake, Oklahoma in 2011, ages from dentaries were estimated using three independent readers and precision was compared with coefficient of variation between locations and sexes. Ages were more precisely estimated from Grand Lake and from females.
","language":"English","publisher":"Wiley","doi":"10.1111/jai.13394","usgsCitation":"Long, J.M., and Nealis, A., 2017, Comparative precision of age estimates from two southern reservoir populations of paddlefish [Polyodon spathula (Walbaum, 1792)]: Journal of Applied Ichthyology, v. 33, no. 4, p. 819-820, https://doi.org/10.1111/jai.13394.","productDescription":"2 p.","startPage":"819","endPage":"820","ipdsId":"IP-069058","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":469898,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jai.13394","text":"Publisher Index Page"},{"id":354164,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oklahoma","otherGeospatial":"Grand Lake, Keystone Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": 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Growth dynamics of large, mobile animals are particularly useful as bio-indicators of environmental change at regional scales. We assembled growth rate data from throughout the West Atlantic for green turtles, Chelonia mydas, which are long-lived, highly migratory, primarily herbivorous mega-consumers that may migrate over hundreds to thousands of kilometers. Our dataset, the largest ever compiled for sea turtles, has 9690 growth increments from 30 sites from Bermuda to Uruguay from 1973 to 2015. Using generalized additive mixed models, we evaluated covariates that could affect growth rates; body size, diet, and year have significant effects on growth. Growth increases in early years until 1999, then declines by 26% to 2015. The temporal (year) effect is of particular interest because two carnivorous species of sea turtles – hawksbills, Eretmochelys imbricata, and loggerheads, Caretta caretta – exhibited similar significant declines in growth rates starting in 1997 in the West Atlantic, based on previous studies. These synchronous declines in productivity among three sea turtle species across a trophic spectrum provide strong evidence that an ecological regime shift (ERS) in the Atlantic is driving growth dynamics. The ERS resulted from a synergy of the 1997/1998 El Niño Southern Oscillation (ENSO) – the strongest on record – combined with an unprecedented warming rate over the last two to three decades. Further support is provided by the strong correlations between annualized mean growth rates of green turtles and both sea surface temperatures (SST) in the West Atlantic for years of declining growth rates (r = -0.94) and the Multivariate ENSO Index (MEI) for all years (r = 0.74). Granger-causality analysis also supports the latter finding. We discuss multiple stressors that could reinforce and prolong the effect of the ERS. This study demonstrates the importance of region-wide collaborations.
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By two days after the seawater flooding that occurred at the beginning of dry season, the observed salinity of water withdrawn by the island’s main skimming well increased to 100% seawater concentration, but by ten days later already decreased to only 10–20% of seawater fraction. However, the damaging impact on the potability of the groundwater supply (when pumped water had concentrations above 1% seawater fraction) lasted 22 months longer. The data collected make possible analyses of the hydrologic factors that control recovery and management of the groundwater-supply quality on Roi-Namur and on similar low-lying islands.
With the observed data as a guide, three-dimensional numerical-model simulation analyses reveal how recovery is controlled by the island’s hydrology. These also allow evaluation of the efficacy of basic water-quality management/mitigation alternatives and elucidate how groundwater withdrawal and timing of the seawater-flooding event affect the length of recovery. Simulations show that, as might be expected, by adding surplus captured rainwater as artificial recharge, the freshwater-lens recovery period (after which potable groundwater may again be produced) can be shortened, with groundwater salinity remaining lower even during the dry season, a period during which no artificial recharge is applied. Simulations also show that the recovery period is not lengthened appreciably by groundwater withdrawals during recovery. Simulations further show that had the flooding event occurred at the start of the wet season, the recovery period would have been about 25% (5.5 months) shorter than actually occurred during the monitored flood that occurred at the dry-season start. Finally, analyses show that artificial recharge improves freshwater-lens water quality, making possible longer use of groundwater as a water supply throughout each year, even when no seawater flooding has occurred.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2017.03.001","usgsCitation":"Gingerich, S.B., Voss, C.I., and Johnson, A.G., 2017, Seawater-flooding events and impact on freshwater lenses of low-lying islands: Controlling factors, basic management and mitigation: Journal of Hydrology, v. 551, p. 676-688, https://doi.org/10.1016/j.jhydrol.2017.03.001.","productDescription":"13 p.","startPage":"676","endPage":"688","ipdsId":"IP-079924","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":469900,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2017.03.001","text":"Publisher Index Page"},{"id":340578,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"551","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5904549fe4b022cee40dc21c","contributors":{"authors":[{"text":"Gingerich, Stephen B. 0000-0002-4381-0746 sbginger@usgs.gov","orcid":"https://orcid.org/0000-0002-4381-0746","contributorId":1426,"corporation":false,"usgs":true,"family":"Gingerich","given":"Stephen","email":"sbginger@usgs.gov","middleInitial":"B.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":693330,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Voss, Clifford I. 0000-0001-5923-2752 cvoss@usgs.gov","orcid":"https://orcid.org/0000-0001-5923-2752","contributorId":1559,"corporation":false,"usgs":true,"family":"Voss","given":"Clifford","email":"cvoss@usgs.gov","middleInitial":"I.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":693332,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Adam G. 0000-0003-2448-5746 ajohnson@usgs.gov","orcid":"https://orcid.org/0000-0003-2448-5746","contributorId":4752,"corporation":false,"usgs":true,"family":"Johnson","given":"Adam","email":"ajohnson@usgs.gov","middleInitial":"G.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":693331,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70170060,"text":"sim3356 - 2017 - Geologic map of Meridiani Planum, Mars","interactions":[],"lastModifiedDate":"2023-03-20T18:09:16.256306","indexId":"sim3356","displayToPublicDate":"2017-04-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3356","title":"Geologic map of Meridiani Planum, Mars","docAbstract":"The Meridiani Planum region of Mars—originally named due to its proximity to the Martian prime meridian—contains a variety of geologic units, including those that are crater‑related, that span the Early Noachian to Late Amazonian Epochs. Mars Global Surveyor (MGS) data indicate this area contains extensive layered deposits, some of which are rich in the mineral hematite. The National Aeronautics and Space Administration’s (NASA) Mars Exploration Rover (MER) Opportunity landed in Meridiani Planum in early 2004 and, at the time of this writing, is still conducting operations. A variety of water-altered bedrock outcrops have been studied and contain indications of prolonged surface and near-surface fluid/rock interactions. The purpose of this study is to use the more recent orbiter data to place the rover’s findings in a broader context by assessing the geologic and hydrologic histories of the region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3356","collaboration":"Prepared in cooperation with the National Aeronautics and Space Administration","usgsCitation":"Hynek, B.M., and Di Achille, G., 2017, Geologic map of Meridiani Planum, Mars (ver. 1.1, April 2017): U.S. Geological Survey Scientific Investigations Map 3356, pamphlet 9 p., scale 1:2,000,000, https://doi.org/10.3133/sim3356.","productDescription":"Pamphlet: i, 9 p.; Sheet: 55.90 x 40.00 inches; Metadata; Spatial Data","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-070106","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":438359,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DG4NAB","text":"USGS data release","linkHelpText":"Interactive Map: USGS SIM 3356 Geologic Map of Meridiani Planum"},{"id":405428,"rank":7,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://doi.org/10.5066/P9DG4NAB","text":"Interactive Web Map","description":"Hynek, B.M., and Di Achille, G., 2017, Geologic map of Meridiani Planum, Mars (ver. 1.1, April 2017): U.S. Geological Survey Scientific Investigations Map 3356, pamphlet 9 p., scale 1:2,000,000, https://doi.org/10.3133/sim3356","linkHelpText":"- Geologic Map of Meridiani Planum, Mars, 1:2M. Hynek and Di Achille (2017)"},{"id":340635,"rank":6,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sim/3356/sim3356_revHistory.txt","text":"Version history","size":"12.5 KB","linkFileType":{"id":2,"text":"txt"}},{"id":334386,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3356/sim3356_sheet1.pdf","text":"Map","size":"25.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3356"},{"id":334388,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3356/sim3356_metadata.txt","text":"Metadata","size":"12.4 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3356 Metadata"},{"id":334387,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3356/sim3356_pamphlet.pdf","text":"Pamphlet","size":"598 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3356 Pamphlet"},{"id":334385,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3356/coverthb.jpg"},{"id":334389,"rank":5,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3356/sim3356_gis.zip","text":"GIS Data","size":"293 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3356 GIS"}],"edition":"Version 1.0: Originally posted January 31, 2017; Version 1.1: April 28, 2017","contact":"A safe, practical, and accurate method for the determination of selenium (Se) in range of environmental samples was developed. Small sample masses, 5–20 mg, were amended with 82Se enriched isotope for the isotope dilution (ID), preceding a multi-step wet digestion with nitric acid (HNO3) and hydrogen peroxide (H2O2). Samples were incubated in an autoclave for 3 h at 20 psi and 126°C. Digestates were subsequently reduced with concentrated hydrochloric acid to Se(IV) the most favorable valence for hydride generation (HG). The solutions were then analyzed on an ICP-MS equipped with Flow Injection system (FIAS-400). Polyatomic, isobaric, and background interferences were removed through the use of HG and ID with an 82Se enriched isotope spike. Recoveries for certified reference materials were determined and averaged 96% for biological tissues (NRCC DOLT3, DOLT4, DORM2, TORT2, and TORT3, and NIST 2976) and 108% for estuarine sediment (NRCC PACS2) with an average coefficient of variation for replicate measurements of ∼ 3.5%. Limit of detection was 0.13 ng Se g−1 dry weight or 0.19 ng Se L−1. This method can be broadly applied to biological tissues, sediments, suspended particulates, and water samples with minimal modifications making this method highly useful for assessing the ecotoxicology of total Se in aquatic ecosystems.
","language":"English","publisher":"ASLO","doi":"10.1002/lom3.10164","usgsCitation":"Kleckner, A., Kakouros, E., and Stewart, A., 2017, A practical method for the determination of total selenium in environmental samples using isotope dilution-hydride generation-inductively coupled plasma-mass spectrometry: Limnology and Oceanography: Methods, v. 15, no. 4, p. 363-371, https://doi.org/10.1002/lom3.10164.","productDescription":"9 p.","startPage":"363","endPage":"371","ipdsId":"IP-076493","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":461625,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lom3.10164","text":"Publisher Index Page"},{"id":340630,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-11","publicationStatus":"PW","scienceBaseUri":"590454a0e4b022cee40dc21e","contributors":{"authors":[{"text":"Kleckner, Amy E.","contributorId":191501,"corporation":false,"usgs":false,"family":"Kleckner","given":"Amy E.","affiliations":[],"preferred":false,"id":693312,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kakouros, Evangelos 0000-0002-4778-4039 kakouros@usgs.gov","orcid":"https://orcid.org/0000-0002-4778-4039","contributorId":2587,"corporation":false,"usgs":true,"family":"Kakouros","given":"Evangelos","email":"kakouros@usgs.gov","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":693313,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stewart, A. Robin 0000-0003-2918-546X","orcid":"https://orcid.org/0000-0003-2918-546X","contributorId":82436,"corporation":false,"usgs":true,"family":"Stewart","given":"A. Robin","affiliations":[],"preferred":false,"id":693311,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70187244,"text":"70187244 - 2017 - Using a full annual cycle model to evaluate long-term population viability of the conservation-reliant Kirtland's warbler after successful recovery","interactions":[],"lastModifiedDate":"2017-04-28T13:30:30","indexId":"70187244","displayToPublicDate":"2017-04-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Using a full annual cycle model to evaluate long-term population viability of the conservation-reliant Kirtland's warbler after successful recovery","docAbstract":"Saline-surface crusts and their compositions at ephemeral, dry, and drying lakes are important products of arid-land processes. Detailed understanding is lacking, however, about interactions among locally variable hydrogeologic conditions, compositional control of groundwater on vadose zone and surface salts, and dust composition. Chemical and physical data from groundwater, sediments, and salts reveal compositional controls on saline-surface crusts across a wet playa, Mojave Desert, with bearing on similar settings elsewhere. The compositions of chemically and isotopically distinctive shallow (<3 m) water masses are recorded in the composition of associated salts. In areas with deeper and more saline groundwater, however, not all ions are transported through the vadose zone. Retention of arsenic and other elements in the vadose zone diminishes the concentrations of potentially toxic elements in surface salts, but creates a reservoir of these elements that may be brought to the surface during wetter conditions or by human disturbance. Selective wind-erosion loss of sulfate salts was identified by the compositional contrast between surface salt crusts and underlying groundwater. At the sub-basin scale, compositional links exist among groundwater, salt crusts, and dust from wet playas. Across the study basin, however, lateral variations in groundwater and solid-salt compositions are produced by hydrogeologic heterogeneity.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jaridenv.2017.01.010","usgsCitation":"Goldstein, H.L., Breit, G.N., and Reynolds, R.L., 2017, Controls on the chemical composition of saline surface crusts and emitted dust from a wet playa in the Mojave Desert (USA): Journal of Arid Environments, v. 140, p. 50-66, https://doi.org/10.1016/j.jaridenv.2017.01.010.","productDescription":"17 p.","startPage":"50","endPage":"66","ipdsId":"IP-069494","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":469901,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jaridenv.2017.01.010","text":"Publisher Index Page"},{"id":340634,"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 -116.57455444335936,\n 36.13787471840729\n ],\n [\n -116.224365234375,\n 36.13787471840729\n ],\n [\n -116.224365234375,\n 36.667317387570925\n ],\n [\n -116.57455444335936,\n 36.667317387570925\n ],\n [\n -116.57455444335936,\n 36.13787471840729\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"140","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5904549ee4b022cee40dc21a","contributors":{"authors":[{"text":"Goldstein, Harland L. 0000-0002-6092-8818 hgoldstein@usgs.gov","orcid":"https://orcid.org/0000-0002-6092-8818","contributorId":807,"corporation":false,"usgs":true,"family":"Goldstein","given":"Harland","email":"hgoldstein@usgs.gov","middleInitial":"L.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":693575,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Breit, George N. 0000-0003-2188-6798 gbreit@usgs.gov","orcid":"https://orcid.org/0000-0003-2188-6798","contributorId":1480,"corporation":false,"usgs":true,"family":"Breit","given":"George","email":"gbreit@usgs.gov","middleInitial":"N.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":693576,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reynolds, Richard L. 0000-0002-4572-2942 rreynolds@usgs.gov","orcid":"https://orcid.org/0000-0002-4572-2942","contributorId":441,"corporation":false,"usgs":true,"family":"Reynolds","given":"Richard","email":"rreynolds@usgs.gov","middleInitial":"L.","affiliations":[{"id":271,"text":"Federal Center","active":false,"usgs":true}],"preferred":true,"id":693577,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70189697,"text":"70189697 - 2017 - Subsequent-year recaptures at winter sites in three species of shrubland sparrows (Emberizidae)","interactions":[],"lastModifiedDate":"2017-11-22T17:04:47","indexId":"70189697","displayToPublicDate":"2017-04-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3451,"text":"Southwestern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Subsequent-year recaptures at winter sites in three species of shrubland sparrows (Emberizidae)","docAbstract":"The tendency by individual birds to return to winter sites in subsequent years can be important in assessing the potential influence of habitat changes during the nonbreeding period. We recaptured five Brewer's (Spizella breweri), seven sagebrush (Artemisiospiza nevadensis), and three black-throated (Amphispiza bilineata) sparrows from 1–3 subsequent years at the same winter location following their initial capture. Two Brewer's and one sagebrush sparrow returned to the same winter location at least 4 years after their initial capture. Levels of feather deuterium indicated that birds captured together on winter sites had different breeding ranges. Although individuals of these species returned to specific sites used in previous years, the low recapture rate suggests that wintering individuals may use an itinerant strategy adapted to seasonal food resources.
","language":"English","publisher":"Southwestern Association of Naturalists","doi":"10.1894/0038-4909-62.2.165","usgsCitation":"Knick, S.T., Leu, M., and Hanser, S.E., 2017, Subsequent-year recaptures at winter sites in three species of shrubland sparrows (Emberizidae): Southwestern Naturalist, v. 62, no. 2, p. 121-125, https://doi.org/10.1894/0038-4909-62.2.165.","productDescription":"5 p. ","startPage":"121","endPage":"125","ipdsId":"IP-066356","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":344133,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Colorado, Nevada, New Mexico, Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.5205078125,\n 31.80289258670676\n ],\n [\n -102.4365234375,\n 31.80289258670676\n ],\n [\n -102.4365234375,\n 37.96152331396614\n ],\n [\n -118.5205078125,\n 37.96152331396614\n ],\n [\n -118.5205078125,\n 31.80289258670676\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"62","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5971c1c2e4b0ec1a4885dac3","contributors":{"authors":[{"text":"Knick, Steven T. 0000-0003-4025-1704 steve_knick@usgs.gov","orcid":"https://orcid.org/0000-0003-4025-1704","contributorId":159,"corporation":false,"usgs":true,"family":"Knick","given":"Steven","email":"steve_knick@usgs.gov","middleInitial":"T.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":705852,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leu, Matthias 0000-0002-4290-7212","orcid":"https://orcid.org/0000-0002-4290-7212","contributorId":194938,"corporation":false,"usgs":false,"family":"Leu","given":"Matthias","email":"","affiliations":[],"preferred":false,"id":705854,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hanser, Steve E. 0000-0002-4430-2073 shanser@usgs.gov","orcid":"https://orcid.org/0000-0002-4430-2073","contributorId":152523,"corporation":false,"usgs":true,"family":"Hanser","given":"Steve","email":"shanser@usgs.gov","middleInitial":"E.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":705853,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70190190,"text":"70190190 - 2017 - High sensitivity of gross primary production in the Rocky Mountains to summer rain","interactions":[],"lastModifiedDate":"2017-08-16T17:26:47","indexId":"70190190","displayToPublicDate":"2017-04-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"High sensitivity of gross primary production in the Rocky Mountains to summer rain","docAbstract":"In the catchments of the Rocky Mountains, peak snowpack is declining in response to warmer spring temperatures. To understand how this will influence terrestrial gross primary production (GPP), we compared precipitation data across the intermountain west with satellite retrievals of solar-induced fluorescence (SIF), a proxy for GPP. Annual precipitation patterns explained most of the spatial and temporal variability of SIF, but the slope of the response was dependent on site to site differences in the proportion of snowpack to summer rain. We separated the response of SIF to different seasonal precipitation amounts and found that SIF was approximately twice as sensitive to variations in summer rain than snowpack. The response of peak GPP to a secular decline in snowpack will likely be subtle, whereas a change in summer rain amount will have precipitous effects on GPP. The study suggests that the rain use efficiency of Rocky Mountain ecosystems is strongly dependent on precipitation form and timing.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2016GL072495","usgsCitation":"Berkelhammer, M., Stefanescu, I., Joiner, J., and Anderson, L., 2017, High sensitivity of gross primary production in the Rocky Mountains to summer rain: Geophysical Research Letters, v. 44, no. 8, p. 3643-3652, https://doi.org/10.1002/2016GL072495.","productDescription":"10 p.","startPage":"3643","endPage":"3652","ipdsId":"IP-082491","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":482066,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gl072495","text":"Publisher Index Page"},{"id":344912,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-30","publicationStatus":"PW","scienceBaseUri":"599559bbe4b0fe2b9fea6c44","contributors":{"authors":[{"text":"Berkelhammer, M.","contributorId":152270,"corporation":false,"usgs":false,"family":"Berkelhammer","given":"M.","affiliations":[{"id":18133,"text":"University of Illinois Chicago","active":true,"usgs":false}],"preferred":false,"id":707882,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stefanescu, I.C.","contributorId":195687,"corporation":false,"usgs":false,"family":"Stefanescu","given":"I.C.","email":"","affiliations":[],"preferred":false,"id":707883,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Joiner, J.","contributorId":195688,"corporation":false,"usgs":false,"family":"Joiner","given":"J.","email":"","affiliations":[],"preferred":false,"id":707884,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anderson, Lesleigh 0000-0002-5264-089X land@usgs.gov","orcid":"https://orcid.org/0000-0002-5264-089X","contributorId":436,"corporation":false,"usgs":true,"family":"Anderson","given":"Lesleigh","email":"land@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":707881,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70186764,"text":"ofr20171039 - 2017 - Precipitation thresholds for landslide occurrence near Seattle, Mukilteo, and Everett, Washington","interactions":[],"lastModifiedDate":"2017-04-27T12:58:49","indexId":"ofr20171039","displayToPublicDate":"2017-04-27T11:00:00","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":"2017-1039","title":"Precipitation thresholds for landslide occurrence near Seattle, Mukilteo, and Everett, Washington","docAbstract":"Shallow landslides along coastal bluffs frequently occur in the railway corridor between Seattle and Everett, Washington. These slides disrupt passenger rail service, both because of required track maintenance and because the railroad owner, Burlington Northern Santa Fe Railway, does not allow passenger travel for 48 hours after a disruptive landslide. Sound Transit, which operates commuter trains in the corridor, is interested in a decision-making tool to help preemptively cancel passenger railway service in dangerous conditions and reallocate resources to alternative transportation.
Statistical analysis showed that a majority of landslides along the Seattle-Everett Corridor are strongly correlated with antecedent rainfall, but that 21-37 percent of recorded landslide dates experienced less than 1 inch of precipitation in the 3 days preceding the landslide and less than 4 inches of rain in the 15 days prior to the preceding 3 days. We developed two empirical thresholds to identify precipitation conditions correlated with landslide occurrence. The two thresholds are defined as P3 = 2.16-0.44P15 and P3 = 2.16-0.22P32, where P3 is the cumulative precipitation in the 3 days prior to the considered date and P15 or P32 is the cumulative precipitation in the 15 days or 32 days prior to P3 (all measurements given in inches). The two thresholds, when compared to a previously developed threshold, quantitatively improve the prediction rate.
We also investigated rainfall intensity-duration (ID) thresholds to determine whether revision would improve identification of moderate-intensity, landslide-producing storms. New, optimized ID thresholds evaluate rainstorms lasting at least 12 hours and identify landslide-inducing storms that were typically missed by previously published ID thresholds. The main advantage of the ID thresholds appears when they are combined with recent-antecedent thresholds because rainfall conditions that exceed both threshold types are more likely to induce two or more landslides than conditions that exceed only one threshold type.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171039","collaboration":"Prepared in cooperation with Sound Transit","usgsCitation":"Scheevel, C.R., Baum, R.L., Mirus, B.B., and Smith, J.B., 2017, Precipitation thresholds for landslide occurrence near Seattle, Mukilteo, and Everett, Washington: U.S. Geological Survey Open-File Report 2017–1039, 51 p., https://doi.org/10.3133/ofr20171039.","productDescription":"vi, 51 p.","numberOfPages":"60","onlineOnly":"Y","ipdsId":"IP-082570","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":340454,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1039/coverthb.jpg"},{"id":340455,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1039/ofr20171039.pdf","text":"Report","size":"8.96 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1039"}],"country":"United States","state":"Washington","city":"Everett, Mukilteo, Seattle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123,\n 48.3\n ],\n [\n -122,\n 48.3\n ],\n [\n -122,\n 47.3\n ],\n [\n -123,\n 47.3\n ],\n [\n -123,\n 48.3\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, MS–966
Denver, CO 80225-0046
https://www.usgs.gov/centers/geohazards/
","tableOfContents":"Dual-domain models are used to explain anomalous solute transport behavior observed in diverse hydrologic settings and applications, from groundwater remediation to hyporheic exchange. To constrain such models, new methods are needed with sensitivity to both immobile and mobile domains. Recent experiments indicate that dual-domain transport of ionic tracers has an observable geoelectrical signature, appearing as a nonlinear, hysteretic relation between paired bulk and fluid electrical conductivity. Here we present a mechanistic explanation for this geoelectrical signature and evaluate assumptions underlying a previously published petrophysical model for bulk conductivity in dual-domain media. Pore network modeling of fluid flow, solute transport, and electrical conduction (1) verifies the geoelectrical signature of dual-domain transport, (2) reveals limitations of the previously used petrophysical model, and (3) demonstrates that a new petrophysical model, based on differential effective media theory, closely approximates the simulated bulk/fluid conductivity relation. These findings underscore the potential of geophysically based calibration of dual-domain models.