We applied a management strategy evaluation (MSE) model to examine the potential cost-effectiveness of using pheromone-baited trapping along with conventional lampricide treatment to manage invasive sea lamprey. Four pheromone-baited trapping strategies were modeled: (1) stream activation wherein pheromone was applied to existing traps to achieve 10−12 mol/L in-stream concentration, (2) stream activation plus two additional traps downstream with pheromone applied at 2.5 mg/hr (reverse-intercept approach), (3) trap activation wherein pheromone was applied at 10 mg/hr to existing traps, and (4) trap activation and reverse-intercept approach. Each new strategy was applied, with remaining funds applied to conventional lampricide control. Simulating deployment of these hybrid strategies on fourteen Lake Michigan streams resulted in increases of 17 and 11% (strategies 1 and 2) and decreases of 4 and 7% (strategies 3 and 4) of the lakewide mean abundance of adult sea lamprey relative to status quo. MSE revealed performance targets for trap efficacy to guide additional research because results indicate that combining lampricides and high efficacy trapping technologies can reduce sea lamprey abundance on average without increasing control costs.
","language":"English","publisher":"Resource Modeling Association","publisherLocation":"Tempe, AZ","doi":"10.1111/nrm.12096","usgsCitation":"Dawson, H., Jones, M.L., Irwin, B.J., Johnson, N., Wagner, C., and Szymanski, M., 2016, Management strategy evaluation of pheromone-baited trapping techniques to improve management of invasive sea lamprey: Natural Resource Modeling, v. 29, no. 3, p. 448-469, https://doi.org/10.1111/nrm.12096.","startPage":"448","endPage":"469","numberOfPages":"22","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064352","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":470990,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/2027.42/133607","text":"External Repository"},{"id":326443,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-17","publicationStatus":"PW","scienceBaseUri":"57aef343e4b0fc09faae03a6","contributors":{"authors":[{"text":"Dawson, Heather","contributorId":96577,"corporation":false,"usgs":true,"family":"Dawson","given":"Heather","affiliations":[{"id":27267,"text":"University of Michigan-Flint","active":true,"usgs":false}],"preferred":false,"id":645330,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Michael L.","contributorId":139526,"corporation":false,"usgs":false,"family":"Jones","given":"Michael","email":"","middleInitial":"L.","affiliations":[{"id":6596,"text":"Quantitative Fisheries Center, Department of Fisheries and Wildlife Michigan State University","active":true,"usgs":false}],"preferred":false,"id":645331,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Irwin, Brian J. 0000-0002-0666-2641 bjirwin@usgs.gov","orcid":"https://orcid.org/0000-0002-0666-2641","contributorId":4037,"corporation":false,"usgs":true,"family":"Irwin","given":"Brian","email":"bjirwin@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":645332,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Nicholas S. 0000-0002-7419-6013 njohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7419-6013","contributorId":150983,"corporation":false,"usgs":true,"family":"Johnson","given":"Nicholas S.","email":"njohnson@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":645329,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wagner, C. 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The nitration chemistry however is incompletely understood. Moreover, there is a need to understand the reaction of nitric acid with natural organic matter (NOM) in general, in the context of a variety of environmental and biogeochemical processes. Suwannee River NOM, Suwannee River fulvic acid, and Pahokee Peat fulvic acid were treated with 15N-labeled nitric acid at concentrations ranging from 15% to 22% and analyzed by liquid and solid state 15N NMR spectroscopy. Bulk Pahokee peat and Illinois #6 coal were also treated with nitric acid, at 29% and 40% respectively, and analyzed by solid state 15N NMR spectroscopy. In addition to nitro groups from nitration of aromatic carbon, the 15N NMR spectra of all five samples exhibited peaks attributable to nitrosation reactions. These include nitrosophenol peaks in the peat fulvic acid and Suwannee River samples, from nitrosation of phenolic rings, and N-nitroso groups in the peat samples, from nitrosation of secondary amides or amines, the latter consistent with the peat samples having the highest naturally abundant nitrogen contents. Peaks attributable to Beckmann and secondary reactions of the initially formed oximes were present in all spectra, including primary amide, secondary amide, lactam, and nitrile nitrogens. The degree of secondary reaction product formation resulting from nitrosation reactions appeared to correlate inversely with the 13C aromaticities of the samples. The nitrosation reactions are most plausibly effected by nitrous acid formed from the reduction of nitric acid by oxidizable substrates in the NOM and coal samples.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0154981","usgsCitation":"Thorn, K.A., and Cox, L.G., 2016, Nitrosation and nitration of fulvic acid, peat and coal with nitric acid: PLoS ONE, v. 11, no. 5, e0154981: 20 p., https://doi.org/10.1371/journal.pone.0154981.","productDescription":"e0154981: 20 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066627","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":470991,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0154981","text":"Publisher Index Page"},{"id":321277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-13","publicationStatus":"PW","scienceBaseUri":"573ee3d2e4b04a3a6a24ad3b","contributors":{"authors":[{"text":"Thorn, Kevin A. 0000-0003-2236-5193 kathorn@usgs.gov","orcid":"https://orcid.org/0000-0003-2236-5193","contributorId":3288,"corporation":false,"usgs":true,"family":"Thorn","given":"Kevin","email":"kathorn@usgs.gov","middleInitial":"A.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":629380,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cox, Larry G. lgcox@usgs.gov","contributorId":3310,"corporation":false,"usgs":true,"family":"Cox","given":"Larry","email":"lgcox@usgs.gov","middleInitial":"G.","affiliations":[],"preferred":true,"id":629381,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70170990,"text":"70170990 - 2016 - Regional oxygen reduction and denitrification rates in groundwater from multi-model residence time distributions, San Joaquin Valley, USA","interactions":[],"lastModifiedDate":"2018-09-18T10:01:55","indexId":"70170990","displayToPublicDate":"2016-05-17T09:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Regional oxygen reduction and denitrification rates in groundwater from multi-model residence time distributions, San Joaquin Valley, USA","docAbstract":"Rates of oxygen and nitrate reduction are key factors in determining the chemical evolution of groundwater. Little is known about how these rates vary and covary in regional groundwater settings, as few studies have focused on regional datasets with multiple tracers and methods of analysis that account for effects of mixed residence times on apparent reaction rates. This study provides insight into the characteristics of residence times and rates of O2 reduction and denitrification (NO3− reduction) by comparing reaction rates using multi-model analytical residence time distributions (RTDs) applied to a data set of atmospheric tracers of groundwater age and geochemical data from 141 well samples in the Central Eastern San Joaquin Valley, CA. The RTD approach accounts for mixtures of residence times in a single sample to provide estimates of in-situ rates. Tracers included SF6, CFCs, 3H, He from 3H (tritiogenic He),14C, and terrigenic He. Parameter estimation and multi-model averaging were used to establish RTDs with lower error variances than those produced by individual RTD models. The set of multi-model RTDs was used in combination with NO3− and dissolved gas data to estimate zero order and first order rates of O2 reduction and denitrification. Results indicated that O2 reduction and denitrification rates followed approximately log-normal distributions. Rates of O2 and NO3− reduction were correlated and, on an electron milliequivalent basis, denitrification rates tended to exceed O2 reduction rates. Estimated historical NO3− trends were similar to historical measurements. Results show that the multi-model approach can improve estimation of age distributions, and that relatively easily measured O2 rates can provide information about trends in denitrification rates, which are more difficult to estimate.
","language":"English","publisher":"European Geophysical Society","doi":"10.1016/j.jhydrol.2016.05.018","usgsCitation":"Green, C.T., Jurgens, B.C., Zhang, Y., Starn, J., Singleton, M.J., and Esser, B.K., 2016, Regional oxygen reduction and denitrification rates in groundwater from multi-model residence time distributions, San Joaquin Valley, USA: Journal of Hydrology, v. 145, p. 47-55, https://doi.org/10.1016/j.jhydrol.2016.05.018.","productDescription":"9 p.","startPage":"47","endPage":"55","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067486","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":470992,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2016.05.018","text":"Publisher Index Page"},{"id":321295,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Joaquin Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.5,\n 37\n ],\n [\n -121.5,\n 38\n ],\n [\n -120,\n 38\n ],\n [\n -120,\n 37\n ],\n [\n -121.5,\n 37\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"145","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"574d566fe4b07e28b667f7a0","contributors":{"authors":[{"text":"Green, Christopher T. 0000-0002-6480-8194 ctgreen@usgs.gov","orcid":"https://orcid.org/0000-0002-6480-8194","contributorId":1343,"corporation":false,"usgs":true,"family":"Green","given":"Christopher","email":"ctgreen@usgs.gov","middleInitial":"T.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":629354,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jurgens, Bryant C. 0000-0002-1572-113X bjurgens@usgs.gov","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":127842,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant","email":"bjurgens@usgs.gov","middleInitial":"C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629355,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhang, Yong","contributorId":19029,"corporation":false,"usgs":true,"family":"Zhang","given":"Yong","affiliations":[],"preferred":false,"id":629356,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Starn, Jeffrey jjstarn@usgs.gov","contributorId":149231,"corporation":false,"usgs":true,"family":"Starn","given":"Jeffrey","email":"jjstarn@usgs.gov","affiliations":[{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629357,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Singleton, Michael J.","contributorId":44400,"corporation":false,"usgs":true,"family":"Singleton","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":629358,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Esser, Bradley K.","contributorId":33161,"corporation":false,"usgs":true,"family":"Esser","given":"Bradley","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":629359,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70174002,"text":"70174002 - 2016 - The potassic sedimentary rocks in Gale Crater, Mars, as seen by ChemCam Onboard Curiosity","interactions":[],"lastModifiedDate":"2016-11-16T15:19:50","indexId":"70174002","displayToPublicDate":"2016-05-17T03:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"The potassic sedimentary rocks in Gale Crater, Mars, as seen by ChemCam Onboard Curiosity","docAbstract":"The Mars Science Laboratory rover Curiosity encountered potassium-rich clastic sedimentary rocks at two sites in Gale Crater, the waypoints Cooperstown and Kimberley. These rocks include several distinct meters thick sedimentary outcrops ranging from fine sandstone to conglomerate, interpreted to record an ancient fluvial or fluvio-deltaic depositional system. From ChemCam Laser-Induced Breakdown Spectroscopy (LIBS) chemical analyses, this suite of sedimentary rocks has an overall mean K2O abundance that is more than 5 times higher than that of the average Martian crust. The combined analysis of ChemCam data with stratigraphic and geographic locations reveals that the mean K2O abundance increases upward through the stratigraphic section. Chemical analyses across each unit can be represented as mixtures of several distinct chemical components, i.e., mineral phases, including K-bearing minerals, mafic silicates, Fe-oxides, and Fe-hydroxide/oxyhydroxides. Possible K-bearing minerals include alkali feldspar (including anorthoclase and sanidine) and K-bearing phyllosilicate such as illite. Mixtures of different source rocks, including a potassium-rich rock located on the rim and walls of Gale Crater, are the likely origin of observed chemical variations within each unit. Physical sorting may have also played a role in the enrichment in K in the Kimberley formation. The occurrence of these potassic sedimentary rocks provides additional evidence for the chemical diversity of the crust exposed at Gale Crater.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2015JE004987","usgsCitation":"Le Deit, L., Mangold, N., Forni, O., Cousin, A., Lasue, J., Schröder, S., Wiens, R.C., Sumner, D.Y., Fabre, C., Stack, K.M., Anderson, R.B., Blaney, D.L., Clegg, S.M., Dromart, G., Fisk, M., Gasnault, O., Grotzinger, J., Gupta, S., Lanza, N., Le Mouelic, S., Maurice, S., McLennan, S.M., Meslin, P., Nachon, M., Newsom, H.E., Payre, V., Rapin, W., Rice, M., Sautter, V., and Treiman, A.H., 2016, The potassic sedimentary rocks in Gale Crater, Mars, as seen by ChemCam Onboard Curiosity: Journal of Geophysical Research, v. 121, no. 5, p. 784-804, https://doi.org/10.1002/2015JE004987.","productDescription":"21 p.","startPage":"784","endPage":"804","numberOfPages":"21","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071690","costCenters":[{"id":131,"text":"Astrogeology Science 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France","active":true,"usgs":false}],"preferred":false,"id":640216,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Treiman, Allan H.","contributorId":172307,"corporation":false,"usgs":false,"family":"Treiman","given":"Allan","email":"","middleInitial":"H.","affiliations":[{"id":12445,"text":"Lunar and Planetary Institute","active":true,"usgs":false}],"preferred":false,"id":640217,"contributorType":{"id":1,"text":"Authors"},"rank":30}]}} ,{"id":70169143,"text":"sir20165033 - 2016 - Effects of variations in flow characteristics through W.P. Franklin Lock and Dam on downstream water quality in the Caloosahatchee River Estuary and in McIntyre Creek in the J.N. “Ding” Darling National Wildlife Refuge, southern Florida, 2010–13","interactions":[],"lastModifiedDate":"2016-05-18T08:50:38","indexId":"sir20165033","displayToPublicDate":"2016-05-17T00:00:00","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":"2016-5033","title":"Effects of variations in flow characteristics through W.P. Franklin Lock and Dam on downstream water quality in the Caloosahatchee River Estuary and in McIntyre Creek in the J.N. “Ding” Darling National Wildlife Refuge, southern Florida, 2010–13","docAbstract":"The U.S. Geological Survey studied water-quality trends at the mouth of McIntyre Creek, an entry point to the J.N. “Ding” Darling National Wildlife Refuge, to investigate correlations between flow rates and volumes through the W.P. Franklin Lock and Dam and water-quality constituents inside the refuge from March 2010 to December 2013. Outflow from Lake Okeechobee, and flows from Franklin Lock, tributaries to the Caloosahatchee River Estuary, and the Cape Coral canal system were examined to determine the sources and quantity of water to the study area. Salinity, temperature, dissolved-oxygen concentration, pH, turbidity, and chromophoric dissolved organic matter fluorescence (FDOM) were measured during moving-boat surveys and at a fixed location in McIntyre Creek. Chlorophyll fluorescence was also recorded in McIntyre Creek. Water-quality surveys were completed on 20 dates between 2011 and 2014 using moving-boat surveys.
Franklin Lock contributed the majority of flow to the Caloosahatchee River. Between 2010 and 2013, the monthly mean flow rate at Franklin Lock ranged from 29 cubic feet per second in May 2011 to 10,650 cubic feet per second in August 2013. Instantaneous near-surface salinity in McIntyre Creek ranged from 12.9 parts per thousand on September 26, 2013, to 37.9 parts per thousand on June 27, 2011. Salinity in McIntyre Creek decreased with increasing flow rate through Franklin Lock. Flow rates through Franklin Lock explained 61 percent of the variation in salinity in McIntyre Creek. Salinity data from moving-boat surveys also indicate that an increase in flow rate at Franklin Lock decreases salinity in the Caloosahatchee River Estuary, and a reduction or elimination in flow increases salinity. The FDOM in McIntyre Creek was positively correlated with flow at Franklin Lock, and 54 percent of the variation in FDOM can be attributed to the flow rate through Franklin Lock. Data from moving-boat surveys indicate that FDOM increases when flow volume from Franklin Lock increases. The highest FDOM recorded during a survey was at Billy’s Creek. Chlorophyll fluorescence was positively correlated with flow at Franklin Lock, with 23 percent of the variation explained by the flow rate at Franklin Lock. An increase in flow rate at Franklin Lock resulted in a decrease in pH (21 percent of variation explained by flow rates). Data from the pH surveys indicate an increase in pH with distance from Franklin Lock. Turbidity and dissolved oxygen near the surface in McIntyre Creek were not correlated with flow rate at Franklin Lock. Moving-boat surveys did not document a change in turbidity or dissolved oxygen with a change in distance from the Franklin Lock. Correlations between Franklin Lock flow rate and water quality in McIntyre Creek indicate that releases at Franklin Lock affect water quality in the Caloosahatchee River Estuary and Ding Darling Refuge.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165033","collaboration":"Prepared as part of the Greater Everglades Priority Ecosystems Science Initiative and in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Booth, A.C., Soderqvist, L.E., and Knight, T.M., 2016, Effects of variations in flow characteristics through W.P. Franklin Lock and Dam on downstream water quality in the Caloosahatchee River Estuary and in McIntyre Creek in the J.N. “Ding” Darling National Wildlife Refuge, southern Florida, 2010–13: U.S. Geological Survey Scientific Investigations Report 2016–5033, 33 p., https://dx.doi.org/10.3133/sir20165033.","productDescription":"Report: vii, 33 p.; Data Release","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-063026","costCenters":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"links":[{"id":321251,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5033/coverthb.jpg"},{"id":321252,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5033/sir20165033.pdf","text":"Report","size":"11.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5033"},{"id":321253,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://dx.doi.org/10.5066/F70863BC","text":"Data Release","description":"Data Release"}],"country":"United States","state":"Florida","otherGeospatial":"Caloosahatchee River Estuary, J.N. “Ding” Darling National Wildlife Refuge, McIntyre Creek,","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.1942138671875,\n 26.40417061185344\n ],\n [\n -82.1942138671875,\n 26.831423660953195\n ],\n [\n -81.24938964843749,\n 26.831423660953195\n ],\n [\n -81.24938964843749,\n 26.40417061185344\n ],\n [\n -82.1942138671875,\n 26.40417061185344\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
We investigated the occurrence, persistence, and growth potential of Escherichia coli associated with freshwater organic debris (i.e., wrack) frequently deposited along shorelines (shoreline wrack), inputs from rivers (river CPOM), and parking lot runoffs (urban litter). Samples were collected from 9 Great Lakes beaches, 3 creeks, and 4 beach parking lots. Shoreline wrack samples were mainly composed of wood chips, straw, sticks, leaf litter, seeds, feathers, and mussel shells; creek and parking lot samples included dry grass, straw, seeds, wood chips, leaf/pine needle litter; soil particles were present in parking lot samples only. E. coli concentrations (most probable number, MPN) were highly variable in all sample types: shoreline wrack frequently reached 105/g dry weight (dw), river CPOM ranged from 81 to 7,916/g dw, and urban litter ranged from 0.5 to 24,952/g dw. Sequential rinsing studies showed that 61–87% of E. coli concentrations were detected in the first wash of shoreline wrack, with declining concentrations associated with 4–8 subsequent washings; viable counts were still detected even after 8 washes. E. coli grew readily in shoreline wrack and river CPOM incubated at 35 °C. At 30°C, growth was only detected in river CPOM and not in shoreline wrack or urban litter, but the bacteria persisted for at least 16 days. In summary, freshwater wrack is an understudied component of the beach ecosystem that harbors E. coli and thus likely influences estimations of water quality and the microbial community in the nearshore as a result of transfer between environments.
","language":"English","publisher":"International Association for Great Lakes Research","doi":"10.1016/j.jglr.2016.04.011","usgsCitation":"Nevers, M., Przybyla-Kelly, K., Spoljaric, A., Shively, D.A., Whitman, R.L., and Byappanahalli, M., 2016, Freshwater wrack along Great Lakes coasts harbors Escherichia coli: Potential for bacterial transfer between watershed environments: Journal of Great Lakes Research, v. 42, no. 4, p. 760-767, https://doi.org/10.1016/j.jglr.2016.04.011.","productDescription":"8 p.","startPage":"760","endPage":"767","ipdsId":"IP-071134","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":328805,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Illinois, Indiana, Ontario","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": 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Center","active":true,"usgs":true}],"preferred":true,"id":649166,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shively, Dawn A. dshively@usgs.gov","contributorId":2051,"corporation":false,"usgs":true,"family":"Shively","given":"Dawn","email":"dshively@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":649167,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Whitman, Richard L. rwhitman@usgs.gov","contributorId":542,"corporation":false,"usgs":true,"family":"Whitman","given":"Richard","email":"rwhitman@usgs.gov","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":649168,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Byappanahalli, Muruleedhara 0000-0001-5376-597X byappan@usgs.gov","orcid":"https://orcid.org/0000-0001-5376-597X","contributorId":147923,"corporation":false,"usgs":true,"family":"Byappanahalli","given":"Muruleedhara","email":"byappan@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":649169,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70170871,"text":"ofr20161066 - 2016 - Preliminary investigation of groundwater flow and trichloroethene transport in the Surficial Aquifer System, Naval Industrial Reserve Ordnance Plant, Fridley, Minnesota","interactions":[],"lastModifiedDate":"2016-05-18T09:54:58","indexId":"ofr20161066","displayToPublicDate":"2016-05-16T16:00:00","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":"2016-1066","title":"Preliminary investigation of groundwater flow and trichloroethene transport in the Surficial Aquifer System, Naval Industrial Reserve Ordnance Plant, Fridley, Minnesota","docAbstract":"Industrial practices at the Naval Industrial Reserve Ordnance Plant, in Fridley, Minnesota, caused soil and groundwater contamination. Some volatile organic compounds from the plant might have discharged to the Mississippi River, forced by the natural hydraulic gradient in the surficial aquifer system. The U.S. Environmental Protection Agency included the Naval Industrial Reserve Ordnance Plant on the Superfund National Priorities List in 1989.
\nThis report describes a preliminary characterization of trichloroethene transport in the surficial and Cambrian-Ordovician aquifer systems at the Naval Industrial Reserve Ordnance Plant. The characterization first involved simulation of 2001 conditions using a model, followed by an application of this 2001 simulator to 2011 conditions.
\nThe U.S. Geological Survey, in cooperation with the U.S. Department of the Navy, used a steady-state, uniform-density groundwater flow model to simulate measured potentiometric heads in aquifer systems on August 20, 2001, and a single-phase, conservative, non-reactive, miscible transport model to simulate trichloroethene concentrations in aquifer systems measured in 2001. The U.S. Department of the Navy furnished trichloroethene source areas and trichloroethene source area concentrations to the U.S. Geological Survey for this model simulation. Furnished delineations were postulated and informed by data collected from 1995 to 2011. The groundwater flow simulation of August 20, 2001, was superior to the trichloroethene transport simulation at replicating measurements; simulated potentiometric heads matched 90 percent of measured potentiometric heads on August 20, within 2 feet at selected locations whereas simulated trichloroethene concentration contours of 3, 10, 100, 1000, and 10,000 micrograms per liter (µg/L) correctly bounded 52 percent of measured concentrations in 2001 at selected locations. The degree to which the simulated trichloroethene plume does not match trichloroethene measurements in the surficial aquifer system during the 2001 simulation may suggest that furnished trichloroethene source areas and trichloroethene source area concentrations did not accurately represent all trichloroethene sources in the hydrogeologic system.
\nDuring the model simulation of 2001, trichloroethene discharged to the Mississippi River. A simulated 900-foot-long zone of benthic trichloroethene discharge flux existed in the shallow flow zone, across which simulated trichloroethene discharged from the surficial aquifer system to the Mississippi River at simulated trichloroethene concentrations that ranged from 3 µg/L to more than 100 µg/L. The Mississippi River was not sampled for volatile organic compounds in Fridley, Minn., from 1999 to 2016 (the publication of this report). Trichloroethene concentrations were measured in wells close to the Mississippi River in the surficial aquifer system on the downgradient side of the Naval Industrial Reserve Ordnance Plant groundwater flow field; for example, at well MS–43 in the shallow flow zone of the surficial aquifer system 280 feet east of the Mississippi River between December 1999 and August 2012, trichloroethene concentrations ranged from 130 to 220 µg/L. The 220-µg/L maximum concentration was reached in March 2003 and October 2006. The August 2012 concentration was 140 µg/L.
\nThe August 20, 2001, groundwater flow model simulator and the 2001 trichloroethene transport simulator were applied to a groundwater extraction and treatment system that existed in 2011. Furnished trichloroethene source areas and concentrations in the 2001 simulator were replaced with different, furnished, hypothetical source areas and concentrations. Forcing in 2001 was replaced with forcing in 2011. No trichloroethene concentrations greater than 3 µg/L were simulated as discharging to the Mississippi River during applications of the 2001 simulator to the 2011 groundwater extraction and treatment system. These applications were not intended to represent historical conditions. Differences between furnished and actual trichloroethene sources may explain differences between measurements and simulation results for the 2001 trichloroethene transport simulator. Causes of differences between furnished and actual trichloroethene sources may cause differences between hypothetical application results and the performance of the actual U.S. Department of the Navy groundwater extraction and treatment system at the Naval Industrial Reserve Ordnance Plant. Other limitations may also cause differences between application results and performance.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161066","collaboration":"Prepared in cooperation with the U.S. Department of the Navy, Naval Facilities Engineering Command","usgsCitation":"King, J.N., and Davis, J.H., 2016, Preliminary investigation of groundwater flow and trichloroethene transport in the surficial aquifer system, Naval Industrial Reserve Ordnance Plant, Fridley, Minnesota: U.S. Geological Survey Open File Report 2016–1066, 120 p., https://dx.doi.org/10.3133/ofr20161066.","productDescription":"Report: x, 120 p.; Metadata","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-039553","costCenters":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"links":[{"id":321042,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://dx.doi.org/10.5066/F798853M","text":"Data Release","linkFileType":{"id":5,"text":"html"},"description":"OFR 2016-1066"},{"id":321040,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1066/coverthb.jpg"},{"id":321041,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1066/ofr20161066.pdf","text":"Report","size":"12,1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1066"}],"country":"United States","state":"Minnesota","city":"Fridley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.38172912597656,\n 45.09582203415993\n ],\n [\n -93.34877014160155,\n 45.03228854011639\n ],\n [\n -93.27735900878906,\n 45.02986219868277\n ],\n [\n -92.96905517578125,\n 45.180584858570136\n ],\n [\n -93.043212890625,\n 45.25652199219273\n ],\n [\n -93.38172912597656,\n 45.09582203415993\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Minnesota Water Science Center
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2280 Woodale Drive
Mounds View, MN 55112
(763) 783-3100
http://mn.water.usgs.gov/
Several lines of earthquake evidence indicate that the lithospheric plate is broken under the load of the island of Hawai`i, where the geometry of the lithosphere is circular with a central depression. The plate bends concave downward surrounding a stress-free hole, rather than bending concave upward as with past assumptions. Earthquake focal mechanisms show that the center of load stress and the weak hole is between the summits of Mauna Loa and Mauna Kea where the load is greatest. The earthquake gap at 21 km depth coincides with the predicted neutral plane of flexure where horizontal stress changes sign. Focal mechanism P axes below the neutral plane display a striking radial pattern pointing to the stress center. Earthquakes above the neutral plane in the north part of the island have opposite stress patterns; T axes tend to be radial. The M6.2 Honomu and M6.7 Kiholo main shocks (both at 39 km depth) are below the neutral plane and show radial compression, and the M6.0 Kiholo aftershock above the neutral plane has tangential compression. Earthquakes deeper than 20 km define a donut of seismicity around the stress center where flexural bending is a maximum. The hole is interpreted as the soft center where the lithospheric plate is broken. Kilauea's deep conduit is seismically active because it is in the ring of maximum bending. A simplified two-dimensional stress model for a bending slab with a load at one end yields stress orientations that agree with earthquake stress axes and radial P axes below the neutral plane. A previous inversion of deep Hawaiian focal mechanisms found a circular solution around the stress center that agrees with the model. For horizontal faults, the shear stress within the bending slab matches the slip in the deep Kilauea seismic zone and enhances outward slip of active flanks.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2015JB012746","usgsCitation":"Klein, F.W., 2016, Lithospheric flexure under the Hawaiian volcanic load: Internal stresses and a broken plate revealed by earthquakes: Journal of Geophysical Research B: Solid Earth, v. 121, no. 4, p. 2400-2428, https://doi.org/10.1002/2015JB012746.","productDescription":"29 p.","startPage":"2400","endPage":"2428","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070787","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":470994,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jb012746","text":"Publisher Index Page"},{"id":321234,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.08551025390625,\n 18.890695349102117\n ],\n [\n -156.08551025390625,\n 20.2982655686933\n ],\n [\n -154.78912353515625,\n 20.2982655686933\n ],\n [\n -154.78912353515625,\n 18.890695349102117\n ],\n [\n -156.08551025390625,\n 18.890695349102117\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"121","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-08","publicationStatus":"PW","scienceBaseUri":"574d5667e4b07e28b667f77b","contributors":{"authors":[{"text":"Klein, Fred W. klein@usgs.gov","contributorId":4417,"corporation":false,"usgs":true,"family":"Klein","given":"Fred","email":"klein@usgs.gov","middleInitial":"W.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":629311,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70170981,"text":"70170981 - 2016 - Wind energy development: Methods for assessing risks to birds and bats pre-construction","interactions":[],"lastModifiedDate":"2020-12-21T15:09:19.820867","indexId":"70170981","displayToPublicDate":"2016-05-16T12:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1914,"text":"Human-Wildlife Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Wind energy development: Methods for assessing risks to birds and bats pre-construction","docAbstract":"Wind power generation is rapidly expanding. Although wind power is a low-carbon source of energy, it can impact negatively birds and bats, either directly through fatality or indirectly by displacement or habitat loss. Pre-construction risk assessment at wind facilities within the United States is usually required only on public lands. When conducted, it generally involves a 3-tier process, with each step leading to more detailed and rigorous surveys. Preliminary site assessment (U.S. Fish and Wildlife Service, Tier 1) is usually conducted remotely and involves evaluation of existing databases and published materials. If potentially at-risk wildlife are present and the developer wishes to continue the development process, then on-site surveys are conducted (Tier 2) to verify the presence of those species and to assess site-specific features (e.g., topography, land cover) that may influence risk from turbines. The next step in the process (Tier 3) involves quantitative or scientific studies to assess the potential risk of the proposed project to wildlife. Typical Tier-3 research may involve acoustic, aural, observational, radar, capture, tracking, or modeling studies, all designed to understand details of risk to specific species or groups of species at the given site. Our review highlights several features lacking from many risk assessments, particularly the paucity of before-and-after-control- impact (BACI) studies involving modeling and a lack of understanding of cumulative effects of wind facilities on wildlife. Both are essential to understand effective designs for pre-construction monitoring and both would help expand risk assessment beyond eagles.
","language":"English","publisher":"Berryman Institute","doi":"10.26077/phxc-zh11","usgsCitation":"Katzner, T., Bennett, V., Miller, T., Duerr, A.E., Braham, M., and Hale, A., 2016, Wind energy development: Methods for assessing risks to birds and bats pre-construction: Human-Wildlife Interactions, v. 10, no. 1, p. 42-52, https://doi.org/10.26077/phxc-zh11.","productDescription":"11 p.","startPage":"42","endPage":"52","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063881","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":321232,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"574d567fe4b07e28b667f7bf","contributors":{"authors":[{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":5979,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":629316,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bennett, Victoria","contributorId":169316,"corporation":false,"usgs":false,"family":"Bennett","given":"Victoria","affiliations":[{"id":25471,"text":"Texas Christian University","active":true,"usgs":false}],"preferred":false,"id":629317,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Tricia A.","contributorId":64790,"corporation":false,"usgs":true,"family":"Miller","given":"Tricia A.","affiliations":[],"preferred":false,"id":629318,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duerr, Adam E.","contributorId":102324,"corporation":false,"usgs":true,"family":"Duerr","given":"Adam","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":629319,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Braham, Melissa A.","contributorId":140127,"corporation":false,"usgs":false,"family":"Braham","given":"Melissa A.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":629320,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hale, Amanda","contributorId":169317,"corporation":false,"usgs":false,"family":"Hale","given":"Amanda","affiliations":[{"id":25471,"text":"Texas Christian University","active":true,"usgs":false}],"preferred":false,"id":629321,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70170980,"text":"70170980 - 2016 - Wind energy development: Methods to assess bird and bat fatality rates post-construction","interactions":[],"lastModifiedDate":"2020-12-21T15:11:26.049497","indexId":"70170980","displayToPublicDate":"2016-05-16T12:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1914,"text":"Human-Wildlife Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Wind energy development: Methods to assess bird and bat fatality rates post-construction","docAbstract":"Monitoring fatalities at wind energy facilities after they have been constructed can provide valuable information regarding impacts of wind power development on wildlife. The objective of this monitoring is to estimate abundance of a super-population of carcasses that entered the area within a designated period of time. By definition, the population is not closed and carcasses can enter as they are killed through collision with turbines, and leave as they are removed by scavengers or decompose to a point where they are not recognizable. In addition, the population is not inherently mobile, but can only change location through some external force. A focus on number of animal carcasses comprising the super-population, combined with peculiar traits that resist classic assumptions, distinguish fatality estimation at wind-power facilities from more classic abundance estimates that can be addressed through mark-recapture techniques or other well-known abundance estimators. We review the available methods to estimate the super-population of carcasses at wind power facilities. We discuss the role of these estimates in determining appropriate levels of minimization and mitigation of impacts to individual species of concern. We discuss the potential to extrapolate these measurements to reflect the cumulative effect of the industry on individual species. Finally, we suggest avenues of research needed to strengthen our understanding of the effect wind power development has, and might have in the future, on wildlife on this continent and worldwide.
","language":"English","publisher":"Berryman Institute","doi":"10.26077/36fe-0296","usgsCitation":"Huso, M.M., Dalthorp, D., Miller, T.J., and Bruns, D., 2016, Wind energy development: Methods to assess bird and bat fatality rates post-construction: Human-Wildlife Interactions, v. 10, no. 1, p. 62-70, https://doi.org/10.26077/36fe-0296.","productDescription":"9 p.","startPage":"62","endPage":"70","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064458","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":321233,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"574d5680e4b07e28b667f7c1","contributors":{"authors":[{"text":"Huso, Manuela M. 0000-0003-4687-6625 mhuso@usgs.gov","orcid":"https://orcid.org/0000-0003-4687-6625","contributorId":150012,"corporation":false,"usgs":true,"family":"Huso","given":"Manuela","email":"mhuso@usgs.gov","middleInitial":"M.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":629312,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dalthorp, Daniel 0000-0002-4815-6309 ddalthorp@usgs.gov","orcid":"https://orcid.org/0000-0002-4815-6309","contributorId":4902,"corporation":false,"usgs":true,"family":"Dalthorp","given":"Daniel","email":"ddalthorp@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":629313,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, T. J.","contributorId":169314,"corporation":false,"usgs":false,"family":"Miller","given":"T.","email":"","middleInitial":"J.","affiliations":[{"id":25470,"text":"U.S. Fish & Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":629314,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bruns, Dawn","contributorId":169315,"corporation":false,"usgs":false,"family":"Bruns","given":"Dawn","email":"","affiliations":[{"id":25470,"text":"U.S. Fish & Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":629315,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70171015,"text":"70171015 - 2016 - Exotic plant infestation is associated with decreased modularity and increased numbers of connectors in mixed-grass prairie pollination networks","interactions":[],"lastModifiedDate":"2016-05-17T10:22:01","indexId":"70171015","displayToPublicDate":"2016-05-16T11:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Exotic plant infestation is associated with decreased modularity and increased numbers of connectors in mixed-grass prairie pollination networks","docAbstract":"The majority of pollinating insects are generalists whose lifetimes overlap flowering periods of many potentially suitable plant species. Such generality is instrumental in allowing exotic plant species to invade pollination networks. The particulars of how existing networks change in response to an invasive plant over the course of its phenology are not well characterized, but may shed light on the probability of long-term effects on plant-pollinator interactions and the stability of network structure. Here we describe changes in network topology and modular structure of infested and non-infested networks during the flowering season of the generalist non-native flowering plant, Cirsium arvense in mixed-grass prairie at Badlands National Park, South Dakota, USA. Objectives were to compare network-level effects of infestation as they propagate over the season in infested and non-infested (with respect to C. arvense) networks. We characterized plant-pollinator networks on 5 non-infested and 7 infested 1-ha plots during 4 sample periods that collectively covered the length of C. arvense flowering period. Two other abundantly-flowering invasive plants were present during this time: Melilotus officinalis had highly variable floral abundance in both C. arvense-infested and non-infested plots andConvolvulus arvensis, which occurred almost exclusively in infested plots and peaked early in the season. Modularity, including roles of individual species, and network topology were assessed for each sample period as well as in pooled infested and non-infested networks. Differences in modularity and network metrics between infested and non-infested networks were limited to the third and fourth sample periods, during flower senescence of C. arvenseand the other invasive species; generality of pollinators rose concurrently, suggesting rewiring of the network and a lag effect of earlier floral abundance. Modularity was lower and number of connectors higher in infested networks, whether they were assessed in individual sample periods or pooled into infested and non-infested networks over the entire blooming period of C.arvense. Connectors typically did not reside within the same modules as C. arvense, suggesting that effects of the other invasive plants may also influence the modularity results, and that effects of infestation extend to co-flowering native plants. We conclude that the presence of abundantly flowering invasive species is associated with greater network stability due to decreased modularity, but whether this is advantageous for the associated native plant-pollinator communities depends on the nature of perturbations they experience.
","language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0155068","usgsCitation":"Larson, D.L., Rabie, P.A., Droege, S., Larson, J.L., and Haar, M., 2016, Exotic plant infestation is associated with decreased modularity and increased numbers of connectors in mixed-grass prairie pollination networks: PLoS ONE, v. 11, no. 5, p. 1-18, https://doi.org/10.1371/journal.pone.0155068.","productDescription":"18 p.","startPage":"1","endPage":"18","numberOfPages":"18","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069178","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":470995,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0155068","text":"Publisher Index Page"},{"id":321287,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"5","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-16","publicationStatus":"PW","scienceBaseUri":"574d565ee4b07e28b667f764","contributors":{"authors":[{"text":"Larson, Diane L. 0000-0001-5202-0634 dlarson@usgs.gov","orcid":"https://orcid.org/0000-0001-5202-0634","contributorId":2120,"corporation":false,"usgs":true,"family":"Larson","given":"Diane","email":"dlarson@usgs.gov","middleInitial":"L.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":629541,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rabie, Paul A. 0000-0003-4364-2268","orcid":"https://orcid.org/0000-0003-4364-2268","contributorId":74328,"corporation":false,"usgs":true,"family":"Rabie","given":"Paul","email":"","middleInitial":"A.","affiliations":[],"preferred":true,"id":629542,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Droege, Sam sdroege@usgs.gov","contributorId":3464,"corporation":false,"usgs":true,"family":"Droege","given":"Sam","email":"sdroege@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":629543,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Larson, Jennifer L. 0000-0002-6259-0101","orcid":"https://orcid.org/0000-0002-6259-0101","contributorId":68144,"corporation":false,"usgs":true,"family":"Larson","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":629544,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haar, Milton","contributorId":14302,"corporation":false,"usgs":true,"family":"Haar","given":"Milton","email":"","affiliations":[],"preferred":false,"id":629545,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70176572,"text":"70176572 - 2016 - Announcement—guidance document for acquiring reliable data in ecological restoration projects","interactions":[],"lastModifiedDate":"2016-09-21T15:40:21","indexId":"70176572","displayToPublicDate":"2016-05-16T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Announcement—guidance document for acquiring reliable data in ecological restoration projects","docAbstract":"The Laurentian Great Lakes are undergoing intensive ecological restoration in Canada and the United States. In the United States, an interagency committee was formed to facilitate implementation of quality practices for federally funded restoration projects in the Great Lakes basin. The Committee's responsibilities include developing a guidance document that will provide a common approach to the application of quality assurance and quality control (QA/QC) practices for restoration projects. The document will serve as a “how-to” guide for ensuring data quality during each aspect of ecological restoration projects. In addition, the document will provide suggestions on linking QA/QC data with the routine project data and hints on creating detailed supporting documentation. Finally, the document will advocate integrating all components of the project, including QA/QC applications, into an overarching decision-support framework. The guidance document is expected to be released by the U.S. EPA Great Lakes National Program Office in 2017.","language":"English","publisher":"Blackwell Science, Inc.","doi":"10.1111/rec.12367","usgsCitation":"Stapanian, M.A., Rodriguez, K., Lewis, T.E., Blume, L., Palmer, C.J., Walters, L., Schofield, J., Amos, M.M., and Bucher, A., 2016, Announcement—guidance document for acquiring reliable data in ecological restoration projects: Restoration Ecology, v. 24, no. 5, p. 570-572, https://doi.org/10.1111/rec.12367.","productDescription":"3 p.","startPage":"570","endPage":"572","ipdsId":"IP-074032","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":328834,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"24","issue":"5","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-16","publicationStatus":"PW","scienceBaseUri":"57f7c6bbe4b0bc0bec09cb0e","contributors":{"authors":[{"text":"Stapanian, Martin A. 0000-0001-8173-4273 mstapanian@usgs.gov","orcid":"https://orcid.org/0000-0001-8173-4273","contributorId":3425,"corporation":false,"usgs":true,"family":"Stapanian","given":"Martin","email":"mstapanian@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":649249,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rodriguez, Karen","contributorId":174767,"corporation":false,"usgs":false,"family":"Rodriguez","given":"Karen","email":"","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":649250,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lewis, Timothy E.","contributorId":174768,"corporation":false,"usgs":false,"family":"Lewis","given":"Timothy","email":"","middleInitial":"E.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":649251,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blume, Louis","contributorId":174769,"corporation":false,"usgs":false,"family":"Blume","given":"Louis","email":"","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":649252,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Palmer, Craig J.","contributorId":36028,"corporation":false,"usgs":true,"family":"Palmer","given":"Craig","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":649253,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Walters, Lynn","contributorId":174778,"corporation":false,"usgs":false,"family":"Walters","given":"Lynn","email":"","affiliations":[],"preferred":false,"id":649254,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schofield, Judith","contributorId":174779,"corporation":false,"usgs":false,"family":"Schofield","given":"Judith","email":"","affiliations":[],"preferred":false,"id":649255,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Amos, Molly M.","contributorId":174780,"corporation":false,"usgs":false,"family":"Amos","given":"Molly","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":649256,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bucher, Adam","contributorId":174781,"corporation":false,"usgs":false,"family":"Bucher","given":"Adam","email":"","affiliations":[],"preferred":false,"id":649257,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70175784,"text":"70175784 - 2016 - Novel insights from NMR spectroscopy into seasonal changes in the composition of dissolved organic matter exported to the Bering Sea by the Yukon River","interactions":[],"lastModifiedDate":"2016-08-19T10:23:58","indexId":"70175784","displayToPublicDate":"2016-05-15T14:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"Novel insights from NMR spectroscopy into seasonal changes in the composition of dissolved organic matter exported to the Bering Sea by the Yukon River","docAbstract":"Seasonal (spring freshet, summer–autumn, and winter) variability in the chemical composition of dissolved organic matter (DOM) from the Yukon River was determined using advanced one- and two-dimensional (2D) solid-state NMR spectroscopy, coupled with isotopic measurements and UV–visible spectroscopy. Analyses were performed on two major DOM fractions, the hydrophobic organic acid (HPOA) and transphilic organic acid (TPIA) fractions obtained using XAD resins. Together these two fractions comprised 64–74% of the total DOM. Carboxyl-rich alicyclic molecules (CRAM) accounted for the majority of carbon atoms in the HPOA (63–77%) and TPIA (54–78%) samples, and more so in winter and summer than in spring samples. 2D and selective NMR data revealed association of abundant nonprotonated O-alkyl and quaternary alkyl C (OCnp, OCnpO and Cq, 13–17% of HPOA and 15–20% of TPIA) and isolated O–CH structures with CRAM, which were not recognized in previous studies. Spectral editing and 2D NMR allowed for the discrimination of carbohydrate-like O-alkyl C from non-carbohydrate O-alkyl C. Whereas two spring freshet TPIA samples contained carbohydrate clusters such as carboxylated carbohydrates (16% and 26%), TPIA samples from other seasons or HPOA samples mostly had small amounts (<8%) of sugar rings dispersed in a nonpolar alkyl environment. Though nonprotonated aromatic C represented the largest fraction of aromatic C in all HPOA/TPIA isolates, only a small fraction (∼5% in HPOA and 3% in TPIA) was possibly associated with dissolved black carbon. Our results imply a relatively stable portion of DOM exported by the Yukon River across different seasons, due to the predominance of CRAM and their associated nonprotonated C–O and O–C–O structures, and elevated reactivity (bio- and photo-lability) of spring DOM due to the presence of terrestrial inputs enriched in carbohydrates and aromatic structures.
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The latter is an attribute taking non-negative real values, so a simple transformation is sufficient for its spatial modeling applying geostatistics. The analyses, however, involve proportions that follow the properties of compositional data, thus requiring special preprocessing for an adequate modeling already described in a previous publication for the case of proximate analysis data.1 Here we model the results of calorific value and ultimate analysis. We propose to use two different binary partitions, one per analysis, map the corresponding isometric logratio transformations, and backtransform the results. The methodology is illustrated using the same coal bed in the previous paper modeling proximate analysis data. Results are summarized using probability maps that, in the case of this deposit, show a prominent channel crossing the deposit and separating the best quality coal from that of lower quality.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2016.05.005","usgsCitation":"Olea, R., Luppens, J., Egozcue, J.J., and Pawlowsky-Glahn, V., 2016, Calorific value and compositional ultimate analysis with a case study of a Texas lignite: International Journal of Coal Geology, v. 162, p. 27-33, https://doi.org/10.1016/j.coal.2016.05.005.","productDescription":"7 p.","startPage":"27","endPage":"33","ipdsId":"IP-071169","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":357542,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"162","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc0335ae4b0fc368eb53a80","contributors":{"authors":[{"text":"Olea, Ricardo A. 0000-0003-4308-0808","orcid":"https://orcid.org/0000-0003-4308-0808","contributorId":120616,"corporation":false,"usgs":true,"family":"Olea","given":"Ricardo A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":745594,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Luppens, James 0000-0001-7607-8750","orcid":"https://orcid.org/0000-0001-7607-8750","contributorId":208009,"corporation":false,"usgs":true,"family":"Luppens","given":"James","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":745595,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Egozcue, Juan J.","contributorId":208010,"corporation":false,"usgs":false,"family":"Egozcue","given":"Juan","email":"","middleInitial":"J.","affiliations":[{"id":37677,"text":"Dept. Civil and Environmental Engineering, Universitat Politècnica de Catalunya, Barcelona, Spain","active":true,"usgs":false}],"preferred":false,"id":745596,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pawlowsky-Glahn, Vera","contributorId":208011,"corporation":false,"usgs":false,"family":"Pawlowsky-Glahn","given":"Vera","email":"","affiliations":[{"id":37678,"text":"Dept. Informatics, Applied Matematics and Statistics, Universitat de Girona, Spain","active":true,"usgs":false}],"preferred":false,"id":745597,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70173839,"text":"70173839 - 2016 - Hydrogeochemistry and coal-associated bacterial populations from a methanogenic coal bed","interactions":[],"lastModifiedDate":"2016-06-22T16:22:34","indexId":"70173839","displayToPublicDate":"2016-05-15T05:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2033,"text":"International Journal of Coal Geology","active":true,"publicationSubtype":{"id":10}},"title":"Hydrogeochemistry and coal-associated bacterial populations from a methanogenic coal bed","docAbstract":"Biogenic coalbed methane (CBM), a microbially-generated source of natural gas trapped within coal beds, is an important energy resource in many countries. Specific bacterial populations and enzymes involved in coal degradation, the potential rate-limiting step of CBM formation, are relatively unknown. The U.S. Geological Survey (USGS) has established a field site, (Birney test site), in an undeveloped area of the Powder River Basin (PRB), with four wells completed in the Flowers-Goodale coal bed, one in the overlying sandstone formation, and four in overlying and underlying coal beds (Knoblach, Nance, and Terret). The nine wells were positioned to characterize the hydraulic conductivity of the Flowers-Goodale coal bed and were selectively cored to investigate the hydrogeochemistry and microbiology associated with CBM production at the Birney test site. Aquifer-test results indicated the Flowers-Goodale coal bed, in a zone from about 112 to 120 m below land surface at the test site, had very low hydraulic conductivity (0.005 m/d) compared to other PRB coal beds examined. Consistent with microbial methanogenesis, groundwater in the coal bed and overlying sandstone contain dissolved methane (46 mg/L average) with low δ13C values (−67‰ average), high alkalinity values (22 meq/kg average), relatively positive δ13C-DIC values (4‰ average), and no detectable higher chain hydrocarbons, NO3−, or SO42−. Bioassay methane production was greatest at the upper interface of the Flowers-Goodale coal bed near the overlying sandstone. Pyrotag analysis identified Aeribacillus as a dominant in situbacterial community member in the coal near the sandstone and statistical analysis indicated Actinobacteria predominated coal core samples compared to claystone or sandstone cores. These bacteria, which previously have been correlated with hydrocarbon-containing environments such as oil reservoirs, have demonstrated the ability to produce biosurfactants to break down hydrocarbons. Identifying microorganisms involved in coal degradation and the hydrogeochemical conditions that promote their activity is crucial to understanding and improving in situ CBM production.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2016.05.001","usgsCitation":"Barnhart, E.P., Weeks, E.P., Jones, E., Ritter, D.J., McIntosh, J.C., Clark, A.C., Ruppert, L.F., Cunningham, A.B., Vinson, D.S., Orem, W.H., and Fields, M.W., 2016, Hydrogeochemistry and coal-associated bacterial populations from a methanogenic coal bed: International Journal of Coal Geology, v. 162, p. 14-26, https://doi.org/10.1016/j.coal.2016.05.001.","productDescription":"13 p.","startPage":"14","endPage":"26","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071554","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":470997,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.coal.2016.05.001","text":"Publisher Index Page"},{"id":324277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, 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(Lopes, R.M.C. et al., 2010. Icarus, 205, 540–588), are vast expanses of terrains that appear radar-dark and fairly uniform in Cassini Synthetic Aperture Radar (SAR) images. As a result, these terrains are often referred to as “blandlands”. While the interpretation of several other geologic units on Titan – such as dunes, lakes, and well-preserved impact craters – has been relatively straightforward, the origin of the Undifferentiated Plains has remained elusive. SAR images show that these “blandlands” are mostly found at mid-latitudes and appear relatively featureless at radar wavelengths, with no major topographic features. Their gradational boundaries and paucity of recognizable features in SAR data make geologic interpretation particularly challenging. We have mapped the distribution of these terrains using SAR swaths up to flyby T92 (July 2013), which cover >50% of Titan’s surface. We compared SAR images with other data sets where available, including topography derived from the SARTopo method and stereo DEMs, the response from RADAR radiometry, hyperspectral imaging data from Cassini’s Visual and Infrared Mapping Spectrometer (VIMS), and near infrared imaging from the Imaging Science Subsystem (ISS). We examined and evaluated different formation mechanisms, including (i) cryovolcanic origin, consisting of overlapping flows of low relief or (ii) sedimentary origins, resulting from fluvial/lacustrine or aeolian deposition, or accumulation of photolysis products created in the atmosphere. Our analysis indicates that the Undifferentiated Plains unit is consistent with a composition predominantly containing organic rather than icy materials and formed by depositional and/or sedimentary processes. We conclude that aeolian processes played a major part in the formation of the Undifferentiated Plains; however, other processes (fluvial, deposition of photolysis products) are likely to have contributed, possibly in differing proportions depending on location.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2015.11.034","usgsCitation":"Lopes, R., Malaska, M., Solomonidou, A., Le, G.A., Janssen, M., Neish, C.D., Turtle, E.P., Birch, S.P., Hayes, A., Radebaugh, J., Coustenis, A., Schoenfeld, A., Stiles, B., Kirk, R.L., Mitchell, K.L., Stofan, E.R., Lawrence, K.J., and Cassini RADAR Team, 2016, Nature, distribution, and origin of Titan’s Undifferentiated Plains: Icarus, v. 270, p. 162-182, https://doi.org/10.1016/j.icarus.2015.11.034.","productDescription":"21 p.","startPage":"162","endPage":"182","ipdsId":"IP-079696","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":346096,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"270","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59cb6734e4b017cf3141c6a1","contributors":{"authors":[{"text":"Lopes, Rosaly","contributorId":50280,"corporation":false,"usgs":true,"family":"Lopes","given":"Rosaly","affiliations":[],"preferred":false,"id":711166,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Malaska, M. 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J.","affiliations":[],"preferred":false,"id":711167,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Solomonidou, A.","contributorId":196702,"corporation":false,"usgs":false,"family":"Solomonidou","given":"A.","email":"","affiliations":[],"preferred":false,"id":711168,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Le, Gall A.","contributorId":36764,"corporation":false,"usgs":true,"family":"Le","given":"Gall","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":711169,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Janssen, M.A.","contributorId":28345,"corporation":false,"usgs":true,"family":"Janssen","given":"M.A.","email":"","affiliations":[],"preferred":false,"id":711170,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Neish, Catherine D.","contributorId":13355,"corporation":false,"usgs":true,"family":"Neish","given":"Catherine","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":711171,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Turtle, E. P.","contributorId":44281,"corporation":false,"usgs":false,"family":"Turtle","given":"E.","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":711172,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Birch, S. P. D.","contributorId":196703,"corporation":false,"usgs":false,"family":"Birch","given":"S.","email":"","middleInitial":"P. D.","affiliations":[],"preferred":false,"id":711173,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hayes, A. G.","contributorId":31098,"corporation":false,"usgs":false,"family":"Hayes","given":"A. G.","affiliations":[],"preferred":false,"id":711174,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Radebaugh, J.","contributorId":34639,"corporation":false,"usgs":false,"family":"Radebaugh","given":"J.","affiliations":[],"preferred":false,"id":711175,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Coustenis, A.","contributorId":11398,"corporation":false,"usgs":true,"family":"Coustenis","given":"A.","email":"","affiliations":[],"preferred":false,"id":711176,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Schoenfeld, A.","contributorId":196704,"corporation":false,"usgs":false,"family":"Schoenfeld","given":"A.","email":"","affiliations":[],"preferred":false,"id":711177,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Stiles, B.W.","contributorId":43900,"corporation":false,"usgs":true,"family":"Stiles","given":"B.W.","email":"","affiliations":[],"preferred":false,"id":711178,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Kirk, Randolph L. 0000-0003-0842-9226 rkirk@usgs.gov","orcid":"https://orcid.org/0000-0003-0842-9226","contributorId":2765,"corporation":false,"usgs":true,"family":"Kirk","given":"Randolph","email":"rkirk@usgs.gov","middleInitial":"L.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":711179,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Mitchell, K. L.","contributorId":62734,"corporation":false,"usgs":false,"family":"Mitchell","given":"K.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":711180,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Stofan, E. R.","contributorId":103403,"corporation":false,"usgs":false,"family":"Stofan","given":"E.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":711181,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Lawrence, K. J.","contributorId":196705,"corporation":false,"usgs":false,"family":"Lawrence","given":"K.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":711182,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Cassini RADAR Team","contributorId":127942,"corporation":true,"usgs":false,"organization":"Cassini RADAR Team","id":711183,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70191098,"text":"70191098 - 2016 - The tectonics of Titan: Global structural mapping from Cassini RADAR","interactions":[],"lastModifiedDate":"2017-09-26T13:53:52","indexId":"70191098","displayToPublicDate":"2016-05-15T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"The tectonics of Titan: Global structural mapping from Cassini RADAR","docAbstract":"The Cassini RADAR mapper has imaged elevated mountain ridge belts on Titan with a linear-to-arcuate morphology indicative of a tectonic origin. Systematic geomorphologic mapping of the ridges in Synthetic Aperture RADAR (SAR) images reveals that the orientation of ridges is globally E–W and the ridges are more common near the equator than the poles. Comparison with a global topographic map reveals the equatorial ridges are found to lie preferentially at higher-than-average elevations. We conclude the most reasonable formation scenario for Titan’s ridges is that contractional tectonism built the ridges and thickened the icy lithosphere near the equator, causing regional uplift. The combination of global and regional tectonic events, likely contractional in nature, followed by erosion, aeolian activity, and enhanced sedimentation at mid-to-high latitudes, would have led to regional infilling and perhaps covering of some mountain features, thus shaping Titan’s tectonic landforms and surface morphology into what we see today.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2015.11.021","usgsCitation":"Liu, Z.Y., Radebaugh, J., Harris, R.A., Christiansen, E., Neish, C.D., Kirk, R.L., Lorenz, R.D., and Cassini RADAR Team, 2016, The tectonics of Titan: Global structural mapping from Cassini RADAR: Icarus, v. 270, p. 14-29, https://doi.org/10.1016/j.icarus.2015.11.021.","productDescription":"16 p.","startPage":"14","endPage":"29","ipdsId":"IP-079698","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":346098,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"270","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59cb6733e4b017cf3141c69a","contributors":{"authors":[{"text":"Liu, Zac Yung-Chun","contributorId":196708,"corporation":false,"usgs":false,"family":"Liu","given":"Zac","email":"","middleInitial":"Yung-Chun","affiliations":[],"preferred":false,"id":711192,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Radebaugh, Jani","contributorId":101792,"corporation":false,"usgs":true,"family":"Radebaugh","given":"Jani","email":"","affiliations":[],"preferred":false,"id":711193,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harris, Ron A.","contributorId":196709,"corporation":false,"usgs":false,"family":"Harris","given":"Ron","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":711194,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Christiansen, Eric H.","contributorId":71175,"corporation":false,"usgs":true,"family":"Christiansen","given":"Eric H.","affiliations":[],"preferred":false,"id":711195,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Neish, Catherine D.","contributorId":13355,"corporation":false,"usgs":true,"family":"Neish","given":"Catherine","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":711196,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kirk, Randolph L. 0000-0003-0842-9226 rkirk@usgs.gov","orcid":"https://orcid.org/0000-0003-0842-9226","contributorId":2765,"corporation":false,"usgs":true,"family":"Kirk","given":"Randolph","email":"rkirk@usgs.gov","middleInitial":"L.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":711197,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lorenz, Ralph D.","contributorId":56360,"corporation":false,"usgs":false,"family":"Lorenz","given":"Ralph","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":711198,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cassini RADAR Team","contributorId":127942,"corporation":true,"usgs":false,"organization":"Cassini RADAR Team","id":711199,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70191097,"text":"70191097 - 2016 - Fluvial erosion as a mechanism for crater modification on Titan","interactions":[],"lastModifiedDate":"2017-09-26T13:48:41","indexId":"70191097","displayToPublicDate":"2016-05-15T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"Fluvial erosion as a mechanism for crater modification on Titan","docAbstract":"There are few identifiable impact craters on Titan, especially in the polar regions. One explanation for this observation is that the craters are being destroyed through fluvial processes, such as weathering, mass wasting, fluvial incision and deposition. In this work, we use a landscape evolution model to determine whether or not this is a viable mechanism for crater destruction on Titan. We find that fluvial degradation can modify craters to the point where they would be unrecognizable by an orbiting spacecraft such as Cassini, given enough time and a large enough erosion rate. A difference in the erosion rate between the equator and the poles of a factor of a few could explain the latitudinal variation in Titan’s crater population. Fluvial erosion also removes central peaks and fills in central pits, possibly explaining their infrequent occurrence in Titan craters. Although many craters on Titan appear to be modified by aeolian infilling, fluvial modification is necessary to explain the observed impact crater morphologies. Thus, it is an important secondary modification process even in Titan’s drier equatorial regions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2015.07.022","usgsCitation":"Neish, C.D., Molaro, J.L., Lora, J.M., Howard, A., Kirk, R.L., Schenk, P., Bray, V., and Lorenz, R.D., 2016, Fluvial erosion as a mechanism for crater modification on Titan: Icarus, v. 270, p. 114-129, https://doi.org/10.1016/j.icarus.2015.07.022.","productDescription":"16 p.","startPage":"114","endPage":"129","ipdsId":"IP-079697","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":346097,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"270","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59cb6733e4b017cf3141c69e","contributors":{"authors":[{"text":"Neish, Catherine D.","contributorId":13355,"corporation":false,"usgs":true,"family":"Neish","given":"Catherine","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":711184,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Molaro, J. L.","contributorId":196706,"corporation":false,"usgs":false,"family":"Molaro","given":"J.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":711185,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lora, J. M.","contributorId":196707,"corporation":false,"usgs":false,"family":"Lora","given":"J.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":711186,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Howard, A.D.","contributorId":95538,"corporation":false,"usgs":true,"family":"Howard","given":"A.D.","email":"","affiliations":[],"preferred":false,"id":711187,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kirk, Randolph L. 0000-0003-0842-9226 rkirk@usgs.gov","orcid":"https://orcid.org/0000-0003-0842-9226","contributorId":2765,"corporation":false,"usgs":true,"family":"Kirk","given":"Randolph","email":"rkirk@usgs.gov","middleInitial":"L.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":711188,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schenk, P.","contributorId":105484,"corporation":false,"usgs":true,"family":"Schenk","given":"P.","affiliations":[],"preferred":false,"id":711189,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bray, V.J.","contributorId":72692,"corporation":false,"usgs":true,"family":"Bray","given":"V.J.","email":"","affiliations":[],"preferred":false,"id":711190,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lorenz, R. D.","contributorId":90441,"corporation":false,"usgs":false,"family":"Lorenz","given":"R.","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":711191,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70173799,"text":"70173799 - 2016 - Quantifying resilience","interactions":[],"lastModifiedDate":"2016-06-22T16:04:36","indexId":"70173799","displayToPublicDate":"2016-05-14T02:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying resilience","docAbstract":"The biosphere is under unprecedented pressure, reflected in rapid changes in our global ecological, social, technological and economic systems. In many cases, ecological and social systems can adapt to these changes over time, but when a critical threshold is surpassed, a system under stress can undergo catastrophic change and reorganize into a different state. The concept of resilience, introduced more than 40 years ago in the ecological sciences, captures the behaviour of systems that can occur in alternative states. The original definition of resilience forwarded by Holling (1973) is still the most useful. It defines resilience as the amount of disturbance that a system can withstand before it shifts into an alternative stable state. The idea of alternative stable states has clear and profound implications for ecological management. Coral reefs, for example, are high-diversity systems that provide key ecosystem services such as fisheries and coastal protection. Human impacts are causing significant, ongoing reef degradation, and many reefs have shifted from coral- to algal-dominated states in response to anthropogenic pressures such as elevated water temperatures and overfishing. Understanding and differentiating between the factors that help maintain reefs in coral-dominated states vs. those that facilitate a shift to an undesired algal-dominated state is a critical step towards sound management and conservation of these, and other, important social–ecological systems.
\nResilience has gained popularity among both academicians and laypeople, as a term meant to describe a systems’ ability to withstand disturbance. Resilience has become a buzzword in the last decade, as shown by its increasing appearance in calls for research proposals and scientific citation data bases. The term resilience has in many cases lost the clarity of the original definition and in fact is frequently used in a manner in direct opposition to the original definition. Many current uses of the concept are loose and incorrect. The term is becoming increasingly used in a normative sense (Brand & Jax 2007), as if resilience were a desirable quality of systems. However, even systems in highly undesirable states, such as macro-algae dominated reefs, or city cores in poverty traps, may be highly resilient, which is to say they withstand attempts to transform them into different (desirable) states.
\nOperationalizing the concept of resilience for application and management has been difficult. Misuse of the term can have significant negative impacts, because resilience is being used to help guide responses to natural disasters and to assess the sustainability of ecosystems and urban systems and has been driving international research priorities. Resilience has been argued to be a basic emergent property of systems, a process or a rate. We focus on the original concept as described by Holling, which is that of an emergent system property; when a system is in a desirable state and managers wish to enhance resilience, or when the system is in an undesirable state and managers wish to erode resilience and foster a transformation to an alternative state. Fostering or eroding resilience is a process. When a system is perturbed but resilience is not exceeded, then the recovery can be measured as a rate.
\nSeveral frameworks to operationalize resilience have been proposed. A decade ago, a special feature focused on quantifying resilience was published in the journal Ecosystems (Carpenter, Westley & Turner 2005). The approach there was towards identifying surrogates of resilience, but few of the papers proposed quantifiable metrics. Consequently, many ecological resilience frameworks remain vague and difficult to quantify, a problem that this special feature aims to address. However, considerable progress has been made during the last decade (e.g. Pope, Allen & Angeler 2014). Although some argue that resilience is best kept as an unquantifiable, vague concept (Quinlan et al. 2016), to be useful for managers, there must be concrete guidance regarding how and what to manage and how to measure success (Garmestani, Allen & Benson 2013; Spears et al. 2015). Ideas such as ‘resilience thinking’ have utility in helping stakeholders conceptualize their systems, but provide little guidance on how to make resilience useful for ecosystem management, other than suggesting an ambiguous, Goldilocks approach of being just right (e.g. diverse, but not too diverse; connected, but not too connected). Here, we clarify some prominent resilience terms and concepts, introduce and synthesize the papers in this special feature on quantifying resilience and identify core unanswered questions related to resilience.
","language":"English","publisher":"British Ecological Society","publisherLocation":"London, United Kingdom","doi":"10.1111/1365-2664.12649","usgsCitation":"Allen, C.R., and Angeler, D., 2016, Quantifying resilience: Journal of Applied Ecology, v. 53, p. 617-624, https://doi.org/10.1111/1365-2664.12649.","productDescription":"8 p.","startPage":"617","endPage":"624","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071794","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470999,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.12649","text":"Publisher Index Page"},{"id":324270,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-13","publicationStatus":"PW","scienceBaseUri":"576bb6bae4b07657d1a22941","contributors":{"authors":[{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":638379,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Angeler, David G.","contributorId":25027,"corporation":false,"usgs":true,"family":"Angeler","given":"David G.","affiliations":[],"preferred":false,"id":640495,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70176281,"text":"70176281 - 2016 - Decadal-scale export of nitrogen, phosphorus, and sediment from the Susquehanna River basin, USA: Analysis and synthesis of temporal and spatial patterns","interactions":[],"lastModifiedDate":"2016-09-07T12:00:19","indexId":"70176281","displayToPublicDate":"2016-05-14T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Decadal-scale export of nitrogen, phosphorus, and sediment from the Susquehanna River basin, USA: Analysis and synthesis of temporal and spatial patterns","docAbstract":"The export of nitrogen (N), phosphorus (P), and suspended sediment (SS) is a long-standing management concern for the Chesapeake Bay watershed, USA. Here we present a comprehensive evaluation of nutrient and sediment loads over the last three decades at multiple locations in the Susquehanna River basin (SRB), Chesapeake's largest tributary watershed. Sediment and nutrient riverine loadings, including both dissolved and particulate fractions, have generally declined at all sites upstream of Conowingo Dam (non-tidal SRB outlet). Period-of-record declines in riverine yield are generally smaller than those in source input, suggesting the possibility of legacy contributions. Consistent with other watershed studies, these results reinforce the importance of considering lag time between the implementation of management actions and achievement of river quality improvement. Whereas flow-normalized loadings for particulate species have increased recently below Conowingo Reservoir, those for upstream sites have declined, thus substantiating conclusions from prior studies about decreased reservoir trapping efficiency. In regard to streamflow effects, statistically significant log-linear relationships between annual streamflow and annual constituent load suggest the dominance of hydrological control on the inter-annual variability of constituent export. Concentration-discharge relationships revealed general chemostasis and mobilization effects for dissolved and particulate species, respectively, both suggesting transport-limitation conditions. In addition to affecting annual export rates, streamflow has also modulated the relative importance of dissolved and particulate fractions, as reflected by its negative correlations with dissolved P/total P, dissolved N/total N, particulate P/SS, and total N/total P ratios. For land-use effects, period-of-record median annual yields of N, P, and SS all correlate positively with the area fraction of non-forested land but negatively with that of forested land under all hydrological conditions. Overall, this work has informed understanding with respect to four major factors affecting constituent export (i.e., source input, reservoir modulation, streamflow, and land use) and demonstrated the value of long-term river monitoring.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.03.104","usgsCitation":"Zhang, Q., Ball, W.P., and Moyer, D.L., 2016, Decadal-scale export of nitrogen, phosphorus, and sediment from the Susquehanna River basin, USA: Analysis and synthesis of temporal and spatial patterns: Science of the Total Environment, v. 563-564, p. 1016-1029, https://doi.org/10.1016/j.scitotenv.2016.03.104.","productDescription":"14 p.","startPage":"1016","endPage":"1029","ipdsId":"IP-070367","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":471000,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.03.104","text":"Publisher Index Page"},{"id":328310,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, New York, Pennsylvania","otherGeospatial":"Chesapeake Bay, Susquehanna River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.51953125,\n 39.30029918615029\n ],\n [\n -77.51953125,\n 42.309815415686664\n ],\n [\n -75.73974609375,\n 42.309815415686664\n ],\n [\n -75.73974609375,\n 39.30029918615029\n ],\n [\n -77.51953125,\n 39.30029918615029\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"563-564","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57d13a39e4b0571647cf8dbb","contributors":{"authors":[{"text":"Zhang, Qian 0000-0003-0500-5655","orcid":"https://orcid.org/0000-0003-0500-5655","contributorId":174393,"corporation":false,"usgs":false,"family":"Zhang","given":"Qian","email":"","affiliations":[{"id":38802,"text":"University of Maryland Center for Environmental Studies","active":true,"usgs":false}],"preferred":false,"id":648192,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ball, William P.","contributorId":174394,"corporation":false,"usgs":false,"family":"Ball","given":"William","email":"","middleInitial":"P.","affiliations":[{"id":27446,"text":"Johns Hopkins University, Department of Geography and Environmental Engineering","active":true,"usgs":false}],"preferred":false,"id":648193,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moyer, Douglas L. 0000-0001-6330-478X dlmoyer@usgs.gov","orcid":"https://orcid.org/0000-0001-6330-478X","contributorId":174389,"corporation":false,"usgs":true,"family":"Moyer","given":"Douglas","email":"dlmoyer@usgs.gov","middleInitial":"L.","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":648191,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70170966,"text":"70170966 - 2016 - Modeled effects of soil acidification on long-term ecological and economic outcomes for managed forests in the Adirondack region (USA)","interactions":[],"lastModifiedDate":"2016-05-13T13:39:46","indexId":"70170966","displayToPublicDate":"2016-05-13T14:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Modeled effects of soil acidification on long-term ecological and economic outcomes for managed forests in the Adirondack region (USA)","docAbstract":"Sugar maple (Acer saccharum) is among the most ecologically and economically important tree species in North America, and its growth and regeneration is often the focus of silvicultural practices in northern hardwood forests. A key stressor for sugar maple (SM) is acid rain, which depletes base cations from poorly-buffered forest soils and has been associated with much lower SM vigor, growth, and recruitment. However, the potential interactions between forest management and soil acidification – and their implications for the sustainability of SM and its economic and cultural benefits – have not been investigated. In this study, we simulated the development of 50 extant SM stands in the western Adirondack region of NY (USA) for 100 years under different soil chemical conditions and silvicultural prescriptions. We found that interactions between management prescription and soil base saturation will strongly shape the ability to maintain SM in managed forests. Below 12% base saturation, SM did not regenerate sufficiently after harvest and was replaced mainly by red maple (Acer rubrum) and American beech (Fagus grandifolia). Loss of SM on acid-impaired sites was predicted regardless of whether the shelterwood or diameter-limit prescriptions were used. On soils with sufficient base saturation, models predicted that SM will regenerate after harvest and be sustained for future rotations. We then estimated how these different post-harvest outcomes, mediated by acid impairment of forest soils, would affect the potential monetary value of ecosystem services provided by SM forests. Model simulations indicated that a management strategy focused on syrup production – although not feasible across the vast areas where acid impairment has occurred – may generate the greatest economic return. Although pollution from acid rain is declining, its long-term legacy in forest soils will shape future options for sustainable forestry and ecosystem stewardship in the northern hardwood forests of North America.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.scitotenv.2016.04.008","collaboration":"New York State Energy Research and Development Authority; USGS","usgsCitation":"Caputo, J., Beier, C.M., Sullivan, T.J., and Lawrence, G.B., 2016, Modeled effects of soil acidification on long-term ecological and economic outcomes for managed forests in the Adirondack region (USA): Science of the Total Environment, v. 565, p. 401-411, https://doi.org/10.1016/j.scitotenv.2016.04.008.","productDescription":"11 p.","startPage":"401","endPage":"411","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073095","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":471002,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.04.008","text":"Publisher Index 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directing road restoration","docAbstract":"Unpaved forest roads remain a pervasive disturbance on public lands and mitigating sediment from road networks remains a priority for management agencies. Restoring roaded landscapes is becoming increasingly important for many native coldwater fishes that disproportionately rely on public lands for persistence. However, effectively targeting restoration opportunities requires a comprehensive understanding of the effects of roads across different ecosystems. Here, we combine a review and a field study to evaluate the status of knowledge supporting the conceptual framework linking unpaved forest roads with streambed sediment. Through our review, we specifically focused on those studies linking measures of the density of forest roads or sediment delivery with empirical streambed sediment measures. Our field study provides an example of a targeted effort of linking spatially explicit estimates of sediment production with measures of streambed sediment. Surprisingly, our review uncovered few studies (n = 8) that empirically tested the conceptual framework linking unpaved forest roads and streambed sediment, and the results varied considerably. Field results generally supported the conceptual model that unpaved forest roads can control streambed sediment quality, but demonstrated high-spatial variability in the effects of forest roads on streambed sediment and the need to address hotspots of sediment sources. The importance of context in the effects of forest roads is apparent in both our review and field data, suggesting the need for in situ studies to avoid misdirected restoration actions.
","language":"English","publisher":"Wiley","doi":"10.1111/rec.12365","collaboration":"USDA Forest Service, The Wilderness Society, Clearwater Resource Council","usgsCitation":"Al-Chokhachy, R.K., Black, T.A., Thomas, C., Luce, C.H., Rieman, B., Cissel, R., Carlson, A., Hendrickson, S., Archer, E.K., and Kershner, J.L., 2016, Linkages between unpaved forest roads and streambed sediment: why context matters in directing road restoration: Restoration Ecology, v. 24, no. 5, p. 589-598, https://doi.org/10.1111/rec.12365.","productDescription":"10 p.","startPage":"589","endPage":"598","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072870","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":326140,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Pacific Northwest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n 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Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"992","title":"Long-term trends in naturalized rainbow trout (Oncorhynchus mykiss) populations in the upper Esopus Creek, Ulster County, New York, 2009–15","docAbstract":"The U.S. Geological Survey, in cooperation with Cornell Cooperative Extension of Ulster County, New York State Energy Research and Development Authority, the New York State Department of Environmental Conservation, and the New York City Department of Environmental Protection, surveyed fish communities annually on the main stem and tributaries of the upper Esopus Creek, Ulster County, New York, from 2009 to 2015. This report summarizes the density, biomass, and size structure of rainbow trout (Oncorhynchus mykiss) and brown trout (Salmo trutta) populations from the 2015 surveys along with data from the preceding 6 years. The mean density of rainbow trout populations in 2015 was 98 fish per 0.1 hectare, which was the highest value observed since 2010, and the mean biomass of rainbow trout populations in 2015 was 864 grams per 0.1 hectare, which was the highest value observed since 2012.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds992","collaboration":"Prepared in cooperation with Cornell Cooperative Extension of Ulster County, New York State Energy Research and Development Authority, the New York State Department of Environmental Conservation, and the New York City Department of Environmental Protection","usgsCitation":"George, S.D., and Baldigo, B.P., 2016, Long-term trends in naturalized rainbow trout (Oncorhynchus mykiss) populations in the upper Esopus Creek, Ulster County, New York, 2009–15: U.S. Geological Survey Data Series 992, 12 p., https://dx.doi.org/10.3133/ds992.","productDescription":"iv, 12 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070172","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":321177,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0992/coverthb.jpg"},{"id":321178,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0992/ds992.pdf","text":"Report","size":"6.49 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 992"}],"country":"United States","state":"New York","county":"Ulster County","otherGeospatial":"Upper Esopus Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.566667,\n 42.216667\n ],\n [\n -74.566667,\n 41.916667\n ],\n [\n -74.066667,\n 41.916667\n ],\n [\n -74.066667,\n 42.216667\n ],\n [\n -74.566667,\n 42.216667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180-8349
Information requests:
(518) 285-5602
Or visit our Web site at:
http://ny.water.usgs.gov
The distribution of the Lesser Prairie-Chicken (Tympanuchus pallidicinctus) has been markedly reduced due to loss and fragmentation of habitat. Portions of the historical range, however, have been recolonized and even expanded due to planting of conservation reserve program (CRP) fields that provide favorable vegetation structure for Lesser Prairie-Chickens. The source population(s) feeding the range expansion is unknown, yet has resulted in overlap between Lesser and Greater Prairie-Chickens (T. cupido) increasing the potential for hybridization. Our objectives were to characterize connectivity and genetic diversity among populations, identify source population(s) of recent range expansion, and examine hybridization with the Greater Prairie-Chicken. We analyzed 640 samples from across the range using 13 microsatellites. We identified three to four populations corresponding largely to ecoregions. The Shinnery Oak Prairie and Sand Sagebrush Prairie represented genetically distinct populations (F ST > 0.034 and F ST > 0.023 respectively). The Shortgrass/CRP Mosaic and Mixed Grass ecoregions appeared admixed (F ST = 0.009). Genetic diversity was similar among ecoregions and N e ranged from 142 (95 % CI 99–236) for the Shortgrass/CRP Mosaic to 296 (95 % CI 233–396) in the Mixed Grass Prairie. No recent migration was detected among ecoregions, except asymmetric dispersal from both the Mixed Grass Prairie and to a lesser extent the Sand Sagebrush Prairie north into adjacent Shortgrass/CRP Mosaic (m = 0.207, 95 % CI 0.116–0.298, m = 0.097, 95 % CI 0.010–0.183, respectively). Indices investigating potential hybridization in the Shortgrass/CRP Mosaic revealed that six of the 13 individuals with hybrid phenotypes were significantly admixed suggesting hybridization. Continued monitoring of diversity within and among ecoregions is warranted as are actions promoting genetic connectivity and range expansion.
","language":"English","publisher":"Springer","doi":"10.1007/s10592-016-0812-y","usgsCitation":"Oyler-McCance, S.J., DeYoung, R.W., Fike, J.A., Hagen, C.A., Johnson, J., Larsson, L.C., and Patten, M., 2016, Rangewide genetic analysis of Lesser Prairie-Chicken reveals population structure, range expansion, and possible introgression: Conservation Genetics, v. 17, no. 3, p. 643-660, https://doi.org/10.1007/s10592-016-0812-y.","productDescription":"18 p.","startPage":"643","endPage":"660","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067088","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":321173,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Kansas, New Mexico, Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.150390625,\n 34.77771580360469\n ],\n [\n -102.3486328125,\n 34.77771580360469\n ],\n [\n -102.3486328125,\n 38.41055825094609\n ],\n [\n -104.150390625,\n 38.41055825094609\n ],\n [\n -104.150390625,\n 34.77771580360469\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"17","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-01-28","publicationStatus":"PW","scienceBaseUri":"57359b1ce4b0dae0d5dee77d","chorus":{"doi":"10.1007/s10592-016-0812-y","url":"http://dx.doi.org/10.1007/s10592-016-0812-y","publisher":"Springer Nature","authors":"Oyler-McCance Sara J., DeYoung Randall W., Fike Jennifer A., Hagen Christian A., Johnson Jeff A., Larsson Lena C., Patten Michael A.","journalName":"Conservation Genetics","publicationDate":"1/28/2016","auditedOn":"7/29/2016","publiclyAccessibleDate":"1/28/2016"},"contributors":{"authors":[{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":629196,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeYoung, Randall W","contributorId":169285,"corporation":false,"usgs":false,"family":"DeYoung","given":"Randall","email":"","middleInitial":"W","affiliations":[{"id":25464,"text":"2Department of Animal, Rangeland, and Wildlife Sciences, Texas A&M University-Kingsville","active":true,"usgs":false}],"preferred":false,"id":629197,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fike, Jennifer A. 0000-0001-8797-7823 fikej@usgs.gov","orcid":"https://orcid.org/0000-0001-8797-7823","contributorId":140875,"corporation":false,"usgs":true,"family":"Fike","given":"Jennifer","email":"fikej@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":629198,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hagen, Christian A.","contributorId":107574,"corporation":false,"usgs":true,"family":"Hagen","given":"Christian","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":629199,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Jeff A.","contributorId":107208,"corporation":false,"usgs":true,"family":"Johnson","given":"Jeff A.","affiliations":[],"preferred":false,"id":629200,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Larsson, Lena C.","contributorId":169286,"corporation":false,"usgs":false,"family":"Larsson","given":"Lena","email":"","middleInitial":"C.","affiliations":[{"id":7062,"text":"University of Oklahoma","active":true,"usgs":false}],"preferred":false,"id":629201,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Patten, Michael","contributorId":169287,"corporation":false,"usgs":false,"family":"Patten","given":"Michael","email":"","affiliations":[{"id":7062,"text":"University of Oklahoma","active":true,"usgs":false}],"preferred":false,"id":629202,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70170756,"text":"70170756 - 2016 - Reply to comments by Riley and Dunlop on He et al. (2015)","interactions":[],"lastModifiedDate":"2016-05-12T10:13:47","indexId":"70170756","displayToPublicDate":"2016-05-12T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Reply to comments by Riley and Dunlop on He et al. (2015)","docAbstract":"He et al. (2015) described piscivory patterns in the main basin of Lake Huron 1984-2010, during which there was also a pattern of stepwise declines in the abundance of dominant prey fish species. The approach of He et al. (2015) was to couple age-structured stock assessment and fish bioenergetics models to estimate prey fish consumption, and to compare these patterns with prey fish biomass from a bottom trawl survey. Riley and Dunlop (2015) were highly critical of the methods and conclusions reached by He et al. (2015). They claimed that we incorrectly interpreted the bottom trawl survey data, and did not account for uncertainty. We respond to these and other criticisms below, which we find do not undermine our findings.
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