Using three resolutions of the Lyon-Fedder-Mobarry global magnetosphere-ionosphere model (LFM) and the Weimer 2005 empirical model we examine the structure of the high latitude field-aligned current patterns. Each resolution was run for the entire Whole Heliosphere Interval which contained two high speed solar wind streams and modest interplanetary magnetic field strengths. Average states of the field-aligned current (FAC) patterns for 8 interplanetary magnetic field clock angle directions are computed using data from these runs. Generally speaking the patterns obtained agree well with results obtained from the Weimer 2005 computing using the solar wind and IMF conditions that correspond to each bin. As the simulation resolution increases the currents become more intense and narrow. A machine learning analysis of the FAC patterns shows that the ratio of Region 1 (R1) to Region 2 (R2) currents decreases as the simulation resolution increases. This brings the simulation results into better agreement with observational predictions and the Weimer 2005 model results. The increase in R2 current strengths also results in the cross polar cap potential (CPCP) pattern being concentrated in higher latitudes. Current-voltage relationships between the R1 and CPCP are quite similar at the higher resolution indicating the simulation is converging on a common solution. We conclude that LFM simulations are capable of reproducing the statistical features of FAC patterns.
","language":"English","publisher":"Springer","doi":"10.1007/s11214-016-0271-2","usgsCitation":"Wiltberger, M., Rigler, E.J., Merkin, V., and Lyon, J.G., 2016, Structure of high latitude currents in global magnetospheric-ionospheric models: Space Science Reviews, v. 206, no. 1, p. 575-598, https://doi.org/10.1007/s11214-016-0271-2.","productDescription":"24 p.","startPage":"575","endPage":"598","ipdsId":"IP-077646","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":336986,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"206","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-12","publicationStatus":"PW","scienceBaseUri":"58bfd4f5e4b014cc3a3ba4c4","contributors":{"authors":[{"text":"Wiltberger, M","contributorId":187628,"corporation":false,"usgs":false,"family":"Wiltberger","given":"M","affiliations":[],"preferred":false,"id":681102,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rigler, E. J.","contributorId":187639,"corporation":false,"usgs":false,"family":"Rigler","given":"E.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":681103,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Merkin, V","contributorId":187629,"corporation":false,"usgs":false,"family":"Merkin","given":"V","email":"","affiliations":[],"preferred":false,"id":681104,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lyon, J. G","contributorId":187630,"corporation":false,"usgs":false,"family":"Lyon","given":"J.","email":"","middleInitial":"G","affiliations":[],"preferred":false,"id":681105,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70184452,"text":"70184452 - 2016 - Comparison of methods to monitor the distribution and impacts of unauthorized travel routes in a border park","interactions":[],"lastModifiedDate":"2017-03-09T11:27:50","indexId":"70184452","displayToPublicDate":"2016-07-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2821,"text":"Natural Areas Journal","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of methods to monitor the distribution and impacts of unauthorized travel routes in a border park","docAbstract":"The distribution and abundance of human-caused disturbances vary greatly through space and time and are cause for concern among land stewards in natural areas of the southwestern border-lands between the USA and Mexico. Human migration and border protection along the international boundary create Unauthorized Trail and Road (UTR) networks across National Park Service lands and other natural areas. UTRs may cause soil erosion and compaction, damage to vegetation and cultural resources, and may stress wildlife or impede their movements. We quantify the density and severity of UTR disturbances in relation to soils, and compare the use of previously established targeted trail assessments (hereafter — targeted assessments) against randomly placed transects to detect trail densities at Coronado National Memorial in Arizona in 2011. While trail distributions were similar between methods, targeted assessments estimated a large portion of the park to have the lowest density category (0–5 trail encounters per/km2), whereas the random transects in 2011 estimated more of the park as having the higher density categories (e.g., 15–20 encounters per km2category). Soil vulnerability categories that were assigned, a priori, based on published soil texture and composition did not accurately predict the impact of UTRs on soil, indicating that empirical methods may be better suited for identifying severity of compaction. While the estimates of UTR encounter frequencies were greater using the random transects than the targeted assessments for a relatively short period of time, it is difficult to determine whether this difference is dependent on greater cross-border activity, differences in technique, or from confounding environmental factors. Future surveys using standardized sampling techniques would increase accuracy.
","language":"English","publisher":"Natural Areas Association","doi":"10.3375/043.036.0305","usgsCitation":"Esque, T., Inman, R.D., Nussear, K.E., Webb, R., Girard, M., and DeGayner, J., 2016, Comparison of methods to monitor the distribution and impacts of unauthorized travel routes in a border park: Natural Areas Journal, v. 36, no. 3, p. 248-258, https://doi.org/10.3375/043.036.0305.","productDescription":"11 p.","startPage":"248","endPage":"258","ipdsId":"IP-041641","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":337165,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","county":"Cochise County","otherGeospatial":"Coronado National Memorial","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.29037475585936,\n 31.333551415222512\n ],\n [\n -110.22308349609375,\n 31.333551415222512\n ],\n [\n -110.22308349609375,\n 31.36829520164191\n ],\n [\n -110.29037475585936,\n 31.36829520164191\n ],\n [\n -110.29037475585936,\n 31.333551415222512\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","issue":"3","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58c277dbe4b014cc3a3e76d1","contributors":{"authors":[{"text":"Esque, Todd C. 0000-0002-4166-6234 tesque@usgs.gov","orcid":"https://orcid.org/0000-0002-4166-6234","contributorId":168763,"corporation":false,"usgs":true,"family":"Esque","given":"Todd C.","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":681585,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Inman, Richard D. 0000-0002-1982-7791 rdinman@usgs.gov","orcid":"https://orcid.org/0000-0002-1982-7791","contributorId":187754,"corporation":false,"usgs":true,"family":"Inman","given":"Richard","email":"rdinman@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":681583,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nussear, Kenneth E. knussear@usgs.gov","contributorId":2695,"corporation":false,"usgs":true,"family":"Nussear","given":"Kenneth","email":"knussear@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":681582,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Webb, Robert rhwebb@usgs.gov","contributorId":187755,"corporation":false,"usgs":true,"family":"Webb","given":"Robert","email":"rhwebb@usgs.gov","affiliations":[],"preferred":true,"id":681584,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Girard, M.M.","contributorId":187757,"corporation":false,"usgs":false,"family":"Girard","given":"M.M.","email":"","affiliations":[],"preferred":false,"id":681587,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"DeGayner, J.","contributorId":187756,"corporation":false,"usgs":false,"family":"DeGayner","given":"J.","email":"","affiliations":[],"preferred":false,"id":681586,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70184432,"text":"70184432 - 2016 - Anticipated water quality changes in response to climate change and potential consequences for inland fishes","interactions":[],"lastModifiedDate":"2018-02-28T14:35:33","indexId":"70184432","displayToPublicDate":"2016-07-01T00:00:00","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":"Anticipated water quality changes in response to climate change and potential consequences for inland fishes","docAbstract":"Healthy freshwater ecosystems are a critical component of the world's economy, with a critical role in maintaining public health, inland biological diversity, and overall quality of life. Globally, our climate is changing, with air temperature and precipitation regimes deviating significantly from historical patterns. Healthy freshwater ecosystems are a critical component of the world's economy, with a critical role in maintaining public health, inland biological diversity, and overall quality of life. Globally, our climate is changing, with air temperature and precipitation regimes deviating significantly from historical patterns. Changes anticipated with climate change in the future are likely to have a profound effect on inland aquatic ecosystems through diverse pathways, including changes in water quality. In this brief article, we present an initial discussion of several of the water quality responses that can be anticipated to occur within inland water bodies with climate change and how those changes are likely to impact fishes.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/03632415.2016.1182509","usgsCitation":"Chen, Y., Todd, A.S., Murphy, M.H., and Lomnicky, G., 2016, Anticipated water quality changes in response to climate change and potential consequences for inland fishes: Fisheries, v. 41, no. 7, p. 413-416, https://doi.org/10.1080/03632415.2016.1182509.","productDescription":"4 p.","startPage":"413","endPage":"416","ipdsId":"IP-072548","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":337172,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-29","publicationStatus":"PW","scienceBaseUri":"58c277dce4b014cc3a3e76d3","contributors":{"authors":[{"text":"Chen, Yushun","contributorId":146569,"corporation":false,"usgs":false,"family":"Chen","given":"Yushun","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":681464,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Todd, Andrew S. atodd@usgs.gov","contributorId":1022,"corporation":false,"usgs":true,"family":"Todd","given":"Andrew","email":"atodd@usgs.gov","middleInitial":"S.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":681463,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Murphy, Margaret H.","contributorId":187717,"corporation":false,"usgs":false,"family":"Murphy","given":"Margaret","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":681465,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lomnicky, Gregg","contributorId":187718,"corporation":false,"usgs":false,"family":"Lomnicky","given":"Gregg","email":"","affiliations":[],"preferred":false,"id":681466,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70170239,"text":"70170239 - 2016 - Gypsum in 2015","interactions":[],"lastModifiedDate":"2016-07-01T11:30:44","indexId":"70170239","displayToPublicDate":"2016-07-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2755,"text":"Mining Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Gypsum in 2015","docAbstract":"No abstract available.
","language":"English","publisher":"SME","usgsCitation":"Crangle, R., 2016, Gypsum in 2015: Mining Engineering, v. 68, no. 7, p. 30-30.","productDescription":"1 p.","startPage":"30","endPage":"30","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-074845","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":324735,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":324734,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://me.smenet.org/abstract.cfm?preview=1&articleID=6675&page=30"}],"volume":"68","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57778621e4b07dd077c878bb","contributors":{"authors":[{"text":"Crangle, Robert Jr. 0000-0002-8120-3760 rcrangle@usgs.gov","orcid":"https://orcid.org/0000-0002-8120-3760","contributorId":141008,"corporation":false,"usgs":true,"family":"Crangle","given":"Robert","suffix":"Jr.","email":"rcrangle@usgs.gov","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":626570,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70175249,"text":"70175249 - 2016 - The impact of onsite wastewater disposal systems on groundwater in areas inundated by Hurricane Sandy in New York and New Jersey","interactions":[],"lastModifiedDate":"2018-08-07T12:22:24","indexId":"70175249","displayToPublicDate":"2016-06-30T18:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2676,"text":"Marine Pollution Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"The impact of onsite wastewater disposal systems on groundwater in areas inundated by Hurricane Sandy in New York and New Jersey","docAbstract":"Coastal onsite wastewater disposal systems (OWDS) were inundated by Hurricane Sandy's storm tide. This study compares the shallow groundwater quality (nutrients, pharmaceuticals, and hormones) downgradient of OWDS before and after Hurricane Sandy, where available, and establishes a baseline for wastewater influence on groundwater in coastal communities inundated by Hurricane Sandy. Nutrients and contaminants of emerging concern (CECs) were detected in shallow groundwater downgradient of OWDS in two settings along the New Jersey and New York coastlines: 1) a single, centralized OWDS in a park; and 2) multiple OWDS (cesspools) in low-density residential and mixed-use/medium density residential areas. The most frequently detected pharmaceuticals were lidocaine (40%), carbamazepine (36%), and fexofenadine, bupropion, desvenlafaxine, meprobamate, and tramadol (24–32%). Increases in the number and total concentration of pharmaceuticals after Hurricane Sandy may reflect other factors (seasonality, usage) besides inundation, and demonstrate the importance of analyzing for a wide variety of CECs in regional studies.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpolbul.2016.04.038","usgsCitation":"Fisher, I., Phillips, P.J., Colella, K., Fisher, S.C., Tagliaferri, T.N., Foreman, W., and Furlong, E.T., 2016, The impact of onsite wastewater disposal systems on groundwater in areas inundated by Hurricane Sandy in New York and New Jersey: Marine Pollution Bulletin, v. 107, no. 2, p. 509-517, https://doi.org/10.1016/j.marpolbul.2016.04.038.","productDescription":"9 p.","startPage":"509","endPage":"517","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069552","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":326039,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey, New York","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.212890625,\n 40.94671366508002\n ],\n [\n -73.157958984375,\n 40.98819156349393\n ],\n [\n -72.97119140625,\n 40.9840449469281\n ],\n [\n -72.8009033203125,\n 41.00477542222949\n ],\n [\n -72.69653320312499,\n 41.02135510866602\n ],\n [\n -72.5701904296875,\n 41.05035951931887\n ],\n [\n -72.4273681640625,\n 41.13315883477399\n ],\n [\n -72.257080078125,\n 41.17451935556443\n ],\n [\n -72.1966552734375,\n 41.091772220976644\n ],\n [\n -72.11975097656249,\n 41.11660732012894\n ],\n [\n -72.0208740234375,\n 41.11246878918086\n ],\n [\n -71.905517578125,\n 41.10005163093046\n ],\n [\n -71.8231201171875,\n 41.091772220976644\n ],\n [\n -72.11975097656249,\n 40.9052096972736\n ],\n [\n -72.4383544921875,\n 40.830436877649255\n ],\n [\n -73.070068359375,\n 40.64730356252251\n ],\n [\n -73.8336181640625,\n 40.543026009954986\n ],\n [\n -73.89404296875,\n 40.35910267579199\n ],\n [\n -73.9105224609375,\n 40.20824570152502\n ],\n [\n -73.9764404296875,\n 40.09908414736847\n ],\n [\n -74.0478515625,\n 40.01499435375046\n ],\n [\n -74.1522216796875,\n 40.01499435375046\n ],\n [\n -74.1851806640625,\n 40.233411907115055\n ],\n [\n -74.14672851562499,\n 40.33817045213394\n ],\n [\n -74.102783203125,\n 40.43858586704331\n ],\n [\n -74.036865234375,\n 40.543026009954986\n ],\n [\n -73.98193359375,\n 40.60144147645398\n ],\n [\n -73.948974609375,\n 40.697299008636755\n ],\n [\n -73.839111328125,\n 40.772221877329024\n ],\n [\n -73.7677001953125,\n 40.87614141141369\n ],\n [\n -73.6468505859375,\n 40.91351257612758\n ],\n [\n -73.553466796875,\n 40.95915977213492\n ],\n [\n -73.4381103515625,\n 40.979898069620155\n ],\n [\n -73.388671875,\n 40.9840449469281\n ],\n [\n -73.3062744140625,\n 40.98819156349393\n ],\n [\n -73.212890625,\n 40.94671366508002\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"107","issue":"2","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57a315d2e4b006cb45558bb1","contributors":{"authors":[{"text":"Fisher, Irene ifisher@usgs.gov","contributorId":172759,"corporation":false,"usgs":true,"family":"Fisher","given":"Irene","email":"ifisher@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":644533,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Phillips, Patrick J. 0000-0001-5915-2015 pjphilli@usgs.gov","orcid":"https://orcid.org/0000-0001-5915-2015","contributorId":172757,"corporation":false,"usgs":true,"family":"Phillips","given":"Patrick","email":"pjphilli@usgs.gov","middleInitial":"J.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":644534,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Colella, Kaitlyn kcolella@usgs.gov","contributorId":146500,"corporation":false,"usgs":true,"family":"Colella","given":"Kaitlyn","email":"kcolella@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":644535,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fisher, Shawn C. 0000-0001-6324-1061 scfisher@usgs.gov","orcid":"https://orcid.org/0000-0001-6324-1061","contributorId":4843,"corporation":false,"usgs":true,"family":"Fisher","given":"Shawn","email":"scfisher@usgs.gov","middleInitial":"C.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":644536,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tagliaferri, Tristen N. 0000-0001-7408-7899 ttagliaferri@usgs.gov","orcid":"https://orcid.org/0000-0001-7408-7899","contributorId":5138,"corporation":false,"usgs":true,"family":"Tagliaferri","given":"Tristen","email":"ttagliaferri@usgs.gov","middleInitial":"N.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":644537,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Foreman, William T. 0000-0002-2530-3310 wforeman@usgs.gov","orcid":"https://orcid.org/0000-0002-2530-3310","contributorId":169108,"corporation":false,"usgs":true,"family":"Foreman","given":"William T. ","email":"wforeman@usgs.gov","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"preferred":false,"id":644538,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Furlong, Edward T. 0000-0002-7305-4603 efurlong@usgs.gov","orcid":"https://orcid.org/0000-0002-7305-4603","contributorId":740,"corporation":false,"usgs":true,"family":"Furlong","given":"Edward","email":"efurlong@usgs.gov","middleInitial":"T.","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":644539,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70159913,"text":"70159913 - 2016 - Rare earths: Market disruption, innovation, and global supply chains","interactions":[],"lastModifiedDate":"2020-12-17T20:33:59.752908","indexId":"70159913","displayToPublicDate":"2016-06-30T15:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5122,"text":"Environment and Resources","active":true,"publicationSubtype":{"id":10}},"title":"Rare earths: Market disruption, innovation, and global supply chains","docAbstract":"Rare earths, sometimes called the vitamins of modern materials, captured public attention when their prices increased more than ten-fold in 2010 and 2011. As prices fell between 2011 and 2016, rare earths receded from public view—but less visibly they became a major focus of innovative activity in companies, government laboratories and universities. Geoscientists worked to better understand the resource base and improve our knowledge about mineral deposits that will be mines in the future. Process engineers carried out research that is making primary production and recycling more efficient. Materials scientists and engineers searched for substitutes that will require fewer or no rare earths while providing properties comparable or superior to those of existing materials. As a result, even though global supply chains are not significantly different now than they were before the market disruption, the innovative activity motivated by the disruption likely will have far-reaching, if unpredictable, consequences for supply chains of rare earths in the future.
","language":"English","publisher":"Annual Reviews","doi":"10.1146/annurev-environ-110615-085700","usgsCitation":"Eggert, R., Wadia, C., Anderson, C., Bauer, D., Fields, F., Meinert, L.D., and Taylor, P., 2016, Rare earths: Market disruption, innovation, and global supply chains: Environment and Resources, v. 41, p. 199-222, https://doi.org/10.1146/annurev-environ-110615-085700.","productDescription":"24 p.","startPage":"199","endPage":"222","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071063","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":324688,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5776349de4b07dd077c829cd","contributors":{"authors":[{"text":"Eggert, Roderick","contributorId":172613,"corporation":false,"usgs":false,"family":"Eggert","given":"Roderick","email":"","affiliations":[],"preferred":false,"id":641416,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wadia, Cyrus","contributorId":172614,"corporation":false,"usgs":false,"family":"Wadia","given":"Cyrus","email":"","affiliations":[],"preferred":false,"id":641417,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Corby","contributorId":172615,"corporation":false,"usgs":false,"family":"Anderson","given":"Corby","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":641418,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bauer, Diana","contributorId":172616,"corporation":false,"usgs":false,"family":"Bauer","given":"Diana","email":"","affiliations":[],"preferred":false,"id":641419,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fields, Fletcher","contributorId":172617,"corporation":false,"usgs":false,"family":"Fields","given":"Fletcher","email":"","affiliations":[],"preferred":false,"id":641420,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Meinert, Lawrence D. lmeinert@usgs.gov","contributorId":1639,"corporation":false,"usgs":true,"family":"Meinert","given":"Lawrence","email":"lmeinert@usgs.gov","middleInitial":"D.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":581014,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Taylor, Patrick","contributorId":172618,"corporation":false,"usgs":false,"family":"Taylor","given":"Patrick","email":"","affiliations":[],"preferred":false,"id":641421,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70160021,"text":"70160021 - 2016 - Episodic bedrock erosion by gully-head migration, Colorado High Plains, USA","interactions":[],"lastModifiedDate":"2016-09-06T13:49:27","indexId":"70160021","displayToPublicDate":"2016-06-30T14:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Episodic bedrock erosion by gully-head migration, Colorado High Plains, USA","docAbstract":"This study explores the frequency of bedrock exposure in a soil-mantled low-relief (i.e. non-mountainous) landscape. In the High Plains of eastern Colorado, gully headcuts are among the few erosional features that will incise through the soil mantle to expose bedrock. We measured the last time of bedrock exposure using optically stimulated luminescence dating of alluvial sediment overlying bedrock in gully headcuts. Our dating suggests that headcuts in adjacent gullies expose bedrock asynchronously, and therefore, the headcuts are unlikely to have been triggered by a base-level drop in the trunk stream. This finding supports the hypothesis that headcuts can develop locally in gullies as a result of focused scour in locations where hydraulic stress during a flash flood is sufficiently high, and/or ground cover is sufficiently weak, to generate a scour hole that undermines vegetation. Alluvium dating also reveals that gullies have been a persistent part of this landscape since the early Holocene.
","language":"English","publisher":"John Wiley and Sons","doi":"10.1002/esp.3929","usgsCitation":"Rengers, F.K., Tucker, G., and Mahan, S., 2016, Episodic bedrock erosion by gully-head migration, Colorado High Plains, USA: Earth Surface Processes and Landforms, v. 41, no. 11, p. 1574-1582, https://doi.org/10.1002/esp.3929.","productDescription":"9 p.","startPage":"1574","endPage":"1582","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071039","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":324686,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.1,\n 39\n ],\n [\n -105.1,\n 40\n ],\n [\n -103.7,\n 40\n ],\n [\n -103.7,\n 39\n ],\n [\n -105.1,\n 39\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"11","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-20","publicationStatus":"PW","scienceBaseUri":"5776349ce4b07dd077c829b4","contributors":{"authors":[{"text":"Rengers, Francis K. 0000-0002-1825-0943 frengers@usgs.gov","orcid":"https://orcid.org/0000-0002-1825-0943","contributorId":150422,"corporation":false,"usgs":true,"family":"Rengers","given":"Francis","email":"frengers@usgs.gov","middleInitial":"K.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":581612,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tucker, G.E.","contributorId":150423,"corporation":false,"usgs":false,"family":"Tucker","given":"G.E.","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":581613,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mahan, Shannon 0000-0001-5214-7774 smahan@usgs.gov","orcid":"https://orcid.org/0000-0001-5214-7774","contributorId":1215,"corporation":false,"usgs":true,"family":"Mahan","given":"Shannon","email":"smahan@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":581614,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70174453,"text":"70174453 - 2016 - Comparison of wastewater-associated contaminants in the bed sediment of Hempstead Bay, New York, before and after Hurricane Sandy","interactions":[],"lastModifiedDate":"2018-08-09T12:19:14","indexId":"70174453","displayToPublicDate":"2016-06-30T14:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2676,"text":"Marine Pollution Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of wastewater-associated contaminants in the bed sediment of Hempstead Bay, New York, before and after Hurricane Sandy","docAbstract":"Changes in bed sediment chemistry of Hempstead Bay (HB) have been evaluated in the wake of Hurricane Sandy, which resulted in the release of billions of liters of poorly-treated sewage into tributaries and channels throughout the bay. Surficial grab samples (top 5 cm) collected before and (or) after Hurricane Sandy from sixteen sites in HB were analyzed for 74 wastewater tracers and steroid hormones, and total organic carbon. Data from pre- and post-storm comparisons of the most frequently detected wastewater tracers and ratios of steroid hormone and of polycyclic aromatic hydrocarbon concentrations indicate an increased sewage signal near outfalls and downstream of where raw sewage was discharged. Median concentration of wastewater tracers decreased after the storm at sites further from outfalls. Overall, changes in sediment quality probably resulted from a combination of additional sewage inputs, sediment redistribution, and stormwater runoff in the days to weeks following Hurricane Sandy.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpolbul.2016.03.044","usgsCitation":"Fisher, S.C., Phillips, P.J., Brownawell, B., and Browne, J., 2016, Comparison of wastewater-associated contaminants in the bed sediment of Hempstead Bay, New York, before and after Hurricane Sandy: Marine Pollution Bulletin, v. 107, no. 2, p. 499-508, https://doi.org/10.1016/j.marpolbul.2016.03.044.","productDescription":"10 p.","startPage":"499","endPage":"508","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069548","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":325102,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Hempstead Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.828125,\n 40.538851525354644\n ],\n [\n -73.828125,\n 40.71499673906409\n ],\n [\n -73.35708618164062,\n 40.71499673906409\n ],\n [\n -73.35708618164062,\n 40.538851525354644\n ],\n [\n -73.828125,\n 40.538851525354644\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"107","issue":"2","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"579dc1a3e4b0589fa1cb7d82","contributors":{"authors":[{"text":"Fisher, Shawn C. 0000-0001-6324-1061 scfisher@usgs.gov","orcid":"https://orcid.org/0000-0001-6324-1061","contributorId":4843,"corporation":false,"usgs":true,"family":"Fisher","given":"Shawn","email":"scfisher@usgs.gov","middleInitial":"C.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":642194,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Phillips, Patrick J. 0000-0001-5915-2015 pjphilli@usgs.gov","orcid":"https://orcid.org/0000-0001-5915-2015","contributorId":172757,"corporation":false,"usgs":true,"family":"Phillips","given":"Patrick","email":"pjphilli@usgs.gov","middleInitial":"J.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":642195,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brownawell, Bruce J.","contributorId":108264,"corporation":false,"usgs":true,"family":"Brownawell","given":"Bruce J.","affiliations":[],"preferred":false,"id":642196,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Browne, James","contributorId":172825,"corporation":false,"usgs":false,"family":"Browne","given":"James","email":"","affiliations":[{"id":27101,"text":"Conservation Biologist, Town of Hempstead Dept of Conservation & Waterways","active":true,"usgs":false}],"preferred":false,"id":642197,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70170965,"text":"sir20165060 - 2016 - Flood-inundation maps for Lake Champlain in Vermont and in northern Clinton County, New York","interactions":[{"subject":{"id":70170965,"text":"sir20165060 - 2016 - Flood-inundation maps for Lake Champlain in Vermont and in northern Clinton County, New York","indexId":"sir20165060","publicationYear":"2016","noYear":false,"title":"Flood-inundation maps for Lake Champlain in Vermont and in northern Clinton County, New York"},"predicate":"SUPERSEDED_BY","object":{"id":70202005,"text":"sir20185169 - 2019 - Flood-inundation maps for Lake Champlain in Vermont and New York","indexId":"sir20185169","publicationYear":"2019","noYear":false,"title":"Flood-inundation maps for Lake Champlain in Vermont and New York"},"id":1}],"supersededBy":{"id":70202005,"text":"sir20185169 - 2019 - Flood-inundation maps for Lake Champlain in Vermont and New York","indexId":"sir20185169","publicationYear":"2019","noYear":false,"title":"Flood-inundation maps for Lake Champlain in Vermont and New York"},"lastModifiedDate":"2022-11-02T14:53:45.691442","indexId":"sir20165060","displayToPublicDate":"2016-06-30T14:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5060","title":"Flood-inundation maps for Lake Champlain in Vermont and in northern Clinton County, New York","docAbstract":"Digital flood-inundation maps for an approximately100-mile length of Lake Champlain in Addison, Chittenden, Franklin, and Grand Isle Counties in Vermont and northern Clinton County in New York were created by the U.S. Geological Survey (USGS) in cooperation with the International Joint Commission (IJC). The flood-inundationmaps, which can be accessed through the International Joint Commission (IJC) Web site at http://www.ijc.org/en_/, depict estimates of the areal extent flooding correspondingto selected water levels (stages) at the USGS lake gage on the Richelieu River (Lake Champlain) at Rouses Point, N.Y. (station number 04295000). In this study, wind and seiche effects (standing oscillating wave with a long wavelength) were not taken into account and the flood-inundation mapsreflect 11 stages (elevations) for Lake Champlain that are static for the study length of the lake. Near-real-time stages at this lake gage, and others on Lake Champlain, may be obtained on the Internet from the USGS National Water Information System at http://waterdata.usgs.gov/ or the National Weather Service Advanced Hydrologic Prediction Service at http:/water.weather.gov/ahps/, which also forecasts flood hydrographs at the Richelieu River (Lake Champlain) at Rouses Point.
Static flood boundary extents were determined for LakeChamplain in Addison, Chittenden, Franklin, and Grand Isle Counties in Vermont and northern Clinton County in New York using recently acquired (2013–2014) lidar (light detection and ranging) and may be referenced to any of the five USGS lake gages on Lake Champlain. Of these five lakgages, USGS lake gage 04295000, Richelieu River (Lake Champlain) at Rouses Point, N.Y., is the only USGS lake gage that is also a National Weather Service prediction location. Flood boundary extents for the Lake Champlain static flood-inundation map corresponding to the May 201 flood(103.2 feet [ft], National Geodetic Vertical Datum [NGVD] 29) were evaluated by comparing these boundary extents against the inundation area extents determined for the May 2011 flood (which incorporated documented high-water marksfrom the flood of May 201) (Bjerklie and others, 2014).
A digital elevation model (DEM) was created by USGS, within a geographic information system (GIS), from the recently flown and processed light detection and ranging(lidar) data (2013–2014) in Vermont and the lake shore area of northern Clinton County in New York. The lidar data have a vertical accuracy of 0.3 to 0.6-ft (9.6 to 18.0-centimeters [cm]) and a horizontal resolution of 2.3 to 4.6 ft (0.7 to 1.4 meters). This DEM was used in determining the floodboundary for 11 flood stages at 0.5-ft intervals from 100.0 to104.0 ft (NGVD 29) and 1-ft intervals from 104.0 to 106.0 ft (NGVD 29) as referenced to the USGS lake gage 04295000, Richelieu River (Lake Champlain) at Rouses Point, N.Y. In addition, the May 2011 flood-inundation area for elevation103.20 ft (NGVD 29) (102.77 ft, North American Vertical Datum [NAVD] 88) was determined from this DEM. The May 2011 flood is the highest recorded lake water level (stage)at the Rouses Point, N.Y., lake gage. Flood stages greater than 101.5 ft (NGVD 29) exceed the “major flood stage”as defined by the NationalWeather Service for USGS lake gage 04295000.
The availability of these maps, along with Internet information regarding current stage from the USGS lake gage and forecasted high-flow stages from the NationalWeather Service, will provide emergency management personnel and residents with information that is critical for flood responseactivities such as evacuations and road closures, as well as for post-flood recovery eforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165060","collaboration":"Prepared in cooperation with the International Joint Commission","usgsCitation":"Flynn, R.H., and Hayes, Laura, 2016, Flood-inundation maps for Lake Champlain in Vermont and in northern Clinton County, New York: U.S. Geological Survey Scientific Investigations Report 2016–5060, 11 p., https://dx.doi.org/10.3133/sir20165060.","productDescription":"vi, 11 p.","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-068359","costCenters":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"links":[{"id":323821,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5060/sir20165060.pdf","text":"Report","size":"1.54 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5060"},{"id":323820,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5060/coverthb.jpg"}],"country":"United States","state":"New York, Vermont","otherGeospatial":"Lake Champlain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.4600830078125,\n 43.614205328810954\n ],\n [\n -73.4600830078125,\n 45.00753503123719\n ],\n [\n -73.11676025390625,\n 45.00753503123719\n ],\n [\n -73.11676025390625,\n 43.614205328810954\n ],\n [\n -73.4600830078125,\n 43.614205328810954\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
331 Commerce Way, Suite 2
Pembroke, NH 03275
Or visit our Web site at:
http://newengland.water.usgs.gov
Wildfire can significantly alter the hydrologic response of a watershed to the extent that even modest rainstorms can generate dangerous flash floods and debris flows. To reduce public exposure to hazard, the U.S. Geological Survey produces post-fire debris-flow hazard assessments for select fires in the western United States. We use publicly available geospatial data describing basin morphology, burn severity, soil properties, and rainfall characteristics to estimate the statistical likelihood that debris flows will occur in response to a storm of a given rainfall intensity. Using an empirical database and refined geospatial analysis methods, we defined new equations for the prediction of debris-flow likelihood using logistic regression methods. We showed that the new logistic regression model outperformed previous models used to predict debris-flow likelihood.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161106","usgsCitation":"Staley, D.M., Negri, J.A., Kean, J.W., Laber, J.M., Tillery, A.C., and Youberg, A.M., 2016, Updated logistic regression equations for the calculation of post-fire debris-flow likelihood in the western United States: U.S. Geological Survey Open-File Report 2016–1106, 13 p., https://dx.doi.org/ofr20161106.","productDescription":"Report: iv, 13 p.; Appendix 1","numberOfPages":"17","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-076051","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":324673,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1106/ofr20161106.pdf","text":"Report","size":"1.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1106 Report"},{"id":324672,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1106/coverthb.jpg"},{"id":324675,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1106/ofr20161106_appx-1.xlsx","text":"Appendix 1","size":"268 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1106 Appendix 1"}],"contact":"Center Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, MS 966
Denver, CO 80225-0046
Bed sediment samples from 79 coastal New York and New Jersey, USA sites were analyzed for 75 compounds including wastewater associated contaminants, PAHs, and other organic compounds to assess the post-Hurricane Sandy distribution of organic contaminants among six regions. These results provide the first assessment of wastewater compounds, hormones, and PAHs in bed sediment for this region. Concentrations of most wastewater contaminants and PAHs were highest in the most developed region (Upper Harbor/Newark Bay, UHNB) and reflected the wastewater inputs to this area. Although the lack of pre-Hurricane Sandy data for most of these compounds make it impossible to assess the effect of the storm on wastewater contaminant concentrations, PAH concentrations in the UHNB region reflect pre-Hurricane Sandy conditions in this region. Lower hormone concentrations than predicted by the total organic carbon relation occurred in UHNB samples, suggesting that hormones are being degraded in the UHNB region.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpolbul.2016.04.050","usgsCitation":"Phillips, P.J., Gibson, C.A., Fisher, S.C., Fisher, I., Reilly, T.J., Smalling, K., Romanok, K., Foreman, W., ReVello, R., Focazio, M.J., and Jones, D.K., 2016, Regional variability in bed-sediment concentrations of wastewater compounds, hormones and PAHs for portions of coastal New York and New Jersey impacted by hurricane Sandy: Marine Pollution Bulletin, v. 107, no. 2, p. 489-498, https://doi.org/10.1016/j.marpolbul.2016.04.050.","productDescription":"9 p.","startPage":"489","endPage":"498","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069674","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":324936,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey, New York","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.3065185546875,\n 41.1455697310095\n ],\n [\n -72.103271484375,\n 41.000629848685385\n ],\n [\n -72.94921875,\n 40.65147128144057\n ],\n [\n -73.7017822265625,\n 40.543026009954986\n ],\n [\n -73.89404296875,\n 40.534676780615406\n ],\n [\n -73.9324951171875,\n 40.40094763151963\n ],\n [\n -73.9764404296875,\n 40.136890695345905\n ],\n [\n -74.014892578125,\n 39.740986355883564\n ],\n [\n -74.2730712890625,\n 39.42346418978382\n ],\n [\n -74.8004150390625,\n 38.91668153637508\n ],\n [\n -74.99267578125,\n 38.87392853923629\n ],\n [\n -75.07507324218749,\n 38.96795115401593\n ],\n [\n -75.003662109375,\n 39.11301365149975\n ],\n [\n -74.9432373046875,\n 39.25352462727606\n ],\n [\n -75.047607421875,\n 39.35978526869001\n ],\n [\n -75.047607421875,\n 39.49556336059472\n ],\n [\n -75.047607421875,\n 39.65222681530652\n ],\n [\n -75.0146484375,\n 39.812755695478124\n ],\n [\n -74.9212646484375,\n 39.939224840791965\n ],\n [\n -74.652099609375,\n 40.107487419012415\n ],\n [\n -74.4873046875,\n 40.1452892956766\n ],\n [\n -74.432373046875,\n 40.24179856487036\n ],\n [\n -74.476318359375,\n 40.38002840251183\n ],\n [\n -74.6630859375,\n 40.451127265872316\n ],\n [\n -74.6795654296875,\n 40.52215098562377\n ],\n [\n -74.6795654296875,\n 40.60144147645398\n ],\n [\n -74.6795654296875,\n 40.74725696280421\n ],\n [\n -74.6026611328125,\n 40.85537053192496\n ],\n [\n -74.586181640625,\n 41.071069130806414\n ],\n [\n -74.1522216796875,\n 41.17451935556443\n ],\n [\n -73.8720703125,\n 41.15797827873605\n ],\n [\n -73.7896728515625,\n 41.11246878918086\n ],\n [\n -73.7841796875,\n 40.950862628132775\n ],\n [\n -73.685302734375,\n 40.896905775860006\n ],\n [\n -73.4271240234375,\n 40.967455873296714\n ],\n [\n -73.2183837890625,\n 40.93841495689795\n ],\n [\n -73.1689453125,\n 40.992337919312284\n ],\n [\n -72.83935546875,\n 41.02135510866602\n ],\n [\n -72.3065185546875,\n 41.1455697310095\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"107","issue":"2","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5780cebee4b08116168223aa","contributors":{"authors":[{"text":"Phillips, Patrick J. 0000-0001-5915-2015 pjphilli@usgs.gov","orcid":"https://orcid.org/0000-0001-5915-2015","contributorId":172757,"corporation":false,"usgs":true,"family":"Phillips","given":"Patrick","email":"pjphilli@usgs.gov","middleInitial":"J.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":641943,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gibson, Cathy A","contributorId":172758,"corporation":false,"usgs":false,"family":"Gibson","given":"Cathy","email":"","middleInitial":"A","affiliations":[{"id":27091,"text":"Consultant, Ballston Spa NY","active":true,"usgs":false}],"preferred":false,"id":641944,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fisher, Shawn C. 0000-0001-6324-1061 scfisher@usgs.gov","orcid":"https://orcid.org/0000-0001-6324-1061","contributorId":4843,"corporation":false,"usgs":true,"family":"Fisher","given":"Shawn","email":"scfisher@usgs.gov","middleInitial":"C.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":641945,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fisher, Irene ifisher@usgs.gov","contributorId":172759,"corporation":false,"usgs":true,"family":"Fisher","given":"Irene","email":"ifisher@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":641946,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reilly, Timothy J. 0000-0002-2939-3050 tjreilly@usgs.gov","orcid":"https://orcid.org/0000-0002-2939-3050","contributorId":1858,"corporation":false,"usgs":true,"family":"Reilly","given":"Timothy","email":"tjreilly@usgs.gov","middleInitial":"J.","affiliations":[{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":641947,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smalling, Kelly L. 0000-0002-1214-4920 ksmall@usgs.gov","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":149769,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L. ","email":"ksmall@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":false,"id":641948,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Romanok, Kristin M. 0000-0002-8472-8765 kromanok@usgs.gov","orcid":"https://orcid.org/0000-0002-8472-8765","contributorId":169543,"corporation":false,"usgs":true,"family":"Romanok","given":"Kristin M. ","email":"kromanok@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":false,"id":641953,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Foreman, William T. 0000-0002-2530-3310 wforeman@usgs.gov","orcid":"https://orcid.org/0000-0002-2530-3310","contributorId":169108,"corporation":false,"usgs":true,"family":"Foreman","given":"William T. ","email":"wforeman@usgs.gov","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"preferred":false,"id":641949,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"ReVello, Rhiannon C. rcrevell@usgs.gov","contributorId":4128,"corporation":false,"usgs":true,"family":"ReVello","given":"Rhiannon C.","email":"rcrevell@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":641950,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Focazio, Michael J. 0000-0003-0967-5576 mfocazio@usgs.gov","orcid":"https://orcid.org/0000-0003-0967-5576","contributorId":1276,"corporation":false,"usgs":true,"family":"Focazio","given":"Michael","email":"mfocazio@usgs.gov","middleInitial":"J.","affiliations":[{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true},{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true}],"preferred":true,"id":641951,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Jones, Daniel K. 0000-0003-0724-8001 dkjones@usgs.gov","orcid":"https://orcid.org/0000-0003-0724-8001","contributorId":4959,"corporation":false,"usgs":true,"family":"Jones","given":"Daniel","email":"dkjones@usgs.gov","middleInitial":"K.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":641952,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70174225,"text":"70174225 - 2016 - Use of multiple sequencing technologies to produce a high-quality genome of the fungus Pseudogymnoascus destructans, the causative agent of bat White-Nose syndrome","interactions":[],"lastModifiedDate":"2016-07-01T12:59:25","indexId":"70174225","displayToPublicDate":"2016-06-30T13:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5099,"text":"Genome Announcements","active":true,"publicationSubtype":{"id":10}},"title":"Use of multiple sequencing technologies to produce a high-quality genome of the fungus Pseudogymnoascus destructans, the causative agent of bat White-Nose syndrome","docAbstract":"White-Nose syndrome has recently emerged as one of the most devastating wildlife diseases recorded, causing widespread mortality in numerous bat species throughout eastern North America. Here, we present an improvised reference genome of the fungal pathogen Pseudogymnoascus destructans for use in comparative genomic studies.
","language":"English","publisher":"American Society for Microbiology","doi":"10.1128/genomeA.00445-16","usgsCitation":"Drees, K., Palmer, J.M., Sebra, R., Lorch, J.M., Chen, C., Wu, C., Bok, J.W., Keller, N.F., Blehert, D.S., Cuomo, C.A., Linder, D.L., and Foster, J., 2016, Use of multiple sequencing technologies to produce a high-quality genome of the fungus Pseudogymnoascus destructans, the causative agent of bat White-Nose syndrome: Genome Announcements, v. 4, no. 3, e00445-16; 2 p., https://doi.org/10.1128/genomeA.00445-16.","productDescription":"e00445-16; 2 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-074832","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":470804,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1128/genomea.00445-16","text":"Publisher Index Page"},{"id":324679,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5776349ee4b07dd077c829e5","contributors":{"authors":[{"text":"Drees, Kevin P.","contributorId":81759,"corporation":false,"usgs":true,"family":"Drees","given":"Kevin P.","affiliations":[],"preferred":false,"id":641405,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Palmer, Jonathan M.","contributorId":172601,"corporation":false,"usgs":false,"family":"Palmer","given":"Jonathan","email":"","middleInitial":"M.","affiliations":[{"id":27066,"text":"Center for Forest Mycology Research, Northern Research Station, US Forest Service, Madison, Wisconsin, USAb","active":true,"usgs":false}],"preferred":false,"id":641406,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sebra, Robert","contributorId":172602,"corporation":false,"usgs":false,"family":"Sebra","given":"Robert","email":"","affiliations":[{"id":27067,"text":"Department of Genetics and Genomic Sciences and Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, USAc","active":true,"usgs":false}],"preferred":false,"id":641407,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lorch, Jeffrey M. 0000-0003-2239-1252 jlorch@usgs.gov","orcid":"https://orcid.org/0000-0003-2239-1252","contributorId":5565,"corporation":false,"usgs":true,"family":"Lorch","given":"Jeffrey","email":"jlorch@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":641408,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chen, Cynthia","contributorId":172603,"corporation":false,"usgs":false,"family":"Chen","given":"Cynthia","email":"","affiliations":[{"id":27068,"text":"Intact Genomics, Saint Louis, Missouri, USAe","active":true,"usgs":false}],"preferred":false,"id":641409,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wu, ChengCang","contributorId":172604,"corporation":false,"usgs":false,"family":"Wu","given":"ChengCang","email":"","affiliations":[{"id":27068,"text":"Intact Genomics, Saint Louis, Missouri, USAe","active":true,"usgs":false}],"preferred":false,"id":641410,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bok, Jin Woo","contributorId":172605,"corporation":false,"usgs":false,"family":"Bok","given":"Jin","email":"","middleInitial":"Woo","affiliations":[{"id":27069,"text":"Department of Bacteriology and Department of Medical Microbiology and Immunology, University of Wisconsin, Madison, Wisconsin, USAf","active":true,"usgs":false}],"preferred":false,"id":641411,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Keller, Nancy F.","contributorId":172606,"corporation":false,"usgs":false,"family":"Keller","given":"Nancy","email":"","middleInitial":"F.","affiliations":[{"id":27069,"text":"Department of Bacteriology and Department of Medical Microbiology and Immunology, University of Wisconsin, Madison, Wisconsin, USAf","active":true,"usgs":false}],"preferred":false,"id":641412,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Blehert, David S. 0000-0002-1065-9760 dblehert@usgs.gov","orcid":"https://orcid.org/0000-0002-1065-9760","contributorId":140397,"corporation":false,"usgs":true,"family":"Blehert","given":"David","email":"dblehert@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":641404,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cuomo, Christina A.","contributorId":172607,"corporation":false,"usgs":false,"family":"Cuomo","given":"Christina","email":"","middleInitial":"A.","affiliations":[{"id":27070,"text":"Genome Sequencing and Analysis Program, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USAg","active":true,"usgs":false}],"preferred":false,"id":641413,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Linder, Daniel L.","contributorId":127718,"corporation":false,"usgs":false,"family":"Linder","given":"Daniel","email":"","middleInitial":"L.","affiliations":[{"id":6679,"text":"US Forest Service, Rocky Mountain Research Station","active":true,"usgs":false}],"preferred":false,"id":641414,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Foster, Jeffrey T.","contributorId":8744,"corporation":false,"usgs":true,"family":"Foster","given":"Jeffrey T.","affiliations":[],"preferred":false,"id":641415,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70162329,"text":"70162329 - 2016 - Application of SPARROW modeling to understanding contaminant fate and transport from uplands to streams","interactions":[],"lastModifiedDate":"2016-06-30T11:18:18","indexId":"70162329","displayToPublicDate":"2016-06-30T12:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2126,"text":"JAWRA","active":true,"publicationSubtype":{"id":10}},"title":"Application of SPARROW modeling to understanding contaminant fate and transport from uplands to streams","docAbstract":"Understanding spatial variability in contaminant fate and transport is critical to efficient regional water-quality restoration. An approach to capitalize on previously calibrated spatially referenced regression (SPARROW) models to improve the understanding of contaminant fate and transport was developed and applied to the case of nitrogen in the 166,000 km2 Chesapeake Bay watershed. A continuous function of four hydrogeologic, soil, and other landscape properties significant (α = 0.10) to nitrogen transport from uplands to streams was evaluated and compared among each of the more than 80,000 individual catchments (mean area, 2.1 km2) in the watershed. Budgets (including inputs, losses or net change in storage in uplands and stream corridors, and delivery to tidal waters) were also estimated for nitrogen applied to these catchments from selected upland sources. Most (81%) of such inputs are removed, retained, or otherwise processed in uplands rather than transported to surface waters. Combining SPARROW results with previous budget estimates suggests 55% of this processing is attributable to denitrification, 23% to crop or timber harvest, and 6% to volatilization. Remaining upland inputs represent a net annual increase in landscape storage in soils or biomass exceeding 10 kg per hectare in some areas. Such insights are important for planning watershed restoration and for improving future watershed models.
","language":"English","publisher":"American Water Resources Association","doi":"10.1111/1752-1688.12419","usgsCitation":"Ator, S., and Garcia, A.M., 2016, Application of SPARROW modeling to understanding contaminant fate and transport from uplands to streams: JAWRA, v. 52, no. 3, p. 685-704, https://doi.org/10.1111/1752-1688.12419.","productDescription":"20 p.","startPage":"685","endPage":"704","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071433","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":324676,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-09","publicationStatus":"PW","scienceBaseUri":"5776349ce4b07dd077c829aa","contributors":{"authors":[{"text":"Ator, Scott 0000-0002-9186-4837 swator@usgs.gov","orcid":"https://orcid.org/0000-0002-9186-4837","contributorId":152414,"corporation":false,"usgs":true,"family":"Ator","given":"Scott","email":"swator@usgs.gov","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":589240,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garcia, Ana Maria 0000-0002-5388-1281 agarcia@usgs.gov","orcid":"https://orcid.org/0000-0002-5388-1281","contributorId":2035,"corporation":false,"usgs":true,"family":"Garcia","given":"Ana","email":"agarcia@usgs.gov","middleInitial":"Maria","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":589241,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70249350,"text":"70249350 - 2016 - Landsat Science Team: 2016 Winter meeting summary","interactions":[],"lastModifiedDate":"2023-10-05T11:06:26.65642","indexId":"70249350","displayToPublicDate":"2016-06-30T11:55:56","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3555,"text":"The Earth Observer","active":true,"publicationSubtype":{"id":10}},"title":"Landsat Science Team: 2016 Winter meeting summary","docAbstract":"No abstract available.
","language":"English","publisher":"NASA","usgsCitation":"Schroeder, T., Loveland, T., Wulder, M., and Irons, J., 2016, Landsat Science Team: 2016 Winter meeting summary: The Earth Observer, v. 3, no. 28, p. 19-23.","productDescription":"5 p.","startPage":"19","endPage":"23","ipdsId":"IP-080431","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":421609,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":421567,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://eospso.nasa.gov/sites/default/files/eo_pdfs/May_June_2016_color%20508.pdf#page=19"}],"volume":"3","issue":"28","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schroeder, Todd","contributorId":330543,"corporation":false,"usgs":false,"family":"Schroeder","given":"Todd","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":885267,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loveland, Thomas 0000-0003-3114-6646 loveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3114-6646","contributorId":140611,"corporation":false,"usgs":true,"family":"Loveland","given":"Thomas","email":"loveland@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":885268,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wulder, Mike","contributorId":330544,"corporation":false,"usgs":false,"family":"Wulder","given":"Mike","email":"","affiliations":[{"id":13540,"text":"Canadian Forest Service","active":true,"usgs":false}],"preferred":false,"id":885269,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Irons, James","contributorId":330545,"corporation":false,"usgs":false,"family":"Irons","given":"James","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":885270,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70171544,"text":"70171544 - 2016 - Diet of pumas (Puma concolor) in Sonora, Mexico, as determined by GPS kill sites and molecular identified scat, with comments on jaguar (Panthera onca) diet","interactions":[],"lastModifiedDate":"2016-08-02T10:15:17","indexId":"70171544","displayToPublicDate":"2016-06-30T11:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3451,"text":"Southwestern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Diet of pumas (Puma concolor) in Sonora, Mexico, as determined by GPS kill sites and molecular identified scat, with comments on jaguar (Panthera onca) diet","docAbstract":"We documented puma (Puma concolor) and jaguar (Panthera onca) prey consumption in northeastern Sonora, Mexico, by investigating global positioning system cluster sites (n = 220), and conducting molecular analyses of scat (n = 116) collected between 2011 and 2013. We used camera trap data (n = 8,976 camera days) to estimate relative abundances of pumas and jaguars. Deer (Odocoileus virginianus) was the most frequent prey for puma found at kill sites (67%) and identified from scat (74%), although based on relative numbers of prey consumed, deer represented 45% and lagomorphs 20% of the proportion of all individuals eaten. A variety of small prey (weighing <15 kg) comprised the majority (52%) of the jaguar kill sites. From prey found at kill sites, jaguars killed calves (Bos taurus) at a lower frequency than previously reported, whereas pumas preyed on calves at a higher frequency than previously reported in the same area. In our study area, jaguars preyed on calves at approximately the same rate as pumas (jaguars 3.7 calves per year, pumas 4.9 calves per year). Calculated predation rates were limited only to collared animals within our study area and therefore should not be considered applicable to all pumas and jaguars in Sonora.
","language":"English","publisher":"Southwestern Association of Naturalists","publisherLocation":"Dallas, TX","doi":"10.1894/0038-4909-61.2.125","usgsCitation":"Cassaigne, I., Medellin, R., Thompson, R.W., Culver, M., Ochoa, A., Vargas, K., Childs, J.L., Sanderson, J., List, R., and Torres-Gomez, A., 2016, Diet of pumas (Puma concolor) in Sonora, Mexico, as determined by GPS kill sites and molecular identified scat, with comments on jaguar (Panthera onca) diet: Southwestern Naturalist, v. 61, no. 2, p. 125-132, https://doi.org/10.1894/0038-4909-61.2.125.","startPage":"125","endPage":"132","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070010","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":325899,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico","state":"Sonora","volume":"61","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-27","publicationStatus":"PW","scienceBaseUri":"57a1c42fe4b006cb45552c0a","contributors":{"authors":[{"text":"Cassaigne, Ivonne","contributorId":173305,"corporation":false,"usgs":false,"family":"Cassaigne","given":"Ivonne","email":"","affiliations":[],"preferred":false,"id":644216,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Medellin, Rodrigo A.","contributorId":77456,"corporation":false,"usgs":true,"family":"Medellin","given":"Rodrigo A.","affiliations":[],"preferred":false,"id":644217,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Ron W.","contributorId":170001,"corporation":false,"usgs":false,"family":"Thompson","given":"Ron","email":"","middleInitial":"W.","affiliations":[{"id":24784,"text":"Arizona Game and Fish Department, 5000 West Carefree Highway, Phoenix, Arizona 85086, United States","active":true,"usgs":false}],"preferred":false,"id":644218,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Culver, Melanie 0000-0001-5380-3059 mculver@usgs.gov","orcid":"https://orcid.org/0000-0001-5380-3059","contributorId":4327,"corporation":false,"usgs":true,"family":"Culver","given":"Melanie","email":"mculver@usgs.gov","affiliations":[{"id":127,"text":"Arizona Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":12625,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, 85721, USA","active":true,"usgs":false}],"preferred":false,"id":631724,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ochoa, Alexander","contributorId":169994,"corporation":false,"usgs":false,"family":"Ochoa","given":"Alexander","email":"","affiliations":[{"id":17653,"text":"School of Natural Resources & the Environment, The University of Arizona, Tucson","active":true,"usgs":false}],"preferred":false,"id":644219,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vargas, Karla","contributorId":173306,"corporation":false,"usgs":false,"family":"Vargas","given":"Karla","email":"","affiliations":[],"preferred":false,"id":644220,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Childs, Jack L.","contributorId":147124,"corporation":false,"usgs":false,"family":"Childs","given":"Jack","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":644221,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sanderson, Jim","contributorId":173307,"corporation":false,"usgs":false,"family":"Sanderson","given":"Jim","email":"","affiliations":[],"preferred":false,"id":644222,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"List, Rurik","contributorId":167139,"corporation":false,"usgs":false,"family":"List","given":"Rurik","email":"","affiliations":[{"id":17657,"text":"Instituto de Ecología, Universidad Nacional Autónoma de Mexico","active":true,"usgs":false}],"preferred":false,"id":644223,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Torres-Gomez, Armando","contributorId":173309,"corporation":false,"usgs":false,"family":"Torres-Gomez","given":"Armando","email":"","affiliations":[],"preferred":false,"id":644224,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70174223,"text":"70174223 - 2016 - Historical habitat barriers prevent ring-like genetic continuity throughout the distribution of threatened Alameda Striped Racers (Coluber lateralis euryxanthus)","interactions":[],"lastModifiedDate":"2018-11-20T15:45:42","indexId":"70174223","displayToPublicDate":"2016-06-30T11:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1892,"text":"Herpetologica","active":true,"publicationSubtype":{"id":10}},"title":"Historical habitat barriers prevent ring-like genetic continuity throughout the distribution of threatened Alameda Striped Racers (Coluber lateralis euryxanthus)","docAbstract":"We used microsatellites and mtDNA sequences to examine the mixed effects of geophysical, habitat, and contemporary urban barriers on the genetics of threatened Alameda Striped Racers (Coluber lateralis euryxanthus), a species with close ties to declining coastal scrub and chaparral habitat in the eastern San Francisco Bay area of California. We used cluster assignments to characterize population genetic structuring with respect to land management units and approximate Bayesian analysis to rank the ability of five alternative evolutionary hypotheses to explain the inferred structure. Then, we estimated rates of contemporary and historical migration among the major clusters and measured the fit of different historical migration models to better understand the formation of the current population structure. Our results reveal a ring-like pattern of historical connectivity around the Tri-Valley area of the East Bay (i.e., San Ramon, Amador, and Livermore valleys), with clusters largely corresponding to different management units. We found no evidence of continuous gene flow throughout the ring, however, and that the main gap in continuity is centered across the Livermore Valley. Historical migration models support higher rates of gene flow away from the terminal ends of the ring on the north and south sides of the Valley, compared with rates into those areas from western sites that border the interior San Francisco Bay. We attribute the break in ring-like connectivity to the presence of unsuitable habitat within the Livermore Valley that has been reinforced by 20th century urbanization, and the asymmetry in gene flow rates to spatial constraints on movement and east–west environmental gradients influenced by the proximity of the San Francisco Bay.
","language":"English","publisher":"The Herpetologists' League","doi":"10.1655/Herpetologica-D-15-00046.1","usgsCitation":"Richmond, J.Q., Wood, D.A., Swaim, K., Fisher, R.N., and Vandergast, A.G., 2016, Historical habitat barriers prevent ring-like genetic continuity throughout the distribution of threatened Alameda Striped Racers (Coluber lateralis euryxanthus): Herpetologica, v. 72, no. 3, p. 202-213, https://doi.org/10.1655/Herpetologica-D-15-00046.1.","productDescription":"12 p.","startPage":"202","endPage":"213","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066471","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":324669,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Tri-Valley area of the East Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.40280151367188,\n 37.80218877920469\n ],\n [\n -122.20916748046876,\n 37.54457732085582\n ],\n [\n -122.04299926757812,\n 37.42034463389752\n ],\n [\n -121.96746826171875,\n 37.47594794878128\n ],\n [\n -122.20367431640624,\n 37.779398571318765\n ],\n [\n -122.40280151367188,\n 37.80218877920469\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"72","issue":"3","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5776349de4b07dd077c829c3","contributors":{"authors":[{"text":"Richmond, Jonathan Q. 0000-0001-9398-4894 jrichmond@usgs.gov","orcid":"https://orcid.org/0000-0001-9398-4894","contributorId":5400,"corporation":false,"usgs":true,"family":"Richmond","given":"Jonathan","email":"jrichmond@usgs.gov","middleInitial":"Q.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":641399,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wood, Dustin A. 0000-0002-7668-9911 dawood@usgs.gov","orcid":"https://orcid.org/0000-0002-7668-9911","contributorId":4179,"corporation":false,"usgs":true,"family":"Wood","given":"Dustin","email":"dawood@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":641400,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swaim, Karen","contributorId":172600,"corporation":false,"usgs":false,"family":"Swaim","given":"Karen","affiliations":[{"id":27065,"text":"Swaim Biological Inc, Livermore, CA","active":true,"usgs":false}],"preferred":false,"id":641401,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":641402,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vandergast, Amy G. 0000-0002-7835-6571 avandergast@usgs.gov","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":3963,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","email":"avandergast@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":641403,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70174047,"text":"70174047 - 2016 - Understanding the hydrologic impacts of wastewater treatment plant discharge to shallow groundwater: Before and after plant shutdown","interactions":[],"lastModifiedDate":"2018-08-07T12:41:40","indexId":"70174047","displayToPublicDate":"2016-06-30T10:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5112,"text":"Environmental Science: Water Research & Technology","active":true,"publicationSubtype":{"id":10}},"title":"Understanding the hydrologic impacts of wastewater treatment plant discharge to shallow groundwater: Before and after plant shutdown","docAbstract":"Effluent-impacted surface water has the potential to transport not only water, but wastewater-derived contaminants to shallow groundwater systems. To better understand the effects of effluent discharge on in-stream and near-stream hydrologic conditions in wastewater-impacted systems, water-level changes were monitored in hyporheic-zone and shallow-groundwater piezometers in a reach of Fourmile Creek adjacent to and downstream of the Ankeny (Iowa, USA) wastewater treatment plant (WWTP). Water-level changes were monitored from approximately 1.5 months before to 0.5 months after WWTP closure. Diurnal patterns in WWTP discharge were closely mirrored in stream and shallow-groundwater levels immediately upstream and up to 3 km downstream of the outfall, indicating that such discharge was the primary control on water levels before shutdown. The hydrologic response to WWTP shutdown was immediately observed throughout the study reach, verifying the far-reaching hydraulic connectivity and associated contaminant transport risk. The movement of WWTP effluent into alluvial aquifers has implications for potential WWTP-derived contamination of shallow groundwater far removed from the WWTP outfall.
","language":"English","publisher":"The Royal Society of Chemistry","doi":"10.1039/c6ew00128a","usgsCitation":"Hubbard, L.E., Keefe, S.H., Kolpin, D.W., Barber, L.B., Duris, J.W., Hutchinson, K.J., and Bradley, P.M., 2016, Understanding the hydrologic impacts of wastewater treatment plant discharge to shallow groundwater: Before and after plant shutdown: Environmental Science: Water Research & Technology, v. 2, p. 864-874, https://doi.org/10.1039/c6ew00128a.","productDescription":"11 p.","startPage":"864","endPage":"874","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073598","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":438604,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7RF5S3P","text":"USGS data release","linkHelpText":"Precipitation, surface-water discharge, and groundwater elevation data for Fourmile Creek, Ankeny, Iowa, USA during October 1, 2013 to November 30, 2013"},{"id":324665,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","otherGeospatial":"Fourmile Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.7408447265625,\n 41.4684573556768\n ],\n [\n -93.7408447265625,\n 41.75184866809371\n ],\n [\n -93.43185424804688,\n 41.75184866809371\n ],\n [\n -93.43185424804688,\n 41.4684573556768\n ],\n [\n -93.7408447265625,\n 41.4684573556768\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"2","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5776349ee4b07dd077c829d9","contributors":{"authors":[{"text":"Hubbard, Laura E. 0000-0003-3813-1500 lhubbard@usgs.gov","orcid":"https://orcid.org/0000-0003-3813-1500","contributorId":4221,"corporation":false,"usgs":true,"family":"Hubbard","given":"Laura","email":"lhubbard@usgs.gov","middleInitial":"E.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":640682,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keefe, Steffanie H. 0000-0002-3805-6101 shkeefe@usgs.gov","orcid":"https://orcid.org/0000-0002-3805-6101","contributorId":2843,"corporation":false,"usgs":true,"family":"Keefe","given":"Steffanie","email":"shkeefe@usgs.gov","middleInitial":"H.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":640683,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kolpin, Dana W. 0000-0002-3529-6505 dwkolpin@usgs.gov","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":1239,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana","email":"dwkolpin@usgs.gov","middleInitial":"W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":640684,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barber, Larry B. 0000-0002-0561-0831 lbbarber@usgs.gov","orcid":"https://orcid.org/0000-0002-0561-0831","contributorId":921,"corporation":false,"usgs":true,"family":"Barber","given":"Larry","email":"lbbarber@usgs.gov","middleInitial":"B.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":640685,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Duris, Joseph W. 0000-0002-8669-8109 jwduris@usgs.gov","orcid":"https://orcid.org/0000-0002-8669-8109","contributorId":172426,"corporation":false,"usgs":true,"family":"Duris","given":"Joseph","email":"jwduris@usgs.gov","middleInitial":"W.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":false,"id":640686,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hutchinson, Kasey J. khutchin@usgs.gov","contributorId":4223,"corporation":false,"usgs":true,"family":"Hutchinson","given":"Kasey","email":"khutchin@usgs.gov","middleInitial":"J.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":640687,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bradley, Paul M. 0000-0001-7522-8606 pbradley@usgs.gov","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":361,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul","email":"pbradley@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":640688,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70173838,"text":"ofr20161098 - 2016 - Mercury concentrations in water and mercury and selenium concentrations in fish from Brownlee Reservoir and selected sites in the Boise and Snake Rivers, Idaho and Oregon, 2013–15","interactions":[],"lastModifiedDate":"2016-07-11T14:37:22","indexId":"ofr20161098","displayToPublicDate":"2016-06-30T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1098","title":"Mercury concentrations in water and mercury and selenium concentrations in fish from Brownlee Reservoir and selected sites in the Boise and Snake Rivers, Idaho and Oregon, 2013–15","docAbstract":"Mercury (Hg) analyses were conducted on samples of sport fish and water collected from selected sampling sites in Brownlee Reservoir and the Boise and Snake Rivers to meet National Pollution Discharge and Elimination System (NPDES) permit requirements for the City of Boise, Idaho, between 2013 and 2015. City of Boise personnel collected water samples from six sites between October and November 2013 and 2015, with one site sampled in 2014. Total Hg concentrations in unfiltered water samples ranged from 0.48 to 8.8 nanograms per liter (ng/L), with the highest value in Brownlee Reservoir in 2013. All Hg concentrations in water samples were less than the U.S. Environmental Protection Agency (USEPA) Hg chronic aquatic life criterion of 12 ng/L.
The USEPA recommended a water-quality criterion of 0.30 milligrams per kilogram (mg/kg) methylmercury (MeHg) expressed as a fish-tissue residue value (wet-weight MeHg in fish tissue). The Idaho Department of Environmental Quality adopted the USEPA’s fish-tissue criterion and established a reasonable potential to exceed (RPTE) threshold 20 percent lower than the criterion or greater than 0.24 mg/kg Hg based on an average concentration of 10 fish from a receiving waterbody. NPDES permitted discharge to waters with fish having Hg concentrations exceeding 0.24 mg/kg are said to have a reasonable potential to exceed the water-quality criterion and thus are subject to additional permit obligations, such as requirements for increased monitoring and the development of a Hg minimization plan. The Idaho Fish Consumption Advisory Program (IFCAP) issues fish advisories to protect general and sensitive populations of fish consumers and has developed an action level of 0.22 mg/kg Hg in fish tissue. Fish consumption advisories are water body- and species-specific and are used to advise allowable fish consumption from specific water bodies. The geometric mean Hg concentration of 10 fish of a single species collected from a single water body (lake or stream) in Idaho is compared to the action level to determine if a fish consumption advisory should be issued.
The U.S. Geological Survey collected and analyzed individual fillets of mountain whitefish (Prosopium williamsoni), rainbow trout (Oncorhynchus mykiss), smallmouth bass (Micropterus dolomieu), and channel catfish (Ictalurus punctatus) for Hg. The 2013 average Hg concentration for small mouth bass (0.32 mg/kg) collected at Brownlee Reservoir and for channel catfish (0.33 mg/kg) collected at the Boise River mouth, exceeded the Idaho water quality criterion (>0.3 mg/kg), the Hg RPTE threshold (>0.24 mg/kg), and the IFCAP action level (>0.22 mg/kg). Average Hg concentrations in fish collected in 2014 or 2015 did not exceed evaluation criteria for any of the species assessed.
Selenium (Se) analysis was conducted on one composite fish tissue sample per site to assess general concentrations and to provide information for future risk assessments. Composite concentrations of Se in fish tissue collected between 2013 and 2015 ranged from 0.07 and 0.49 mg/kg wet weight with the highest concentration collected from smallmouth bass from the Snake River near Murphy, and the lowest from mountain whitefish from the Boise River at Eckert Road.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161098","collaboration":"Prepared in cooperation with the City of Boise, Idaho","usgsCitation":"Williams, M.L., and MacCoy, D.E., 2016, Mercury concentrations in water and mercury and selenium concentrations in fish from Brownlee Reservoir and selected sites in the Boise and Snake Rivers, Idaho and Oregon, 2013–15: U.S. Geological Survey Open-File Report 2016–1098, 29 p., https://dx.doi.org/10.3133/ofr20161098.","productDescription":"iv, 38p.","startPage":"1","endPage":"29","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070289","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":324695,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1098/ofr20161098.pdf","text":"Report","size":"6.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1098"},{"id":324694,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1098/coverthb.jpg"}],"country":"United States","state":"Idaho","city":"Boise","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.6912841796875,\n 43.07089421067248\n ],\n [\n -116.6912841796875,\n 44.004669106432225\n ],\n [\n -115.58990478515625,\n 44.004669106432225\n ],\n [\n -115.58990478515625,\n 43.07089421067248\n ],\n [\n -116.6912841796875,\n 43.07089421067248\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
http://id.water.usgs.gov
Though characterization of, and understanding determinants of, social structure in bats is increasing, little is known about how bat social groups respond to disturbance resulting in roost loss. Given that many species of bats roost in ephemeral or transitory resources such as plants, it is clear that bat social groups can tolerate some level of roost loss. Understanding responses of bat social groups to roost loss can provide insight into social structure that have applied conservation use. Herein, we review the existing literature on the effects of disturbance on bat social groups, and present a parameterizable agent-based model that can be used to explore the relationships among roost dynamics, population dynamics, and social behavior.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Sociality in bats","language":"English","publisher":"Springer","doi":"10.1007/978-3-319-38953-0_13","usgsCitation":"Silvis, A., Abaid, N., Ford, W., and Britzke, E.R., 2016, Responses of bat social groups to roost loss: More questions than answers, chap. of Sociality in bats, p. 261-280, https://doi.org/10.1007/978-3-319-38953-0_13.","productDescription":"20 p.","startPage":"261","endPage":"280","ipdsId":"IP-066788","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":340718,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-08","publicationStatus":"PW","scienceBaseUri":"59099aaee4b0fc4e449157ee","contributors":{"editors":[{"text":"Ortega, Jorge","contributorId":191697,"corporation":false,"usgs":false,"family":"Ortega","given":"Jorge","email":"","affiliations":[],"preferred":false,"id":693882,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Silvis, Alexander","contributorId":171585,"corporation":false,"usgs":false,"family":"Silvis","given":"Alexander","email":"","affiliations":[{"id":26923,"text":"Virginia Polytechnic Institute, Blacksburg, VA","active":true,"usgs":false}],"preferred":false,"id":693879,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Abaid, Nicole","contributorId":171663,"corporation":false,"usgs":false,"family":"Abaid","given":"Nicole","email":"","affiliations":[],"preferred":false,"id":693880,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":693147,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Britzke, Eric R.","contributorId":8327,"corporation":false,"usgs":true,"family":"Britzke","given":"Eric","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":693881,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70170927,"text":"sir20165049 - 2016 - Adjusting annual maximum peak discharges at selected stations in northeastern Illinois for changes in land-use conditions","interactions":[],"lastModifiedDate":"2016-07-06T17:17:02","indexId":"sir20165049","displayToPublicDate":"2016-06-30T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5049","title":"Adjusting annual maximum peak discharges at selected stations in northeastern Illinois for changes in land-use conditions","docAbstract":"The effects of urbanization on annual maximum peak discharges in northeastern Illinois and nearby areas from 1945 to 2009 were analyzed with a two-step longitudinal-quantile linear regression approach. The peak discharges were then adjusted to 2010 land-use conditions. The explanatory variables used were daily precipitation at the time of the peak discharge event and a housing density-based measure of developed land use. The effect of the implementation of stormwater detention was assessed indirectly. Peak discharge records affected by the construction of large reservoirs that affect channel routing were identified and were split into segments at the time of completion of the reservoir. Longitudinal regressions of the peak discharge records on linear and logarithmic transformations of the selected measures of urbanization and precipitation were tested, and the best fitting model was selected for quantile regression and adjustment of the peak discharges.
\nBecause the uncertainties of streamgage-by-streamgage regressions of peak discharges as a function of urbanization are so large, a regional urbanization response was computed. Streamgages used in this study fit the following two criteria: (1) drainage area is at most 200 square miles and, (2) at least 10 consecutive years of peak discharge record are available. In the first step of the regression analysis, linear longitudinal regression models with fixed intercepts estimated for each segment of the peak discharge records were computed. The segment intercepts were then subtracted from the discharge records to homogenize the discharge dataset across the segments in preparation for the quantile regression analysis. From the quantile regression analysis, the effect of urbanization on peak discharge varies strongly with the exceedance probability of the peak discharge event; coefficients monotonically increase from 0.340 to 0.969 over exceedance probabilities from 0.002 to 0.99. The regression analyses yield estimates of the population-wide effect of the explanatory variables on the dependent variables as a function of exceedance probability. These estimates are similar to the coefficients of the regional regression relations in USGS regional flood-frequency studies such as those implemented in the Web application StreamStats; although in the longitudinal analysis used in this study, it is the temporal not the spatial (between-streamgage) variations that are taken into account.
\nThe observed and adjusted values for each streamgage are tabulated. To illustrate the overall effect of the adjustments, differences in the mean, standard deviation, and skewness of the log-transformed observed and urbanization-adjusted peak discharge series by streamgage are computed. For almost every streamgage where an adjustment was applied (no increase in urbanization was reported for a few streamgages), the mean increased and the standard deviation decreased; the effect on skewness values was more variable but usually they increased. Significant positive peak discharge trends were common in the observed values, occurring at 27.3 percent of streamgages at a p-value of 0.05 according to a Kendall’s tau correlation test; in the adjusted values, the incidence of such trends was reduced to 7.0 percent.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165049","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers—Chicago District, the Illinois Center for Transportation, the Illinois Department of Transportation, and the Federal Highway Administration","usgsCitation":"Over, T.M., Saito, R.J., and Soong, D.T., 2016, Adjusting annual maximum peak discharges at selected stations in northeastern Illinois for changes in land-use conditions: U.S. Geological Survey Scientific Investigations Report 2016–5049, 33 p., https://dx.doi.org/10.3133/sir20165049.","productDescription":"Report: viii, 33 p.; Tables; Spatial Data","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-050378","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":324541,"rank":4,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2016/5049/sir20165049_Theobald_tifs.zip","text":"1940–2030 Housing Density Data","size":"1.04 GB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2016–5049 Spatial Data"},{"id":324540,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5049/sir20165049_tables.xlsx","text":"Tables 1, 3, 4, and 7","size":"375 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016–5049 Tables"},{"id":324534,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5049/coverthb.jpg"},{"id":324535,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5049/sir20165049.pdf","text":"Report","size":"4.89 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5049"}],"country":"United States","state":"Illinois","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.14056396484375,\n 42.282389042899574\n ],\n [\n -88.03619384765625,\n 42.28340504748079\n ],\n [\n -87.9730224609375,\n 42.28289704723818\n ],\n [\n -87.95310974121094,\n 42.28315104787148\n ],\n [\n -87.93319702148438,\n 42.28340504748079\n ],\n [\n -87.89337158203125,\n 42.28264304558087\n ],\n [\n -87.87277221679688,\n 42.28340504748079\n ],\n [\n -87.835693359375,\n 42.28442103567816\n ],\n [\n -87.7659,\n 42.155\n ],\n [\n -87.7572,\n 42.1548\n ],\n [\n -87.753,\n 42.1502\n ],\n [\n -87.7447,\n 42.137\n ],\n [\n -87.7399,\n 42.1319\n ],\n [\n -87.7393,\n 42.1296\n ],\n [\n -87.7351,\n 42.125\n ],\n [\n -87.7302,\n 42.1218\n ],\n [\n -87.729,\n 42.1213\n ],\n [\n -87.7272,\n 42.1194\n ],\n [\n -87.7261,\n 42.1153\n ],\n [\n -87.72,\n 42.1089\n ],\n [\n -87.7079,\n 42.0983\n ],\n [\n -87.6976,\n 42.0909\n ],\n [\n -87.6916,\n 42.0863\n ],\n [\n -87.6885,\n 42.0835\n ],\n [\n -87.6861,\n 42.0812\n ],\n [\n -87.685,\n 42.0784\n ],\n [\n -87.6807,\n 42.0766\n ],\n [\n -87.6771,\n 42.0729\n ],\n [\n -87.6747,\n 42.0692\n ],\n [\n -87.6742,\n 42.066\n ],\n [\n -87.6729,\n 42.0651\n ],\n [\n -87.6731,\n 42.0587\n ],\n [\n -87.6704,\n 42.0446\n ],\n [\n -87.6674,\n 42.0428\n ],\n [\n -87.6681,\n 42.0396\n ],\n [\n -87.6669,\n 42.0359\n ],\n [\n -87.6657,\n 42.0336\n ],\n [\n -87.6646,\n 42.0295\n ],\n [\n -87.6617,\n 42.0213\n ],\n [\n -87.6589,\n 42.0122\n ],\n [\n -87.6577,\n 42.0095\n ],\n [\n -87.6535,\n 42.0049\n ],\n [\n -87.6523,\n 42.0021\n ],\n [\n -87.6506,\n 41.9994\n ],\n [\n -87.6494,\n 41.9962\n ],\n [\n -87.6509,\n 41.9871\n ],\n [\n -87.6498,\n 41.9826\n ],\n [\n -87.6467,\n 41.9807\n ],\n [\n -87.6449,\n 41.9789\n ],\n [\n -87.6443,\n 41.9779\n ],\n [\n -87.6419,\n 41.9765\n ],\n [\n -87.6419,\n 41.9756\n ],\n [\n -87.642,\n 41.972\n ],\n [\n -87.6396,\n 41.9692\n ],\n [\n -87.6378,\n 41.9669\n ],\n [\n -87.6354,\n 41.9651\n ],\n [\n -87.6317,\n 41.9646\n ],\n [\n -87.6287,\n 41.9636\n ],\n [\n -87.6275,\n 41.9622\n ],\n [\n -87.6288,\n 41.9604\n ],\n [\n -87.6331,\n 41.9587\n ],\n [\n -87.6362,\n 41.9592\n ],\n [\n -87.6369,\n 41.9578\n ],\n [\n -87.6351,\n 41.9533\n ],\n [\n -87.6316,\n 41.9473\n ],\n [\n -87.6298,\n 41.945\n ],\n [\n -87.6292,\n 41.9432\n ],\n [\n -87.6293,\n 41.9396\n ],\n [\n -87.6281,\n 41.9373\n ],\n [\n -87.6263,\n 41.9359\n ],\n [\n -87.627,\n 41.9323\n ],\n [\n -87.6258,\n 41.9309\n ],\n [\n -87.6253,\n 41.9282\n ],\n [\n -87.6254,\n 41.9245\n ],\n [\n -87.6231,\n 41.9186\n ],\n [\n -87.6207,\n 41.9145\n ],\n [\n -87.6195,\n 41.9135\n ],\n [\n -87.6177,\n 41.914\n ],\n [\n -87.6164,\n 41.913\n ],\n [\n -87.6183,\n 41.9117\n ],\n [\n -87.6209,\n 41.9099\n ],\n [\n -87.6215,\n 41.9077\n ],\n [\n -87.621,\n 41.9058\n ],\n [\n -87.6204,\n 41.9036\n ],\n [\n -87.6186,\n 41.9031\n ],\n [\n -87.6161,\n 41.9017\n ],\n [\n -87.6149,\n 41.9007\n ],\n [\n -87.6131,\n 41.8994\n ],\n [\n -87.6108,\n 41.8957\n ],\n [\n -87.6096,\n 41.8943\n ],\n [\n -87.5985,\n 41.8932\n ],\n [\n -87.5973,\n 41.8928\n ],\n [\n -87.5973,\n 41.8919\n ],\n [\n -87.5985,\n 41.8914\n ],\n [\n -87.6066,\n 41.8915\n ],\n [\n -87.6084,\n 41.8907\n ],\n [\n -87.6103,\n 41.8889\n ],\n [\n -87.6097,\n 41.8875\n ],\n [\n -87.611,\n 41.8848\n ],\n [\n -87.6124,\n 41.8821\n ],\n [\n -87.6131,\n 41.878\n ],\n [\n -87.6127,\n 41.8698\n ],\n [\n -87.6109,\n 41.8689\n ],\n [\n -87.609,\n 41.8675\n ],\n [\n -87.6041,\n 41.8674\n ],\n [\n -87.6029,\n 41.8674\n ],\n [\n -87.603,\n 41.8629\n ],\n [\n -87.6038,\n 41.8579\n ],\n [\n -87.6038,\n 41.8561\n ],\n [\n -87.6063,\n 41.8552\n ],\n [\n -87.6088,\n 41.8539\n ],\n [\n -87.6059,\n 41.8457\n ],\n [\n -87.6031,\n 41.8384\n ],\n [\n -87.5995,\n 41.832\n ],\n [\n -87.5954,\n 41.826\n ],\n [\n -87.5894,\n 41.8177\n ],\n [\n -87.5841,\n 41.8117\n ],\n [\n -87.5811,\n 41.8081\n ],\n [\n -87.5793,\n 41.8053\n ],\n [\n -87.5782,\n 41.8021\n ],\n [\n -87.5764,\n 41.7998\n ],\n [\n -87.5758,\n 41.7989\n ],\n [\n -87.574,\n 41.7984\n ],\n [\n -87.5734,\n 41.798\n ],\n [\n -87.5728,\n 41.797\n ],\n [\n -87.574,\n 41.7962\n ],\n [\n -87.5765,\n 41.7944\n ],\n [\n -87.576,\n 41.7921\n ],\n [\n -87.5748,\n 41.7898\n ],\n [\n -87.5742,\n 41.7884\n ],\n [\n -87.5743,\n 41.7871\n ],\n [\n -87.5743,\n 41.7857\n ],\n [\n -87.5737,\n 41.7848\n ],\n [\n -87.5719,\n 41.7839\n ],\n [\n -87.5694,\n 41.7834\n ],\n [\n -87.5676,\n 41.7824\n ],\n [\n -87.5689,\n 41.7815\n ],\n [\n -87.5713,\n 41.7816\n ],\n [\n -87.5732,\n 41.7812\n ],\n [\n -87.5745,\n 41.7803\n ],\n [\n -87.5745,\n 41.7794\n ],\n [\n -87.5739,\n 41.778\n ],\n [\n -87.5727,\n 41.7775\n ],\n [\n -87.5714,\n 41.7779\n ],\n [\n -87.5677,\n 41.7788\n ],\n [\n -87.5665,\n 41.7774\n ],\n [\n -87.5659,\n 41.7765\n ],\n [\n -87.5611,\n 41.7719\n ],\n [\n -87.5606,\n 41.7705\n ],\n [\n -87.56,\n 41.7691\n ],\n [\n -87.5594,\n 41.7687\n ],\n [\n -87.5576,\n 41.7668\n ],\n [\n -87.5576,\n 41.765\n ],\n [\n -87.5528,\n 41.7604\n ],\n [\n -87.5504,\n 41.7599\n ],\n [\n -87.5479,\n 41.7594\n ],\n [\n -87.5461,\n 41.7594\n ],\n [\n -87.5449,\n 41.7598\n ],\n [\n -87.5412,\n 41.7593\n ],\n [\n -87.54,\n 41.7584\n ],\n [\n -87.5394,\n 41.7566\n ],\n [\n -87.5407,\n 41.7552\n ],\n [\n -87.5407,\n 41.7534\n ],\n [\n -87.5395,\n 41.7525\n ],\n [\n -87.5377,\n 41.7525\n ],\n [\n -87.5359,\n 41.7511\n ],\n [\n -87.5334,\n 41.7497\n ],\n [\n -87.531,\n 41.7483\n ],\n [\n -87.5298,\n 41.7469\n ],\n [\n -87.5283,\n 41.736\n ],\n [\n -87.5277,\n 41.7337\n ],\n [\n -87.5272,\n 41.73\n ],\n [\n -87.5257,\n 41.7182\n ],\n [\n -87.524,\n 41.7135\n ],\n [\n -87.5239,\n 41.6941\n ],\n [\n -87.5255,\n 41.5516\n ],\n [\n -87.5265,\n 41.4712\n ],\n [\n -87.5565,\n 41.4712\n ],\n [\n -87.6706,\n 41.4715\n ],\n [\n -87.7888,\n 41.4723\n ],\n [\n -87.7891,\n 41.4855\n ],\n [\n -87.7894,\n 41.5\n ],\n [\n -87.7922,\n 41.5377\n ],\n [\n -87.7923,\n 41.5595\n ],\n [\n -87.9071,\n 41.5578\n ],\n [\n -87.9106,\n 41.6445\n ],\n [\n -88.0299,\n 41.6428\n ],\n [\n -88.0308,\n 41.6868\n ],\n [\n -88.0317,\n 41.7295\n ],\n [\n -88.1499,\n 41.7272\n ],\n [\n -88.2625,\n 41.7251\n ],\n [\n -88.2628,\n 41.811\n ],\n [\n -88.2632,\n 41.8623\n ],\n [\n -88.2631,\n 41.9\n ],\n [\n -88.2634,\n 41.9876\n ],\n [\n -88.2632,\n 42.0675\n ],\n [\n -88.2632,\n 42.0685\n ],\n [\n -88.2379,\n 42.0682\n ],\n [\n -88.24630737304688,\n 42.28442103567816\n ],\n [\n -88.14056396484375,\n 42.282389042899574\n ]\n ]\n ]\n },\n \"properties\": {\n \"name\": \"Cook\",\n \"state\": \"IL\"\n }\n }\n ]\n}","contact":"Director, Illinois Water Science Center
U.S. Geological Survey
405 North Goodwin Avenue
Urbana, IL 61801
In 2015, the U.S. Geological Survey, in cooperation with the U.S. Department of Energy, drilled and constructed boreholes TAN-2271 and TAN-2272 for stratigraphic framework analyses and long-term groundwater monitoring of the eastern Snake River Plain aquifer at the Idaho National Laboratory in southeast Idaho. Borehole TAN-2271 initially was cored to collect continuous geologic data, and then re-drilled to complete construction as a monitor well. Borehole TAN-2272 was partially cored between 210 and 282 feet (ft) below land surface (BLS) then drilled and constructed as a monitor well. Boreholes TAN-2271 and TAN-2272 are separated by about 63 ft and have similar geologic layers and hydrologic characteristics based on geologic, geophysical, and aquifer test data collected. The final construction for boreholes TAN-2271 and TAN-2272 required 10-inch (in.) diameter carbon-steel well casing and 9.9-in. diameter open-hole completion below the casing to total depths of 282 and 287 ft BLS, respectively. Depth to water is measured near 228 ft BLS in both boreholes. Following construction and data collection, temporary submersible pumps and water-level access lines were placed to allow for aquifer testing, for collecting periodic water samples, and for measuring water levels.
Borehole TAN-2271 was cored continuously, starting at the first basalt contact (about 33 ft BLS) to a depth of 284 ft BLS. Excluding surface sediment, recovery of basalt and sediment core at borehole TAN-2271 was better than 98 percent. Based on visual inspection of core and geophysical data, material examined from 33 to 211ft BLS primarily consists of two massive basalt flows that are about 78 and 50 ft in thickness and three sediment layers near 122, 197, and 201 ft BLS. Between 211 and 284 ft BLS, geophysical data and core material suggest a high occurrence of fractured and vesicular basalt. For the section of aquifer tested, there are two primary fractured aquifer intervals: the first between 235 and 255 ft BLS and the second between 272 and 282 ft BLS. Basalt texture for borehole TAN-2271 generally was described as aphanitic, phaneritic, and porphyritic. Sediment layers, starting near 122 ft BLS, generally were composed of fine-grained sand and silt with a lesser amount of clay. Basalt flows generally ranged in thickness from 2 to 78 ft and varied from highly fractured to dense with high to low vesiculation. Geophysical data and limited core material collected from TAN-2272 show similar lithologic sequences to those reported for TAN-2271.
Geophysical and borehole video logs were collected during certain stages of the drilling and construction process at boreholes TAN-2271 and TAN-2272. Geophysical logs were examined synergistically with available core material to confirm geologic and hydrologic similarities and suggest possible fractured network interconnection between boreholes TAN-2271 and TAN-2272. Natural gamma log measurements were used to assess the completeness of the vapor port lines behind 10-in. diameter well casing. Electromagnetic flow meter results were used to identify downward flow conditions that exist for boreholes TAN-2271 and TAN-2272. Furthermore, gyroscopic deviation measurements were used to measure horizontal and vertical displacement at all depths in boreholes TAN-2271 and TAN-2272.
After borehole construction was completed, single‑well aquifer tests were done within wells TAN-2271 and TAN‑2272 to provide estimates of transmissivity and hydraulic conductivity. The transmissivity and hydraulic conductivity were estimated for the pumping well and observation well during the aquifer tests conducted on August 25 and August 27, 2015. Estimates for transmissivity range from 4.1 . 103 feet squared per day (ft2/d) to 8.1 . 103 ft2/d; estimates for hydraulic conductivity range from 5.8 to 11.5 feet per day (ft/d). Both TAN-2271 and TAN‑2272 show sustained pumping rates of about 30 gallons per minute (gal/min) with measured drawdown in the pumping well of 1.96 ft and 1.14 ft, respectively. The transmissivity estimates for wells tested were within the range of values determined from previous aquifer tests in other wells near Test Area North.
Groundwater samples were collected from both wells and were analyzed for cations, anions, metals, nutrients, volatile organic compounds, stable isotopes, and radionuclides. Groundwater samples for most of the inorganic constituents showed similar water chemistry in both wells. Groundwater samples for strontium-90, trichloroethene, and vinyl chloride exceeded maximum contaminant levels for public drinking water supplies in one or both wells.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165088","collaboration":"DOE/ID-22239Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
http://id.water.usgs.gov
Excess sediment in rivers and estuaries poses serious environmental and economic challenges. The U.S. Army Corps of Engineers (USACE) routinely dredges sediment in Federal navigation channels to maintain commercial shipping operations. The USACE initiated a 3-year pilot project in 2013 to use navigation channel dredged material to aid in restoration of shoreline habitat in the 21st Avenue West Channel Embayment of the Duluth-Superior Harbor. Placing dredged material in the 21st Avenue West Channel Embayment supports the restoration of shallow bay aquatic habitat aiding in the delisting of the St. Louis River Estuary Area of Concern.
The U.S. Geological Survey, in cooperation with the USACE, collected turbidity and suspended-sediment concentrations (SSCs) in 2014 and 2015 to measure the horizontal and vertical distribution of SSCs during placement operations of dredged materials. These data were collected to help the USACE evaluate the use of several best management practices, including various dredge material placement techniques and a silt curtain, to mitigate the dispersion of suspended sediment.
Three-dimensional visualization maps are a valuable tool for assessing the spatial displacement of SSCs. Data collection was designed to coincide with four dredged placement configurations that included periods with and without a silt curtain as well as before and after placement of dredged materials. Approximately 230 SSC samples and corresponding turbidity values collected in 2014 and 2015 were used to develop a simple linear regression model between SSC and turbidity. Using the simple linear regression model, SSCs were estimated for approximately 3,000 turbidity values at approximately 100 sampling sites in the 21st Avenue West Channel Embayment of the Duluth-Superior Harbor. The estimated SSCs served as input for development of 12 three-dimensional visualization maps.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165086","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Groten, J.T., Ellison, C.A., and Mahoney, M.H., 2016, Three-dimensional visualization maps of suspended-sediment concentrations during placement of dredged material in 21st Avenue West Channel Embayment, Duluth-Superior Harbor, Duluth, Minnesota, 2015: U.S. Geological Survey Scientific Investigations Report 2016–5086, 26 p., https://dx.doi.org/10.3133/sir20165086.","productDescription":"Report: vi, 26 p.; Appendix Tables: 1-1 through 1-4","startPage":"1","endPage":"26","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-069759","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":324664,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5086/sir20165086_appendix1.xlsx","text":"Appendix Tables 1–1 through 1–4","size":"277 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016–5086 Appendix Tables"},{"id":324663,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5086/sir20165086.pdf","text":"Report","size":"8.41 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5086"},{"id":324662,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5086/coverthb.jpg"}],"country":"United States","state":"Minnesota","city":"Duluth","otherGeospatial":"Duluth-Superior Harbor","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.12679862976073,\n 46.75162347434115\n ],\n [\n -92.12679862976073,\n 46.76626466624822\n ],\n [\n -92.10474014282227,\n 46.76626466624822\n ],\n [\n -92.10474014282227,\n 46.75162347434115\n ],\n [\n -92.12679862976073,\n 46.75162347434115\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Minnesota Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, Minnesota 55112
Characterizing the impacts of hydrologic alterations, pollutants, and habitat degradation on macroinvertebrate species assemblages is of critical value for managers wishing to categorize stream ecosystem condition. A combination of approaches including trait-based metrics and traditional bioassessments provides greater information, particularly in anthropogenic stream ecosystems where traditional approaches can be confounded by variously interacting land use impacts. Macroinvertebrates were collected from two rural and three urban nested study sites in central Missouri, USA during the spring and fall seasons of 2011. Land use responses of conventional taxonomic and trait-based metrics were compared to streamflow indices, physical habitat metrics, and water quality indices. Results show that biotic index was significantly different (p < 0.05) between sites with differences detected in 54 % of trait-based metrics. The most consistent response to urbanization was observed in size metrics, with significantly (p < 0.05) fewer small bodied organisms. Increases in fine streambed sediment, decreased submerged woody rootmats, significantly higher winter Chloride concentrations, and decreased mean suspended sediment particle size in lower urban stream reaches also influenced macroinvertebrate assemblages. Riffle habitats in urban reaches contained 21 % more (p = 0.03) multivoltine organisms, which was positively correlated to the magnitude of peak flows (r2 = 0.91, p = 0.012) suggesting that high flow events may serve as a disturbance in those areas. Results support the use of macroinvertebrate assemblages and multiple stressors to characterize urban stream system condition and highlight the need to better understand the complex interactions of trait-based metrics and anthropogenic aquatic ecosystem stressors.
","language":"English","publisher":"Springer","doi":"10.1007/s11252-016-0534-4","usgsCitation":"Nichols, J.W., Hubbart, J.A., and Poulton, B.C., 2016, Using macroinvertebrate assemblages and multiple stressors to infer urban stream system condition: A case study in the central US: Urban Ecosystems, v. 19, no. 2, p. 679-704, https://doi.org/10.1007/s11252-016-0534-4.","productDescription":"26 p. ","startPage":"679","endPage":"704","ipdsId":"IP-081283","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":343550,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri ","otherGeospatial":"Hinkson Creek Watershed ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.43450164794922,\n 38.872859384572244\n ],\n [\n -92.43450164794922,\n 39.00637903337455\n ],\n [\n -92.22335815429688,\n 39.00637903337455\n ],\n [\n -92.22335815429688,\n 38.872859384572244\n ],\n [\n -92.43450164794922,\n 38.872859384572244\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"19","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-03","publicationStatus":"PW","scienceBaseUri":"5965b31ee4b0d1f9f05b380a","contributors":{"authors":[{"text":"Nichols, John W.","contributorId":175334,"corporation":false,"usgs":false,"family":"Nichols","given":"John","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":704134,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hubbart, Jason A.","contributorId":194439,"corporation":false,"usgs":false,"family":"Hubbart","given":"Jason","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":704135,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Poulton, Barry C. 0000-0002-7219-4911 bpoulton@usgs.gov","orcid":"https://orcid.org/0000-0002-7219-4911","contributorId":2421,"corporation":false,"usgs":true,"family":"Poulton","given":"Barry","email":"bpoulton@usgs.gov","middleInitial":"C.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":704133,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70168828,"text":"70168828 - 2016 - Predicting the stability of endangered stonecats in the LaPlatte River, Vermont","interactions":[],"lastModifiedDate":"2022-11-02T15:02:18.422065","indexId":"70168828","displayToPublicDate":"2016-06-29T17:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Predicting the stability of endangered stonecats in the LaPlatte River, Vermont","docAbstract":"Stonecats Noturus flavus in Vermont conform to a rare distribution pattern (as designated by Rabinowitz 1981) because their known distribution within the state is limited to the LaPlatte and Missisquoi rivers. We focused on Stonecats in the LaPlatte River to predict the stability of the population. During 2012–2014, we captured Stonecats via backpack electrofishing; fish were PIT-tagged (>90 mm TL) and marked with visible implant elastomer. Among the 1,671 Stonecats that were captured, 1,252 were PIT-tagged. Only 156 (12%) of the PIT-tagged fish were recaptured, and only 22 of those individuals were recaptured more than once. The Pradel model in Program MARK was used to estimate apparent survival (Φ) and seniority, which were used to derive the rate of population change (λ) for the Stonecat encounter histories we studied. We examined a total of 64 models in our candidate set, with the following covariates: TL at first capture, maximum temperature, season, maximum discharge, and area sampled. Survival estimates were highest in the spring (range of daily Φ = 0.9993–0.9995) and increased with greater TL at first capture. We also estimated increases in capture probability with increasing area sampled. We derived an annual λ of 0.9794, which indicates a slightly decreasing population. However, our λ estimate contained uncertainty that was likely increased due to the low recapture rates. Additional years of data could increase the accuracy of the λ estimate. In the meantime, we have provided insight into Stonecat population parameters that were otherwise unknown.
","language":"English","publisher":"American Fisheries Society","doi":"10.1080/00028487.2016.1167779","usgsCitation":"Puchala, E.A., Parrish, D.L., and Donovan, T., 2016, Predicting the stability of endangered stonecats in the LaPlatte River, Vermont: Transactions of the American Fisheries Society, v. 145, no. 4, p. 903-912, https://doi.org/10.1080/00028487.2016.1167779.","productDescription":"10 p.","startPage":"903","endPage":"912","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069044","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":324657,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Vermont","otherGeospatial":"LaPlatte River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.21598052978516,\n 44.3795759047351\n ],\n [\n -73.21340560913086,\n 44.37564968766977\n ],\n [\n -73.21134567260742,\n 44.37123237879009\n ],\n [\n -73.21443557739258,\n 44.367305602292426\n ],\n [\n -73.20653915405273,\n 44.36632386703344\n ],\n [\n -73.20430755615234,\n 44.36632386703344\n ],\n [\n -73.20138931274414,\n 44.36546483518457\n ],\n [\n -73.19538116455078,\n 44.36202858181481\n ],\n [\n -73.1964111328125,\n 44.35859212688665\n ],\n [\n -73.19023132324219,\n 44.35834665810766\n ],\n [\n -73.18611145019531,\n 44.3587148608905\n ],\n [\n -73.17838668823242,\n 44.3587148608905\n ],\n [\n -73.17684173583984,\n 44.35662834786087\n ],\n [\n -73.17581176757812,\n 44.35159586369938\n ],\n [\n -73.17649841308594,\n 44.34791328441686\n ],\n [\n -73.17684173583984,\n 44.343984944818594\n ],\n [\n -73.17340850830078,\n 44.343248351836074\n ],\n [\n -73.17014694213867,\n 44.34435323783919\n ],\n [\n -73.16225051879883,\n 44.34300281878521\n ],\n [\n -73.15950393676758,\n 44.34337111797587\n ],\n [\n -73.15023422241211,\n 44.344476001665214\n ],\n [\n -73.14525604248047,\n 44.34435323783919\n ],\n [\n -73.14250946044922,\n 44.34288005187414\n ],\n [\n -73.1224250793457,\n 44.337478053272804\n ],\n [\n -73.1198501586914,\n 44.33477686732845\n ],\n [\n -73.12105178833008,\n 44.331216023015294\n ],\n [\n -73.125,\n 44.328882938821394\n ],\n [\n -73.13203811645508,\n 44.32851454862283\n ],\n [\n -73.14422607421875,\n 44.332689502057086\n ],\n [\n -73.15229415893555,\n 44.332689502057086\n ],\n [\n -73.16413879394531,\n 44.33158439624637\n ],\n [\n -73.17255020141602,\n 44.3329350782982\n ],\n [\n -73.18525314331055,\n 44.33465408319267\n ],\n [\n -73.18902969360352,\n 44.338337495433734\n ],\n [\n -73.18937301635742,\n 44.34668570657191\n ],\n [\n -73.18937301635742,\n 44.35049111420936\n ],\n [\n -73.20602416992188,\n 44.35257784576407\n ],\n [\n -73.20791244506836,\n 44.35797845301104\n ],\n [\n -73.21512222290038,\n 44.358837594637265\n ],\n [\n -73.22233200073242,\n 44.3584693926257\n ],\n [\n -73.22593688964844,\n 44.36092402899763\n ],\n [\n -73.22559356689453,\n 44.36914631155484\n ],\n [\n -73.22628021240234,\n 44.37270485210456\n ],\n [\n -73.22851181030273,\n 44.37614047920012\n ],\n [\n -73.2297134399414,\n 44.37982128456053\n ],\n [\n -73.23022842407227,\n 44.38313381155159\n ],\n [\n -73.22851181030273,\n 44.38583276904476\n ],\n [\n -73.22507858276367,\n 44.38656882676517\n ],\n [\n -73.22319030761719,\n 44.38693685215458\n ],\n [\n -73.21701049804688,\n 44.38436062583777\n ],\n [\n -73.21598052978516,\n 44.3795759047351\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"145","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-29","publicationStatus":"PW","scienceBaseUri":"5774e34ae4b07dd077c5fcda","contributors":{"authors":[{"text":"Puchala, Elizabeth A.","contributorId":38862,"corporation":false,"usgs":true,"family":"Puchala","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":641374,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parrish, Donna L. 0000-0001-9693-6329 dparrish@usgs.gov","orcid":"https://orcid.org/0000-0001-9693-6329","contributorId":138661,"corporation":false,"usgs":true,"family":"Parrish","given":"Donna","email":"dparrish@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":621877,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Donovan, Therese M. tdonovan@usgs.gov","contributorId":2653,"corporation":false,"usgs":true,"family":"Donovan","given":"Therese M.","email":"tdonovan@usgs.gov","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":641375,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}