{"pageNumber":"399","pageRowStart":"9950","pageSize":"25","recordCount":46619,"records":[{"id":70193338,"text":"70193338 - 2016 - Response of fish assemblages to decreasing acid deposition in Adirondack Mountain lakes","interactions":[],"lastModifiedDate":"2018-02-14T11:45:45","indexId":"70193338","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":5590,"text":"NYSERDA Report","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"17-01","title":"Response of fish assemblages to decreasing acid deposition in Adirondack Mountain lakes","docAbstract":"The CAA and other federal regulations have clearly reduced emissions of NOx and SOx, acidic deposition, and the acidity and toxicity of waters in the ALTM lakes, but these changes have not triggered widespread recovery of brook trout populations or fish communities. The lack of detectable biological recovery appears to result from relatively recent chemical recovery and an insufficient period for species populations to take advantage of improved water quality. Recovery of extirpated species’ populations may simply require more time for individuals to migrate to and repopulate formerly occupied lakes. Supplemental stocking of selected species may be required in some lakes with no remnant (or nearby) populations or with physical barriers between the recovered lake and source populations. The lack of detectable biological recovery could also be related to our inability to calculate measures of uncertainty or error and, thus, examine temporal changes or differences in populations and community metrics in more depth (e.g., within individual lakes) using existing datasets. Indeed, recovery of brook trout populations and partial recovery of fish communities are documented in several lakes of the region, both with and without human intervention. Multiple fish surveys (annually or within the same year) or the use of mark and recapture methods within individual lakes would help alleviate the issue (provide measures of error for key fishery metrics) within the context of a more focused sampling strategy. Efforts to evaluate and detect recovery in fish assemblages from streams may be more effective than in lakes because various life stages, species’ populations, and entire assemblages are easier to quantify, with known levels of error, in streams than in lakes. Such long-term monitoring efforts could increase our ability to detect and quantify biological recovery in recovering (neutralizing) surface waters throughout the Adirondack Region.","language":"English","publisher":"New York State Energy Research and Development Authority","usgsCitation":"Baldigo, B.P., Roy, K., and Driscoll, C.T., 2016, Response of fish assemblages to decreasing acid deposition in Adirondack Mountain lakes: NYSERDA Report 17-01, iv, 15 p.","productDescription":"iv, 15 p.","numberOfPages":"24","ipdsId":"IP-084560","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":351604,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":347915,"type":{"id":15,"text":"Index Page"},"url":"https://www.nyserda.ny.gov/-/media/Files/Publications/Research/Environmental/17-01-Response-fish-Assemblages-decreasing-acid-deposition.pdf"}],"country":"United States","state":"New York","otherGeospatial":"Adirondacks","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -75.25,\n              43\n            ],\n            [\n              -73.311767578125,\n              43\n            ],\n            [\n              -73.311767578125,\n              44.88798544802555\n            ],\n            [\n              -75.25,\n              44.88798544802555\n            ],\n            [\n              -75.25,\n              43\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee92ee4b0da30c1bfc532","contributors":{"authors":[{"text":"Baldigo, Barry P. 0000-0002-9862-9119 bbaldigo@usgs.gov","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":1234,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","email":"bbaldigo@usgs.gov","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":718736,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roy, Karen","contributorId":178106,"corporation":false,"usgs":false,"family":"Roy","given":"Karen","affiliations":[],"preferred":false,"id":718737,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Driscoll, Charles T.","contributorId":167460,"corporation":false,"usgs":false,"family":"Driscoll","given":"Charles","email":"","middleInitial":"T.","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":718738,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70190306,"text":"70190306 - 2016 - Re-Occupancy of Breeding Territories by Ferruginous Hawks in Wyoming: Relationships to Environmental and Anthropogenic Factors","interactions":[],"lastModifiedDate":"2017-08-28T13:35:41","indexId":"70190306","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Re-Occupancy of Breeding Territories by Ferruginous Hawks in Wyoming: Relationships to Environmental and Anthropogenic Factors","docAbstract":"<p><span>Grassland and shrubland birds are declining globally due in part to anthropogenic habitat modification. Because population performance of these species is also influenced by non-anthropogenic factors, it is important to incorporate all relevant ecological drivers into demographic models. We used design-based sampling and occupancy models to test relationships of environmental factors that influence raptor demographics with re-occupancy of breeding territories by ferruginous hawks (</span><i>Buteo regalis</i><span>) across Wyoming, USA, 2011–2013. We also tested correlations of territory re-occupancy with oil and gas infrastructure—a leading cause of habitat modification throughout the range of this species of conservation concern. Probability of re-occupancy was not related to any covariates we investigated in 2011, had a strong negative relationship with cover of sagebrush (</span><i>Artemisia</i><span><span>&nbsp;</span>spp.) in 2012, was slightly higher for territories with artificial platforms than other nest substrates in 2013, and had a positive relationship with abundance of ground squirrels (</span><i>Urocitellus</i><span><span>&nbsp;</span>spp.) that was strong in 2012 and weak in 2013. Associations with roads were weak and varied by year, road-type, and scale: in 2012, re-occupancy probability had a weak positive correlation with density of roads not associated with oil and gas fields at the territory-scale; however, in 2013 re-occupancy had a very weak negative correlation with density of oil and gas field roads near nest sites (≤500 m). Although our results indicate re-occupancy of breeding territories by ferruginous hawks was compatible with densities of anthropogenic infrastructure in our study area, the lack of relationships between oil and gas well density and territory re-occupancy may have occurred because pre-treatment data were unavailable. We used probabilistic sampling at a broad spatial extent, methods to account for imperfect detection, and conducted extensive prey sampling; nonetheless, future research using before-after-control-impact designs is needed to fully assess impacts of oil and gas development on ferruginous hawks.</span></p>","language":"English","publisher":"PLOS ONE","doi":"10.1371/journal.pone.0152977","usgsCitation":"Wallace, Z.P., Kennedy, P.L., Squires, J.R., Oakleaf, R.J., Olson, L.E., and Dugger, K.M., 2016, Re-Occupancy of Breeding Territories by Ferruginous Hawks in Wyoming: Relationships to Environmental and Anthropogenic Factors: PLoS ONE, v. 11, no. 4, e0152977; 16 p., https://doi.org/10.1371/journal.pone.0152977.","productDescription":"e0152977; 16 p.","ipdsId":"IP-059418","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470387,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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R.","contributorId":195901,"corporation":false,"usgs":false,"family":"Squires","given":"John","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":708635,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oakleaf, Robert J.","contributorId":195902,"corporation":false,"usgs":false,"family":"Oakleaf","given":"Robert","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":708636,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Olson, Lucretia E.","contributorId":195903,"corporation":false,"usgs":false,"family":"Olson","given":"Lucretia","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":708637,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dugger, Katie M. 0000-0002-4148-246X","orcid":"https://orcid.org/0000-0002-4148-246X","contributorId":36037,"corporation":false,"usgs":true,"family":"Dugger","given":"Katie","email":"","middleInitial":"M.","affiliations":[{"id":517,"text":"Oregon Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"preferred":false,"id":708363,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70178781,"text":"70178781 - 2016 - Oxygen, hydrogen, sulfur, and carbon isotopes in the Pea Ridge magnetite-apatite deposit, southeast Missouri, and sulfur isotope comparisons to other iron deposits in the region","interactions":[],"lastModifiedDate":"2016-12-07T14:09:06","indexId":"70178781","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":"Oxygen, hydrogen, sulfur, and carbon isotopes in the Pea Ridge magnetite-apatite deposit, southeast Missouri, and sulfur isotope comparisons to other iron deposits in the region","docAbstract":"<p id=\"p-1\">Oxygen, hydrogen, sulfur, and carbon isotopes have been analyzed in the Pea Ridge magnetite-apatite deposit, the largest historic producer among the known iron deposits in the southeast Missouri portion of the 1.5 to 1.3 Ga eastern granite-rhyolite province. The data were collected to investigate the sources of ore fluids, conditions of ore formation, and provenance of sulfur, and to improve the general understanding of the copper, gold, and rare earth element potential of iron deposits regionally. The <i>δ</i><sup>18</sup>O values of Pea Ridge magnetite are 1.9 to 4.0‰, consistent with a model in which some magnetite crystallized from a melt and other magnetite—perhaps the majority—precipitated from an aqueous fluid of magmatic origin. The <i>δ</i><sup>18</sup>O values of quartz, apatite, actinolite, K-feldspar, sulfates, and calcite are significantly higher, enough so as to indicate growth or equilibration under cooler conditions than magnetite and/or in the presence of a fluid that was not entirely magmatic. A variety of observations, including stable isotope observations, implicate a second fluid that may ultimately have been meteoric in origin and may have been modified by isotopic exchange with rocks or by evaporation during storage in lakes.</p><p id=\"p-2\">Sulfur isotope analyses of sulfides from Pea Ridge and seven other mineral deposits in the region reveal two distinct populations that average 3 and 13‰. Two sulfur sources are implied. One was probably igneous melts or rocks belonging to the mafic- to intermediate-composition volcanic suite that is present at or near most of the iron deposits; the other was either melts or volcanic rocks that had degassed very extensively, or else volcanic lakes that had trapped rising magmatic gases. The higher <i>δ</i><sup>34</sup>S values correspond to deposits or prospects where copper is noteworthy—the Central Dome portion of the Boss deposit, the Bourbon deposit, and the Vilander prospective area. The correspondence suggests that (1) sulfur either limited the deposition of copper or was cotransported with copper, and (2) sulfur isotope analysis may be useful in evaluating southeast Missouri iron deposits for copper and possibly for gold.</p>","language":"English","publisher":"Society of Economic Geologists","doi":"10.2113/econgeo.111.8.2017","usgsCitation":"Johnson, C.A., Day, W.C., and Rye, R.O., 2016, Oxygen, hydrogen, sulfur, and carbon isotopes in the Pea Ridge magnetite-apatite deposit, southeast Missouri, and sulfur isotope comparisons to other iron deposits in the region: Economic Geology, v. 111, no. 8, p. 2017-2032, https://doi.org/10.2113/econgeo.111.8.2017.","productDescription":"16 p.","startPage":"2017","endPage":"2032","ipdsId":"IP-069800","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":331639,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","volume":"111","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-16","publicationStatus":"PW","scienceBaseUri":"58492df2e4b06d80b7b093a0","contributors":{"authors":[{"text":"Johnson, Craig A. 0000-0002-1334-2996 cjohnso@usgs.gov","orcid":"https://orcid.org/0000-0002-1334-2996","contributorId":909,"corporation":false,"usgs":true,"family":"Johnson","given":"Craig","email":"cjohnso@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":655118,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":655119,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rye, Robert O. rrye@usgs.gov","contributorId":1486,"corporation":false,"usgs":true,"family":"Rye","given":"Robert","email":"rrye@usgs.gov","middleInitial":"O.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":655120,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70192492,"text":"70192492 - 2016 - Satellite-derived temperature data for monitoring water status in a floodplain forest of the Upper Sabine River, Texas","interactions":[],"lastModifiedDate":"2017-10-26T12:23:04","indexId":"70192492","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3444,"text":"Southeastern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Satellite-derived temperature data for monitoring water status in a floodplain forest of the Upper Sabine River, Texas","docAbstract":"<p><span>Decreased water availability due to hydrologic modifications, groundwater withdrawal, and climate change threaten bottomland hardwood (BLH) forest communities. We used satellite-derived (MODIS) land-surface temperature (LST) data to investigate spatial heterogeneity of canopy temperature (an indicator of plant-water status) in a floodplain forest of the upper Sabine River for 2008–2014. High LST pixels were generally further from the river and at higher topographic locations, indicating lower water-availability. Increasing rainfall-derived soil moisture corresponded with decreased heterogeneity of LST between pixels but there was weaker association between Sabine River stage and heterogeneity. Stronger dependence of LST convergence on rainfall rather than river flow suggests that some regions are less hydrologically connected to the river, and vegetation may rely on local precipitation and other contributions to the riparian aquifer to replenish soil moisture. Observed LST variations associated with hydrology encourage further investigation of the utility of this approach for monitoring forest stress, especially with considerations of climate change and continued river management.</span></p>","language":"English","publisher":"Eagle Hill Institute","doi":"10.1656/058.015.0sp911","usgsCitation":"Lemon, M.G., Allen, S.T., Edwards, B., King, S.L., and Keim, R., 2016, Satellite-derived temperature data for monitoring water status in a floodplain forest of the Upper Sabine River, Texas: Southeastern Naturalist, v. 15, no. sp9, p. 90-102, https://doi.org/10.1656/058.015.0sp911.","productDescription":"13 p.","startPage":"90","endPage":"102","ipdsId":"IP-066074","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":347463,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Upper Sabine River","volume":"15","issue":"sp9","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a07e98de4b09af898c8cc2c","contributors":{"authors":[{"text":"Lemon, Mary Grace T.","contributorId":198501,"corporation":false,"usgs":false,"family":"Lemon","given":"Mary","email":"","middleInitial":"Grace T.","affiliations":[],"preferred":false,"id":716258,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allen, Scott T.","contributorId":168409,"corporation":false,"usgs":false,"family":"Allen","given":"Scott","email":"","middleInitial":"T.","affiliations":[{"id":25282,"text":"School of Renewable Natural Resources, Louisiana State University, Baton Rouge, LA","active":true,"usgs":false}],"preferred":false,"id":716259,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Edwards, Brandon L.","contributorId":35231,"corporation":false,"usgs":true,"family":"Edwards","given":"Brandon L.","affiliations":[],"preferred":false,"id":716260,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"King, Sammy L. 0000-0002-5364-6361 sking@usgs.gov","orcid":"https://orcid.org/0000-0002-5364-6361","contributorId":557,"corporation":false,"usgs":true,"family":"King","given":"Sammy","email":"sking@usgs.gov","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":716068,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Keim, Richard F.","contributorId":21858,"corporation":false,"usgs":true,"family":"Keim","given":"Richard F.","affiliations":[],"preferred":false,"id":716261,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"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":"<p><span>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 (</span><i class=\"EmphasisTypeItalic \">Calidris pussila</i><span>) 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.</span></p>","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":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":"<p><span>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.</span></p>","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":70192677,"text":"70192677 - 2016 - Development of a Kemp’s ridley sea turtle stock assessment model","interactions":[],"lastModifiedDate":"2020-12-21T14:45:16.380494","indexId":"70192677","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1873,"text":"Gulf of Mexico Science","active":true,"publicationSubtype":{"id":10}},"title":"Development of a Kemp’s ridley sea turtle stock assessment model","docAbstract":"<p><span>We developed a Kemp’s ridley (</span><i>Lepidochelys kempii</i><span>) stock assessment model to evaluate the relative contributions of conservation efforts and other factors toward this critically endangered species’ recovery. The Kemp’s ridley demographic model developed by the Turtle Expert Working Group (TEWG) in 1998 and 2000 and updated for the binational recovery plan in 2011 was modified for use as our base model. The TEWG model uses indices of the annual reproductive population (number of nests) and hatchling recruitment to predict future annual numbers of nests on the basis of a series of assumptions regarding age and maturity, remigration interval, sex ratios, nests per female, juvenile mortality, and a putative ‘‘turtle excluder device effect’’ multiplier starting in 1990. This multiplier was necessary to fit the number of nests observed in 1990 and later. We added the effects of shrimping effort directly, modified by habitat weightings, as a proxy for all sources of anthropogenic mortality. Additional data included in our model were incremental growth of Kemp’s ridleys marked and recaptured in the Gulf of Mexico, and the length frequency of stranded Kemp’s ridleys. We also added a 2010 mortality factor that was necessary to fit the number of nests for 2010 and later (2011 and 2012). Last, we used an empirical basis for estimating natural mortality, on the basis of a Lorenzen mortality curve and growth estimates. Although our model generated reasonable estimates of annual total turtle deaths attributable to shrimp trawling, as well as additional deaths due to undetermined anthropogenic causes in 2010, we were unable to provide a clear explanation for the observed increase in the number of stranded Kemp’s ridleys in recent years, and subsequent disruption of the species’ exponential growth since the 2009 nesting season. Our consensus is that expanded data collection at the nesting beaches is needed and of high priority, and that 2015 be targeted for the next stock assessment to evaluate the 2010 event using more recent nesting and in-water data.</span></p>","language":"English","publisher":"Gulf of Mexico Science","doi":"10.18785/goms.3302.03","usgsCitation":"Gallaway, B.J., Gazey, W., Caillouet, C.W., Plotkin, P.T., Abreu Grobois, F.A., Amos, A.F., Burchfield, P.M., Carthy, R.R., Castro Martinez, M.A., Cole, J.G., Coleman, A.T., Cook, M., DiMarco, S.F., Epperly, S.P., Fujiwara, M., Gamez, D.G., Graham, G.L., Griffin, W.L., Illescas Martinez, F., Lamont, M.M., Lewison, R.L., Lohmann, K.J., Nance, J.M., Pitchford, J., Putman, N.F., Raborn, S.W., Rester, J.K., Rudloe, J.J., Sarti Martinez, L., Schexnayder, M., Schmid, J.R., Shaver, D.J., Slay, C., Tucker, A.D., Tumlin, M., Wibbels, T., and Zapata Najera, B.M., 2016, Development of a Kemp’s ridley sea turtle stock assessment model: Gulf of Mexico 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rayc@usgs.gov","orcid":"https://orcid.org/0000-0001-8978-5083","contributorId":3685,"corporation":false,"usgs":true,"family":"Carthy","given":"Raymond","email":"rayc@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":723495,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Castro Martinez, Marco A.","contributorId":200821,"corporation":false,"usgs":false,"family":"Castro Martinez","given":"Marco","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":723496,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cole, John G.","contributorId":200822,"corporation":false,"usgs":false,"family":"Cole","given":"John","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":723497,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Coleman, Andrew T.","contributorId":200823,"corporation":false,"usgs":false,"family":"Coleman","given":"Andrew","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":723498,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Cook, Melissa","contributorId":200824,"corporation":false,"usgs":false,"family":"Cook","given":"Melissa","email":"","affiliations":[],"preferred":false,"id":723499,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"DiMarco, Steven F.","contributorId":15435,"corporation":false,"usgs":true,"family":"DiMarco","given":"Steven","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":723500,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Epperly, Sheryan P.","contributorId":200825,"corporation":false,"usgs":false,"family":"Epperly","given":"Sheryan","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":723501,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Fujiwara, Masami","contributorId":200826,"corporation":false,"usgs":false,"family":"Fujiwara","given":"Masami","email":"","affiliations":[],"preferred":false,"id":723502,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Gamez, Daniel Gomez","contributorId":32065,"corporation":false,"usgs":true,"family":"Gamez","given":"Daniel","email":"","middleInitial":"Gomez","affiliations":[],"preferred":false,"id":723503,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Graham, Gary L.","contributorId":200827,"corporation":false,"usgs":false,"family":"Graham","given":"Gary","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":723504,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Griffin, Wade L.","contributorId":200828,"corporation":false,"usgs":false,"family":"Griffin","given":"Wade","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":723505,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Illescas Martinez, Francisco","contributorId":200829,"corporation":false,"usgs":false,"family":"Illescas Martinez","given":"Francisco","email":"","affiliations":[],"preferred":false,"id":723506,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Lamont, Margaret M. 0000-0001-7520-6669 mlamont@usgs.gov","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":4525,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","email":"mlamont@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":723507,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Lewison, Rebecca L.","contributorId":194537,"corporation":false,"usgs":false,"family":"Lewison","given":"Rebecca","email":"","middleInitial":"L.","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":723508,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Lohmann, Kenneth J.","contributorId":172284,"corporation":false,"usgs":false,"family":"Lohmann","given":"Kenneth","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":723509,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Nance, James M.","contributorId":200830,"corporation":false,"usgs":false,"family":"Nance","given":"James","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":723510,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Pitchford, Jonathan","contributorId":200831,"corporation":false,"usgs":false,"family":"Pitchford","given":"Jonathan","affiliations":[],"preferred":false,"id":723511,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Putman, Nathan Freeman","contributorId":145423,"corporation":false,"usgs":false,"family":"Putman","given":"Nathan","email":"","middleInitial":"Freeman","affiliations":[{"id":16119,"text":"National Marine Fisheries Service, Miami, FL","active":true,"usgs":false}],"preferred":false,"id":723512,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Raborn, Scott W.","contributorId":145575,"corporation":false,"usgs":false,"family":"Raborn","given":"Scott","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":723513,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Rester, Jeffrey K.","contributorId":200832,"corporation":false,"usgs":false,"family":"Rester","given":"Jeffrey","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":723514,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Rudloe, Jack J.","contributorId":200833,"corporation":false,"usgs":false,"family":"Rudloe","given":"Jack","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":723515,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Sarti Martinez, Laura","contributorId":200834,"corporation":false,"usgs":false,"family":"Sarti Martinez","given":"Laura","email":"","affiliations":[],"preferred":false,"id":723516,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Schexnayder, Mark","contributorId":200835,"corporation":false,"usgs":false,"family":"Schexnayder","given":"Mark","email":"","affiliations":[],"preferred":false,"id":723517,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Schmid, Jeffrey R.","contributorId":200836,"corporation":false,"usgs":false,"family":"Schmid","given":"Jeffrey","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":723518,"contributorType":{"id":1,"text":"Authors"},"rank":31},{"text":"Shaver, Donna J.","contributorId":11104,"corporation":false,"usgs":true,"family":"Shaver","given":"Donna","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":723519,"contributorType":{"id":1,"text":"Authors"},"rank":32},{"text":"Slay, Christopher","contributorId":200837,"corporation":false,"usgs":false,"family":"Slay","given":"Christopher","email":"","affiliations":[],"preferred":false,"id":723520,"contributorType":{"id":1,"text":"Authors"},"rank":33},{"text":"Tucker, Anton D.","contributorId":79232,"corporation":false,"usgs":false,"family":"Tucker","given":"Anton","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":723521,"contributorType":{"id":1,"text":"Authors"},"rank":34},{"text":"Tumlin, Mandy","contributorId":200838,"corporation":false,"usgs":false,"family":"Tumlin","given":"Mandy","email":"","affiliations":[],"preferred":false,"id":723522,"contributorType":{"id":1,"text":"Authors"},"rank":35},{"text":"Wibbels, Thane","contributorId":200839,"corporation":false,"usgs":false,"family":"Wibbels","given":"Thane","email":"","affiliations":[],"preferred":false,"id":723523,"contributorType":{"id":1,"text":"Authors"},"rank":36},{"text":"Zapata Najera, Blanca M.","contributorId":200840,"corporation":false,"usgs":false,"family":"Zapata Najera","given":"Blanca","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":723524,"contributorType":{"id":1,"text":"Authors"},"rank":37}]}}
,{"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":"<p>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 (<i>Glaucomys sabrinus coloratus</i>) 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 (<i>P </i>= 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.</p>","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":70189656,"text":"70189656 - 2016 - Unusual clockwise loop migration lengthens travel distances and increases potential risks for a central Asian, long distance, trans-equatorial migrant, the Red-footed Falcon <i>Falco vespertinus</i>","interactions":[],"lastModifiedDate":"2017-11-22T17:15:16","indexId":"70189656","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1052,"text":"Bird Study","active":true,"publicationSubtype":{"id":10}},"title":"Unusual clockwise loop migration lengthens travel distances and increases potential risks for a central Asian, long distance, trans-equatorial migrant, the Red-footed Falcon <i>Falco vespertinus</i>","docAbstract":"<p><strong>Capsule:</strong><span>&nbsp;</span>Red-footed Falcons<span>&nbsp;</span><i>Falco vespertinus</i><span>&nbsp;</span>migrating from northern Kazakhstan proceed west before heading south to Africa; their northbound travel follows a different route with passage close to shooting hotspots in the Mediterranean.</p><p><strong>Aim:</strong><span>&nbsp;</span>To use tracking and ringing data to document for the first time the migration of globally threatened Red-footed Falcons from northern Kazakhstan.</p><p><strong>Methods:</strong><span>&nbsp;</span>Light-level geolocators were deployed on breeding adults in Kazakhstan and recovered one year later. Ringing and observational data from more than 100 years of Russian-language and other literature were summarized and mapped alongside the geolocator data.</p><p><strong>Results:</strong><span>&nbsp;</span>Geolocator, ringing and observational data together demonstrate that Red-footed Falcons from northern Kazakhstan have a clockwise loop migration that begins with a long and unusual westward trek around eastern Europe’s large inland seas before continuing to extreme southern Africa. Return migration is farther west and requires crossing two major migratory barriers: the Sahara and the Mediterranean.</p><p><strong>Conclusion:</strong><span>&nbsp;</span>The loop migration we describe requires an extensive longitudinal movement, exposes central Asian Red-footed Falcons to multiple desert, mountain and marine crossings, and, at outbound and return Mediterranean bottlenecks, crosses sites where raptor shooting is common.</p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00063657.2016.1214107","usgsCitation":"Katzner, T., Bragin, E.A., Bragin, A.E., McGrady, M.J., Miller, T., and Bildstein, K.L., 2016, Unusual clockwise loop migration lengthens travel distances and increases potential risks for a central Asian, long distance, trans-equatorial migrant, the Red-footed Falcon <i>Falco vespertinus</i>: Bird Study, v. 63, no. 3, p. 406-412, https://doi.org/10.1080/00063657.2016.1214107.","productDescription":"7 p.","startPage":"406","endPage":"412","ipdsId":"IP-071710","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":344054,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"63","issue":"3","noUsgsAuthors":false,"publicationDate":"2016-08-17","publicationStatus":"PW","scienceBaseUri":"59706fb7e4b0d1f9f065a899","contributors":{"authors":[{"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":705614,"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":705615,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bragin, Alexander E.","contributorId":193027,"corporation":false,"usgs":false,"family":"Bragin","given":"Alexander","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":705616,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McGrady, Michael J.","contributorId":189117,"corporation":false,"usgs":false,"family":"McGrady","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":705617,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miller, Tricia A.","contributorId":64790,"corporation":false,"usgs":true,"family":"Miller","given":"Tricia A.","affiliations":[],"preferred":false,"id":705618,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bildstein, Keith L.","contributorId":150854,"corporation":false,"usgs":false,"family":"Bildstein","given":"Keith","email":"","middleInitial":"L.","affiliations":[{"id":18119,"text":"Hawk Mountain Sanctuary, Acopian Center for Conservation Learning","active":true,"usgs":false}],"preferred":false,"id":705619,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70184983,"text":"70184983 - 2016 - Haemosporidian parasite infections in grouse and ptarmigan: Prevalence and genetic diversity of blood parasites in resident Alaskan birds","interactions":[],"lastModifiedDate":"2017-03-13T13:58:05","indexId":"70184983","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2025,"text":"International Journal for Parasitology: Parasites and Wildlife","active":true,"publicationSubtype":{"id":10}},"title":"Haemosporidian parasite infections in grouse and ptarmigan: Prevalence and genetic diversity of blood parasites in resident Alaskan birds","docAbstract":"<p><span>Projections related to future climate warming indicate the potential for an increase in the distribution and prevalence of blood parasites in northern regions. However, baseline data are lacking for resident avian host species in Alaska. Grouse and ptarmigan occupy a diverse range of habitat types throughout the northern hemisphere and are among the most well-known and important native game birds in North America. Information regarding the prevalence and diversity of haemosporidian parasites in tetraonid species is limited, with few recent studies and an almost complete lack of genetic data. To better understand the genetic diversity of haemosporidian parasites in Alaskan tetraonids and to determine current patterns of geographic range and host specificity, we used molecular methods to screen 459 tissue samples collected from grouse and ptarmigan species across multiple regions of Alaska for infection by </span><i>Leucocytozoon, Haemoproteus,</i><span> and </span><i>Plasmodium</i><span> blood parasites. Infections were detected in 342 individuals, with overall apparent prevalence of 53% for </span><i>Leucocytozoon</i><span>, 21% for </span><i>Haemoproteus</i><span>, and 9% for </span><i>Plasmodium</i><span>. Parasite prevalence varied by region, with different patterns observed between species groups (grouse versus ptarmigan). </span><i>Leucocytozoon</i><span> was more common in ptarmigan, whereas </span><i>Haemoproteus</i><span> was more common in grouse. We detected </span><i>Plasmodium</i><span> infections in grouse only. Analysis of haemosporidian mitochondrial DNA cytochrome </span><i>b</i><span> sequences revealed 23 unique parasite haplotypes, several of which were identical to lineages previously detected in other avian hosts. Phylogenetic analysis showed close relationships between haplotypes from our study and those identified in Alaskan waterfowl for </span><i>Haemoproteus</i><span> and </span><i>Plasmodium</i><span> parasites. In contrast, </span><i>Leucocytozoon</i><span> lineages were structured strongly by host family. Our results provide some of the first genetic data for haemosporidians in grouse and ptarmigan species, and provide an initial baseline on the prevalence and diversity of blood parasites in a group of northern host species.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ijppaw.2016.07.003","usgsCitation":"Smith, M.M., Van Hemert, C.R., and Merizon, R., 2016, Haemosporidian parasite infections in grouse and ptarmigan: Prevalence and genetic diversity of blood parasites in resident Alaskan birds: International Journal for Parasitology: Parasites and Wildlife, v. 5, no. 3, p. 229-239, https://doi.org/10.1016/j.ijppaw.2016.07.003.","productDescription":"11 p.","startPage":"229","endPage":"239","ipdsId":"IP-073727","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":462007,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ijppaw.2016.07.003","text":"Publisher Index Page"},{"id":337444,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"5","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58c7af9de4b0849ce9795e88","chorus":{"doi":"10.1016/j.ijppaw.2016.07.003","url":"http://dx.doi.org/10.1016/j.ijppaw.2016.07.003","publisher":"Elsevier BV","authors":"Smith Matthew M., Van Hemert Caroline, Merizon Richard","journalName":"International Journal for Parasitology: Parasites and Wildlife","publicationDate":"12/2016","publiclyAccessibleDate":"7/19/2016"},"contributors":{"authors":[{"text":"Smith, Matthew M. 0000-0002-2259-5135 mmsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-2259-5135","contributorId":5115,"corporation":false,"usgs":true,"family":"Smith","given":"Matthew","email":"mmsmith@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":683822,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Hemert, Caroline R. 0000-0002-6858-7165 cvanhemert@usgs.gov","orcid":"https://orcid.org/0000-0002-6858-7165","contributorId":3592,"corporation":false,"usgs":true,"family":"Van Hemert","given":"Caroline","email":"cvanhemert@usgs.gov","middleInitial":"R.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":683823,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Merizon, Richard","contributorId":189144,"corporation":false,"usgs":false,"family":"Merizon","given":"Richard","email":"","affiliations":[],"preferred":false,"id":683966,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70191260,"text":"70191260 - 2016 - Geochemistry, Nd-Pb Isotopes, and Pb-Pb Ages of the Mesoproterozoic Pea Ridge Iron Oxide-Apatite–Rare Earth Element Deposit, Southeast Missouri","interactions":[],"lastModifiedDate":"2017-10-02T16:32:15","indexId":"70191260","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":"Geochemistry, Nd-Pb Isotopes, and Pb-Pb Ages of the Mesoproterozoic Pea Ridge Iron Oxide-Apatite–Rare Earth Element Deposit, Southeast Missouri","docAbstract":"<p id=\"p-1\">Iron oxide-apatite and iron oxide-copper-gold deposits occur within ~1.48 to 1.47 Ga volcanic rocks of the St. Francois Mountains terrane near a regional boundary separating crustal blocks having contrasting depleted-mantle Sm-Nd model ages (T<sub>DM</sub>). Major and trace element analyses and Nd and Pb isotope data were obtained to characterize the Pea Ridge deposit, improve identification of exploration targets, and better understand the regional distribution of mineralization with respect to crustal blocks. The Pea Ridge deposit is spatially associated with felsic volcanic rocks and plutons. Mafic to intermediate-composition rocks are volumetrically minor. Data for major element variations are commonly scattered and strongly suggest element mobility. Ratios of relatively immobile elements indicate that the felsic rocks are evolved subalkaline dacite and rhyolite; the mafic rocks are basalt to basaltic andesite. Granites and rhyolites display geochemical features typical of rocks produced by subduction. Rare earth element (REE) variations for the rhyolites are diagnostic of rocks affected by hydrothermal alteration and associated REE mineralization. The magnetite-rich rocks and REE-rich breccias show similar REE and mantle-normalized trace element patterns.</p><p id=\"p-2\">Nd isotope compositions (age corrected) show that: (1) host rhyolites have<span>&nbsp;</span><i>ɛ</i><sub>Nd</sub><span>&nbsp;</span>from 3.44 to 4.25 and T<sub>DM</sub><span>&nbsp;</span>from 1.51 to 1.59 Ga; (2) magnetite ore and specular hematite rocks display<span>&nbsp;</span><i>ɛ</i><sub>Nd</sub><span>&nbsp;</span>from 3.04 to 4.21 and T<sub>DM</sub><span>&nbsp;</span>from 1.6 to 1.51 Ga, and<span>&nbsp;</span><i>ɛ</i><sub>Nd</sub><span>&nbsp;</span>from 2.23 to 2.81, respectively; (3) REE-rich breccias have<span>&nbsp;</span><i>ɛ</i><sub>Nd</sub><span>&nbsp;</span>from 3.04 to 4.11 and T<sub>DM</sub><span>&nbsp;</span>from 1.6 to 1.51 Ga; and (4) mafic to intermediate-composition rocks range in<span>&nbsp;</span><i>ɛ</i><sub>Nd</sub><span>&nbsp;</span>from 2.35 to 3.66 and in T<sub>DM</sub><span>&nbsp;</span>from 1.66 to 1.56. The<span>&nbsp;</span><i>ɛ</i><sub>Nd</sub><span>&nbsp;</span>values of the magnetite and specular hematite samples show that the REE mineralization is magmatic; no evidence exists for major overprinting by younger, crustal meteoric fluids, or by externally derived Nd. Host rocks, breccias, and magnetite ore shared a common origin from a similar source.</p><p id=\"p-3\">Lead isotope ratios are diverse: (1) host rhyolite has<span>&nbsp;</span><sup>206</sup>Pb/<sup>204</sup>Pb from 24.261 to 50.091; (2) Pea Ridge and regional galenas have<span>&nbsp;</span><sup>206</sup>Pb/<sup>204</sup>Pb from 16.030 to 33.548; (3) REE-rich breccia, magnetite ore, and specular hematite rock are more radiogenic than galena; (4) REE-rich breccias have high<span>&nbsp;</span><sup>206</sup>Pb/<sup>204</sup>Pb (38.122–1277.61) compared to host rhyolites; and (5) REE-rich breccias are more radiogenic than magnetite ore and specular-hematite rock, having<span>&nbsp;</span><sup>206</sup>Pb/<sup>204</sup>Pb up to 230.65. Radiogenic<span>&nbsp;</span><sup>207</sup>Pb/<sup>206</sup>Pb age estimates suggest the following: (1) rhyolitic host rocks have ages of ~1.50 Ga, (2) magnetite ore is ~1.44 Ga, and (3) REE-rich breccias are ~1.48 Ga. These estimates are broadly consistent and genetically link the host rhyolite, REE-rich breccia, and magnetite ore as being contemporaneous.</p><p id=\"p-4\">Alteration style and mineralogical or textural distinctions among the magnetite-rich rocks and REE-rich breccias do not correlate with different isotopic sources. In our model, magmatic fluids leached metals from the coeval felsic rocks (rhyolites), which provided the metal source reflected in the compositions of the REE-rich breccias and mineralized rocks. This model allows for the likelihood of contributions from other genetically related felsic and intermediate to more mafic rocks stored deeper in the crust. The deposit thus records an origin as a magmatic-hydrothermal system that was not affected by Nd and Pb remobilization processes, particularly if these processes also triggered mixing with externally sourced metal-bearing fluids. The Pea Ridge deposit was part of a single, widespread, homogeneous mixing system that produced a uniform isotopic composition, thus representing an excellent example of an igneous-dominated system that generated coeval magmatism and REE mineralization. Geochemical features suggest that components in the Pea Ridge deposit originated from sources in an orogenic margin. Basaltic magmatism produced by mantle decompression melting provided heat for extracting melts from the middle or lower crust. Continual addition of mafic magmas to the base of the subcontinental lithosphere, in a back-arc setting, remelted calc-alkaline rocks enriched in metals that were stored in the crust.</p><p id=\"p-5\">The St. Francois Mountains terrane is adjacent to the regional T<sub>DM</sub><span>&nbsp;</span>line (defined at a value of 1.55 Ga) that separates ~1600 Ma basement to the west, from younger basements to the east. Data for Pea Ridge straddle the T<sub>DM</sub><span>&nbsp;</span>values proposed for the line. The Sm-Nd isotope system has been closed since formation of the deposit and the original igneous signatures have not been affected by cycles of alteration or superimposed mineralizing events. No evidence exists for externally derived Nd or Sm. The source region for metals within the Pea Ridge deposit had a moderate compositional variation and the REE-rich breccias and mineralized rocks are generally isotopically homogeneous. The Pea Ridge deposit thus constitutes a distinctive isotopic target for use as a model in identifying other mineralized systems that may share the same metal source in the St. Francois Mountains terrane and elsewhere in the eastern Granite-Rhyolite province.</p>","language":"English","publisher":"Society of Economic Geologists","doi":"10.2113/econgeo.111.8.1935","usgsCitation":"Ayuso, R.A., Slack, J.F., Day, W.C., and McCafferty, A.E., 2016, Geochemistry, Nd-Pb Isotopes, and Pb-Pb Ages of the Mesoproterozoic Pea Ridge Iron Oxide-Apatite–Rare Earth Element Deposit, Southeast Missouri: Economic Geology, v. 111, no. 8, p. 1935-1962, https://doi.org/10.2113/econgeo.111.8.1935.","productDescription":"28 p.","startPage":"1935","endPage":"1962","ipdsId":"IP-070054","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":346336,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -91.5,\n              37\n            ],\n            [\n              -89,\n              37\n            ],\n            [\n              -89,\n              38.5\n            ],\n            [\n              -91.5,\n              38.5\n            ],\n            [\n              -91.5,\n              37\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"111","issue":"8","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-16","publicationStatus":"PW","scienceBaseUri":"59d35028e4b05fe04cc34d5f","contributors":{"authors":[{"text":"Ayuso, Robert A. 0000-0002-8496-9534 rayuso@usgs.gov","orcid":"https://orcid.org/0000-0002-8496-9534","contributorId":2654,"corporation":false,"usgs":true,"family":"Ayuso","given":"Robert","email":"rayuso@usgs.gov","middleInitial":"A.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":711725,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Slack, John F. 0000-0001-6600-3130 jfslack@usgs.gov","orcid":"https://orcid.org/0000-0001-6600-3130","contributorId":1032,"corporation":false,"usgs":true,"family":"Slack","given":"John","email":"jfslack@usgs.gov","middleInitial":"F.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":711726,"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":711727,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCafferty, Anne E. 0000-0001-5574-9201 anne@usgs.gov","orcid":"https://orcid.org/0000-0001-5574-9201","contributorId":1120,"corporation":false,"usgs":true,"family":"McCafferty","given":"Anne","email":"anne@usgs.gov","middleInitial":"E.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":711728,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"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":"<p><span>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.</span></p>","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":"<p><span>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 &lt;0.04 to 41.8 mg L</span><sup>−1</sup><span> as N (mean, 5.31 mg L</span><sup>−1</sup><span>). 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</span><sup>−1</sup><span>, 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.</span></p>","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":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},{"id":27111,"text":"National Water Quality Program","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":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky 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":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","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":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado 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":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","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":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":513,"text":"Ohio 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":70178703,"text":"70178703 - 2016 - Baseline reference range for trace metal concentrations in whole blood of wild and managed West Indian Manatees (<i>Trichechus manatus</i>) in Florida and Belize","interactions":[],"lastModifiedDate":"2016-12-06T11:38:32","indexId":"70178703","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":869,"text":"Aquatic Mammals","active":true,"publicationSubtype":{"id":10}},"title":"Baseline reference range for trace metal concentrations in whole blood of wild and managed West Indian Manatees (<i>Trichechus manatus</i>) in Florida and Belize","docAbstract":"<p><span>The West Indian manatee (</span><i>Trichechus manatus</i><span>) is exposed to a number of anthropogenic influences, including metals, as they inhabit shallow waters with close proximity to shore. While maintaining homeostasis of many metals is crucial for health, there is currently no baseline reference range that can be used to make clinical and environmental decisions for this endangered species. In this study, whole blood samples from 151 manatees were collected during health assessments performed in Florida and Belize from 2008 through 2011. Whole blood samples (n = 37) from managed care facilities in Florida and Belize from 2009 through 2011 were also used in this study. The concentrations of 17 metals in whole blood were determined, and the data were used to derive a baseline reference range. Impacts of capture location, age, and sex on whole blood metal concentrations were examined. Location and age were related to copper concentrations as values were significantly higher in habitats near urban areas and in calves. Copper may also be a husbandry concern as concentrations were significantly higher in managed manatees (1.17 ± 0.04 ppm) than wild manatees (0.73 ± 0.02 ppm). Zinc (11.20 ± 0.30 ppm) was of special interest as normal concentrations were two to five times higher than other marine mammal species. Arsenic concentrations were higher in Belize (0.43 ± 0.07 ppm), with Placencia Lagoon having twice the concentration of Belize City and Southern Lagoon. Selenium concentrations were lower (0.18 ± 0.09 ppm) than in other marine mammal species. The lowest selenium concentrations were observed in rehabilitating and managed manatees which may warrant additional monitoring in managed care facilities. The established preliminary baseline reference range can be used by clinicians, biologists, and managers to monitor the health of West Indian manatees.</span></p>","language":"English","publisher":"Aquatic Mammals","doi":"10.1578/AM.42.4.2016.440","usgsCitation":"Takeuchi, N.Y., Walsh, M.T., Bonde, R.K., Powell, J., Bass, D.A., Gaspard, J.C., and Barber, D.S., 2016, Baseline reference range for trace metal concentrations in whole blood of wild and managed West Indian Manatees (<i>Trichechus manatus</i>) in Florida and Belize: Aquatic Mammals, v. 42, no. 4, p. 440-453, https://doi.org/10.1578/AM.42.4.2016.440.","productDescription":"14 p.","startPage":"440","endPage":"453","ipdsId":"IP-066887","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":331515,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":331467,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1578/AM.42.4.2016.440"}],"volume":"42","issue":"4","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-01","publicationStatus":"PW","scienceBaseUri":"5847dc7ce4b06d80b7af6aad","contributors":{"authors":[{"text":"Takeuchi, Noel Y.","contributorId":177192,"corporation":false,"usgs":false,"family":"Takeuchi","given":"Noel","email":"","middleInitial":"Y.","affiliations":[],"preferred":false,"id":654954,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walsh, Michael T.","contributorId":177177,"corporation":false,"usgs":false,"family":"Walsh","given":"Michael","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":654955,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bonde, Robert K. 0000-0001-9179-4376 rbonde@usgs.gov","orcid":"https://orcid.org/0000-0001-9179-4376","contributorId":2675,"corporation":false,"usgs":true,"family":"Bonde","given":"Robert","email":"rbonde@usgs.gov","middleInitial":"K.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":654956,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Powell, James A.","contributorId":53514,"corporation":false,"usgs":true,"family":"Powell","given":"James A.","affiliations":[],"preferred":false,"id":654957,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bass, Dean A.","contributorId":177193,"corporation":false,"usgs":false,"family":"Bass","given":"Dean","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":654958,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gaspard, Joseph C.","contributorId":177194,"corporation":false,"usgs":false,"family":"Gaspard","given":"Joseph","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":654959,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Barber, David S.","contributorId":177195,"corporation":false,"usgs":false,"family":"Barber","given":"David","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":654960,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70179636,"text":"70179636 - 2016 - mizuRoute version 1: A river network routing tool for a continental domain water resources applications","interactions":[],"lastModifiedDate":"2017-01-09T11:33:05","indexId":"70179636","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1818,"text":"Geoscientific Model Development","active":true,"publicationSubtype":{"id":10}},"title":"mizuRoute version 1: A river network routing tool for a continental domain water resources applications","docAbstract":"<p><span>This paper describes the first version of a stand-alone runoff routing tool, mizuRoute. The mizuRoute tool post-processes runoff outputs from any distributed hydrologic model or land surface model to produce spatially distributed streamflow at various spatial scales from headwater basins to continental-wide river systems. The tool can utilize both traditional grid-based river network and vector-based river network data. Both types of river network include river segment lines and the associated drainage basin polygons, but the vector-based river network can represent finer-scale river lines than the grid-based network. Streamflow estimates at any desired location in the river network can be easily extracted from the output of mizuRoute. The routing process is simulated as two separate steps. First, hillslope routing is performed with a gamma-distribution-based unit-hydrograph to transport runoff from a hillslope to a catchment outlet. The second step is river channel routing, which is performed with one of two routing scheme options: (1)&nbsp;a kinematic wave tracking (KWT) routing procedure; and (2)&nbsp;an impulse response function – unit-hydrograph (IRF-UH) routing procedure. The mizuRoute tool also includes scripts (python, NetCDF operators) to pre-process spatial river network data. This paper demonstrates mizuRoute's capabilities to produce spatially distributed streamflow simulations based on river networks from the United States Geological Survey (USGS) Geospatial Fabric (GF) data set in which over 54 000 river segments and their contributing areas are mapped across the contiguous United States (CONUS). A brief analysis of model parameter sensitivity is also provided. The mizuRoute tool can assist model-based water resources assessments including studies of the impacts of climate change on streamflow.</span></p>","language":"English","publisher":"European Geosciences Union","doi":"10.5194/gmd-9-2223-2016","usgsCitation":"Mizukami, N., Clark, M.P., Sampson, K., Nijssen, B., Mao, Y., McMillan, H., Viger, R.J., Markstrom, S.L., Hay, L.E., Woods, R., Arnold, J.R., and Brekke, L.D., 2016, mizuRoute version 1: A river network routing tool for a continental domain water resources applications: Geoscientific Model Development, v. 9, p. 2223-2238, https://doi.org/10.5194/gmd-9-2223-2016.","productDescription":"16 p.","startPage":"2223","endPage":"2238","ipdsId":"IP-075055","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":470378,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/gmd-9-2223-2016","text":"Publisher Index Page"},{"id":332987,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-23","publicationStatus":"PW","scienceBaseUri":"5874b0ade4b0a829a320bb67","contributors":{"authors":[{"text":"Mizukami, Naoki","contributorId":178120,"corporation":false,"usgs":false,"family":"Mizukami","given":"Naoki","email":"","affiliations":[],"preferred":false,"id":657982,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clark, Martyn P.","contributorId":178121,"corporation":false,"usgs":false,"family":"Clark","given":"Martyn","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":657983,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sampson, Kevin","contributorId":178122,"corporation":false,"usgs":false,"family":"Sampson","given":"Kevin","email":"","affiliations":[],"preferred":false,"id":657984,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nijssen, Bart","contributorId":178123,"corporation":false,"usgs":false,"family":"Nijssen","given":"Bart","email":"","affiliations":[],"preferred":false,"id":657985,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mao, Yixin","contributorId":139783,"corporation":false,"usgs":false,"family":"Mao","given":"Yixin","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":657986,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McMillan, Hilary","contributorId":176321,"corporation":false,"usgs":false,"family":"McMillan","given":"Hilary","email":"","affiliations":[],"preferred":false,"id":657987,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Viger, Roland J. 0000-0003-2520-714X rviger@usgs.gov","orcid":"https://orcid.org/0000-0003-2520-714X","contributorId":168799,"corporation":false,"usgs":true,"family":"Viger","given":"Roland","email":"rviger@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":657988,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Markstrom, Steven L. 0000-0001-7630-9547 markstro@usgs.gov","orcid":"https://orcid.org/0000-0001-7630-9547","contributorId":146553,"corporation":false,"usgs":true,"family":"Markstrom","given":"Steven","email":"markstro@usgs.gov","middleInitial":"L.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":657989,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hay, Lauren E. 0000-0003-3763-4595 lhay@usgs.gov","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":1287,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","email":"lhay@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":657981,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Woods, Ross","contributorId":178124,"corporation":false,"usgs":false,"family":"Woods","given":"Ross","affiliations":[],"preferred":false,"id":657990,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Arnold, Jeffrey R.","contributorId":178125,"corporation":false,"usgs":false,"family":"Arnold","given":"Jeffrey","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":657991,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Brekke, Levi D.","contributorId":178126,"corporation":false,"usgs":false,"family":"Brekke","given":"Levi","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":657992,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70182203,"text":"70182203 - 2016 - Historical reconstructions of California wildfires vary by data source","interactions":[],"lastModifiedDate":"2017-02-21T10:35:06","indexId":"70182203","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2083,"text":"International Journal of Wildland Fire","active":true,"publicationSubtype":{"id":10}},"title":"Historical reconstructions of California wildfires vary by data source","docAbstract":"<p><span>Historical data are essential for understanding how fire activity responds to different drivers. It is important that the source of data is commensurate with the spatial and temporal scale of the question addressed, but fire history databases are derived from different sources with different restrictions. In California, a frequently used fire history dataset is the State of California Fire and Resource Assessment Program (FRAP) fire history database, which circumscribes fire perimeters at a relatively fine scale. It includes large fires on both state and federal lands but only covers fires that were mapped or had other spatially explicit data. A different database is the state and federal governments’ annual reports of all fires. They are more complete than the FRAP database but are only spatially explicit to the level of county (California Department of Forestry and Fire Protection – Cal Fire) or forest (United States Forest Service – USFS). We found substantial differences between the FRAP database and the annual summaries, with the largest and most consistent discrepancy being in fire frequency. The FRAP database missed the majority of fires and is thus a poor indicator of fire frequency or indicators of ignition sources. The FRAP database is also deficient in area burned, especially before 1950. Even in contemporary records, the huge number of smaller fires not included in the FRAP database account for substantial cumulative differences in area burned. Wildfires in California account for nearly half of the western United States fire suppression budget. Therefore, the conclusions about data discrepancies and the implications for fire research are of broad importance.</span></p>","language":"English","publisher":"CSIRO Publishing","doi":"10.1071/WF16050","usgsCitation":"Syphard, A.D., and Keeley, J.E., 2016, Historical reconstructions of California wildfires vary by data source: International Journal of Wildland Fire, v. 25, p. 1221-1227, https://doi.org/10.1071/WF16050.","productDescription":"7 p.","startPage":"1221","endPage":"1227","ipdsId":"IP-070536","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":335863,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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 \"}}]}","volume":"25","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58ad5fc1e4b01ccd54f8b51b","contributors":{"authors":[{"text":"Syphard, Alexandra D.","contributorId":8977,"corporation":false,"usgs":false,"family":"Syphard","given":"Alexandra","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":669971,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keeley, Jon E. 0000-0002-4564-6521 jon_keeley@usgs.gov","orcid":"https://orcid.org/0000-0002-4564-6521","contributorId":1268,"corporation":false,"usgs":true,"family":"Keeley","given":"Jon","email":"jon_keeley@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":669970,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70182061,"text":"70182061 - 2016 - Application of ground penetrating radar for identification of washover deposits and other stratigraphic features: Assateague Island, MD","interactions":[],"lastModifiedDate":"2025-05-13T16:45:38.273515","indexId":"70182061","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3928,"text":"Journal of Environmental & Engineering Geophysics","printIssn":"1083-1363","active":true,"publicationSubtype":{"id":10}},"title":"Application of ground penetrating radar for identification of washover deposits and other stratigraphic features: Assateague Island, MD","docAbstract":"<p><span>A combination of ground penetrating radar (GPR) data, core data, and aerial photographs were analyzed to better understand the evolution of two portions of Assateague Island, Maryland. The focus of the study was to investigate the applicability of using GPR data to image washover deposits in the stratigraphic record. High amplitude reflections observed in two shore-perpendicular GPR profiles were correlated to shallow (&lt;1 m) lithologic contacts observed in sediment cores. At these contacts, deposits consisting primarily of quartz sand overlie sediments with organic matter that include degraded plant root or stem material. The underlying organic matter likely represents the vegetated portion of the barrier island that was buried by washover fans deposited during hurricanes Irene (2011) and Sandy (2012), as indicated in high-resolution aerial photographs. The GPR data were able to delineate the washover deposits from the underlying stratigraphic unit; however, the radar data did not resolve finer structures necessary to definitively differentiate washover facies from other sand-rich deposits (</span><i>e.g.,</i><span><span>&nbsp;</span>flood-tide deltas and dunes). Other GPR profiles contain reflections that likely correlate to geomorphic features like tidal channels and vegetated zones observed in historical aerial imagery. Burial of these features by overwash fluxes were observed in the aerial imagery and thus the resulting radar sequence is largely interpreted as washover deposits. Deeper, channel-like features that have been infilled were also observed in shore-parallel profiles and these features coincide with scour channels observed in the 1966 aerial photography. Additional sedimentological data are required to determine what role overwash played in the in-filling of these features.</span></p>","language":"English","publisher":"Environmental & Engineering Geophysical Society","doi":"10.2113/JEEG21.4.173","usgsCitation":"Zaremba, N., Smith, C.G., Bernier, J., and Forde, A.S., 2016, Application of ground penetrating radar for identification of washover deposits and other stratigraphic features: Assateague Island, MD: Journal of Environmental & Engineering Geophysics, v. 21, no. 4, p. 173-186, https://doi.org/10.2113/JEEG21.4.173.","productDescription":"14 p.","startPage":"173","endPage":"186","ipdsId":"IP-074256","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":337659,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"21","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58ca52cde4b0849ce97c86a0","contributors":{"authors":[{"text":"Zaremba, Nicholas 0000-0002-2361-2881 nzaremba@usgs.gov","orcid":"https://orcid.org/0000-0002-2361-2881","contributorId":181756,"corporation":false,"usgs":true,"family":"Zaremba","given":"Nicholas","email":"nzaremba@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":669428,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Christopher G. 0000-0002-8075-4763 cgsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-8075-4763","contributorId":3410,"corporation":false,"usgs":true,"family":"Smith","given":"Christopher","email":"cgsmith@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":669429,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bernier, Julie 0000-0002-9918-5353 jbernier@usgs.gov","orcid":"https://orcid.org/0000-0002-9918-5353","contributorId":3549,"corporation":false,"usgs":true,"family":"Bernier","given":"Julie","email":"jbernier@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":669430,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Forde, Arnell S. 0000-0002-5581-2255 aforde@usgs.gov","orcid":"https://orcid.org/0000-0002-5581-2255","contributorId":376,"corporation":false,"usgs":true,"family":"Forde","given":"Arnell","email":"aforde@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":669431,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"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":"<p><span>To better protect endangered green sea turtles </span><i>Chelonia mydas</i><span>, 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.</span></p>","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":70193685,"text":"70193685 - 2016 - Semiautomatic mapping of permafrost in the Yukon Flats, Alaska","interactions":[],"lastModifiedDate":"2017-11-02T16:37:20","indexId":"70193685","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Semiautomatic mapping of permafrost in the Yukon Flats, Alaska","docAbstract":"<p>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.</p>","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":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":"<p><span>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 (</span><i>Odobenus rosmarus divergens</i><span>) and fishers (</span><i>Pekania pennanti</i><span>). 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.</span></p>","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":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":"<p><span>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.</span></p>","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":7065,"text":"USGS emeritus","active":true,"usgs":false},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"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":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":"<p><span>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 (</span><i>Cervus canadensis</i><span>) 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:<span>&nbsp;</span></span><i>d </i><span>= 0.19; 1200–1800 hr:<span>&nbsp;</span></span><i>d </i><span>= 0.64) and decreased during midday and night (0000 hr, 1200 hr) when elk were least active (1800–0000 hr:<span>&nbsp;</span></span><i>d </i><span>= −0.39; 0600–1200 hr:<span>&nbsp;</span></span><i>d </i><span>= −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.</span></p>","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":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 (<i>Cephus cinctus</i>, 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":"<p><span>Wheat stem sawfly (</span><i>Cephus cinctus</i><span><span>&nbsp;</span>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<span>&nbsp;</span></span><i>C. cinctus</i><span><span>&nbsp;</span>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<span>&nbsp;</span></span><i>C. cinctus</i><span><span>&nbsp;</span>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<span>&nbsp;</span></span><i>C. cinctus</i><span><span>&nbsp;</span>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<span>&nbsp;</span></span><i>C. cinctus</i><span><span>&nbsp;</span>establishment in currently uninfested regions.</span></p>","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":477,"text":"North Central Climate Science Center","active":true,"usgs":true},{"id":569,"text":"Southwest 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":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":"<p><span>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.</span></p>","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":70191263,"text":"70191263 - 2016 - Trace elements at the intersection of marine biological and geochemical evolution","interactions":[],"lastModifiedDate":"2017-10-02T13:21:19","indexId":"70191263","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1431,"text":"Earth-Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Trace elements at the intersection of marine biological and geochemical evolution","docAbstract":"<p><span>Life requires a wide variety of bioessential trace elements to act as structural components and reactive centers in metalloenzymes. These requirements differ between organisms and have evolved over geological time, likely guided in some part by environmental conditions. Until recently, most of what was understood regarding trace element concentrations in the Precambrian oceans was inferred by extrapolation, geochemical modeling, and/or genomic studies. However, in the past decade, the increasing availability of trace element and isotopic data for sedimentary rocks of all ages has yielded new, and potentially more direct, insights into secular changes in seawater composition – and ultimately the evolution of the marine biosphere. Compiled records of many bioessential trace elements (including Ni, Mo, P, Zn, Co, Cr, Se, and I) provide new insight into how trace element abundance in Earth's ancient oceans may have been linked to biological evolution. Several of these trace elements display redox-sensitive behavior, while others are redox-sensitive but not bioessential (e.g., Cr, U). Their temporal trends in sedimentary archives provide useful constraints on changes in atmosphere-ocean redox conditions that are linked to biological evolution, for example, the activity of oxygen-producing, photosynthetic cyanobacteria. In this review, we summarize available Precambrian trace element proxy data, and discuss how temporal trends in the seawater concentrations of specific trace elements may be linked to the evolution of both simple and complex life. We also examine several biologically relevant and/or redox-sensitive trace elements that have yet to be fully examined in the sedimentary rock record (e.g., Cu, Cd, W) and suggest several directions for future studies.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.earscirev.2016.10.013","usgsCitation":"Robbins, L.J., Lalonde, S.V., Planavsky, N.J., Partin, C.A., Reinhard, C.T., Kendall, B., Scott, C., Hardisty, D.S., Gill, B.C., Alessi, D.S., Dupont, C.L., Saito, M.A., Crowe, S.A., Poulton, S.W., Bekker, A., Lyons, T.W., and Konhauser, K.O., 2016, Trace elements at the intersection of marine biological and geochemical evolution: Earth-Science Reviews, v. 163, p. 323-348, https://doi.org/10.1016/j.earscirev.2016.10.013.","productDescription":"26 p.","startPage":"323","endPage":"348","ipdsId":"IP-079724","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":470348,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10012/13782","text":"External Repository"},{"id":346313,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"163","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59d35027e4b05fe04cc34d59","contributors":{"authors":[{"text":"Robbins, Leslie J.","contributorId":196838,"corporation":false,"usgs":false,"family":"Robbins","given":"Leslie","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":711744,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lalonde, Stefan V.","contributorId":196839,"corporation":false,"usgs":false,"family":"Lalonde","given":"Stefan","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":711745,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Planavsky, Noah J.","contributorId":196840,"corporation":false,"usgs":false,"family":"Planavsky","given":"Noah","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":711746,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Partin, Camille A.","contributorId":196841,"corporation":false,"usgs":false,"family":"Partin","given":"Camille","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":711747,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reinhard, Christopher 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