Thawing of permafrost due to global warming can have major impacts on hydrogeological processes, climate feedback, arctic ecology, and local environments. To understand these effects and processes, it is crucial to know the distribution of permafrost. In this study we exploit the fact that airborne electromagnetic (AEM) data are sensitive to the distribution of permafrost and demonstrate how the distribution of permafrost in the Yukon Flats, Alaska, is mapped in an efficient (semiautomatic) way, using a combination of supervised and unsupervised (machine) learning algorithms, i.e., Smart Interpretation and K-means clustering. Clustering is used to sort unfrozen and frozen regions, and Smart Interpretation is used to predict the depth of permafrost based on expert interpretations. This workflow allows, for the first time, a quantitative and objective approach to efficiently map permafrost based on large amounts of AEM data.
","language":"English","publisher":"AGU","doi":"10.1002/2016GL071334","usgsCitation":"Gulbrandsen, M.L., Minsley, B.J., Ball, L.B., and Hansen, T.M., 2016, Semiautomatic mapping of permafrost in the Yukon Flats, Alaska: Geophysical Research Letters, v. 43, no. 23, p. 12131-12137, https://doi.org/10.1002/2016GL071334.","productDescription":"7 p.","startPage":"12131","endPage":"12137","ipdsId":"IP-080706","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":470396,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/2016gl071334","text":"External Repository"},{"id":348149,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Yukon Flats","volume":"43","issue":"23","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-09","publicationStatus":"PW","scienceBaseUri":"59fc2ea6e4b0531197b27f87","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":719885,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":719884,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":719886,"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":719887,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70191453,"text":"70191453 - 2016 - Reinforcement and validation of the analyses and conclusions related to fishway evaluation data from Bunt et al.: ‘Performance of fish passage structures at upstream barriers to migration’","interactions":[],"lastModifiedDate":"2017-10-13T12:46:21","indexId":"70191453","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Reinforcement and validation of the analyses and conclusions related to fishway evaluation data from Bunt et al.: ‘Performance of fish passage structures at upstream barriers to migration’","docAbstract":"Detailed re-examination of the datasets that were used for a meta-analysis of fishway attraction and passage revealed a number of errors that we addressed and corrected. We subsequently re-analysed the revised dataset, and results showed no significant changes in the primary conclusions of the original study; for most species, effective performance cannot be assured for any fishway type.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.3095","usgsCitation":"Bunt, C., Castro-Santos, T.R., and Haro, A., 2016, Reinforcement and validation of the analyses and conclusions related to fishway evaluation data from Bunt et al.: ‘Performance of fish passage structures at upstream barriers to migration’: River Research and Applications, v. 32, no. 10, p. 2125-2137, https://doi.org/10.1002/rra.3095.","productDescription":"13 p.","startPage":"2125","endPage":"2137","ipdsId":"IP-078011","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":346592,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"10","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-29","publicationStatus":"PW","scienceBaseUri":"59e1d099e4b05fe04cd117b9","contributors":{"authors":[{"text":"Bunt, C.M.","contributorId":96976,"corporation":false,"usgs":true,"family":"Bunt","given":"C.M.","affiliations":[],"preferred":false,"id":712412,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":712335,"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":712413,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70193163,"text":"70193163 - 2016 - Bayesian analysis of Jolly-Seber type models","interactions":[],"lastModifiedDate":"2017-11-20T15:57:21","indexId":"70193163","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1573,"text":"Environmental and Ecological Statistics","active":true,"publicationSubtype":{"id":10}},"title":"Bayesian analysis of Jolly-Seber type models","docAbstract":"We propose the use of finite mixtures of continuous distributions in modelling the process by which new individuals, that arrive in groups, become part of a wildlife population. We demonstrate this approach using a data set of migrating semipalmated sandpipers (Calidris pussila) for which we extend existing stopover models to allow for individuals to have different behaviour in terms of their stopover duration at the site. We demonstrate the use of reversible jump MCMC methods to derive posterior distributions for the model parameters and the models, simultaneously. The algorithm moves between models with different numbers of arrival groups as well as between models with different numbers of behavioural groups. The approach is shown to provide new ecological insights about the stopover behaviour of semipalmated sandpipers but is generally applicable to any population in which animals arrive in groups and potentially exhibit heterogeneity in terms of one or more other processes.
","language":"English","publisher":"Springer","doi":"10.1007/s10651-016-0352-0","usgsCitation":"Matechou, E., Nicholls, G.K., Morgan, B.J., Collazo, J., and Lyons, J.E., 2016, Bayesian analysis of Jolly-Seber type models: Environmental and Ecological Statistics, v. 23, no. 4, p. 531-547, https://doi.org/10.1007/s10651-016-0352-0.","productDescription":"17 p.","startPage":"531","endPage":"547","ipdsId":"IP-057563","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":470376,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10651-016-0352-0","text":"Publisher Index Page"},{"id":349161,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","issue":"4","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-04","publicationStatus":"PW","scienceBaseUri":"5a60fc7de4b06e28e9c23f0f","contributors":{"authors":[{"text":"Matechou, Eleni","contributorId":200631,"corporation":false,"usgs":false,"family":"Matechou","given":"Eleni","email":"","affiliations":[],"preferred":false,"id":722930,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nicholls, Geoff K.","contributorId":200632,"corporation":false,"usgs":false,"family":"Nicholls","given":"Geoff","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":722931,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morgan, Byron J. T.","contributorId":200633,"corporation":false,"usgs":false,"family":"Morgan","given":"Byron","email":"","middleInitial":"J. T.","affiliations":[],"preferred":false,"id":722932,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Collazo, Jaime A. 0000-0002-1816-7744 jaime_collazo@usgs.gov","orcid":"https://orcid.org/0000-0002-1816-7744","contributorId":173448,"corporation":false,"usgs":true,"family":"Collazo","given":"Jaime A.","email":"jaime_collazo@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":718111,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lyons, James E. 0000-0002-9810-8751 jelyons@usgs.gov","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":177546,"corporation":false,"usgs":true,"family":"Lyons","given":"James","email":"jelyons@usgs.gov","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":722933,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70179638,"text":"70179638 - 2016 - Multi-decadal increases in dissolved organic carbon and alkalinity flux from the Mackenzie drainage basin to the Arctic Ocean","interactions":[],"lastModifiedDate":"2017-01-09T11:24:20","indexId":"70179638","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Multi-decadal increases in dissolved organic carbon and alkalinity flux from the Mackenzie drainage basin to the Arctic Ocean","docAbstract":"Riverine exports of organic and inorganic carbon (OC, IC) to oceans are intricately linked to processes occurring on land. Across high latitudes, thawing permafrost, alteration of hydrologic flow paths, and changes in vegetation may all affect this flux, with subsequent implications for regional and global carbon (C) budgets. Using a unique, multi-decadal dataset of continuous discharge coupled with water chemistry measurements for the Mackenzie River, we show major increases in dissolved OC (DOC) and IC (as alkalinity) fluxes since the early 1970s, for a watershed that covers 1.8 M km2 of northwestern Canada, and provides substantial inputs of freshwater and biogeochemical constituents to the Arctic Ocean. Over a 39-year period of record, DOC flux at the Mackenzie mouth increased by 39.3% (44.5 ± 22.6 Gmol), while alkalinity flux increased by 12.5% (61.5 ± 60.1 Gmol). Isotopic analyses and substantial increases in sulfate flux indicate that increases in alkalinity are driven by accelerating sulfide oxidation, a process that liberates IC from rock and soils in the absence of CO2 consumption. Seasonal and sub-catchment trends suggest that permafrost thaw plays an important role in the observed increases in DOC and alkalinity: sub-catchment increases for all constituents are confined to northern, permafrost-affected regions, while observed increases in autumn to winter are consistent with documented landscape-scale changes that have resulted from changing thaw dynamics. This increase in DOC and sulfide-derived alkalinity represents a substantial intensification of land-to-ocean C mobilization, at a level that is significant within the regional C budget. The change we observe, for example, is similar to current and projected future rates of CO2 consumption by weathering in the Mackenzie basin.
","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/11/5/054015","usgsCitation":"Tank, S.E., Striegl, R.G., McClelland, J.W., and Kokelj, S.V., 2016, Multi-decadal increases in dissolved organic carbon and alkalinity flux from the Mackenzie drainage basin to the Arctic Ocean: Environmental Research Letters, v. 11, no. 5, p. 1-10, https://doi.org/10.1088/1748-9326/11/5/054015.","productDescription":"Article 054015; 10 p.","startPage":"1","endPage":"10","ipdsId":"IP-067063","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":470414,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/11/5/054015","text":"Publisher Index Page"},{"id":332985,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-11","publicationStatus":"PW","scienceBaseUri":"5874b0ade4b0a829a320bb65","contributors":{"authors":[{"text":"Tank, Suzanne E.","contributorId":150795,"corporation":false,"usgs":false,"family":"Tank","given":"Suzanne","email":"","middleInitial":"E.","affiliations":[{"id":18102,"text":"University of Alberta, Edmonton, Canada","active":true,"usgs":false}],"preferred":false,"id":658001,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Striegl, Robert G. 0000-0002-8251-4659 rstriegl@usgs.gov","orcid":"https://orcid.org/0000-0002-8251-4659","contributorId":1630,"corporation":false,"usgs":true,"family":"Striegl","given":"Robert","email":"rstriegl@usgs.gov","middleInitial":"G.","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":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":658000,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McClelland, James W.","contributorId":94905,"corporation":false,"usgs":true,"family":"McClelland","given":"James","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":658002,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kokelj, Steven V.","contributorId":178128,"corporation":false,"usgs":false,"family":"Kokelj","given":"Steven","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":658003,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70178570,"text":"70178570 - 2016 - Graphical function mapping as a new way to explore cause-and-effect chains","interactions":[],"lastModifiedDate":"2018-02-28T14:36:31","indexId":"70178570","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1657,"text":"Fisheries","onlineIssn":"1548-8446","printIssn":"0363-2415","active":true,"publicationSubtype":{"id":10}},"title":"Graphical function mapping as a new way to explore cause-and-effect chains","docAbstract":"Graphical function mapping provides a simple method for improving communication within interdisciplinary research teams and between scientists and nonscientists. This article introduces graphical function mapping using two examples and discusses its usefulness. Function mapping projects the outcome of one function into another to show the combined effect. Using this mathematical property in a simpler, even cartoon-like, graphical way allows the rapid combination of multiple information sources (models, empirical data, expert judgment, and guesses) in an intuitive visual to promote further discussion, scenario development, and clear communication.
","language":"English","publisher":"American Fisheries Society","publisherLocation":"Bethesda, MD","doi":"10.1080/03632415.2016.1221404","usgsCitation":"Evans, M.A., 2016, Graphical function mapping as a new way to explore cause-and-effect chains: Fisheries, v. 41, no. 11, p. 638-643, https://doi.org/10.1080/03632415.2016.1221404.","productDescription":"6 p.","startPage":"638","endPage":"643","ipdsId":"IP-060085","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":331372,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"11","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-04","publicationStatus":"PW","scienceBaseUri":"584144dde4b04fc80e50737f","contributors":{"authors":[{"text":"Evans, Mary Anne 0000-0002-1627-7210 maevans@usgs.gov","orcid":"https://orcid.org/0000-0002-1627-7210","contributorId":4883,"corporation":false,"usgs":true,"family":"Evans","given":"Mary","email":"maevans@usgs.gov","middleInitial":"Anne","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":654409,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70170146,"text":"70170146 - 2016 - Iron and oxygen isotope signatures of the Pea Ridge and Pilot Knob magnetite-apatite deposits, southeast Missouri, USA","interactions":[],"lastModifiedDate":"2017-04-14T11:04:57","indexId":"70170146","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Iron and oxygen isotope signatures of the Pea Ridge and Pilot Knob magnetite-apatite deposits, southeast Missouri, USA","docAbstract":"New O and Fe stable isotope ratios are reported for magnetite samples from high-grade massive magnetite of the Mesoproterozoic Pea Ridge and Pilot Knob magnetite-apatite ore deposits and these results are compared with data for other iron oxide-apatite deposits to shed light on the origin of the southeast Missouri deposits. The δ18O values of magnetite from Pea Ridge (n = 12) and Pilot Knob (n = 3) range from 1.0 to 7.0 and 3.3 to 6.7‰, respectively. The δ56Fe values of magnetite from Pea Ridge (n = 10) and Pilot Knob (n = 6) are 0.03 to 0.35 and 0.06 to 0.27‰, respectively. These δ18O and the δ56Fe values suggest that magnetite crystallized from a silicate melt (typical igneous δ56Fe ranges 0.06–0.49‰) and grew in equilibrium with a magmatic-hydrothermal aqueous fluid. We propose that the δ18O and δ56Fe data for the Pea Ridge and Pilot Knob magnetite-apatite deposits are consistent with the flotation model recently proposed by Knipping et al. (2015a), which invokes flotation of a magmatic magnetite-fluid suspension and offers a plausible explanation for the igneous (i.e., up to ~15.9 wt % TiO2 in magnetite) and hydrothermal features of the deposits.
","language":"English","publisher":"Society of Economic Geologists","doi":"10.2113/econgeo.111.8.2033","usgsCitation":"Childress, T., Simon, A.C., Day, W.C., Lundstrom, C.C., and Bindeman, I.N., 2016, Iron and oxygen isotope signatures of the Pea Ridge and Pilot Knob magnetite-apatite deposits, southeast Missouri, USA: Economic Geology, v. 111, no. 8, p. 2033-2044, https://doi.org/10.2113/econgeo.111.8.2033.","productDescription":"12 p.","startPage":"2033","endPage":"2044","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-074047","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":339731,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"111","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-16","publicationStatus":"PW","scienceBaseUri":"58f1e0c9e4b08144348b7dfa","contributors":{"authors":[{"text":"Childress, Tristan","contributorId":168528,"corporation":false,"usgs":false,"family":"Childress","given":"Tristan","affiliations":[{"id":6649,"text":"University of Michigan, School of Natural Resources and Environment","active":true,"usgs":false}],"preferred":false,"id":626277,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Simon, Adam C.","contributorId":27573,"corporation":false,"usgs":true,"family":"Simon","given":"Adam","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":626278,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Day, Warren C. 0000-0002-9278-2120 wday@usgs.gov","orcid":"https://orcid.org/0000-0002-9278-2120","contributorId":1308,"corporation":false,"usgs":true,"family":"Day","given":"Warren","email":"wday@usgs.gov","middleInitial":"C.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":626276,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lundstrom, Craig C.","contributorId":168529,"corporation":false,"usgs":false,"family":"Lundstrom","given":"Craig","email":"","middleInitial":"C.","affiliations":[{"id":15289,"text":"University of Illinois, Ven Te Chow Hydrosystems Laboratory","active":true,"usgs":false}],"preferred":false,"id":626279,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bindeman, Ilya N.","contributorId":7992,"corporation":false,"usgs":true,"family":"Bindeman","given":"Ilya","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":626280,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70184992,"text":"70184992 - 2016 - Dog days of summer: Influences on decision of wolves to move pups","interactions":[],"lastModifiedDate":"2017-03-13T13:01:23","indexId":"70184992","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2373,"text":"Journal of Mammalogy","onlineIssn":"1545-1542","printIssn":"0022-2372","active":true,"publicationSubtype":{"id":10}},"title":"Dog days of summer: Influences on decision of wolves to move pups","docAbstract":"For animals that forage widely, protecting young from predation can span relatively long time periods due to the inability of young to travel with and be protected by their parents. Moving relatively immobile young to improve access to important resources, limit detection of concentrated scent by predators, and decrease infestations by ectoparasites can be advantageous. Moving young, however, can also expose them to increased mortality risks (e.g., accidents, getting lost, predation). For group-living animals that live in variable environments and care for young over extended time periods, the influence of biotic factors (e.g., group size, predation risk) and abiotic factors (e.g., temperature and precipitation) on the decision to move young is unknown. We used data from 25 satellite-collared wolves ( Canis lupus ) in Idaho, Montana, and Yellowstone National Park to evaluate how these factors could influence the decision to move pups during the pup-rearing season. We hypothesized that litter size, the number of adults in a group, and perceived predation risk would positively affect the number of times gray wolves moved pups. We further hypothesized that wolves would move their pups more often when it was hot and dry to ensure sufficient access to water. Contrary to our hypothesis, monthly temperature above the 30-year average was negatively related to the number of times wolves moved their pups. Monthly precipitation above the 30-year average, however, was positively related to the amount of time wolves spent at pup-rearing sites after leaving the natal den. We found little relationship between risk of predation (by grizzly bears, humans, or conspecifics) or group and litter sizes and number of times wolves moved their pups. Our findings suggest that abiotic factors most strongly influence the decision of wolves to move pups, although responses to unpredictable biotic events (e.g., a predator encountering pups) cannot be ruled out.
","language":"English","publisher":"American Society of Mammalogists","doi":"10.1093/jmammal/gyw114","usgsCitation":"Ausband, D., Mitchell, M.S., Bassing, S.B., Nordhagen, M., Smith, D., and Stahler, D.R., 2016, Dog days of summer: Influences on decision of wolves to move pups: Journal of Mammalogy, v. 97, no. 5, p. 1282-1287, https://doi.org/10.1093/jmammal/gyw114.","productDescription":"6 p.","startPage":"1282","endPage":"1287","ipdsId":"IP-076548","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470363,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jmammal/gyw114","text":"Publisher Index Page"},{"id":337431,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"97","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-12","publicationStatus":"PW","scienceBaseUri":"58c7af9de4b0849ce9795e80","contributors":{"authors":[{"text":"Ausband, David E.","contributorId":51441,"corporation":false,"usgs":true,"family":"Ausband","given":"David E.","affiliations":[],"preferred":false,"id":683907,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mitchell, Michael S. 0000-0002-0773-6905 mmitchel@usgs.gov","orcid":"https://orcid.org/0000-0002-0773-6905","contributorId":3716,"corporation":false,"usgs":true,"family":"Mitchell","given":"Michael","email":"mmitchel@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":683854,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bassing, Sarah B.","contributorId":81006,"corporation":false,"usgs":true,"family":"Bassing","given":"Sarah","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":683908,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nordhagen, Matthew","contributorId":189127,"corporation":false,"usgs":false,"family":"Nordhagen","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":683909,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Douglas W.","contributorId":179181,"corporation":false,"usgs":false,"family":"Smith","given":"Douglas W.","affiliations":[],"preferred":false,"id":683910,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stahler, Daniel R.","contributorId":179180,"corporation":false,"usgs":false,"family":"Stahler","given":"Daniel","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":683911,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70193693,"text":"70193693 - 2016 - Use of noninvasive genetics to assess nest and space use by white-tailed eagles","interactions":[],"lastModifiedDate":"2017-11-22T17:19:58","indexId":"70193693","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2442,"text":"Journal of Raptor Research","active":true,"publicationSubtype":{"id":10}},"title":"Use of noninvasive genetics to assess nest and space use by white-tailed eagles","docAbstract":"Movement and space use are important components of animal interactions with the environment. However, for hard-to-monitor raptor species, there are substantial gaps in our understanding of these key determinants. We used noninvasive genetic tools to evaluate the details of space use over a 3-yr period by White-tailed Eagles (Haliaeetus albicilla) at the Naurzum Zapovednik in northern Kazakhstan. We genotyped, at 10 microsatellite markers and one mitochondrial marker, 859 eagle feathers and assigned naturally shed feathers to individuals. We identified 124 White-tailed Eagles, including both members of 5–10 pairs per year, and were able to monitor birds across years. Distances between eagle nests and hunting perches were always greater than nearest neighbor distances, eagles never used the closest available hunting perch, and hunting perches were always shared with other eagles. When eagles switched nests between years, the nests they chose were almost always well outside the space that theory predicted they defended the prior year. Our data are inconsistent with classical territorial and colonial models of resource use; they more closely resemble semi-colonial behavior. It is unlikely that standard methods of animal tracking (e.g., marking and telemetry), would have provided a similarly cost-effective mechanism to gain these insights into spatial and temporal aspects of eagle behavior. When combined with existing information on space use of other local species, these data suggest that partitioning of spatial resources among White-tailed Eagles and other eagles at the Zapovednik may be facilitated by the alternative strategies of space use they employ.
","language":"English","publisher":"The Raptor Research Foundation","doi":"10.3356/JRR-15-84.1","usgsCitation":"Bulut, Z., Bragin, E.A., DeWoody, J.A., Braham, M.A., Katzner, T., and Doyle, J.M., 2016, Use of noninvasive genetics to assess nest and space use by white-tailed eagles: Journal of Raptor Research, v. 50, no. 4, p. 351-362, https://doi.org/10.3356/JRR-15-84.1.","productDescription":"12 p.","startPage":"351","endPage":"362","ipdsId":"IP-069074","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":470350,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.bioone.org/doi/10.3356/JRR-15-84.1","text":"External Repository"},{"id":348205,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Kazakhstan","otherGeospatial":"Naurzum Zapovednik","volume":"50","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a003151e4b0531197b5a74e","contributors":{"authors":[{"text":"Bulut, Zafer","contributorId":182413,"corporation":false,"usgs":false,"family":"Bulut","given":"Zafer","email":"","affiliations":[{"id":30222,"text":"Selcuk University","active":true,"usgs":false}],"preferred":false,"id":720398,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bragin, Evgeny A.","contributorId":194894,"corporation":false,"usgs":false,"family":"Bragin","given":"Evgeny","email":"","middleInitial":"A.","affiliations":[{"id":35656,"text":"Science Department, Naurzum National Nature Reserve, Kostanay Oblast, Naurzumski Raijon, Karamendy, Kazakhstan","active":true,"usgs":false}],"preferred":false,"id":720399,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeWoody, J. Andrew","contributorId":175103,"corporation":false,"usgs":false,"family":"DeWoody","given":"J.","email":"","middleInitial":"Andrew","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":720400,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Braham, Melissa A.","contributorId":199740,"corporation":false,"usgs":false,"family":"Braham","given":"Melissa","email":"","middleInitial":"A.","affiliations":[{"id":34303,"text":"West Virginia University, Department of Geology & Geography","active":true,"usgs":false}],"preferred":false,"id":720401,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":5979,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":720402,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Doyle, Jacqueline M.","contributorId":175099,"corporation":false,"usgs":false,"family":"Doyle","given":"Jacqueline","email":"","middleInitial":"M.","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":720403,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70179026,"text":"70179026 - 2016 - Prediction of fish and sediment mercury in streams using landscape variables and historical mining","interactions":[],"lastModifiedDate":"2018-08-07T12:06:20","indexId":"70179026","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Prediction of fish and sediment mercury in streams using landscape variables and historical mining","docAbstract":"Widespread mercury (Hg) contamination of aquatic systems in the Sierra Nevada of California, U.S., is associated with historical use to enhance gold (Au) recovery by amalgamation. In areas affected by historical Au mining operations, including the western slope of the Sierra Nevada and downstream areas in northern California, such as San Francisco Bay and the Sacramento River–San Joaquin River Delta, microbial conversion of Hg to methylmercury (MeHg) leads to bioaccumulation of MeHg in food webs, and increased risks to humans and wildlife. This study focused on developing a predictive model for THg in stream fish tissue based on geospatial data, including land use/land cover data, and the distribution of legacy Au mines. Data on total mercury (THg) and MeHg concentrations in fish tissue and streambed sediment collected during 1980–2012 from stream sites in the Sierra Nevada, California were combined with geospatial data to estimate fish THg concentrations across the landscape. THg concentrations of five fish species (Brown Trout, Rainbow Trout, Sacramento Pikeminnow, Sacramento Sucker, and Smallmouth Bass) within stream sections were predicted using multi-model inference based on Akaike Information Criteria, using geospatial data for mining history and landscape characteristics as well as fish species and length (r2 = 0.61, p < 0.001). Including THg concentrations in streambed sediment did not improve the model's fit, however including MeHg concentrations in streambed sediment, organic content (loss on ignition), and sediment grain size resulted in an improved fit (r2 = 0.63, p < 0.001). These models can be used to estimate THg concentrations in stream fish based on landscape variables in the Sierra Nevada in areas where direct measurements of THg concentration in fish are unavailable.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.05.088","usgsCitation":"Alpers, C.N., Yee, J.L., Ackerman, J., Orlando, J.L., Slotton, D., and Marvin-DiPasquale, M.C., 2016, Prediction of fish and sediment mercury in streams using landscape variables and historical mining: Science of the Total Environment, v. 571, p. 364-379, https://doi.org/10.1016/j.scitotenv.2016.05.088.","productDescription":"16 p.","startPage":"364","endPage":"379","ipdsId":"IP-071053","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":470382,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.05.088","text":"Publisher Index Page"},{"id":332083,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"571","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"585116bbe4b08138bf1abd50","contributors":{"authors":[{"text":"Alpers, Charles N. 0000-0001-6945-7365 cnalpers@usgs.gov","orcid":"https://orcid.org/0000-0001-6945-7365","contributorId":411,"corporation":false,"usgs":true,"family":"Alpers","given":"Charles","email":"cnalpers@usgs.gov","middleInitial":"N.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":655814,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yee, Julie L. 0000-0003-1782-157X julie_yee@usgs.gov","orcid":"https://orcid.org/0000-0003-1782-157X","contributorId":3246,"corporation":false,"usgs":true,"family":"Yee","given":"Julie","email":"julie_yee@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":655815,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":655816,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Orlando, James L. 0000-0002-0099-7221 jorlando@usgs.gov","orcid":"https://orcid.org/0000-0002-0099-7221","contributorId":1368,"corporation":false,"usgs":true,"family":"Orlando","given":"James","email":"jorlando@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":655817,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Slotton, Darrell G.","contributorId":103361,"corporation":false,"usgs":true,"family":"Slotton","given":"Darrell G.","affiliations":[],"preferred":false,"id":655818,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Marvin-DiPasquale, Mark C. 0000-0002-8186-9167 mmarvin@usgs.gov","orcid":"https://orcid.org/0000-0002-8186-9167","contributorId":1485,"corporation":false,"usgs":true,"family":"Marvin-DiPasquale","given":"Mark","email":"mmarvin@usgs.gov","middleInitial":"C.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":655819,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70189481,"text":"70189481 - 2016 - Eastern Whip-poor-wills (Antrostomus vociferus) are positively associated with low elevation forest In the central Appalachians","interactions":[],"lastModifiedDate":"2018-03-26T11:46:34","indexId":"70189481","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3784,"text":"Wilson Journal of Ornithology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Eastern Whip-poor-wills (Antrostomus vociferus) are positively associated with low elevation forest In the central Appalachians","title":"Eastern Whip-poor-wills (Antrostomus vociferus) are positively associated with low elevation forest In the central Appalachians","docAbstract":"Populations of the Eastern Whip-poor-will (Antrostomus vociferus) are thought to be declining because of a range of potential factors including habitat loss, pesticide use, and predation. However, this species is nocturnal and, as a consequence, it is poorly studied, and its population status is not well assessed by traditional diurnal bird surveys. We used nocturnal road surveys to study habitat associations and distribution of Eastern Whip-poor-wills to better understand and contextualize their population status and to provide a framework for subsequent research and management. We used occupancy models to associate presence of Eastern Whip-poor-wills with habitat characteristics. Global models with habitat associations at a radius of 1600 m (1.0-ha area) were the best supported by the data, suggesting that this was the scale at which the species responded to the habitat parameters we measured. At this scale, Eastern Whip-poor-wills most frequently occupied areas lower in elevation and characterized by forested, herbaceous, and wetland cover types. In contrast, high elevation conifer forest communities had substantially fewer Eastern Whip-poor-wills. Detection rates were positively correlated with moon visibility and negatively correlated with noise. We used the results of our surveys to generate a regional model to predict distributions of Eastern Whip-poor-wills and that can be used as a framework for future management. Our results suggest that succession of agricultural fields and other clearings into forested habitats with dense understory may be a contributing factor to ongoing declines of Eastern Whip-poor-wills.
","language":"English","publisher":"The Wilson Ornithological Society","doi":"10.1676/15-156.1","usgsCitation":"Slover, C.L., and Katzner, T., 2016, Eastern Whip-poor-wills (Antrostomus vociferus) are positively associated with low elevation forest In the central Appalachians: Wilson Journal of Ornithology, v. 128, no. 4, p. 846-856, https://doi.org/10.1676/15-156.1.","productDescription":"11 p.","startPage":"846","endPage":"856","ipdsId":"IP-073699","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":343818,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","otherGeospatial":"Appalachians, Monongahela National Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.6231689453125,\n 38.02213147353745\n ],\n [\n -79.398193359375,\n 38.02213147353745\n ],\n [\n -79.398193359375,\n 39.198205348894795\n ],\n [\n -80.6231689453125,\n 39.198205348894795\n ],\n [\n -80.6231689453125,\n 38.02213147353745\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"128","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"596886a1e4b0d1f9f05f59ac","contributors":{"authors":[{"text":"Slover, Christina L.","contributorId":194653,"corporation":false,"usgs":false,"family":"Slover","given":"Christina","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":704879,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":5979,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":704880,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70185040,"text":"70185040 - 2016 - Statistical comparison of methods for estimating sediment thickness from Horizontal-to-Vertical Spectral Ratio (HVSR) seismic methods: An example from Tylerville, Connecticut, USA","interactions":[],"lastModifiedDate":"2018-08-06T12:31:12","indexId":"70185040","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Statistical comparison of methods for estimating sediment thickness from Horizontal-to-Vertical Spectral Ratio (HVSR) seismic methods: An example from Tylerville, Connecticut, USA","docAbstract":"Determining sediment thickness and delineating bedrock topography are important for assessing groundwater availability and characterizing contamination sites. In recent years, the horizontal-to-vertical spectral ratio (HVSR) seismic method has emerged as a non-invasive, cost-effective approach for estimating the thickness of unconsolidated sediments above bedrock. Using a three-component seismometer, this method uses the ratio of the average horizontal- and vertical-component amplitude spectrums to produce a spectral ratio curve with a peak at the fundamental resonance frequency. The HVSR method produces clear and repeatable resonance frequency peaks when there is a sharp contrast (>2:1) in acoustic impedance at the sediment/bedrock boundary. Given the resonant frequency, sediment thickness can be determined either by (1) using an estimate of average local sediment shear-wave velocity or by (2) application of a power-law regression equation developed from resonance frequency observations at sites with a range of known depths to bedrock. Two frequently asked questions about the HVSR method are (1) how accurate are the sediment thickness estimates? and (2) how much do sediment thickness/bedrock depth estimates change when using different published regression equations? This paper compares and contrasts different approaches for generating HVSR depth estimates, through analysis of HVSR data acquired in the vicinity of Tylerville, Connecticut, USA.
Mountain snowpacks are a vital natural resource for ∼1.5 billion people in the northern Hemisphere, helping to meet human and ecological demand for water in excess of that provided by summer rain. Springtime warming and aeolian dust deposition accelerate snowmelt, increasing the risk of water shortages during late summer, when demand is greatest. While climate networks provide data that can be used to evaluate the effect of warming on snowpack resources, there are no established regional networks for monitoring aeolian dust deposition to snow. In this study, we test the hypothesis that chemistry of snow, wet deposition, and aerosols can be used as a surrogate for dust deposition to snow. We then analyze spatial patterns and temporal trends in inferred springtime dust deposition to snow across the Rocky Mountains, USA, for 1993–2014. Geochemical evidence, including strong correlations (r2 ≥ 0.94) between Ca2+, alkalinity, and dust concentrations in snow deposited during dust events, indicate that carbonate minerals in dust impart a strong chemical signature that can be used to track dust deposition to snow. Spatial patterns in chemistry of snow, wet deposition, and aerosols indicate that dust deposition increases from north to south in the Rocky Mountains, and temporal trends indicate that winter/spring dust deposition increased by 81% in the southern Rockies during 1993–2014. Using a multivariate modeling approach, we determined that increases in dust deposition and decreases in springtime snowfall combined to accelerate snowmelt timing in the southern Rockies by approximately 7–18 days between 1993 and 2014. Previous studies have shown that aeolian dust emissions may have doubled globally during the 20th century, possibly due to drought and land-use change. Climate projections for increased aridity in the southwestern U.S., northern Africa, and other mid-latitude regions of the northern Hemisphere suggest that aeolian dust emissions may continue to increase, compounding the risk that climate warming poses to snowpack water resources in arid/semi-arid regions of the world.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.atmosenv.2016.06.076","usgsCitation":"Clow, D.W., Williams, M.W., and Schuster, P.F., 2016, Increasing aeolian dust deposition to snowpacks in the Rocky Mountains inferred from snowpack, wet deposition, and aerosol chemistry: Atmospheric Environment, v. 146, p. 183-194, https://doi.org/10.1016/j.atmosenv.2016.06.076.","productDescription":"12 p.","startPage":"183","endPage":"194","ipdsId":"IP-073260","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":470368,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.atmosenv.2016.06.076","text":"Publisher Index Page"},{"id":337479,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"146","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58c7af9ce4b0849ce9795e7a","contributors":{"authors":[{"text":"Clow, David W. 0000-0001-6183-4824 dwclow@usgs.gov","orcid":"https://orcid.org/0000-0001-6183-4824","contributorId":1671,"corporation":false,"usgs":true,"family":"Clow","given":"David","email":"dwclow@usgs.gov","middleInitial":"W.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":684061,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, Mark W.","contributorId":43046,"corporation":false,"usgs":true,"family":"Williams","given":"Mark","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":684062,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schuster, Paul F. 0000-0002-8314-1372 pschuste@usgs.gov","orcid":"https://orcid.org/0000-0002-8314-1372","contributorId":1360,"corporation":false,"usgs":true,"family":"Schuster","given":"Paul","email":"pschuste@usgs.gov","middleInitial":"F.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":684063,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70175402,"text":"70175402 - 2016 - Trading shallow safety for deep sleep: Juvenile green turtles select deeper resting sites as they grow","interactions":[],"lastModifiedDate":"2018-03-27T09:55:26","indexId":"70175402","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"title":"Trading shallow safety for deep sleep: Juvenile green turtles select deeper resting sites as they grow","docAbstract":"To better protect endangered green sea turtles Chelonia mydas, a more thorough understanding of the behaviors of each life stage is needed. Although dive profile analyses obtained using time-depth loggers have provided some insights into habitat use, recent work has shown that more fine-scale monitoring of body movements is needed to elucidate physical activity patterns. We monitored 11 juvenile green sea turtles with tri-axial acceleration data loggers in their foraging grounds in Dry Tortugas National Park, Florida, USA, for periods ranging from 43 to 118 h (mean ± SD: 72.8 ± 27.3 h). Approximately half of the individuals (n = 5) remained in shallow (overall mean depth less than 2 m) water throughout the experiment, whereas the remaining individuals (n = 6) made excursions to deeper (4 to 27 m) waters, often at night. Despite these differences in depth use, acceleration data revealed a consistent pattern of diurnal activity and nocturnal resting in most individuals. Nocturnal depth differences thus do not appear to represent differences in behavior, but rather different strategies to achieve the same behavior: rest. We calculated overall dynamic body acceleration (ODBA) to assess the relative energetic cost of each behavioral strategy in an attempt to explain the differences between them. Animals in deeper water experienced longer resting dives, more time resting per hour, and lower mean hourly ODBA. These results suggest that resting in deeper water provides energetic benefits that outweigh the costs of transiting to deep water and a potential increased risk of predation.
","language":"English","publisher":"Inter-Research","doi":"10.3354/esr00750","usgsCitation":"Hart, K.M., White, C.F., Iverson, A., and Whitney, N., 2016, Trading shallow safety for deep sleep: Juvenile green turtles select deeper resting sites as they grow: Endangered Species Research, v. 31, p. 61-73, https://doi.org/10.3354/esr00750.","productDescription":"13 p.","startPage":"61","endPage":"73","ipdsId":"IP-072587","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":470364,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr00750","text":"Publisher Index Page"},{"id":337665,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Dry Tortugas National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.11363220214844,\n 24.472150437226865\n ],\n [\n -82.6776123046875,\n 24.472150437226865\n ],\n [\n -82.6776123046875,\n 24.795461666933413\n ],\n [\n -83.11363220214844,\n 24.795461666933413\n ],\n [\n -83.11363220214844,\n 24.472150437226865\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"31","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58ca52cde4b0849ce97c86a4","contributors":{"authors":[{"text":"Hart, Kristen M. 0000-0002-5257-7974 kristen_hart@usgs.gov","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":1966,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","email":"kristen_hart@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":645072,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White, Connor F.","contributorId":173554,"corporation":false,"usgs":false,"family":"White","given":"Connor","email":"","middleInitial":"F.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":645073,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Iverson, Autumn R. 0000-0002-8353-6745","orcid":"https://orcid.org/0000-0002-8353-6745","contributorId":173555,"corporation":false,"usgs":false,"family":"Iverson","given":"Autumn R.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":645074,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Whitney, Nick","contributorId":173556,"corporation":false,"usgs":false,"family":"Whitney","given":"Nick","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":645075,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70193635,"text":"70193635 - 2016 - Accurate recapture identification for genetic mark–recapture studies with error-tolerant likelihood-based match calling and sample clustering","interactions":[],"lastModifiedDate":"2017-11-13T14:58:13","indexId":"70193635","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3908,"text":"Royal Society Open Science","active":true,"publicationSubtype":{"id":10}},"title":"Accurate recapture identification for genetic mark–recapture studies with error-tolerant likelihood-based match calling and sample clustering","docAbstract":"Error-tolerant likelihood-based match calling presents a promising technique to accurately identify recapture events in genetic mark–recapture studies by combining probabilities of latent genotypes and probabilities of observed genotypes, which may contain genotyping errors. Combined with clustering algorithms to group samples into sets of recaptures based upon pairwise match calls, these tools can be used to reconstruct accurate capture histories for mark–recapture modelling. Here, we assess the performance of a recently introduced error-tolerant likelihood-based match-calling model and sample clustering algorithm for genetic mark–recapture studies. We assessed both biallelic (i.e. single nucleotide polymorphisms; SNP) and multiallelic (i.e. microsatellite; MSAT) markers using a combination of simulation analyses and case study data on Pacific walrus (Odobenus rosmarus divergens) and fishers (Pekania pennanti). A novel two-stage clustering approach is demonstrated for genetic mark–recapture applications. First, repeat captures within a sampling occasion are identified. Subsequently, recaptures across sampling occasions are identified. The likelihood-based matching protocol performed well in simulation trials, demonstrating utility for use in a wide range of genetic mark–recapture studies. Moderately sized SNP (64+) and MSAT (10–15) panels produced accurate match calls for recaptures and accurate non-match calls for samples from closely related individuals in the face of low to moderate genotyping error. Furthermore, matching performance remained stable or increased as the number of genetic markers increased, genotyping error notwithstanding.
","language":"English","publisher":"The Royal Society Publishing","doi":"10.1098/rsos.160457","usgsCitation":"Sethi, S., Linden, D., Wenburg, J., Lewis, C., Lemons, P.R., Fuller, A.K., and Hare, M.P., 2016, Accurate recapture identification for genetic mark–recapture studies with error-tolerant likelihood-based match calling and sample clustering: Royal Society Open Science, v. 3, p. 1-14, https://doi.org/10.1098/rsos.160457.","productDescription":"Article 160457; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-076769","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":470349,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rsos.160457","text":"Publisher Index Page"},{"id":348725,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fc7de4b06e28e9c23f09","contributors":{"authors":[{"text":"Sethi, Suresh 0000-0002-0053-1827 ssethi@usgs.gov","orcid":"https://orcid.org/0000-0002-0053-1827","contributorId":191424,"corporation":false,"usgs":true,"family":"Sethi","given":"Suresh","email":"ssethi@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":719697,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Linden, Daniel","contributorId":199671,"corporation":false,"usgs":false,"family":"Linden","given":"Daniel","affiliations":[],"preferred":false,"id":719698,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wenburg, John","contributorId":199672,"corporation":false,"usgs":false,"family":"Wenburg","given":"John","affiliations":[],"preferred":false,"id":719699,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lewis, Cara","contributorId":199673,"corporation":false,"usgs":false,"family":"Lewis","given":"Cara","affiliations":[],"preferred":false,"id":719700,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lemons, Patrick R.","contributorId":11014,"corporation":false,"usgs":true,"family":"Lemons","given":"Patrick","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":719701,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fuller, Angela K. 0000-0002-9247-7468 afuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-7468","contributorId":3984,"corporation":false,"usgs":true,"family":"Fuller","given":"Angela","email":"afuller@usgs.gov","middleInitial":"K.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":719703,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hare, Matthew P.","contributorId":171454,"corporation":false,"usgs":false,"family":"Hare","given":"Matthew","email":"","middleInitial":"P.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":719702,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70193670,"text":"70193670 - 2016 - Comparison of survey techniques on detection of northern flying squirrels","interactions":[],"lastModifiedDate":"2017-11-04T13:50:51","indexId":"70193670","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of survey techniques on detection of northern flying squirrels","docAbstract":"The ability to detect a species is central to the success of monitoring for conservation and management purposes, especially if the species is rare or endangered. Traditional methods, such as live capture, can be labor-intensive, invasive, and produce low detection rates. Technological advances and new approaches provide opportunities to more effectively survey for species both in terms of accuracy and efficiency than previous methods. We conducted a pilot comparison study of a traditional technique (live-trapping) and 2 novel noninvasive techniques (camera-trapping and ultrasonic acoustic surveys) on detection rates of the federally endangered Carolina northern flying squirrel (Glaucomys sabrinus coloratus) in occupied habitat within the Roan Mountain Highlands of North Carolina, USA. In 2015, we established 3 5 × 5 live-trapping grids (6.5 ha) with 4 camera traps and 4 acoustic detectors systematically embedded in each grid. All 3 techniques were used simultaneously during 2 4-day survey periods. We compared techniques by assessing probability of detection (POD), latency to detection (LTD; i.e., no. of survey nights until initial detection), and survey effort. Acoustics had the greatest POD (0.37 ± 0.06 SE), followed by camera traps (0.30 ± 0.06) and live traps (0.01 ± 0.005). Acoustics had a lower LTD than camera traps (P = 0.017), where average LTD was 1.5 nights for acoustics and 3.25 nights for camera traps. Total field effort was greatest with live traps (111.9 hr) followed by acoustics (8.4 hr) and camera traps (9.6 hr), although processing and examination for data of noninvasive techniques made overall effort similar among the 3 methods. This pilot study demonstrated that both noninvasive methods were better rapid-assessment detection techniques for flying squirrels than live traps. However, determining seasonal effects between survey techniques and further development of protocols for both noninvasive techniques is necessary prior to widespread application in the region. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.
","language":"English","publisher":"Wiley","doi":"10.1002/wsb.715","usgsCitation":"Diggins, C.A., Gilley, L.M., Kelly, C.A., and Ford, W.M., 2016, Comparison of survey techniques on detection of northern flying squirrels: Wildlife Society Bulletin, v. 40, no. 4, p. 654-662, https://doi.org/10.1002/wsb.715.","productDescription":"13 p.","startPage":"654","endPage":"662","ipdsId":"IP-074552","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":500004,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/6e146450458c4b5e965d92d9b6f7a9e5","text":"External Repository"},{"id":348195,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"40","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-27","publicationStatus":"PW","scienceBaseUri":"59fedfb5e4b0531197b573c6","contributors":{"authors":[{"text":"Diggins, Corinne A.","contributorId":171667,"corporation":false,"usgs":false,"family":"Diggins","given":"Corinne","email":"","middleInitial":"A.","affiliations":[{"id":33131,"text":"Dept of Fish and Wildlife Conservation, Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":720349,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gilley, L. Michelle","contributorId":171670,"corporation":false,"usgs":false,"family":"Gilley","given":"L.","email":"","middleInitial":"Michelle","affiliations":[{"id":35652,"text":"Mars Hill University, Mars Hill, NC","active":true,"usgs":false}],"preferred":false,"id":720350,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelly, Christine A.","contributorId":171661,"corporation":false,"usgs":false,"family":"Kelly","given":"Christine","email":"","middleInitial":"A.","affiliations":[{"id":35598,"text":"North Carolina Wildlife Resources Commission ","active":true,"usgs":false}],"preferred":false,"id":720351,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ford, W. Mark wford@usgs.gov","contributorId":3858,"corporation":false,"usgs":true,"family":"Ford","given":"W.","email":"wford@usgs.gov","middleInitial":"Mark","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":720352,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70191724,"text":"70191724 - 2016 - MODIS imagery improves pest risk assessment: A case study of wheat stem sawfly (Cephus cinctus, Hymenoptera: Cephidae) in Colorado, USA","interactions":[],"lastModifiedDate":"2017-10-25T12:30:57","indexId":"70191724","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1536,"text":"Environmental Entomology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"MODIS imagery improves pest risk assessment: A case study of wheat stem sawfly (Cephus cinctus, Hymenoptera: Cephidae) in Colorado, USA","title":"MODIS imagery improves pest risk assessment: A case study of wheat stem sawfly (Cephus cinctus, Hymenoptera: Cephidae) in Colorado, USA","docAbstract":"Wheat stem sawfly (Cephus cinctus Norton, Hymenoptera: Cephidae) has long been a significant insect pest of spring, and more recently, winter wheat in the northern Great Plains. Wheat stem sawfly was first observed infesting winter wheat in Colorado in 2010 and, subsequently, has spread rapidly throughout wheat production regions of the state. Here, we used maximum entropy modeling (MaxEnt) to generate habitat suitability maps in order to predict the risk of crop damage as this species spreads throughout the winter wheat-growing regions of Colorado. We identified environmental variables that influence the current distribution of wheat stem sawfly in the state and evaluated whether remotely sensed variables improved model performance. We used presence localities of C. cinctus and climatic, topographic, soils, and normalized difference vegetation index and enhanced vegetation index data derived from Moderate Resolution Imaging Spectroradiometer (MODIS) imagery as environmental variables. All models had high performance in that they were successful in predicting suitable habitat for C. cinctus in its current distribution in eastern Colorado. The enhanced vegetation index for the month of April improved model performance and was identified as a top contributor to MaxEnt model. Soil clay percent at 0–5 cm, temperature seasonality, and precipitation seasonality were also associated with C. cinctus distribution in Colorado. The improved model performance resulting from integrating vegetation indices in our study demonstrates the ability of remote sensing technologies to enhance species distribution modeling. These risk maps generated can assist managers in planning control measures for current infestations and assess the future risk of C. cinctus establishment in currently uninfested regions.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/ee/nvw095","usgsCitation":"Lestina, J., Cook, M., Kumar, S., Morisette, J.T., Ode, P.J., and Peirs, F., 2016, MODIS imagery improves pest risk assessment: A case study of wheat stem sawfly (Cephus cinctus, Hymenoptera: Cephidae) in Colorado, USA: Environmental Entomology, v. 45, no. 6, p. 1343-1351, https://doi.org/10.1093/ee/nvw095.","productDescription":"9 p.","startPage":"1343","endPage":"1351","ipdsId":"IP-077680","costCenters":[{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true}],"links":[{"id":347349,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","volume":"45","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-22","publicationStatus":"PW","scienceBaseUri":"59f1a2a7e4b0220bbd9d9f72","contributors":{"authors":[{"text":"Lestina, Jordan","contributorId":197312,"corporation":false,"usgs":false,"family":"Lestina","given":"Jordan","email":"","affiliations":[],"preferred":false,"id":713173,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cook, Maxwell","contributorId":197313,"corporation":false,"usgs":false,"family":"Cook","given":"Maxwell","email":"","affiliations":[],"preferred":false,"id":713174,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kumar, Sunil","contributorId":195493,"corporation":false,"usgs":false,"family":"Kumar","given":"Sunil","affiliations":[],"preferred":false,"id":713175,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morisette, Jeffrey T. 0000-0002-0483-0082 morisettej@usgs.gov","orcid":"https://orcid.org/0000-0002-0483-0082","contributorId":307,"corporation":false,"usgs":true,"family":"Morisette","given":"Jeffrey","email":"morisettej@usgs.gov","middleInitial":"T.","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":713176,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ode, Paul J.","contributorId":197314,"corporation":false,"usgs":false,"family":"Ode","given":"Paul","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":713177,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Peirs, Frank","contributorId":197315,"corporation":false,"usgs":false,"family":"Peirs","given":"Frank","email":"","affiliations":[],"preferred":false,"id":713178,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70184994,"text":"70184994 - 2016 - Temporal and spatial trends in nutrient and sediment loading to Lake Tahoe, California-Nevada, USA","interactions":[],"lastModifiedDate":"2017-03-13T12:56:10","indexId":"70184994","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","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":"Temporal and spatial trends in nutrient and sediment loading to Lake Tahoe, California-Nevada, USA","docAbstract":"Since 1980, the Lake Tahoe Interagency Monitoring Program (LTIMP) has provided stream-discharge and water quality data—nitrogen (N), phosphorus (P), and suspended sediment—at more than 20 stations in Lake Tahoe Basin streams. To characterize the temporal and spatial patterns in nutrient and sediment loading to the lake, and improve the usefulness of the program and the existing database, we have (1) identified and corrected for sources of bias in the water quality database; (2) generated synthetic datasets for sediments and nutrients, and resampled to compare the accuracy and precision of different load calculation models; (3) using the best models, recalculated total annual loads over the period of record; (4) regressed total loads against total annual and annual maximum daily discharge, and tested for time trends in the residuals; (5) compared loads for different forms of N and P; and (6) tested constituent loads against land use-land cover (LULC) variables using multiple regression. The results show (1) N and P loads are dominated by organic N and particulate P; (2) there are significant long-term downward trends in some constituent loads of some streams; and (3) anthropogenic impervious surface is the most important LULC variable influencing water quality in basin streams. Many of our recommendations for changes in water quality monitoring and load calculation methods have been adopted by the LTIMP.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12461","usgsCitation":"Coats, R., Lewis, J., Alvarez, N., and Arneson, P., 2016, Temporal and spatial trends in nutrient and sediment loading to Lake Tahoe, California-Nevada, USA: Journal of the American Water Resources Association, v. 52, no. 6, p. 1347-1365, https://doi.org/10.1111/1752-1688.12461.","productDescription":"19 p.","startPage":"1347","endPage":"1365","ipdsId":"IP-075203","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":337429,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Lake Tahoe","volume":"52","issue":"6","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-04","publicationStatus":"PW","scienceBaseUri":"58c7af9ce4b0849ce9795e7c","contributors":{"authors":[{"text":"Coats, Robert","contributorId":108007,"corporation":false,"usgs":true,"family":"Coats","given":"Robert","affiliations":[],"preferred":false,"id":683865,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lewis, Jack","contributorId":189105,"corporation":false,"usgs":false,"family":"Lewis","given":"Jack","email":"","affiliations":[],"preferred":false,"id":683866,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alvarez, Nancy L. nalvarez@usgs.gov","contributorId":4570,"corporation":false,"usgs":true,"family":"Alvarez","given":"Nancy L.","email":"nalvarez@usgs.gov","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":683864,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arneson, Patricia","contributorId":189106,"corporation":false,"usgs":false,"family":"Arneson","given":"Patricia","email":"","affiliations":[],"preferred":false,"id":683867,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70184986,"text":"70184986 - 2016 - High nitrate concentrations in some Midwest United States streams in 2013 after the 2012 drought","interactions":[],"lastModifiedDate":"2017-03-13T13:44:58","indexId":"70184986","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2262,"text":"Journal of Environmental Quality","active":true,"publicationSubtype":{"id":10}},"title":"High nitrate concentrations in some Midwest United States streams in 2013 after the 2012 drought","docAbstract":"Nitrogen sources in the Mississippi River basin have been linked to degradation of stream ecology and to Gulf of Mexico hypoxia. In 2013, the USGS and the USEPA characterized water quality stressors and ecological conditions in 100 wadeable streams across the midwestern United States. Wet conditions in 2013 followed a severe drought in 2012, a weather pattern associated with elevated nitrogen concentrations and loads in streams. Nitrate concentrations during the May to August 2013 sampling period ranged from <0.04 to 41.8 mg L−1 as N (mean, 5.31 mg L−1). Observed mean May to June nitrate concentrations at the 100 sites were compared with May to June concentrations predicted from a regression model developed using historical nitrate data. Observed concentrations for 17 sites, centered on Iowa and southern Minnesota, were outside the 95% confidence interval of the regression-predicted mean, indicating that they were anomalously high. The sites with a nitrate anomaly had significantly higher May to June nitrate concentrations than sites without an anomaly (means, 19.8 and 3.6 mg L−1, respectively) and had higher antecedent precipitation indices, a measure of the departure from normal precipitation, in 2012 and 2013. Correlations between nitrate concentrations and watershed characteristics and nitrogen and oxygen isotopes of nitrate indicated that fertilizer and manure used in crop production, principally corn, were the dominant sources of nitrate. The anomalously high nitrate levels in parts of the Midwest in 2013 coincide with reported higher-than-normal nitrate loads in the Mississippi River.
","language":"English","publisher":"ACSESS","doi":"10.2134/jeq2015.12.0591","usgsCitation":"Van Metre, P., Frey, J.W., Musgrove, M., Nakagaki, N., Qi, S.L., Mahler, B., Wieczorek, M., and Button, D.T., 2016, High nitrate concentrations in some Midwest United States streams in 2013 after the 2012 drought: Journal of Environmental Quality, v. 45, no. 5, p. 1696-1704, https://doi.org/10.2134/jeq2015.12.0591.","productDescription":"9 p.","startPage":"1696","endPage":"1704","ipdsId":"IP-064530","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":470355,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2134/jeq2015.12.0591","text":"Publisher Index Page"},{"id":337440,"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 -99.36035156249999,\n 36.63316209558658\n ],\n [\n -82.265625,\n 36.63316209558658\n ],\n [\n -82.265625,\n 45.42929873257377\n ],\n [\n -99.36035156249999,\n 45.42929873257377\n ],\n [\n -99.36035156249999,\n 36.63316209558658\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","issue":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58c7af9de4b0849ce9795e82","contributors":{"authors":[{"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":583,"text":"Texas Water Science Center","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}],"preferred":false,"id":683826,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Frey, Jeffrey W. 0000-0002-3453-5009 jwfrey@usgs.gov","orcid":"https://orcid.org/0000-0002-3453-5009","contributorId":487,"corporation":false,"usgs":true,"family":"Frey","given":"Jeffrey","email":"jwfrey@usgs.gov","middleInitial":"W.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":683827,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Musgrove, MaryLynn 0000-0003-1607-3864 mmusgrov@usgs.gov","orcid":"https://orcid.org/0000-0003-1607-3864","contributorId":1316,"corporation":false,"usgs":true,"family":"Musgrove","given":"MaryLynn","email":"mmusgrov@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":false,"id":683828,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nakagaki, Naomi 0000-0003-3653-0540 nakagaki@usgs.gov","orcid":"https://orcid.org/0000-0003-3653-0540","contributorId":1067,"corporation":false,"usgs":true,"family":"Nakagaki","given":"Naomi","email":"nakagaki@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":683829,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Qi, Sharon L. 0000-0001-7278-4498 slqi@usgs.gov","orcid":"https://orcid.org/0000-0001-7278-4498","contributorId":1130,"corporation":false,"usgs":true,"family":"Qi","given":"Sharon","email":"slqi@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":683830,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":683831,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wieczorek, Michael E. 0000-0003-0999-5457 mewieczo@usgs.gov","orcid":"https://orcid.org/0000-0003-0999-5457","contributorId":178736,"corporation":false,"usgs":true,"family":"Wieczorek","given":"Michael E.","email":"mewieczo@usgs.gov","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":683833,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Button, Daniel T. 0000-0002-7479-884X dtbutton@usgs.gov","orcid":"https://orcid.org/0000-0002-7479-884X","contributorId":2084,"corporation":false,"usgs":true,"family":"Button","given":"Daniel","email":"dtbutton@usgs.gov","middleInitial":"T.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":true,"id":683832,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70191980,"text":"70191980 - 2016 - Application of activity sensors for estimating behavioral patterns","interactions":[],"lastModifiedDate":"2017-10-19T11:09:20","indexId":"70191980","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Application of activity sensors for estimating behavioral patterns","docAbstract":"The increasing use of Global Positioning System (GPS) collars in habitat selection studies provides large numbers of precise location data points with reduced field effort. However, inclusion of activity sensors in many GPS collars also grants the potential to remotely estimate behavioral state. Thus, only using GPS collars to collect location data belies their full capabilities. Coupling behavioral state with location data would allow researchers and managers to refine habitat selection models by using diel behavioral state changes to partition fine-scale temporal shifts in habitat selection. We tested the capability of relatively unsophisticated GPS-collar activity sensors to estimate behavior throughout diel periods using free-ranging female elk (Cervus canadensis) in the Jemez Mountains of north-central New Mexico, USA, 2013–2014. Collars recorded cumulative number of movements (hits) per 15-min recording period immediately preceding GPS fixes at 0000, 0600, 1200, and 1800 hr. We measured diel behavioral patterns of focal elk, categorizing active (i.e., foraging, traveling, vigilant, grooming) and inactive (i.e., resting) states. Active behaviors (foraging, traveling) produced more average hits (0.87 ± 0.69 hits/min, 4.0 ± 2.2 hits/min, respectively; 95% CI) and inactive (resting) behavior fewer hits (−1.1 ± 0.61 95% CI). We differentiated active and inactive behavioral states with a bootstrapped threshold of 5.9 ± 3.9 hits/15-min recording period. Mean cumulative activity-sensor hits corresponded with observed diel behavioral patterns: hits increased during crepuscular (0600, 1800 hr) observations when elk were most active (0000–0600 hr: d = 0.19; 1200–1800 hr: d = 0.64) and decreased during midday and night (0000 hr, 1200 hr) when elk were least active (1800–0000 hr: d = −0.39; 0600–1200 hr: d = −0.43). Even using relatively unsophisticated GPS-collar activity sensors, managers can remotely estimate behavioral states, approximate diel behavioral patterns, and potentially complement location data in developing habitat selection models.
","language":"English","publisher":"Wildlife Society","doi":"10.1002/wsb.717","usgsCitation":"Roberts, C.P., Cain, J.W., and Cox, R.D., 2016, Application of activity sensors for estimating behavioral patterns: Wildlife Society Bulletin, v. 40, no. 4, p. 764-771, https://doi.org/10.1002/wsb.717.","productDescription":"8 p.","startPage":"764","endPage":"771","ipdsId":"IP-073791","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500012,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/98820d4696184f24abba83a7368a9360","text":"External Repository"},{"id":346951,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Jemez Mountains, Valles Caldera National Preserve","volume":"40","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-04","publicationStatus":"PW","scienceBaseUri":"59e9b997e4b05fe04cd65cc3","contributors":{"authors":[{"text":"Roberts, Caleb P. 0000-0002-8716-0423","orcid":"https://orcid.org/0000-0002-8716-0423","contributorId":197604,"corporation":false,"usgs":true,"family":"Roberts","given":"Caleb","middleInitial":"P.","affiliations":[],"preferred":false,"id":713899,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cain, James W. III 0000-0003-4743-516X jwcain@usgs.gov","orcid":"https://orcid.org/0000-0003-4743-516X","contributorId":4063,"corporation":false,"usgs":true,"family":"Cain","given":"James","suffix":"III","email":"jwcain@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":713807,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cox, Robert D.","contributorId":26240,"corporation":false,"usgs":true,"family":"Cox","given":"Robert","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":713900,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70192211,"text":"70192211 - 2016 - A possible source mechanism of the 1946 Unimak Alaska far-field tsunami, uplift of the mid-slope terrace above a splay fault zone","interactions":[],"lastModifiedDate":"2018-01-08T12:39:20","indexId":"70192211","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3208,"text":"Pure and Applied Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"A possible source mechanism of the 1946 Unimak Alaska far-field tsunami, uplift of the mid-slope terrace above a splay fault zone","docAbstract":"In 1946, megathrust seismicity along the Unimak segment of the Alaska subduction zone generated the largest ever recorded Alaska/Aleutian tsunami. The tsunami severely damaged Pacific islands and coastal areas from Alaska to Antarctica. It is the charter member of “tsunami” earthquakes that produce outsized far-field tsunamis for the recorded magnitude. Its source mechanisms were unconstrained by observations because geophysical data for the Unimak segment were sparse and of low resolution. Reprocessing of legacy geophysical data reveals a deep water, high-angle reverse or splay thrust fault zone that leads megathrust slip upward to the mid-slope terrace seafloor rather than along the plate boundary toward the trench axis. Splay fault uplift elevates the outer mid-slope terrace and its inner area subsides. Multibeam bathymetry along the splay fault zone shows recent but undated seafloor disruption. The structural configuration of the nearby Semidi segment is similar to that of the Unimak segment, portending generation of a future large tsunami directed toward the US West coast.
","language":"English","publisher":"Springer","doi":"10.1007/s00024-016-1393-x","usgsCitation":"von Huene, R.E., Miller, J.J., Klaeschen, D., and Dartnell, P., 2016, A possible source mechanism of the 1946 Unimak Alaska far-field tsunami, uplift of the mid-slope terrace above a splay fault zone: Pure and Applied Geophysics, v. 173, no. 12, p. 4189-4201, https://doi.org/10.1007/s00024-016-1393-x.","productDescription":"13 p.","startPage":"4189","endPage":"4201","ipdsId":"IP-078916","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":347112,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -168,\n 52\n ],\n [\n -154,\n 52\n ],\n [\n -154,\n 58\n ],\n [\n -168,\n 58\n ],\n [\n -168,\n 52\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"173","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-22","publicationStatus":"PW","scienceBaseUri":"59eeffaae4b0220bbd988fbd","contributors":{"authors":[{"text":"von Huene, Roland E. 0000-0003-1301-3866 rvonhuene@usgs.gov","orcid":"https://orcid.org/0000-0003-1301-3866","contributorId":191070,"corporation":false,"usgs":true,"family":"von Huene","given":"Roland","email":"rvonhuene@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":7065,"text":"USGS emeritus","active":true,"usgs":false}],"preferred":false,"id":714821,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, John J. 0000-0002-9098-0967 jjmiller@usgs.gov","orcid":"https://orcid.org/0000-0002-9098-0967","contributorId":5759,"corporation":false,"usgs":true,"family":"Miller","given":"John","email":"jjmiller@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":false,"id":714822,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klaeschen, Dirk","contributorId":198022,"corporation":false,"usgs":false,"family":"Klaeschen","given":"Dirk","email":"","affiliations":[],"preferred":false,"id":714823,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dartnell, Peter 0000-0002-9554-729X pdartnell@usgs.gov","orcid":"https://orcid.org/0000-0002-9554-729X","contributorId":2688,"corporation":false,"usgs":true,"family":"Dartnell","given":"Peter","email":"pdartnell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":714824,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70178609,"text":"70178609 - 2016 - Was everything bigger in Texas? Characterization and trends of a land-based recreational shark fishery","interactions":[],"lastModifiedDate":"2016-11-30T15:30:22","indexId":"70178609","displayToPublicDate":"2016-11-30T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2680,"text":"Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science","active":true,"publicationSubtype":{"id":10}},"title":"Was everything bigger in Texas? Characterization and trends of a land-based recreational shark fishery","docAbstract":"Although current assessments of shark population trends involve both fishery-independent and fishery-dependent data, the latter are generally limited to commercial landings that may neglect nearshore coastal habitats. Texas has supported the longest organized land-based recreational shark fishery in the United States, yet no studies have used this “non-traditional” data source to characterize the catch composition or trends in this multidecadal fishery. We analyzed catch records from two distinct periods straddling heavy commercial exploitation of sharks in the Gulf of Mexico (historical period = 1973–1986; modern period = 2008–2015) to highlight and make available the current status and historical trends in Texas’ land-based shark fishery. Catch records describing large coastal species (>1,800 mm stretched total length [STL]) were examined using multivariate techniques to assess catch seasonality and potential temporal shifts in species composition. These fishery-dependent data revealed consistent seasonality that was independent of the data set examined, although distinct shark assemblages were evident between the two periods. Similarity percentage analysis suggested decreased contributions of Lemon Shark Negaprion brevirostris over time and a general shift toward the dominance of Bull Shark Carcharhinus leucas and Blacktip Shark C. limbatus. Comparisons of mean STL for species captured in historical and modern periods further identified significant decreases for both Bull Sharks and Lemon Sharks. Size structure analysis showed a distinct paucity of landed individuals over 2,000 mm STL in recent years. Although inherent biases in reporting and potential gear-related inconsistencies undoubtedly influenced this fishery-dependent data set, the patterns in our findings documented potential declines in the size and occurrence of select large coastal shark species off Texas, consistent with declines reported in the Gulf of Mexico. Future management efforts should consider the use of non-traditional fishery-dependent data sources, such as land-based records, as data streams in stock assessments.
","language":"English","publisher":"American Fisheries Society","doi":"10.1080/19425120.2016.1227404","usgsCitation":"Ajemian, M.J., Jose, P.D., Froeschke, J.T., Wildhaber, M.L., and Stunz, G., 2016, Was everything bigger in Texas? Characterization and trends of a land-based recreational shark fishery: Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science, v. 8, no. 1, p. 553-566, https://doi.org/10.1080/19425120.2016.1227404.","productDescription":"14 p.","startPage":"553","endPage":"566","ipdsId":"IP-070564","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":470400,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/19425120.2016.1227404","text":"Publisher Index Page"},{"id":331354,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Padre Island National Seashore","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.2894287109375,\n 27.649472352561876\n ],\n [\n -97.196044921875,\n 27.620273282414246\n ],\n [\n -97.2015380859375,\n 27.518015241965667\n ],\n [\n -97.22900390625,\n 27.366889032381295\n ],\n [\n -97.2454833984375,\n 27.205785724383325\n ],\n [\n -97.23999023437499,\n 26.838776064165863\n ],\n [\n -97.2125244140625,\n 26.711266913515747\n ],\n [\n -97.22900390625,\n 26.598351182358293\n ],\n [\n -97.2894287109375,\n 26.5737895138798\n ],\n [\n -97.3828125,\n 26.5737895138798\n ],\n [\n -97.57507324218749,\n 26.62781822639305\n ],\n [\n -97.62451171875,\n 26.735799020431674\n ],\n [\n -97.62451171875,\n 26.877980817017615\n ],\n [\n -97.5860595703125,\n 27.108033801463115\n ],\n [\n -97.58056640625,\n 27.23997867180821\n ],\n [\n -97.5640869140625,\n 27.430289738862594\n ],\n [\n -97.525634765625,\n 27.537500308359462\n ],\n [\n -97.46520996093749,\n 27.6251403350933\n ],\n [\n -97.3828125,\n 27.6543381066919\n ],\n [\n -97.2894287109375,\n 27.649472352561876\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-10","publicationStatus":"PW","scienceBaseUri":"583ff348e4b04fc80e43724e","contributors":{"authors":[{"text":"Ajemian, Matthew J.","contributorId":177080,"corporation":false,"usgs":false,"family":"Ajemian","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":654534,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jose, Philip D.","contributorId":177082,"corporation":false,"usgs":false,"family":"Jose","given":"Philip","email":"","middleInitial":"D.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":654535,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Froeschke, John T.","contributorId":101794,"corporation":false,"usgs":true,"family":"Froeschke","given":"John","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":654536,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wildhaber, Mark L. 0000-0002-6538-9083 mwildhaber@usgs.gov","orcid":"https://orcid.org/0000-0002-6538-9083","contributorId":1386,"corporation":false,"usgs":true,"family":"Wildhaber","given":"Mark","email":"mwildhaber@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":654537,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stunz, Gregory W.","contributorId":51006,"corporation":false,"usgs":true,"family":"Stunz","given":"Gregory W.","affiliations":[],"preferred":false,"id":654538,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70178577,"text":"70178577 - 2016 - Vive la résistance: genome-wide selection against introduced alleles in invasive hybrid zones","interactions":[],"lastModifiedDate":"2016-11-30T17:45:04","indexId":"70178577","displayToPublicDate":"2016-11-30T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3174,"text":"Proceedings of the Royal Society B: Biological Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Vive la résistance: genome-wide selection against introduced alleles in invasive hybrid zones","docAbstract":"Evolutionary and ecological consequences of hybridization between native and invasive species are notoriously complicated because patterns of selection acting on non-native alleles can vary throughout the genome and across environments. Rapid advances in genomics now make it feasible to assess locus-specific and genome-wide patterns of natural selection acting on invasive introgression within and among natural populations occupying diverse environments. We quantified genome-wide patterns of admixture across multiple independent hybrid zones of native westslope cutthroat trout and invasive rainbow trout, the world's most widely introduced fish, by genotyping 339 individuals from 21 populations using 9380 species-diagnostic loci. A significantly greater proportion of the genome appeared to be under selection favouring native cutthroat trout (rather than rainbow trout), and this pattern was pervasive across the genome (detected on most chromosomes). Furthermore, selection against invasive alleles was consistent across populations and environments, even in those where rainbow trout were predicted to have a selective advantage (warm environments). These data corroborate field studies showing that hybrids between these species have lower fitness than the native taxa, and show that these fitness differences are due to selection favouring many native genes distributed widely throughout the genome.
","language":"English","publisher":"The Royal Society Publishing","doi":"10.1098/rspb.2016.1380","usgsCitation":"Kovach, R., Hand, B.K., Hohenlohe, P.A., Cosart, T.F., Boyer, M.C., Neville, H.H., Muhlfeld, C.C., Amish, S.J., Carim, K., Narum, S.R., Lowe, W.H., Allendorf, F., and Luikart, G., 2016, Vive la résistance: genome-wide selection against introduced alleles in invasive hybrid zones: Proceedings of the Royal Society B: Biological Sciences, v. 283, 20161380, https://doi.org/10.1098/rspb.2016.1380.","productDescription":"20161380","ipdsId":"IP-077981","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":470399,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1098/rspb.2016.1380","text":"External 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of Montana, Flathead Lake Biological Station, Polson, Montana 59860, USA","active":true,"usgs":false}],"preferred":false,"id":654447,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hand, Brian K.","contributorId":145915,"corporation":false,"usgs":false,"family":"Hand","given":"Brian","email":"","middleInitial":"K.","affiliations":[{"id":16296,"text":"University of Montana, Polson Montana 59860 USA","active":true,"usgs":false}],"preferred":false,"id":654448,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hohenlohe, Paul A.","contributorId":46399,"corporation":false,"usgs":false,"family":"Hohenlohe","given":"Paul","email":"","middleInitial":"A.","affiliations":[{"id":12708,"text":"Institute for Bioinformatics and Evolutionary Studies, Department of Biological Sciences, University of Idaho, Moscow, ID 83844","active":true,"usgs":false}],"preferred":false,"id":654449,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cosart, Ted 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H.","contributorId":177092,"corporation":false,"usgs":false,"family":"Neville","given":"Helen","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":654452,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Muhlfeld, Clint C. 0000-0002-4599-4059 cmuhlfeld@usgs.gov","orcid":"https://orcid.org/0000-0002-4599-4059","contributorId":924,"corporation":false,"usgs":true,"family":"Muhlfeld","given":"Clint","email":"cmuhlfeld@usgs.gov","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":654453,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Amish, Stephen J.","contributorId":104799,"corporation":false,"usgs":false,"family":"Amish","given":"Stephen","email":"","middleInitial":"J.","affiliations":[{"id":5097,"text":"University of Montana, Division of Biological 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USA.","active":true,"usgs":false}],"preferred":false,"id":654457,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Allendorf, Fred W.","contributorId":83432,"corporation":false,"usgs":false,"family":"Allendorf","given":"Fred W.","affiliations":[{"id":5091,"text":"Flathead Lake Biological Station, Fish and Wildlife Genomics Group, Division of Biological Sciences, University of Montana, Polson, MT 59860, USA","active":true,"usgs":false}],"preferred":false,"id":654458,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Luikart, Gordon","contributorId":145746,"corporation":false,"usgs":false,"family":"Luikart","given":"Gordon","email":"","affiliations":[{"id":16220,"text":"Flathead Lake Biological Station, Div. Biological Science, UM","active":true,"usgs":false}],"preferred":false,"id":654459,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70189828,"text":"70189828 - 2016 - Annualized earthquake loss estimates for California and their sensitivity to site amplification","interactions":[],"lastModifiedDate":"2017-07-27T14:36:20","indexId":"70189828","displayToPublicDate":"2016-11-30T00:00:00","publicationYear":"2016","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":"Annualized earthquake loss estimates for California and their sensitivity to site amplification","docAbstract":"Input datasets for annualized earthquake loss (AEL) estimation for California were updated recently by the scientific community, and include the National Seismic Hazard Model (NSHM), site‐response model, and estimates of shear‐wave velocity. Additionally, the Federal Emergency Management Agency’s loss estimation tool, Hazus, was updated to include the most recent census and economic exposure data. These enhancements necessitated a revisit to our previous AEL estimates and a study of the sensitivity of AEL estimates subjected to alternate inputs for site amplification. The NSHM ground motions for a uniform site condition are modified to account for the effect of local near‐surface geology. The site conditions are approximated in three ways: (1) by VS30 (time‐averaged shear‐wave velocity in the upper 30 m) value obtained from a geology‐ and topography‐based map consisting of 15 VS30 groups, (2) by site classes categorized according to National Earthquake Hazards Reduction Program (NEHRP) site classification, and (3) by a uniform NEHRP site class D. In case 1, ground motions are amplified using the Seyhan and Stewart (2014) semiempirical nonlinear amplification model. In cases 2 and 3, ground motions are amplified using the 2014 version of the NEHRP site amplification factors, which are also based on the Seyhan and Stewart model but are approximated to facilitate their use for building code applications. Estimated AELs are presented at multiple resolutions, starting with the state level assessment and followed by detailed assessments for counties, metropolitan statistical areas (MSAs), and cities. AEL estimate at the state level is ∼$3.7 billion, 70% of which is contributed from Los Angeles–Long Beach–Santa Ana, San Francisco–Oakland–Fremont, and Riverside–San Bernardino–Ontario MSAs. The statewide AEL estimate is insensitive to alternate assumptions of site amplification. However, we note significant differences in AEL estimates among the three sensitivity cases for smaller geographic units.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220160099","usgsCitation":"Chen, R., Jaiswal, K.S., Bausch, D., Seligson, H., and Wills, C., 2016, Annualized earthquake loss estimates for California and their sensitivity to site amplification: Seismological Research Letters, v. 87, no. 6, p. 1363-1372, https://doi.org/10.1785/0220160099.","productDescription":"10 p.","startPage":"1363","endPage":"1372","ipdsId":"IP-078937","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":344403,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","volume":"87","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-07","publicationStatus":"PW","scienceBaseUri":"597afba7e4b0a38ca2750b62","contributors":{"authors":[{"text":"Chen, Rui","contributorId":187504,"corporation":false,"usgs":false,"family":"Chen","given":"Rui","email":"","affiliations":[],"preferred":false,"id":706485,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaiswal, Kishor S. 0000-0002-5803-8007 kjaiswal@usgs.gov","orcid":"https://orcid.org/0000-0002-5803-8007","contributorId":149796,"corporation":false,"usgs":true,"family":"Jaiswal","given":"Kishor","email":"kjaiswal@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":706486,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bausch, D","contributorId":195187,"corporation":false,"usgs":false,"family":"Bausch","given":"D","affiliations":[],"preferred":false,"id":706487,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Seligson, H","contributorId":195188,"corporation":false,"usgs":false,"family":"Seligson","given":"H","email":"","affiliations":[],"preferred":false,"id":706488,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wills, C.J.","contributorId":195189,"corporation":false,"usgs":false,"family":"Wills","given":"C.J.","email":"","affiliations":[],"preferred":false,"id":706489,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70178563,"text":"70178563 - 2016 - Lidar-based mapping of flood control levees in south Louisiana","interactions":[],"lastModifiedDate":"2022-04-22T14:50:07.222","indexId":"70178563","displayToPublicDate":"2016-11-30T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2068,"text":"International Journal of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Lidar-based mapping of flood control levees in south Louisiana","docAbstract":"Flood protection in south Louisiana is largely dependent on earthen levees, and in the aftermath of Hurricane Katrina the state’s levee system has received intense scrutiny. Accurate elevation data along the levees are critical to local levee district managers responsible for monitoring and maintaining the extensive system of non-federal levees in coastal Louisiana. In 2012, high resolution airborne lidar data were acquired over levees in Lafourche Parish, Louisiana, and a mobile terrestrial lidar survey was conducted for selected levee segments using a terrestrial lidar scanner mounted on a truck. The mobile terrestrial lidar data were collected to test the feasibility of using this relatively new technology to map flood control levees and to compare the accuracy of the terrestrial and airborne lidar. Metrics assessing levee geometry derived from the two lidar surveys are also presented as an efficient, comprehensive method to quantify levee height and stability. The vertical root mean square error values of the terrestrial lidar and airborne lidar digital-derived digital terrain models were 0.038 m and 0.055 m, respectively. The comparison of levee metrics derived from the airborne and terrestrial lidar-based digital terrain models showed that both types of lidar yielded similar results, indicating that either or both surveying techniques could be used to monitor geomorphic change over time. Because airborne lidar is costly, many parts of the USA and other countries have never been mapped with airborne lidar, and repeat surveys are often not available for change detection studies. Terrestrial lidar provides a practical option for conducting repeat surveys of levees and other terrain features that cover a relatively small area, such as eroding cliffs or stream banks, and dunes.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/01431161.2016.1249304","usgsCitation":"Thatcher, C.A., Lim, S., Palaseanu-Lovejoy, M., Danielson, J.J., and Kimbrow, D.R., 2016, Lidar-based mapping of flood control levees in south Louisiana: International Journal of Remote Sensing, v. 37, no. 24, p. 5708-5725, https://doi.org/10.1080/01431161.2016.1249304.","productDescription":"18 p.","startPage":"5708","endPage":"5725","ipdsId":"IP-055230","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":331364,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","county":"Lafourche Parish","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.56,\n 29.56\n ],\n [\n -90.56,\n 29.65\n ],\n [\n -90.45,\n 29.65\n ],\n [\n -90.45,\n 29.56\n ],\n [\n -90.56,\n 29.56\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"37","issue":"24","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-28","publicationStatus":"PW","scienceBaseUri":"583ff34be4b04fc80e437256","contributors":{"authors":[{"text":"Thatcher, Cindy A. 0000-0003-0331-071X thatcherc@usgs.gov","orcid":"https://orcid.org/0000-0003-0331-071X","contributorId":2868,"corporation":false,"usgs":true,"family":"Thatcher","given":"Cindy","email":"thatcherc@usgs.gov","middleInitial":"A.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":654379,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lim, Samsung","contributorId":177043,"corporation":false,"usgs":false,"family":"Lim","given":"Samsung","email":"","affiliations":[],"preferred":false,"id":654380,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Palaseanu-Lovejoy, Monica 0000-0002-3786-5118 mpal@usgs.gov","orcid":"https://orcid.org/0000-0002-3786-5118","contributorId":3639,"corporation":false,"usgs":true,"family":"Palaseanu-Lovejoy","given":"Monica","email":"mpal@usgs.gov","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":654381,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Danielson, Jeffrey J. 0000-0003-0907-034X daniels@usgs.gov","orcid":"https://orcid.org/0000-0003-0907-034X","contributorId":3996,"corporation":false,"usgs":true,"family":"Danielson","given":"Jeffrey","email":"daniels@usgs.gov","middleInitial":"J.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":654382,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kimbrow, Dustin R. dkimbrow@usgs.gov","contributorId":3915,"corporation":false,"usgs":true,"family":"Kimbrow","given":"Dustin","email":"dkimbrow@usgs.gov","middleInitial":"R.","affiliations":[{"id":105,"text":"Alabama Water Science Center","active":true,"usgs":true}],"preferred":true,"id":654383,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70177047,"text":"sir20165145 - 2016 - Characterization and relation of precipitation, streamflow, and water-quality data at the U.S. Army Garrison Fort Carson and Piñon Canyon Maneuver Site, Colorado, water years 2013–14","interactions":[],"lastModifiedDate":"2016-11-30T11:06:37","indexId":"sir20165145","displayToPublicDate":"2016-11-29T16:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5145","title":"Characterization and relation of precipitation, streamflow, and water-quality data at the U.S. Army Garrison Fort Carson and Piñon Canyon Maneuver Site, Colorado, water years 2013–14","docAbstract":"To evaluate the influence of military training activities on streamflow and water quality, the U.S. Geological Survey, in cooperation with the U.S. Department of the Army, began a hydrologic data collection network on the U.S. Army Garrison Fort Carson in 1978 and on the Piñon Canyon Maneuver Site in 1983. This report is a summary and characterization of the precipitation, streamflow, and water-quality data collected at 43 sites between October 1, 2012, and September 30, 2014 (water years 2013 and 2014).
Variations in the frequency of daily precipitation, seasonal distribution, and seasonal and annual precipitation at 5 stations at the U.S. Army Garrison Fort Carson and 18 stations at or near the Piñon Canyon Maneuver Site were evaluated. Isohyetal diagrams indicated a general pattern of increase in total annual precipitation from east to west at the U.S. Army Garrison Fort Carson and the Piñon Canyon Maneuver Site. Between about 54 and 79 percent of daily precipitation was 0.1 inch or less in magnitude. Precipitation events were larger and more frequent between July and September.
Daily streamflow data from 16 sites were used to evaluate temporal and spatial variations in streamflow for the water years 2013 and 2014. At all sites, median daily mean streamflow for the 2-year period ranged from 0.0 to 9.60 cubic feet per second. Daily mean streamflow hydrographs are included in this report. Five sites on the Piñon Canyon Maneuver Site were monitored for peak stage using crest-stage gages.
At the Piñon Canyon Maneuver Site, five sites had a stage recorder and precipitation gage, providing a paired streamflow-precipitation dataset. There was a statistically significant correlation between precipitation and streamflow based on Spearman’s rho correlation (rho values ranged from 0.17 to 0.35).
Suspended-sediment samples were collected in April through October for water years 2013–14 at one site at the U.S. Army Garrison Fort Carson and five sites at the Piñon Canyon Maneuver Site. Suspended-sediment-transport curves were used to illustrate the relation between streamflow and suspended-sediment concentration. All these sediment-transport curves showed a streamflow dependent suspended-sediment concentration relation except for the U.S. Geological Survey station Bent Canyon Creek at mouth near Timpas, CO.
Water-quality data were collected and reported from seven sites on the U.S. Army Garrison Fort Carson and the Piñon Canyon Maneuver Site during water years 2013–14. Sample results exceeding an established water-quality standard were identified. Selected water-quality properties and constituents were stratified to compare spatial variation among selected characteristics using boxplots.
Trilinear diagrams were used to classify water type based on ionic concentrations of water-quality samples collected during the study period.
At the U.S. Army Garrison Fort Carson and the Piñon Canyon Maneuver Site, 27 samples were classified as very hard or brackish. Seven samples had a lower hardness character relative to the other samples. Four of those nine samples were collected at two U.S. Geological Survey stations (Turkey Creek near Fountain, CO, and Little Fountain Creek above Highway 115 at Fort Carson, CO), which have different geologic makeup. Three samples collected at the Piñon Canyon Maneuver Site had a markedly lower hardness likely because of dilution from an increase in streamflow.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165145","collaboration":"Prepared in cooperation the U.S. Department of the Army","usgsCitation":"Holmberg, M.J., Stogner, R.W., Sr., and Bruce, J.F., 2016, Characterization and relation of precipitation, streamflow, and water-quality data at the U.S. Army Garrison Fort Carson and Piñon Canyon Maneuver Site, Colorado, water years 2013–14: U.S. Geological Survey Scientific Investigations Report 2016–5145, 58 p., https://doi.org/10.3133/sir20165145.","productDescription":"viii, 58 p.","onlineOnly":"Y","ipdsId":"IP-071890","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":331269,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5145/coverthb.jpg"},{"id":331270,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5145/sir20165145.pdf","text":"Report","size":"6.82 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5145"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.5,\n 38\n ],\n [\n -104.5,\n 39\n ],\n [\n -105,\n 39\n ],\n [\n -105,\n 38\n ],\n [\n -104.5,\n 38\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.2,\n 37.5\n ],\n [\n -104.2,\n 38\n ],\n [\n -103.5,\n 38\n ],\n [\n -103.5,\n 37.5\n ],\n [\n -104.2,\n 37.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, USGS Colorado Water Science Center
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