{"pageNumber":"125","pageRowStart":"3100","pageSize":"25","recordCount":10457,"records":[{"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":"<p><span>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,&nbsp;</span><i>Cirsium arvense</i><span>&nbsp;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&nbsp;</span><i>C</i><span>.&nbsp;</span><i>arvense</i><span>) 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&nbsp;</span><i>C</i><span>.&nbsp;</span><i>arvense</i><span>&nbsp;flowering period. Two other abundantly-flowering invasive plants were present during this time:&nbsp;</span><i>Melilotus officinalis</i><span>&nbsp;had highly variable floral abundance in both&nbsp;</span><i>C</i><span>.&nbsp;</span><i>arvense-</i><span>infested and non-infested plots and</span><i>Convolvulus arvensis</i><span>, 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&nbsp;</span><i>C</i><span>.&nbsp;</span><i>arvense</i><span>and 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&nbsp;</span><i>C</i><span>.</span><i>arvense</i><span>.&nbsp;</span><i>C</i><span>onnectors typically did not reside within the same modules as&nbsp;</span><i>C</i><span>.&nbsp;</span><i>arvense</i><span>, 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.</span></p>","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":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":"<p><span>Seasonal (spring freshet, summer&ndash;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&ndash;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&ndash;74% of the total DOM. Carboxyl-rich alicyclic molecules (CRAM) accounted for the majority of carbon atoms in the HPOA (63&ndash;77%) and TPIA (54&ndash;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 (OC</span><sub>np</sub><span>, OC</span><sub>np</sub><span>O and C</span><sub>q</sub><span>, 13&ndash;17% of HPOA and 15&ndash;20% of TPIA) and isolated O&ndash;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 (&lt;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 (&sim;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&ndash;O and O&ndash;C&ndash;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.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2016.02.029","usgsCitation":"Cao, X., Aiken, G.R., Spencer, R., Butler, K.D., Mao, J., and Schmidt-Rohr, K., 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: Geochimica et Cosmochimica Acta, v. 181, p. 72-88, https://doi.org/10.1016/j.gca.2016.02.029.","productDescription":"16 p.","startPage":"72","endPage":"88","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073317","costCenters":[{"id":5044,"text":"National Research 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M.","contributorId":139731,"corporation":false,"usgs":false,"family":"Spencer","given":"Robert G. M.","affiliations":[{"id":12894,"text":"Department of Land, Air, and Water Resources, University of California, One Shields Avenue, Davis, CA, 95616, USA","active":true,"usgs":false}],"preferred":false,"id":646349,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Butler, Kenna D. kebutler@usgs.gov","contributorId":3283,"corporation":false,"usgs":true,"family":"Butler","given":"Kenna","email":"kebutler@usgs.gov","middleInitial":"D.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":646350,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mao, Jingdong","contributorId":79373,"corporation":false,"usgs":true,"family":"Mao","given":"Jingdong","affiliations":[],"preferred":false,"id":646351,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schmidt-Rohr, Klaus","contributorId":173865,"corporation":false,"usgs":false,"family":"Schmidt-Rohr","given":"Klaus","email":"","affiliations":[{"id":27307,"text":"Dept. of Chemistry, Brandeis University, Waltham, MA","active":true,"usgs":false}],"preferred":false,"id":646352,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70199499,"text":"70199499 - 2016 - Calorific value and compositional ultimate analysis with a case study of a Texas lignite","interactions":[],"lastModifiedDate":"2018-09-20T10:52:43","indexId":"70199499","displayToPublicDate":"2016-05-15T10:52:21","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":"Calorific value and compositional ultimate analysis with a case study of a Texas lignite","docAbstract":"<p><span>Measurements to determine&nbsp;coal&nbsp;quality as fuel include proximate analysis, ultimate analysis and calorific value. The latter is an attribute taking non-negative real values, so a simple transformation is sufficient for its&nbsp;spatial modeling&nbsp;applying&nbsp;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.</span><sup>1</sup><span>&nbsp;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&nbsp;coal bed&nbsp;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.</span></p>","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":"<p><span>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&nbsp;m below land surface at the test site, had very low hydraulic conductivity (0.005&nbsp;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&nbsp;mg/L average) with low&nbsp;</span><i>&delta;</i><sup>13</sup><span>C values (&minus;67&permil; average), high alkalinity values (22&nbsp;meq/kg average), relatively positive&nbsp;</span><i>&delta;</i><sup>13</sup><span>C-DIC values (4&permil; average), and no detectable higher chain hydrocarbons, NO</span><sub>3</sub><sup>&minus;</sup><sub>,</sub><span>&nbsp;or SO</span><sub>4</sub><sup>2&minus;</sup><span>. Bioassay methane production was greatest at the upper interface of the Flowers-Goodale coal bed near the overlying sandstone. Pyrotag analysis identified&nbsp;</span><i>Aeribacillus</i><span>&nbsp;as a dominant&nbsp;</span><i>in situ</i><span>bacterial community member in the coal near the sandstone and statistical analysis indicated&nbsp;</span><i>Actinobacteria</i><span>&nbsp;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&nbsp;</span><i>in situ</i><span>&nbsp;CBM production.</span></p>","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 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J.","contributorId":139869,"corporation":false,"usgs":false,"family":"Ritter","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":13301,"text":"Department of Hydrology and Water Resources, University of Arizona, Tucson, Arizona","active":true,"usgs":false}],"preferred":false,"id":640508,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McIntosh, Jennifer C. 0000-0001-5055-4202","orcid":"https://orcid.org/0000-0001-5055-4202","contributorId":150557,"corporation":false,"usgs":false,"family":"McIntosh","given":"Jennifer","email":"","middleInitial":"C.","affiliations":[{"id":6624,"text":"University of Arizona, Laboratory of Tree-Ring Research","active":true,"usgs":false}],"preferred":false,"id":640509,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Clark, Arthur C. aclark@usgs.gov","contributorId":2320,"corporation":false,"usgs":true,"family":"Clark","given":"Arthur","email":"aclark@usgs.gov","middleInitial":"C.","affiliations":[],"preferred":true,"id":640510,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ruppert, Leslie F. 0000-0002-7453-1061 lruppert@usgs.gov","orcid":"https://orcid.org/0000-0002-7453-1061","contributorId":660,"corporation":false,"usgs":true,"family":"Ruppert","given":"Leslie","email":"lruppert@usgs.gov","middleInitial":"F.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":640511,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cunningham, Alfred B.","contributorId":172389,"corporation":false,"usgs":false,"family":"Cunningham","given":"Alfred","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":640512,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Vinson, David S.","contributorId":172390,"corporation":false,"usgs":false,"family":"Vinson","given":"David","email":"","middleInitial":"S.","affiliations":[{"id":25392,"text":"Department of Geography and Earth Science, University of North Carolina at Charlotte, North Carolina, USA","active":true,"usgs":false}],"preferred":false,"id":640513,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Orem, William H. 0000-0003-4990-0539 borem@usgs.gov","orcid":"https://orcid.org/0000-0003-4990-0539","contributorId":577,"corporation":false,"usgs":true,"family":"Orem","given":"William","email":"borem@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":640514,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Fields, Matthew W.","contributorId":172391,"corporation":false,"usgs":false,"family":"Fields","given":"Matthew","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":640515,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"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":"<p><span>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.</span></p>","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":70170931,"text":"70170931 - 2016 - The effects of large beach debris on nesting sea turtles","interactions":[],"lastModifiedDate":"2016-07-17T23:03:58","indexId":"70170931","displayToPublicDate":"2016-05-11T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2277,"text":"Journal of Experimental Marine Biology and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"The effects of large beach debris on nesting sea turtles","docAbstract":"<p><span>A field experiment was conducted to understand the effects of large beach debris on sea turtle nesting behavior as well as the effectiveness of large debris removal for habitat restoration. Large natural and anthropogenic debris were removed from one of three sections of a sea turtle nesting beach and distributions of nests and false crawls (non-nesting crawls) in pre- (2011&ndash;2012) and post- (2013&ndash;2014) removal years in the three sections were compared. The number of nests increased 200% and the number of false crawls increased 55% in the experimental section, whereas a corresponding increase in number of nests and false crawls was not observed in the other two sections where debris removal was not conducted. The proportion of nest and false crawl abundance in all three beach sections was significantly different between pre- and post-removal years. The nesting success, the percent of successful nests in total nesting attempts (number of nests&nbsp;+&nbsp;false crawls), also increased from 24% to 38%; however the magnitude of the increase was comparably small because both the number of nests and false crawls increased, and thus the proportion of the nesting success in the experimental beach in pre- and post-removal years was not significantly different. The substantial increase in sea turtle nesting activities after the removal of large debris indicates that large debris may have an adverse impact on sea turtle nesting behavior. Removal of large debris could be an effective restoration strategy to improve sea turtle nesting.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jembe.2016.04.005","usgsCitation":"Fujisaki, I., and Lamont, M.M., 2016, The effects of large beach debris on nesting sea turtles: Journal of Experimental Marine Biology and Ecology, v. 482, p. 33-37, https://doi.org/10.1016/j.jembe.2016.04.005.","productDescription":"5 p.","startPage":"33","endPage":"37","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070631","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471010,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jembe.2016.04.005","text":"Publisher Index Page"},{"id":321117,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"482","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5734499de4b0dae0d5dd6911","contributors":{"authors":[{"text":"Fujisaki, Ikuko","contributorId":38359,"corporation":false,"usgs":false,"family":"Fujisaki","given":"Ikuko","affiliations":[],"preferred":false,"id":629141,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lamont, Margaret M. 0000-0001-7520-6669 mlamont@usgs.gov","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":4525,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","email":"mlamont@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":629140,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70170932,"text":"70170932 - 2016 - Three-dimensional flow structure and patterns of bed shear stress in an evolving compound meander bend","interactions":[],"lastModifiedDate":"2016-07-07T10:04:44","indexId":"70170932","displayToPublicDate":"2016-05-11T11:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Three-dimensional flow structure and patterns of bed shear stress in an evolving compound meander bend","docAbstract":"<p><span>Compound meander bends with multiple lobes of maximum curvature are common in actively evolving lowland rivers. Interaction among spatial patterns of mean flow, turbulence, bed morphology, bank failures and channel migration in compound bends is poorly understood. In this paper, acoustic Doppler current profiler (ADCP) measurements of the three-dimensional (3D) flow velocities in a compound bend are examined to evaluate the influence of channel curvature and hydrologic variability on the structure of flow within the bend. Flow structure at various flow stages is related to changes in bed morphology over the study timeframe. Increases in local curvature within the upstream lobe of the bend reduce outer bank velocities at morphologically significant flows, creating a region that protects the bank from high momentum flow and high bed shear stresses. The dimensionless radius of curvature in the upstream lobe is one-third less than that of the downstream lobe, with average bank erosion rates less than half of the erosion rates for the downstream lobe. Higher bank erosion rates within the downstream lobe correspond to the shift in a core of high velocity and bed shear stresses toward the outer bank as flow moves through the two lobes. These erosion patterns provide a mechanism for continued migration of the downstream lobe in the near future. Bed material size distributions within the bend correspond to spatial patterns of bed shear stress magnitudes, indicating that bed material sorting within the bend is governed by bed shear stress. Results suggest that patterns of flow, sediment entrainment, and planform evolution in compound meander bends are more complex than in simple meander bends. Moreover, interactions among local influences on the flow, such as woody debris, local topographic steering, and locally high curvature, tend to cause compound bends to evolve toward increasing planform complexity over time rather than stable configurations.</span></p>","language":"English","publisher":"John Wiley & Sons","doi":"10.1002/esp.3895","usgsCitation":"Engel, F.L., and Rhoads, B.L., 2016, Three-dimensional flow structure and patterns of bed shear stress in an evolving compound meander bend: Earth Surface Processes and Landforms, v. 41, no. 9, p. 1211-1226, https://doi.org/10.1002/esp.3895.","productDescription":"16 p.","startPage":"1211","endPage":"1226","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059802","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":321116,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"9","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-15","publicationStatus":"PW","scienceBaseUri":"5734499ee4b0dae0d5dd691b","contributors":{"authors":[{"text":"Engel, Frank L. 0000-0002-4253-2625 fengel@usgs.gov","orcid":"https://orcid.org/0000-0002-4253-2625","contributorId":5463,"corporation":false,"usgs":true,"family":"Engel","given":"Frank","email":"fengel@usgs.gov","middleInitial":"L.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629142,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rhoads, Bruce L.","contributorId":20248,"corporation":false,"usgs":true,"family":"Rhoads","given":"Bruce","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":629143,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70170899,"text":"70170899 - 2016 - Regional-scale controls on dissolved nitrous oxide in the Upper Mississippi River","interactions":[],"lastModifiedDate":"2016-06-02T11:14:56","indexId":"70170899","displayToPublicDate":"2016-05-11T11:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Regional-scale controls on dissolved nitrous oxide in the Upper Mississippi River","docAbstract":"<p>The U.S. Corn Belt is one of the most intensive agricultural regions of the world and is drained by the Upper Mississippi River (UMR), which forms one of the largest drainage basins in the U.S. While the effects of agricultural nitrate (NO<sub>3</sub><sup>-</sup>) on water quality in the UMR have been well documented, its impact on the production of nitrous oxide (N<sub>2</sub>O) has not been reported. Using a novel equilibration technique, we present the largest data set of freshwater dissolved N<sub>2</sub>O concentrations (0.7 to 6 times saturation) and examine the controls on its variability over a 350 km reach of the UMR. Driven by a supersaturated water column, the UMR was an important atmospheric N<sub>2</sub>O source (+68 mg N<sub>2</sub>ONm<sup>-2</sup> yr<sup>-1</sup>) that varies nonlinearly with the NO<sub>3</sub><sup>-</sup>concentration. Our analyses indicated that a projected doubling of the NO<sub>3</sub><sup>-</sup>concentration by 2050 would cause dissolved N<sub>2</sub>O concentrations and emissions to increase by about 40%.</p>","language":"English","publisher":"AGU Publications","doi":"10.1002/2016GL068710","usgsCitation":"Turner, P., Griffis, T., Baker, J., Lee, X., Crawford, J.T., Loken, L., and Venterea, R., 2016, Regional-scale controls on dissolved nitrous oxide in the Upper Mississippi River: Geophysical Research Letters, v. 43, no. 9, p. 4400-4407, https://doi.org/10.1002/2016GL068710.","productDescription":"8 p.","startPage":"4400","endPage":"4407","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071258","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":471012,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gl068710","text":"Publisher Index Page"},{"id":321112,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Upper Mississippi River","volume":"43","issue":"9","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-06","publicationStatus":"PW","scienceBaseUri":"5734499ce4b0dae0d5dd6903","contributors":{"authors":[{"text":"Turner, P.A.","contributorId":169214,"corporation":false,"usgs":false,"family":"Turner","given":"P.A.","email":"","affiliations":[{"id":25441,"text":"University of Minnesota, Department of Soil, Water and Climate","active":true,"usgs":false}],"preferred":false,"id":628997,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Griffis, T.J.","contributorId":169215,"corporation":false,"usgs":false,"family":"Griffis","given":"T.J.","email":"","affiliations":[{"id":25442,"text":"U.S. Department of Agriculture - Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":628998,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baker, J.M.","contributorId":169216,"corporation":false,"usgs":false,"family":"Baker","given":"J.M.","email":"","affiliations":[{"id":25443,"text":"Yale University, School of Forestry and Environmental Studies","active":true,"usgs":false}],"preferred":false,"id":628999,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lee, X.","contributorId":169217,"corporation":false,"usgs":false,"family":"Lee","given":"X.","email":"","affiliations":[{"id":25444,"text":"Yale-Nanjing University of Information, Science and Technology","active":true,"usgs":false}],"preferred":false,"id":629000,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Crawford, John T. 0000-0003-4440-6945 jtcrawford@usgs.gov","orcid":"https://orcid.org/0000-0003-4440-6945","contributorId":4081,"corporation":false,"usgs":true,"family":"Crawford","given":"John","email":"jtcrawford@usgs.gov","middleInitial":"T.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":628996,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Loken, Luke C. lloken@usgs.gov","contributorId":169218,"corporation":false,"usgs":true,"family":"Loken","given":"Luke C.","email":"lloken@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":629001,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Venterea, R.T.","contributorId":53994,"corporation":false,"usgs":true,"family":"Venterea","given":"R.T.","email":"","affiliations":[],"preferred":false,"id":629002,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70170904,"text":"70170904 - 2016 - Persistent and novel threats to the biodiversity of Kazakhstan’s steppes and semi-deserts","interactions":[],"lastModifiedDate":"2017-11-22T17:29:34","indexId":"70170904","displayToPublicDate":"2016-05-10T13:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1006,"text":"Biodiversity and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Persistent and novel threats to the biodiversity of Kazakhstan’s steppes and semi-deserts","docAbstract":"<p><span>Temperate grasslands have suffered disproportionally from conversion to cropland, degradation and fragmentation. A large proportion of the world&rsquo;s remaining near-natural grassland is situated in Kazakhstan. We aimed to assess current and emerging threats to steppe and semi-desert biodiversity in Kazakhstan and evaluate conservation research priorities. We conducted a horizon-scanning exercise among conservationists from academia and practice. We first compiled a list of 45 potential threats. These were then ranked by the survey participants according to their perceived severity, the need for research on them, and their novelty. The highest-ranked threats were related to changes in land use (leading to habitat loss and deterioration), direct persecution of wildlife, and rapid infrastructure development due to economic and population growth. Research needs were identified largely in the same areas, and the mean scores of threat severity and research need were highly correlated. Novel threats comprised habitat loss by photovoltaic and wind power stations, climate change and changes in agriculture such as the introduction of biofuels. However, novelty was not correlated with threat severity or research priority, suggesting that the most severe threats are the established ones. Important goals towards more effective steppe and semi-desert conservation in Kazakhstan include more cross-sector collaboration (e.g. by involving stakeholders in conservation and agriculture), greater allocation of funds to under-staffed areas (e.g. protected area management), better representativeness and complementarity in the protected area system and enhanced data collection for wildlife monitoring and threat assessments (including the use of citizen-science databases).</span></p>","language":"English","publisher":"SpringerLink","doi":"10.1007/s10531-016-1083-0","usgsCitation":"Kamp, J., Koshkin, M.A., Bragina, T.M., Katzner, T., Milner-Gulland, E., Schreiber, D., Sheldon, R., Shmalenko, A., Smelansky, I., Terraube, J., and Urazaliev, R., 2016, Persistent and novel threats to the biodiversity of Kazakhstan’s steppes and semi-deserts: Biodiversity and Conservation, v. 25, no. 12, p. 2521-2541, https://doi.org/10.1007/s10531-016-1083-0.","productDescription":"22 p.","startPage":"2521","endPage":"2541","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072885","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":471015,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://ora.ox.ac.uk/objects/uuid:52eb1886-2ef5-4c70-bf17-b0a616f99a04","text":"External Repository"},{"id":321092,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Kazakhstan","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              47.02148437499999,\n              40.88029480552824\n            ],\n            [\n              47.02148437499999,\n              55.25407706707272\n            ],\n            [\n              85.7373046875,\n              55.25407706707272\n            ],\n            [\n              85.7373046875,\n              40.88029480552824\n            ],\n            [\n              47.02148437499999,\n              40.88029480552824\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"25","issue":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-19","publicationStatus":"PW","scienceBaseUri":"5732f820e4b0dae0d5dc6443","contributors":{"authors":[{"text":"Kamp, Johannes","contributorId":169223,"corporation":false,"usgs":false,"family":"Kamp","given":"Johannes","email":"","affiliations":[{"id":25445,"text":"University of Münster","active":true,"usgs":false}],"preferred":false,"id":629012,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Koshkin, Maxim A","contributorId":169224,"corporation":false,"usgs":false,"family":"Koshkin","given":"Maxim","email":"","middleInitial":"A","affiliations":[{"id":16617,"text":"University of East Anglia","active":true,"usgs":false}],"preferred":false,"id":629013,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bragina, Tatyana M","contributorId":169225,"corporation":false,"usgs":false,"family":"Bragina","given":"Tatyana","email":"","middleInitial":"M","affiliations":[{"id":25446,"text":"Kostanai State University","active":true,"usgs":false}],"preferred":false,"id":629014,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":629011,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Milner-Gulland, E. 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,{"id":70170913,"text":"70170913 - 2016 - Not all droughts are created equal: The impacts of interannual drought pattern and magnitude on grassland carbon cycling","interactions":[],"lastModifiedDate":"2016-05-10T12:00:19","indexId":"70170913","displayToPublicDate":"2016-05-10T13:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Not all droughts are created equal: The impacts of interannual drought pattern and magnitude on grassland carbon cycling","docAbstract":"<p><span>Climate extremes, such as drought, may have immediate and potentially prolonged effects on carbon cycling. Grasslands store approximately one-third of all terrestrial carbon and may become carbon sources during droughts. However, the magnitude and duration of drought-induced disruptions to the carbon cycle, as well as the mechanisms responsible, remain poorly understood. Over the next century, global climate models predict an increase in two types of drought: chronic but subtle &lsquo;press-droughts&rsquo;, and shorter term but extreme &lsquo;pulse-droughts&rsquo;. Much of our current understanding of the ecological impacts of drought comes from experimental rainfall manipulations. These studies have been highly valuable, but are often short term and rarely quantify carbon feedbacks. To address this knowledge gap, we used the Community Land Model 4.0 to examine the individual and interactive effects of pulse- and press-droughts on carbon cycling in a mesic grassland of the US Great Plains. A series of modeling experiments were imposed by varying drought magnitude (precipitation amount) and interannual pattern (press- vs. pulse-droughts) to examine the effects on carbon storage and cycling at annual to century timescales. We present three main findings. First, a single-year pulse-drought had immediate and prolonged effects on carbon storage due to differential sensitivities of ecosystem respiration and gross primary production. Second, short-term pulse-droughts caused greater carbon loss than chronic press-droughts when total precipitation reductions over a 20-year period were equivalent. Third, combining pulse- and press-droughts had intermediate effects on carbon loss compared to the independent drought types, except at high drought levels. Overall, these results suggest that interannual drought pattern may be as important for carbon dynamics as drought magnitude and that extreme droughts may have long-lasting carbon feedbacks in grassland ecosystems.</span></p>","language":"English","publisher":"John Wiley & Sons","doi":"10.1111/gcb.13161","usgsCitation":"Hoover, D.L., and Rogers, B.M., 2016, Not all droughts are created equal: The impacts of interannual drought pattern and magnitude on grassland carbon cycling: Global Change Biology, v. 22, no. 5, p. 1809-1820, https://doi.org/10.1111/gcb.13161.","productDescription":"12 p.","startPage":"1809","endPage":"1820","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066574","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":321090,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-25","publicationStatus":"PW","scienceBaseUri":"5732f81ee4b0dae0d5dc643f","contributors":{"authors":[{"text":"Hoover, David L. dlhoover@usgs.gov","contributorId":5843,"corporation":false,"usgs":true,"family":"Hoover","given":"David","email":"dlhoover@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":629058,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rogers, Brendan M.","contributorId":169247,"corporation":false,"usgs":false,"family":"Rogers","given":"Brendan","email":"","middleInitial":"M.","affiliations":[{"id":25456,"text":"Woods Hole Research Center, Falmouth, MA, United States","active":true,"usgs":false}],"preferred":false,"id":629059,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70170799,"text":"70170799 - 2016 - Contamination with bacterial zoonotic pathogen genes in U.S. streams influenced by varying types of animal agriculture","interactions":[],"lastModifiedDate":"2018-09-12T17:04:25","indexId":"70170799","displayToPublicDate":"2016-05-05T11:45:00","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":"Contamination with bacterial zoonotic pathogen genes in U.S. streams influenced by varying types of animal agriculture","docAbstract":"<p><span>Animal waste, stream water, and streambed sediment from 19 small (&lt;&nbsp;32&nbsp;km</span><sup>2</sup><span>) watersheds in 12&nbsp;U.S. states having either no major animal agriculture (control, </span><i>n</i><span>&nbsp;=&nbsp;4), or predominantly beef (</span><i>n</i><span>&nbsp;=&nbsp;4), dairy (</span><i>n</i><span>&nbsp;=&nbsp;3), swine (</span><i>n</i><span>&nbsp;=&nbsp;5), or poultry (</span><i>n</i><span>&nbsp;=&nbsp;3) were tested for: 1) cholesterol, coprostanol, estrone, and fecal indicator bacteria (FIB) concentrations, and 2) shiga-toxin producing and enterotoxigenic </span><i>Escherichia coli</i><span>, </span><i>Salmonella</i><span>, </span><i>Campylobacter</i><span>, and pathogenic and vancomycin-resistant enterococci by polymerase chain reaction (PCR) on enrichments, and/or direct quantitative PCR. Pathogen genes were most frequently detected in dairy wastes, followed by beef, swine and poultry wastes in that order; there was only one detection of an animal-source-specific pathogen gene (</span><i>stx1</i><span>) in any water or sediment sample in any control watershed. Post-rainfall pathogen gene numbers in stream water were significantly correlated with FIB, cholesterol and coprostanol concentrations, and were most highly correlated in dairy watershed samples collected from 3 different states. Although collected across multiple states and ecoregions, animal-waste gene profiles were distinctive via discriminant analysis. Stream water gene profiles could also be discriminated by the watershed animal type. Although pathogen genes were not abundant in stream water or streambed samples, PCR on enrichments indicated that many genes were from viable organisms, including several (shiga-toxin producing or enterotoxigenic </span><i>E. coli</i><span>, </span><i>Salmonella</i><span>, vancomycin-resistant enterococci) that could potentially affect either human or animal health. Pathogen gene numbers and types in stream water samples were influenced most by animal type, by local factors such as whether animals had stream access, and by the amount of local rainfall, and not by studied watershed soil or physical characteristics. Our results indicated that stream water in small agricultural U.S. watersheds was susceptible to pathogen gene inputs under typical agricultural practices and environmental conditions. Pathogen gene profiles may offer the potential to address both source of, and risks associated with, fecal pollution.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.04.087","usgsCitation":"Haack, S.K., Duris, J., Kolpin, D.W., Focazio, M.J., Meyer, M.T., Johnson, H., Oster, R.J., and Foreman, W., 2016, Contamination with bacterial zoonotic pathogen genes in U.S. streams influenced by varying types of animal agriculture: Science of the Total Environment, v. 563-564, p. 340-350, https://doi.org/10.1016/j.scitotenv.2016.04.087.","productDescription":"11 p.","startPage":"340","endPage":"350","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059123","costCenters":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology 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,{"id":70178255,"text":"70178255 - 2016 - Mapping rice-fallow cropland areas for short-season grain legumes intensification in South Asia using MODIS 250 m time-series data","interactions":[],"lastModifiedDate":"2016-11-09T15:29:43","indexId":"70178255","displayToPublicDate":"2016-05-04T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2035,"text":"International Journal of Digital Earth","active":true,"publicationSubtype":{"id":10}},"title":"Mapping rice-fallow cropland areas for short-season grain legumes intensification in South Asia using MODIS 250 m time-series data","docAbstract":"<p>The goal of this study was to map rainfed and irrigated <i>rice-fallow</i> cropland areas across South Asia, using MODIS 250 m time-series data and identify where the farming system may be intensified by the inclusion of a short-season crop during the fallow period. <i>Rice-fallow</i> cropland areas are those areas where rice is grown during the <i>kharif</i> growing season (June–October), followed by a fallow during the <i>rabi</i> season (November–February). These cropland areas are not suitable for growing <i>rabi</i>-season rice due to their high water needs, but are suitable for a short -season (≤3 months), low water-consuming grain legumes such as chickpea (<i>Cicer arietinum</i> L.), black gram, green gram, and lentils. Intensification (double-cropping) in this manner can improve smallholder farmer’s incomes and soil health via rich nitrogen-fixation legume crops as well as address food security challenges of ballooning populations without having to expand croplands. Several grain legumes, primarily chickpea, are increasingly grown across Asia as a source of income for smallholder farmers and at the same time providing rich and cheap source of protein that can improve the nutritional quality of diets in the region. The suitability of rainfed and irrigated <i>rice-fallow</i> croplands for grain legume cultivation across South Asia were defined by these identifiers: (a) rice crop is grown during the primary (<i>kharif</i>) crop growing season or during the north-west monsoon season (June–October); (b) same croplands are left <i>fallow</i> during the second (<i>rabi</i>) season or during the south-east monsoon season (November–February); and (c) ability to support low water-consuming, short-growing season (≤3 months) grain legumes (chickpea, black gram, green gram, and lentils) during <i>rabi</i> season. Existing irrigated or rainfed crops such as rice or wheat that were grown during <i>kharif</i> were not considered suitable for growing during the <i>rabi</i> season, because the moisture/water demand of these crops is too high. The study established cropland classes based on the every 16-day 250 m normalized difference vegetation index (NDVI) time series for one year (June 2010–May 2011) of Moderate Resolution Imaging Spectroradiometer (MODIS) data, using spectral matching techniques (SMTs), and extensive field knowledge. Map accuracy was evaluated based on independent ground survey data as well as compared with available sub-national level statistics. The producers’ and users’ accuracies of the cropland fallow classes were between 75% and 82%. The overall accuracy and the kappa coefficient estimated for rice classes were 82% and 0.79, respectively. The analysis estimated approximately 22.3 Mha of suitable <i>rice-fallow</i> areas in South Asia, with 88.3% in India, 0.5% in Pakistan, 1.1% in Sri Lanka, 8.7% in Bangladesh, 1.4% in Nepal, and 0.02% in Bhutan. Decision-makers can target these areas for sustainable intensification of short-duration grain legumes.</p>","language":"English","doi":"10.1080/17538947.2016.1168489","usgsCitation":"Gumma, M., Thenkabail, P.S., Teluguntla, P.G., Rao, M.N., Mohammed, I., and Whitbread, A.M., 2016, Mapping rice-fallow cropland areas for short-season grain legumes intensification in South Asia using MODIS 250 m time-series data: International Journal of Digital Earth, v. 9, no. 10, p. 981-1003, https://doi.org/10.1080/17538947.2016.1168489.","productDescription":"23 p.","startPage":"981","endPage":"1003","ipdsId":"IP-070335","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":471026,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/17538947.2016.1168489","text":"Publisher Index Page"},{"id":330906,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Bangladesh, Bhutan, India, Nepal, Pakistan, Sri Lanka","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              83.97949218750001,\n              15.284185114076433\n            ],\n            [\n              82.3095703125,\n              11.996338401936226\n            ],\n            [\n              83.32031250000001,\n              7.754537346539373\n            ],\n            [\n              81.78222656250001,\n              5.266007882805485\n            ],\n            [\n              79.365234375,\n              5.747174076651375\n            ],\n            [\n              76.81640625,\n              7.406047717076271\n            ],\n            [\n              72.59765625,\n              12.382928338487396\n            ],\n            [\n              66.4013671875,\n              25.64152637306577\n            ],\n            [\n              80.4638671875,\n              29.11377539511439\n            ],\n            [\n              95.61523437500003,\n              30.34192736497245\n            ],\n            [\n              91.62597656250001,\n              20.67390526467282\n            ],\n            [\n              83.97949218750001,\n              15.284185114076433\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"9","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-04","publicationStatus":"PW","scienceBaseUri":"582443f5e4b09065cdf30528","contributors":{"authors":[{"text":"Gumma, Murali Krishna","contributorId":50426,"corporation":false,"usgs":true,"family":"Gumma","given":"Murali Krishna","affiliations":[],"preferred":false,"id":653404,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thenkabail, Prasad S. 0000-0002-2182-8822 pthenkabail@usgs.gov","orcid":"https://orcid.org/0000-0002-2182-8822","contributorId":570,"corporation":false,"usgs":true,"family":"Thenkabail","given":"Prasad","email":"pthenkabail@usgs.gov","middleInitial":"S.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":653405,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Teluguntla, Pardhasaradhi G. 0000-0001-8060-9841 pteluguntla@usgs.gov","orcid":"https://orcid.org/0000-0001-8060-9841","contributorId":5275,"corporation":false,"usgs":true,"family":"Teluguntla","given":"Pardhasaradhi","email":"pteluguntla@usgs.gov","middleInitial":"G.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":653406,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rao, Mahesh N.","contributorId":127588,"corporation":false,"usgs":false,"family":"Rao","given":"Mahesh","email":"","middleInitial":"N.","affiliations":[{"id":7067,"text":"Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":653407,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mohammed, Irshad A.","contributorId":176755,"corporation":false,"usgs":false,"family":"Mohammed","given":"Irshad A.","affiliations":[{"id":7069,"text":"International Crops Research Institute for the Semi Arid Tropics (ICRISAT)","active":true,"usgs":false}],"preferred":false,"id":653408,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Whitbread, Anthony M.","contributorId":176756,"corporation":false,"usgs":false,"family":"Whitbread","given":"Anthony","email":"","middleInitial":"M.","affiliations":[{"id":7069,"text":"International Crops Research Institute for the Semi Arid Tropics (ICRISAT)","active":true,"usgs":false}],"preferred":false,"id":653409,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70209271,"text":"70209271 - 2016 - Practical bias correction in aerial surveys of large mammals: Validation of hybrid double-observer with sightability method against known abundance of feral horse (Equus caballus) populations","interactions":[],"lastModifiedDate":"2020-03-26T11:47:16","indexId":"70209271","displayToPublicDate":"2016-05-03T11:31:24","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}},"displayTitle":"Practical bias correction in aerial surveys of large mammals: Validation of hybrid double-observer with sightability method against known abundance of feral horse (<i>Equus caballus</i>) populations","title":"Practical bias correction in aerial surveys of large mammals: Validation of hybrid double-observer with sightability method against known abundance of feral horse (Equus caballus) populations","docAbstract":"<p><span>Reliably estimating wildlife abundance is fundamental to effective management. Aerial surveys are one of the only spatially robust tools for estimating large mammal populations, but statistical sampling methods are required to address detection biases that affect accuracy and precision of the estimates. Although various methods for correcting aerial survey bias are employed on large mammal species around the world, these have rarely been rigorously validated. Several populations of feral horses (</span><i>Equus caballus</i><span>) in the western United States have been intensively studied, resulting in identification of all unique individuals. This provided a rare opportunity to test aerial survey bias correction on populations of known abundance. We hypothesized that a hybrid method combining simultaneous double-observer and sightability bias correction techniques would accurately estimate abundance. We validated this integrated technique on populations of known size and also on a pair of surveys before and after a known number was removed. Our analysis identified several covariates across the surveys that explained and corrected biases in the estimates. All six tests on known populations produced estimates with deviations from the known value ranging from -8.5% to +13.7% and &lt;0.7 standard errors. Precision varied widely, from 6.1% CV to 25.0% CV. In contrast, the pair of surveys conducted around a known management removal produced an estimated change in population between the surveys that was significantly larger than the known reduction. Although the deviation between was only 9.1%, the precision estimate (CV = 1.6%) may have been artificially low. It was apparent that use of a helicopter in those surveys perturbed the horses, introducing detection error and heterogeneity in a manner that could not be corrected by our statistical models. Our results validate the hybrid method, highlight its potentially broad applicability, identify some limitations, and provide insight and guidance for improving survey designs.</span></p>","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0154902","usgsCitation":"Lubow, B., and Ransom, J.I., 2016, Practical bias correction in aerial surveys of large mammals: Validation of hybrid double-observer with sightability method against known abundance of feral horse (Equus caballus) populations: PLoS ONE, v. 11, no. 5, e0154902, 15 p., https://doi.org/10.1371/journal.pone.0154902.","productDescription":"e0154902, 15 p.","ipdsId":"IP-074372","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":471028,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0154902","text":"Publisher Index Page"},{"id":373550,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Nevada, Utah, Wyoming","otherGeospatial":"Cedar Mountain Herd Management Area,  Little Owyhee Herd Management Area, McCullough Peaks Herd Management Area, Sand Wash Herd Management Area, Snowstorm Mountains Herd Management Area ","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -109.00634765625,\n              44.308126684886126\n            ],\n            [\n              -107.89672851562499,\n              44.308126684886126\n            ],\n            [\n              -107.89672851562499,\n              44.98034238084973\n            ],\n            [\n              -109.00634765625,\n              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State University","active":true,"usgs":false}],"preferred":false,"id":785656,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ransom, Jason I.","contributorId":139841,"corporation":false,"usgs":false,"family":"Ransom","given":"Jason","email":"","middleInitial":"I.","affiliations":[{"id":6924,"text":"National Park Service, Upper Columbia Basin Network","active":true,"usgs":false}],"preferred":false,"id":785657,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70170957,"text":"70170957 - 2016 - Challenges for mapping cyanotoxin patterns from remote sensing of cyanobacteria","interactions":[],"lastModifiedDate":"2018-08-09T12:12:53","indexId":"70170957","displayToPublicDate":"2016-04-30T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1878,"text":"Harmful Algae","active":true,"publicationSubtype":{"id":10}},"title":"Challenges for mapping cyanotoxin patterns from remote sensing of cyanobacteria","docAbstract":"<p><span>Using satellite imagery to quantify the spatial patterns of cyanobacterial toxins has several challenges. These challenges include the need for surrogate pigments &ndash; since cyanotoxins cannot be directly detected by remote sensing, the variability in the relationship between the pigments and cyanotoxins &ndash; especially microcystins (MC), and the lack of standardization of the various measurement methods. A dual-model strategy can provide an approach to address these challenges. One model uses either chlorophyll</span><i>-a</i><span>&nbsp;(Chl</span><i>-a</i><span>) or phycocyanin (PC) collected&nbsp;</span><i>in situ</i><span>&nbsp;as a surrogate to estimate the MC concentration. The other uses a remote sensing algorithm to estimate the concentration of the surrogate pigment. Where blooms are mixtures of cyanobacteria and eukaryotic algae, PC should be the preferred surrogate to Chl</span><i>-a</i><span>. Where cyanobacteria dominate, Chl</span><i>-a</i><span>&nbsp;is a better surrogate than PC for remote sensing. Phycocyanin is less sensitive to detection by optical remote sensing, it is less frequently measured, PC laboratory methods are still not standardized, and PC has greater intracellular variability. Either pigment should not be presumed to have a fixed relationship with MC for any water body. The MC-pigment relationship can be valid over weeks, but have considerable intra- and inter-annual variability due to changes in the amount of MC produced relative to cyanobacterial biomass. To detect pigments by satellite, three classes of algorithms (analytic, semi-analytic, and derivative) have been used. Analytical and semi-analytical algorithms are more sensitive but less robust than derivatives because they depend on accurate atmospheric correction; as a result derivatives are more commonly used. Derivatives can estimate Chl</span><i>-a</i><span>&nbsp;concentration, and research suggests they can detect and possibly quantify PC. Derivative algorithms, however, need to be standardized in order to evaluate the reproducibility of parameterizations between lakes. A strategy for producing useful estimates of microcystins from cyanobacterial biomass is described, provided cyanotoxin variability is addressed.</span></p>","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.hal.2016.01.005","usgsCitation":"Stumpf, R.P., Davis, T.W., Wynne, T.T., Graham, J., Loftin, K.A., Johengen, T., Gossiaux, D., Palladino, D., and Burtner, A., 2016, Challenges for mapping cyanotoxin patterns from remote sensing of cyanobacteria: Harmful Algae, v. 54, p. 160-173, https://doi.org/10.1016/j.hal.2016.01.005.","productDescription":"14 p.","startPage":"160","endPage":"173","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070534","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":471038,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.hal.2016.01.005","text":"Publisher Index Page"},{"id":321204,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"54","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5736faade4b0dae0d5e03bf4","contributors":{"authors":[{"text":"Stumpf, Rick P","contributorId":169288,"corporation":false,"usgs":false,"family":"Stumpf","given":"Rick","email":"","middleInitial":"P","affiliations":[{"id":6637,"text":"National Oceanic and Atmospheric Administration, Northwest Fisheries Science Center, 2725 Montlake Blvd E, Seattle, WA 98112","active":true,"usgs":false}],"preferred":false,"id":629218,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davis, Timothy W.","contributorId":169289,"corporation":false,"usgs":false,"family":"Davis","given":"Timothy","email":"","middleInitial":"W.","affiliations":[{"id":6637,"text":"National Oceanic and Atmospheric Administration, Northwest Fisheries Science Center, 2725 Montlake Blvd E, Seattle, WA 98112","active":true,"usgs":false}],"preferred":false,"id":629219,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wynne, Timothy T.","contributorId":169290,"corporation":false,"usgs":false,"family":"Wynne","given":"Timothy","email":"","middleInitial":"T.","affiliations":[{"id":6637,"text":"National Oceanic and Atmospheric Administration, Northwest Fisheries Science Center, 2725 Montlake Blvd E, Seattle, WA 98112","active":true,"usgs":false}],"preferred":false,"id":629220,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Graham, Jennifer L. 0000-0002-6420-9335 jlgraham@usgs.gov","orcid":"https://orcid.org/0000-0002-6420-9335","contributorId":150737,"corporation":false,"usgs":true,"family":"Graham","given":"Jennifer L.","email":"jlgraham@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":629217,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loftin, Keith A. 0000-0001-5291-876X kloftin@usgs.gov","orcid":"https://orcid.org/0000-0001-5291-876X","contributorId":868,"corporation":false,"usgs":true,"family":"Loftin","given":"Keith","email":"kloftin@usgs.gov","middleInitial":"A.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":629221,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johengen, T.H.","contributorId":169291,"corporation":false,"usgs":false,"family":"Johengen","given":"T.H.","affiliations":[{"id":25465,"text":"Cooperative Institute for Limnology and Ecosystem Research","active":true,"usgs":false}],"preferred":false,"id":629222,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gossiaux, D.","contributorId":169292,"corporation":false,"usgs":false,"family":"Gossiaux","given":"D.","affiliations":[{"id":25466,"text":"National Oceanic and Atmostpheric Administration","active":true,"usgs":false}],"preferred":false,"id":629223,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Palladino, D.","contributorId":169293,"corporation":false,"usgs":false,"family":"Palladino","given":"D.","email":"","affiliations":[{"id":25465,"text":"Cooperative Institute for Limnology and Ecosystem Research","active":true,"usgs":false}],"preferred":false,"id":629224,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Burtner, A.","contributorId":169294,"corporation":false,"usgs":false,"family":"Burtner","given":"A.","email":"","affiliations":[{"id":25465,"text":"Cooperative Institute for Limnology and Ecosystem Research","active":true,"usgs":false}],"preferred":false,"id":629225,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70170560,"text":"70170560 - 2016 - Fluctuating water depths affect American alligator (<i>Alligator mississippiensis</i>) body condition in the Everglades, Florida, USA","interactions":[],"lastModifiedDate":"2016-07-11T15:40:41","indexId":"70170560","displayToPublicDate":"2016-04-27T10:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Fluctuating water depths affect American alligator (<i>Alligator mississippiensis</i>) body condition in the Everglades, Florida, USA","docAbstract":"<p>Successful restoration of wetland ecosystems requires knowledge of wetland hydrologic patterns and an understanding of how those patterns affect wetland plant and animal populations.Within the Everglades, Florida, USA restoration, an applied science strategy including conceptual ecological models linking drivers to indicators is being used to organize current scientific understanding to support restoration efforts. A key driver of the ecosystem affecting the distribution and abundance of organisms is the timing, distribution, and volume of water flows that result in water depth patterns across the landscape. American alligators (Alligator mississippiensis) are one of the ecological indicators being used to assess Everglades restoration because they are a keystone species and integrate biological impacts of hydrological operations through all life stages. Alligator body condition (the relative fatness of an animal) is one of the metrics being used and targets have been set to allow us to track progress. We examined trends in alligator body condition using Fulton&rsquo;s K over a 15 year period (2000&ndash;2014) at seven different wetland areas within the Everglades ecosystem, assessed patterns and trends relative to restoration targets, and related those trends to hydrologic variables. We developed a series of 17 a priori hypotheses that we tested with an information theoretic approach to identify which hydrologic factors affect alligator body condition. Alligator body condition was highest throughout the Everglades during the early 2000s and is approximately 5&ndash;10% lower now (2014). Values have varied by year, area, and hydrology. Body condition was positively correlated with range in water depth and fall water depth. Our top model was the &ldquo;Current&rdquo; model and included variables that describe current year hydrology (spring depth, fall depth, hydroperiod, range, interaction of range and fall depth, interaction of range and hydroperiod). Across all models, interaction between range and fall water depth was the most important variable (relative weight of 1.0) followed by spring and fall water depths (0.99), range (0.96), hydroperiod (0.95) and interaction between range and hydroperiod (0.95). Our work provides additional evidence that restoring a greater range in annual water depths is important for improvement of alligator body condition and ecosystem function. This information can be incorporated into both planning and operations to assist in reaching Everglades restoration goals.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2016.03.003","usgsCitation":"Brandt, L., Beauchamp, J.S., Jeffery, B.M., Cherkiss, M.S., and Mazzotti, F., 2016, Fluctuating water depths affect American alligator (<i>Alligator mississippiensis</i>) body condition in the Everglades, Florida, USA: Ecological Indicators, v. 67, p. 441-450, https://doi.org/10.1016/j.ecolind.2016.03.003.","productDescription":"10 p.","startPage":"441","endPage":"450","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069792","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471046,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2016.03.003","text":"Publisher Index 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,{"id":70171475,"text":"70171475 - 2016 - Longitudinal evaluation of leukocyte transcripts in killer whales (<i>Orcinus Orca</i>)","interactions":[],"lastModifiedDate":"2016-06-01T15:27:21","indexId":"70171475","displayToPublicDate":"2016-04-27T01:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3682,"text":"Veterinary Immunology and Immunopathology","active":true,"publicationSubtype":{"id":10}},"title":"Longitudinal evaluation of leukocyte transcripts in killer whales (<i>Orcinus Orca</i>)","docAbstract":"<p><span>Early identification of illness and/or presence of environmental and/or social stressors in free-ranging and domestic cetaceans is a priority for marine mammal health care professionals. Incorporation of leukocyte gene transcript analysis into the diagnostic tool kit has the potential to augment classical diagnostics based upon ease of sample storage and shipment, inducible nature and well-defined roles of transcription and associated downstream actions. Development of biomarkers that could serve to identify &ldquo;insults&rdquo; and potentially differentiate disease etiology would be of great diagnostic value. To this end, a modest number of peripheral blood leukocyte gene transcripts were selected for application to a domestic killer whale population with a focus on broad representation of inducible immunologically relevant genes. Normalized leukocyte transcript values, longitudinally acquired from 232 blood samples derived from 26 clinically healthy whales, were not visibly influenced temporally nor by sex or the specific Park in which they resided. Stability in leukocyte transcript number during periods of health enhances their potential use in diagnostics through identification of outliers. Transcript levels of two cytokine genes, IL-4 and IL-17, were highly variable within the group as compared to the other transcripts. IL-4 transcripts were typically absent. Analysis of transcript levels on the other genes of interest, on an individual animal basis, identified more outliers than were visible when analyzed in the context of the entire population. The majority of outliers (9 samples) were low, though elevated transcripts were identified for IL-17 from 2 animals and one each for Cox-2 and IL-10. The low number of outliers was not unexpected as sample selection was intentionally directed towards animals that were clinically healthy at the time of collection. Outliers may reflect animals experiencing subclinical disease that is transient and self-limiting. The immunologic knowledge derived from longitudinal immunologic studies in killer whales, as was the target of the present study, has the potential to improve diagnostics and health related decision making for this and other domestic and free-ranging cetacean species.</span></p>","language":"English","publisher":"Science Direct","doi":"10.1016/j.vetimm.2016.04.011","usgsCitation":"Sitt, T., Bowen, L., Lee, C., Blanchard, M., McBain, J., Dold, C., and Stott, J.L., 2016, Longitudinal evaluation of leukocyte transcripts in killer whales (<i>Orcinus Orca</i>): Veterinary Immunology and Immunopathology, v. 175, p. 7-15, https://doi.org/10.1016/j.vetimm.2016.04.011.","productDescription":"8 p.","startPage":"7","endPage":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-076179","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":322042,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"175","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57500769e4b0ee97d51bb677","contributors":{"authors":[{"text":"Sitt, Tatjana","contributorId":169842,"corporation":false,"usgs":false,"family":"Sitt","given":"Tatjana","email":"","affiliations":[{"id":25601,"text":"Dep't Animal and Vet Sciences, UVM, Burlington, VT","active":true,"usgs":false}],"preferred":false,"id":631232,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bowen, Lizabeth 0000-0001-9115-4336 lbowen@usgs.gov","orcid":"https://orcid.org/0000-0001-9115-4336","contributorId":4539,"corporation":false,"usgs":true,"family":"Bowen","given":"Lizabeth","email":"lbowen@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":631231,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lee, Chia-Shan","contributorId":169843,"corporation":false,"usgs":false,"family":"Lee","given":"Chia-Shan","email":"","affiliations":[{"id":25602,"text":"Dep't Pathology, Vet School, UC Davis, CA","active":true,"usgs":false}],"preferred":false,"id":631233,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blanchard, Myra","contributorId":169844,"corporation":false,"usgs":false,"family":"Blanchard","given":"Myra","email":"","affiliations":[{"id":25603,"text":"Dep't of Pathology, Vet School, UC Davis, CA","active":true,"usgs":false}],"preferred":false,"id":631234,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McBain, James","contributorId":169845,"corporation":false,"usgs":false,"family":"McBain","given":"James","email":"","affiliations":[{"id":25604,"text":"Vet consultant, San Diego, CA","active":true,"usgs":false}],"preferred":false,"id":631235,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dold, Christopher","contributorId":169846,"corporation":false,"usgs":false,"family":"Dold","given":"Christopher","email":"","affiliations":[{"id":25605,"text":"Corp. VP, Vet Services, SeaWorld Parks & Entertainment, Orlando, FL","active":true,"usgs":false}],"preferred":false,"id":631236,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stott, Jeffrey L.","contributorId":82146,"corporation":false,"usgs":true,"family":"Stott","given":"Jeffrey","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":631237,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70173814,"text":"70173814 - 2016 - The structure of genetic diversity in eelgrass (Zostera marina L.) along the North Pacific and Bering Sea coasts of Alaska","interactions":[],"lastModifiedDate":"2018-08-19T10:07:55","indexId":"70173814","displayToPublicDate":"2016-04-22T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The structure of genetic diversity in eelgrass (<i>Zostera marina</i> L.) along the North Pacific and Bering Sea coasts of Alaska","title":"The structure of genetic diversity in eelgrass (Zostera marina L.) along the North Pacific and Bering Sea coasts of Alaska","docAbstract":"<p>Eelgrass (<i>Zostera marina)</i> populations occupying coastal waters of Alaska are separated by a peninsula and island archipelago into two Large Marine Ecosystems (LMEs). From populations in both LMEs, we characterize genetic diversity, population structure, and polarity in gene flow using nuclear microsatellite fragment and chloroplast and nuclear sequence data. An inverse relationship between genetic diversity and latitude was observed (heterozygosity: R<sup>2</sup> = 0.738, <i>P &lt;</i> 0.001; allelic richness: R<sup>2</sup> = 0.327, P = 0.047), as was significant genetic partitioning across most sampling sites (θ = 0.302, <i>P &lt;</i> 0.0001). Variance in allele frequency was significantly partitioned by region only in cases when a population geographically in the Gulf of Alaska LME (Kinzarof Lagoon) was instead included with populations in the Eastern Bering Sea LME (θ<sub>p</sub> = 0.128–0.172; <i>P &lt;</i> 0.003), suggesting gene flow between the two LMEs in this region. Gene flow among locales was rarely symmetrical, with notable exceptions generally following net coastal ocean current direction. Genetic data failed to support recent proposals that multiple <i>Zostera</i> species (i.e. <i>Z</i>. <i>japonica</i> and <i>Z</i>. <i>angustifolia</i>) are codistributed with <i>Z</i>. <i>marina</i> in Alaska. Comparative analyses also failed to support the hypothesis that eelgrass populations in the North Atlantic derived from eelgrass retained in northeastern Pacific Last Glacial Maximum refugia. These data suggest northeastern Pacific populations are derived from populations expanding northward from temperate populations following climate amelioration at the terminus of the last Pleistocene glaciation.</p>","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0152701","usgsCitation":"Talbot, S.L., Sage, G.K., Rearick, J.R., Fowler, M., Muñiz-Salazar, R., Baibak, B., Wyllie-Echeverria, S., Cabello-Pasini, A., and Ward, D.H., 2016, The structure of genetic diversity in eelgrass (Zostera marina L.) along the North Pacific and Bering Sea coasts of Alaska: PLoS ONE, v. 11, no. 4, Article e0152701; 31 p., https://doi.org/10.1371/journal.pone.0152701.","productDescription":"Article e0152701; 31 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-061219","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":471053,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0152701","text":"Publisher Index Page"},{"id":438617,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7GQ6VTK","text":"USGS data release","linkHelpText":"Eelgrass (Zostera marina) Microsatellite DNA Data; Pacific Coast of North America, 2000-2009"},{"id":323474,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Bering Sea, Gulf of Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -169.013671875,\n              65.25670649344259\n            ],\n            [\n              -179.033203125,\n              62.34960927573045\n            ],\n            [\n              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ksage@usgs.gov","orcid":"https://orcid.org/0000-0003-1431-2286","contributorId":87833,"corporation":false,"usgs":true,"family":"Sage","given":"George","email":"ksage@usgs.gov","middleInitial":"K.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":638486,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rearick, Jolene R. 0000-0003-0942-8268 jrearick@usgs.gov","orcid":"https://orcid.org/0000-0003-0942-8268","contributorId":195245,"corporation":false,"usgs":true,"family":"Rearick","given":"Jolene","email":"jrearick@usgs.gov","middleInitial":"R.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":638487,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fowler, Megan C. 0000-0002-4947-0236 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University","active":true,"usgs":false}],"preferred":false,"id":638490,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wyllie-Echeverria, Sandy","contributorId":24874,"corporation":false,"usgs":true,"family":"Wyllie-Echeverria","given":"Sandy","email":"","affiliations":[],"preferred":false,"id":638491,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cabello-Pasini, Alehandro","contributorId":171746,"corporation":false,"usgs":false,"family":"Cabello-Pasini","given":"Alehandro","email":"","affiliations":[{"id":26938,"text":"Instituto de Investigaciones Oceanológicas, Universidad Autónoma de Baja California","active":true,"usgs":false}],"preferred":false,"id":638492,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ward, David H. 0000-0002-5242-2526 dward@usgs.gov","orcid":"https://orcid.org/0000-0002-5242-2526","contributorId":3247,"corporation":false,"usgs":true,"family":"Ward","given":"David","email":"dward@usgs.gov","middleInitial":"H.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":638493,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70169966,"text":"70169966 - 2016 - “One Health” or three? Publication silos among the One Health disciplines","interactions":[],"lastModifiedDate":"2018-08-07T12:40:50","indexId":"70169966","displayToPublicDate":"2016-04-21T14:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2979,"text":"PLoS Biology","active":true,"publicationSubtype":{"id":10}},"title":"“One Health” or three? Publication silos among the One Health disciplines","docAbstract":"<p><span>The One Health initiative is a global effort fostering interdisciplinary collaborations to address challenges in human, animal, and environmental health. While One Health has received considerable press, its benefits remain unclear because its effects have not been quantitatively described. We systematically surveyed the published literature and used social network analysis to measure interdisciplinarity in One Health studies constructing dynamic pathogen transmission models. The number of publications fulfilling our search criteria increased by 14.6% per year, which is faster than growth rates for life sciences as a whole and for most biology subdisciplines. Surveyed publications clustered into three communities: one used by ecologists, one used by veterinarians, and a third diverse-authorship community used by population biologists, mathematicians, epidemiologists, and experts in human health. Overlap between these communities increased through time in terms of author number, diversity of co-author affiliations, and diversity of citations. However, communities continue to differ in the systems studied, questions asked, and methods employed. While the infectious disease research community has made significant progress toward integrating its participating disciplines, some segregation&mdash;especially along the veterinary/ecological research interface&mdash;remains.</span></p>","language":"English","publisher":"Public library of science","doi":"10.1371/journal.pbio.1002448","usgsCitation":"Manlove, K., Walker, J.G., Craft, M.E., Huyvaert, K., Joseph, M.B., Miller, R.S., Nol, P., Patyk, K.A., O’Brian, D., Walsh, D.P., and Cross, P.C., 2016, “One Health” or three? Publication silos among the One Health disciplines: PLoS Biology, v. 14, no. 4, e1002448; 14 p., https://doi.org/10.1371/journal.pbio.1002448.","productDescription":"e1002448; 14 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072536","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":471055,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pbio.1002448","text":"Publisher Index Page"},{"id":321692,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-21","publicationStatus":"PW","scienceBaseUri":"5746ccc8e4b07e28b662dd7b","contributors":{"authors":[{"text":"Manlove, Kezia","contributorId":68204,"corporation":false,"usgs":true,"family":"Manlove","given":"Kezia","affiliations":[],"preferred":false,"id":625715,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walker, Josephine G","contributorId":168371,"corporation":false,"usgs":false,"family":"Walker","given":"Josephine","email":"","middleInitial":"G","affiliations":[{"id":7172,"text":"University of Bristol, U.K. and University of Oregon, Eugene","active":true,"usgs":false}],"preferred":false,"id":625716,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Craft, Meggan E.","contributorId":168372,"corporation":false,"usgs":false,"family":"Craft","given":"Meggan","email":"","middleInitial":"E.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":625717,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Huyvaert, Kathryn P.","contributorId":73906,"corporation":false,"usgs":true,"family":"Huyvaert","given":"Kathryn P.","affiliations":[],"preferred":false,"id":625718,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Joseph, Maxwell B.","contributorId":39678,"corporation":false,"usgs":true,"family":"Joseph","given":"Maxwell","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":625719,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miller, Ryan S.","contributorId":49005,"corporation":false,"usgs":false,"family":"Miller","given":"Ryan","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":625720,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nol, Pauline","contributorId":34053,"corporation":false,"usgs":false,"family":"Nol","given":"Pauline","email":"","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":625721,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Patyk, Kelly A.","contributorId":139696,"corporation":false,"usgs":false,"family":"Patyk","given":"Kelly","email":"","middleInitial":"A.","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":625722,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"O’Brian, Daniel","contributorId":168373,"corporation":false,"usgs":false,"family":"O’Brian","given":"Daniel","email":"","affiliations":[{"id":7024,"text":"Michigan Department of Natural Resources, Fisheries Research Station","active":true,"usgs":false}],"preferred":false,"id":625723,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Walsh, Daniel P. 0000-0002-7772-2445 dwalsh@usgs.gov","orcid":"https://orcid.org/0000-0002-7772-2445","contributorId":4758,"corporation":false,"usgs":true,"family":"Walsh","given":"Daniel","email":"dwalsh@usgs.gov","middleInitial":"P.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":625724,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Cross, Paul C. 0000-0001-8045-5213 pcross@usgs.gov","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":2709,"corporation":false,"usgs":true,"family":"Cross","given":"Paul","email":"pcross@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":625714,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70170766,"text":"70170766 - 2016 - Biogeographical history and coalescent species delimitation of Pacific island skinks (Squamata: Scincidae: <i>Emoia cyanura</i> species group)","interactions":[],"lastModifiedDate":"2016-09-28T16:26:11","indexId":"70170766","displayToPublicDate":"2016-04-20T16:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2193,"text":"Journal of Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"Biogeographical history and coalescent species delimitation of Pacific island skinks (Squamata: Scincidae: <i>Emoia cyanura</i> species group)","docAbstract":"<h3>Aim</h3>\n<p>A prevailing hypothesis for how Pacific islands organisms have obtained their extant distributions is that of a stepping-stone model, in which populations originate from Papua New Guinea in the western Pacific and gradually disperse eastward. Here, we test this model using a spatiotemporal framework for&nbsp;<i>Emoia cyanura</i>&nbsp;and&nbsp;<i>E. impar</i>, two species within the&nbsp;<i>Emoia cyanura</i>&nbsp;species group (ECSG; Family: Scincidae). We further assess species limits within the group, utilizing novel coalescent methods.</p>\n<h3>Location</h3>\n<p>Pacific Islands.</p>\n<h3>Methods</h3>\n<p>We obtained DNA sequence data from one mitochondrial and three nuclear markers for 117 individuals, representing seven of the nine species within the ECSG. These data were analysed for concordance with the stepping-stone model using estimation of population structure, divergence dates, and historical biogeographical range. To assess hypotheses of independent lineages within each widespread species, we also employed the Bayesian Phylogenetics &amp; Phylogeography (BPP) program to define operational taxonomic units in *BEAST.</p>\n<h3>Results</h3>\n<p>Population structure analyses consistently found individuals from western island groups representing divergent populations, with central and eastern populations demonstrating minimal genetic variation. Phylogenetic hypotheses support a western origin for&nbsp;<i>E. cyanura</i>&nbsp;and&nbsp;<i>E. impar</i>, while biogeographical and divergence time estimations predict a recent and rapid expansion out of the western Pacific. The BPP and *BEAST analyses found evidence for five independent lineages within&nbsp;<i>E. impar</i>&nbsp;and five independent lineages within&nbsp;<i>E. cyanura</i>/<i>E. pseudocyanura</i>.</p>\n<h3>Main conclusions</h3>\n<p>In contrast to the expectations of a stepping-stone model,&nbsp;<i>E. cyanura</i>&nbsp;and&nbsp;<i>E. impar</i>&nbsp;each exhibit the genetic signature of a rapid radiation during the mid to late Pleistocene, with evidence for newly identified lineages, mainly on western islands. Of these recovered lineages, we propose three to be elevated to species status. These findings expand our understanding of endemic Pacific biota, which are subject to conservation threats from human impacts and climate change.</p>","language":"English","publisher":"Blackwell Scientific Publications","doi":"10.1111/jbi.12772","usgsCitation":"Klein, E., Harris, R., Fisher, R.N., and Reeder, T., 2016, Biogeographical history and coalescent species delimitation of Pacific island skinks (Squamata: Scincidae: <i>Emoia cyanura</i> species group): Journal of Biogeography, v. 43, no. 10, p. 1917-1929, https://doi.org/10.1111/jbi.12772.","productDescription":"13 p.","startPage":"1917","endPage":"1929","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071494","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":320843,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Pacific islands","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  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,{"id":70170507,"text":"70170507 - 2016 - Magma transport and olivine crystallization depths in Kīlauea’s East Rift Zone inferred from experimentally rehomogenized melt inclusions","interactions":[],"lastModifiedDate":"2016-06-16T10:57:57","indexId":"70170507","displayToPublicDate":"2016-04-18T10:45:00","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":"Magma transport and olivine crystallization depths in Kīlauea’s East Rift Zone inferred from experimentally rehomogenized melt inclusions","docAbstract":"<div class=\"abstract svAbstract \" data-etype=\"ab\">\n<p id=\"sp0005\">Concentrations of H<sub>2</sub>O and CO<sub>2</sub>&nbsp;in olivine-hosted melt inclusions can be used to estimate crystallization depths for the olivine host. However, the original dissolved CO<sub>2</sub>concentration of melt inclusions at the time of trapping can be difficult to measure directly because in many cases substantial CO<sub>2</sub>&nbsp;is transferred to shrinkage bubbles that form during post-entrapment cooling and crystallization. To investigate this problem, we heated olivine from the 1959 Kīlauea Iki and 1960 Kapoho (Hawai&lsquo;i) eruptions in a 1-atm furnace to temperatures above the melt inclusion trapping temperature to redissolve the CO<sub>2</sub>&nbsp;in shrinkage bubbles. The measured CO<sub>2</sub>&nbsp;concentrations of the experimentally rehomogenized inclusions (⩽590 ppm for Kīlauea Iki [n=10]; ⩽880 ppm for Kapoho, with one inclusion at 1863 ppm [n=38]) overlap with values for naturally quenched inclusions from the same samples, but experimentally rehomogenized inclusions have higher within-sample median CO<sub>2</sub>&nbsp;values than naturally quenched inclusions, indicating at least partial dissolution of CO<sub>2</sub>&nbsp;from the vapor bubble during heating. Comparison of our data with predictions from modeling of vapor bubble formation and published Raman data on the density of CO<sub>2</sub>&nbsp;in the vapor bubbles suggests that 55-85% of the dissolved CO<sub>2</sub>&nbsp;in the melt inclusions at the time of trapping was lost to post-entrapment shrinkage bubbles. Our results combined with the Raman data demonstrate that olivine from the early part of the Kīlauea Iki eruption crystallized at &lt;6 km depth, with the majority of olivine in the 1-3 km depth range. These depths are consistent with the interpretation that the Kīlauea Iki magma was supplied from Kīlauea&rsquo;s summit magma reservoir (&sim;2-5 km depth). In contrast, olivine from Kapoho, which was the rift zone extension of the Kīlauea Iki eruption, crystallized over a much wider range of depths (&sim;1-16 km). The wider depth range requires magma transport during the Kapoho eruption from deep beneath the summit region and/or from deep beneath Kīlauea&rsquo;s east rift zone. The deeply derived olivine crystals and their host magma mixed with stored, more evolved magma in the rift zone, and the mixture was later erupted at Kapoho.</p>\n</div>","language":"English","publisher":"Geochemical Society","publisherLocation":"Oxford","doi":"10.1016/j.gca.2016.04.020","usgsCitation":"Tuohy, R.M., Wallace, P., Loewen, M., Swanson, D., and Kent, A.J., 2016, Magma transport and olivine crystallization depths in Kīlauea’s East Rift Zone inferred from experimentally rehomogenized melt inclusions: Geochimica et Cosmochimica Acta, v. 185, p. 232-250, https://doi.org/10.1016/j.gca.2016.04.020.","productDescription":"19 p.","startPage":"232","endPage":"250","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068885","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":471063,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gca.2016.04.020","text":"Publisher Index Page"},{"id":320501,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","county":"Hawaii","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-155.8799,20.2589],[-155.8389,20.2672],[-155.7974,20.2483],[-155.7717,20.2467],[-155.7307,20.217],[-155.7276,20.2014],[-155.6597,20.1689],[-155.5966,20.1224],[-155.5519,20.1275],[-155.4406,20.0928],[-155.2746,20.0165],[-155.2142,19.9761],[-155.1417,19.9175],[-155.0839,19.8533],[-155.0923,19.8101],[-155.0842,19.7247],[-155.0378,19.74],[-155.0008,19.735],[-154.9786,19.69],[-154.98,19.6376],[-154.9483,19.6236],[-154.9444,19.6025],[-154.9053,19.5706],[-154.8211,19.5322],[-154.8058,19.5161],[-154.8183,19.4997],[-154.8194,19.4794],[-154.8362,19.46],[-154.8895,19.4144],[-154.9283,19.3947],[-154.9725,19.3489],[-155.0705,19.3112],[-155.1543,19.2657],[-155.2084,19.2564],[-155.2631,19.2709],[-155.2968,19.2616],[-155.3566,19.2069],[-155.4154,19.1838],[-155.4543,19.1464],[-155.5053,19.1312],[-155.5528,19.0803],[-155.5531,19.0467],[-155.5772,19.0208],[-155.6017,18.9683],[-155.6183,18.9692],[-155.6386,18.935],[-155.6771,18.9105],[-155.6886,18.9394],[-155.7159,18.9606],[-155.7587,18.9769],[-155.7975,19.0094],[-155.8508,19.0189],[-155.8817,19.0358],[-155.8844,19.0525],[-155.9067,19.0786],[-155.9186,19.1344],[-155.8994,19.2111],[-155.8864,19.3433],[-155.9106,19.3961],[-155.9061,19.4131],[-155.9292,19.4589],[-155.9194,19.4728],[-155.9503,19.4858],[-155.9774,19.6064],[-155.9944,19.6375],[-156.0308,19.6515],[-156.0269,19.6731],[-156.0601,19.7255],[-156.0503,19.7744],[-156.0394,19.7878],[-155.9739,19.8481],[-155.9242,19.8558],[-155.9017,19.9056],[-155.8872,19.9144],[-155.8895,19.93],[-155.8544,19.9669],[-155.8356,19.9739],[-155.828,19.9894],[-155.8231,20.0228],[-155.8839,20.1058],[-155.9004,20.1635],[-155.8994,20.2281],[-155.8799,20.2589]]]},\"properties\":{\"name\":\"Hawaii\",\"state\":\"HI\"}}]}","volume":"185","publishingServiceCenter":{"id":14,"text":"Menlo 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,{"id":70154778,"text":"70154778 - 2016 - Notes on the origin of copromacrinite based on nitrogen functionalities and δ13C and δ15N determined on samples from the Peach Orchard coal bed, southern Magoffin County, Kentucky","interactions":[],"lastModifiedDate":"2016-06-29T15:54:47","indexId":"70154778","displayToPublicDate":"2016-04-15T00:00:00","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":"Notes on the origin of copromacrinite based on nitrogen functionalities and δ13C and δ15N determined on samples from the Peach Orchard coal bed, southern Magoffin County, Kentucky","docAbstract":"<p id=\"sp0040\">This paper represents the first attempt to show, by means other than just petrographic ones, that one type of macrinite, herein designated copromacrinite, may result from macrofauna feces. For that purpose a combination of coal petrography, X-ray photoelectron spectroscopy, and elemental-analysis continuous-flow isotope ratio mass spectrometry methods were used to determine nitrogen functionalities and&nbsp;<i>&delta;</i><sup>13</sup>C and<i>&delta;</i><sup>15</sup>N compositions in 1) vitrinite-rich, 2) fusinite&nbsp;+&nbsp;semifusinite-rich, and 3) macrinite-rich (with a possible coprolitic origin) samples of the high volatile A bituminous Peach Orchard coal (Bolsovian; Middle Pennsylvanian) from Magoffin County, Kentucky. There were no significant differences between pyridinic-N and quaternary-N abundance in the three samples, however, pyrrolic-N was higher (~&nbsp;54%) in the macrinite-rich sample than in the other two samples (~&nbsp;38%). The data suggest that pyridinic-N and quaternary-N are independent of maceral group composition and that pyrrolic-N is dependent on maceral composition (fusinite&nbsp;+&nbsp;semifusinite versus macrinite).&nbsp;<i>&delta;</i><sup>13</sup>C values obtained for bulk and demineralized coal of the vitrinite- and fusinite&nbsp;+&nbsp;semifusinite-rich samples are similar with&nbsp;<i>&delta;</i><sup>13</sup>C values of &minus;&nbsp;24.80&nbsp;&plusmn;&nbsp;0.01&permil; VPDB and &minus;&nbsp;24.61&nbsp;&plusmn;&nbsp;0.09&permil; VPDB for bulk samples and &minus;&nbsp;24.81&nbsp;&plusmn;&nbsp;0.07&permil; VPDB and &minus;&nbsp;24.52&nbsp;&plusmn;&nbsp;0.04&permil; VPDB for demineralized samples. These values are within the expected range for vitrinite-rich samples and the slightly higher&nbsp;<i>&delta;</i><sup>13</sup>C value of the fusinite&nbsp;+&nbsp;semifusinite-rich sample is expected as&nbsp;<i>&delta;</i><sup>13</sup>C values for inertinite are higher than for vitrinite. However, there was a significant shift to a lower&nbsp;<i>&delta;</i><sup>13</sup>C value (&minus;&nbsp;26.80&nbsp;&plusmn;&nbsp;0.01&permil; VPDB for the bulk sample value) for the macrinite-rich sample. Because the samples are basically isorank, and&nbsp;<i>&delta;</i><sup>13</sup>C (and&nbsp;<i>&delta;</i><sup>15</sup>N) shifts do not occur during maturation until anthracite rank, the difference may be related to the presence or composition of the macrinite within the sample which lacks heat-effect indicators, such as devolatilization vacuoles and distorted pores.&nbsp;<i>&delta;</i><sup>15</sup>N values are also similar for bulk and demineralized coal of the vitrinite- and fusinite&nbsp;+&nbsp;semifusinite-rich samples, and the bulk values were heavier in this samples (3.07&nbsp;&plusmn;&nbsp;0.03&permil; Air and 2.92&nbsp;&plusmn;&nbsp;0.10&permil; Air, respectively), and much lighter (&minus;&nbsp;2.83&nbsp;&plusmn;&nbsp;0.09&permil; Air) for the macrinite-rich sample.</p>\n<p id=\"sp0045\">The study of Peach Orchard coal samples using reflected-light microscopy, isotopic composition, and nitrogen-forms analyses revealed that the macrinite-rich sample contains macrinite with coprolitic features (e.g. oxidation rind, mix of undigested palynomorphs, frequent and randomly located funginite, agglutination pulp of semifusinite reflectance, internal lack of bedding fabric, and suggestion of structures resulting from intestines and stomach walls), more pyrrolic-N (~&nbsp;16%), and lower&nbsp;<i>&delta;</i><sup>13</sup>C (~&nbsp;2&permil; VPDB) and&nbsp;<i>&delta;</i><sup>15</sup>N (~&nbsp;4&permil; Air) values than the vitrinite and semifusinite&nbsp;+&nbsp;fusinite rich samples. These findings suggest that the maceral macrinite has multiple origins based on petrography and measurable chemical differences between the macrinite, vitrinite, and semifusinite&nbsp;+&nbsp;fusinite fractions within the coal. Assuming that copromacrinite observed is an excretion then the anomalies observed may result from the symbiotic relations between the macrofauna (e.g. cockroaches) and microbiota during the digestive processes, and the nitrogen balance mechanisms inside macrofauna body.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2016.05.004","usgsCitation":"Valentim, B., Algarra, M., Guedes, A., Ruppert, L.F., and Hower, J., 2016, Notes on the origin of copromacrinite based on nitrogen functionalities and δ13C and δ15N determined on samples from the Peach Orchard coal bed, southern Magoffin County, Kentucky: International Journal of Coal Geology, v. 160-161, p. 63-72, https://doi.org/10.1016/j.coal.2016.05.004.","productDescription":"10 p.","startPage":"63","endPage":"72","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062704","costCenters":[{"id":241,"text":"Eastern Energy Resources Science 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,{"id":70170264,"text":"70170264 - 2016 - Range expansion of moose in arctic Alaska linked to warming and increased shrub habitat","interactions":[],"lastModifiedDate":"2016-04-15T09:27:27","indexId":"70170264","displayToPublicDate":"2016-04-13T10:30:00","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":"Range expansion of moose in arctic Alaska linked to warming and increased shrub habitat","docAbstract":"<p><span>Twentieth century warming has increased vegetation productivity and shrub cover across northern tundra and treeline regions, but effects on terrestrial wildlife have not been demonstrated on a comparable scale. During this period, Alaskan moose (</span><i>Alces alces gigas</i><span>) extended their range from the boreal forest into tundra riparian shrub habitat; similar extensions have been observed in Canada (</span><i>A</i><span>.&nbsp;</span><i>a</i><span>.&nbsp;</span><i>andersoni</i><span>) and Eurasia (</span><i>A</i><span>.&nbsp;</span><i>a</i><span>.&nbsp;</span><i>alces</i><span>). Northern moose distribution is thought to be limited by forage availability above the snow in late winter, so the observed increase in shrub habitat could be causing the northward moose establishment, but a previous hypothesis suggested that hunting cessation triggered moose establishment. Here, we use recent changes in shrub cover and empirical relationships between shrub height and growing season temperature to estimate available moose habitat in Arctic Alaska c. 1860. We estimate that riparian shrubs were approximately 1.1 m tall c. 1860, greatly reducing the available forage above the snowpack, compared to 2 m tall in 2009. We believe that increases in riparian shrub habitat after 1860 allowed moose to colonize tundra regions of Alaska hundreds of kilometers north and west of previous distribution limits. The northern shift in the distribution of moose, like that of snowshoe hares, has been in response to the spread of their shrub habitat in the Arctic, but at the same time, herbivores have likely had pronounced impacts on the structure and function of these shrub communities. These northward range shifts are a bellwether for other boreal species and their associated predators.</span></p>","language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0152636","collaboration":"UAF","usgsCitation":"Tape, K., Gustine, D.D., Reuss, R.W., Adams, L., and Clark, J.A., 2016, Range expansion of moose in arctic Alaska linked to warming and increased shrub habitat: PLoS ONE, v. 11, no. 4, https://doi.org/10.1371/journal.pone.0152636.","productDescription":"12 p.","startPage":"e0152636","numberOfPages":"12","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-057050","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":471076,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0152636","text":"Publisher Index 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        70.00556654574504\n            ],\n            [\n              -142.14111328125,\n              69.91521433690129\n            ],\n            [\n              -141.83349609375,\n              69.8320477208414\n            ],\n            [\n              -141.50390625,\n              69.7485511291223\n            ],\n            [\n              -141.2841796875,\n              69.67235784229395\n            ],\n            [\n              -140.99853515625,\n              69.64944636884633\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"11","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-13","publicationStatus":"PW","scienceBaseUri":"571210b5e4b0ef3b7ca64428","contributors":{"authors":[{"text":"Tape, Ken D.","contributorId":103570,"corporation":false,"usgs":true,"family":"Tape","given":"Ken D.","affiliations":[],"preferred":false,"id":626692,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gustine, David D. dgustine@usgs.gov","contributorId":3776,"corporation":false,"usgs":true,"family":"Gustine","given":"David","email":"dgustine@usgs.gov","middleInitial":"D.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":626691,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reuss, Roger W.","contributorId":168602,"corporation":false,"usgs":false,"family":"Reuss","given":"Roger","email":"","middleInitial":"W.","affiliations":[{"id":13117,"text":"Institute of Arctic Biology, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":626693,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Adams, Layne G. 0000-0001-6212-2896 ladams@usgs.gov","orcid":"https://orcid.org/0000-0001-6212-2896","contributorId":2776,"corporation":false,"usgs":true,"family":"Adams","given":"Layne G.","email":"ladams@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":626694,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clark, Jason A.","contributorId":168604,"corporation":false,"usgs":false,"family":"Clark","given":"Jason","email":"","middleInitial":"A.","affiliations":[{"id":16761,"text":"Institute of Northern Engineering, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":626710,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70170469,"text":"70170469 - 2016 - Ecosystem level methane fluxes from tidal freshwater and brackish marshes of the Mississippi River Delta: Implications for coastal wetland carbon projects","interactions":[],"lastModifiedDate":"2016-08-25T08:34:10","indexId":"70170469","displayToPublicDate":"2016-04-12T11:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Ecosystem level methane fluxes from tidal freshwater and brackish marshes of the Mississippi River Delta: Implications for coastal wetland carbon projects","docAbstract":"<p><span>Sulfate from seawater inhibits methane production in tidal wetlands, and by extension, salinity has been used as a general predictor of methane emissions. With the need to reduce methane flux uncertainties from tidal wetlands, eddy covariance (EC) techniques provide an integrated methane budget. The goals of this study were to: 1) establish methane emissions from natural, freshwater and brackish wetlands in Louisiana based on EC; and 2) determine if EC estimates conform to a methane-salinity relationship derived from temperate tidal wetlands with chamber sampling. Annual estimates of methane emissions from this study were 62.3&nbsp;g CH</span><sub><span>4</span></sub><span>/m</span><sup><span>2</span></sup><span>/yr and 13.8&nbsp;g CH</span><sub><span>4</span></sub><span>/m</span><sup><span>2</span></sup><span>/yr for the freshwater and brackish (8–10&nbsp;psu) sites, respectively. If it is assumed that long-term, annual soil carbon sequestration rates of natural marshes are ~200&nbsp;g C/m</span><sup><span>2</span></sup><span>/yr (7.3 tCO</span><sub><span>2</span></sub><span>e/ha/yr), healthy brackish marshes could be expected to act as a net radiative sink, equivalent to less than one-half the soil carbon accumulation rate after subtracting methane emissions (4.1 tCO</span><sub><span>2</span></sub><span>e/ha/yr). Carbon sequestration rates would need case-by-case assessment, but the EC methane emissions estimates in this study conformed well to an existing salinity-methane model that should serve as a basis for establishing emission factors for wetland carbon offset projects.</span></p>","language":"English","publisher":"Society of Wetland Scientists","publisherLocation":"McClean, VA","doi":"10.1007/s13157-016-0746-7","usgsCitation":"Holm, G., Perez, B.C., McWhorter, D.E., Krauss, K.W., Johnson, D., Raynie, R.C., and Killebrew, C.J., 2016, Ecosystem level methane fluxes from tidal freshwater and brackish marshes of the Mississippi River Delta: Implications for coastal wetland carbon projects: Wetlands, v. 36, no. 3, p. 401-413, https://doi.org/10.1007/s13157-016-0746-7.","productDescription":"13 p.","startPage":"401","endPage":"413","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066949","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":320398,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -90.2032470703125,\n              29.940655389125002\n            ],\n            [\n              -90.2911376953125,\n              30.007273923504556\n            ],\n            [\n              -90.4998779296875,\n              30.007273923504556\n            ],\n            [\n              -90.68115234375,\n              29.869228848968312\n            ],\n            [\n              -90.758056640625,\n              29.692824739380754\n            ],\n            [\n              -90.7415771484375,\n              29.511330027309146\n            ],\n            [\n              -90.52734374999999,\n              29.420460341013133\n            ],\n            [\n              -90.19775390625,\n              29.477861195816843\n            ],\n            [\n              -90.1593017578125,\n              29.7453016622136\n            ],\n            [\n              -90.2032470703125,\n              29.940655389125002\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"36","issue":"3","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-12","publicationStatus":"PW","scienceBaseUri":"571b4b2de4b071321fe31c63","contributors":{"authors":[{"text":"Holm, Guerry O.","contributorId":79219,"corporation":false,"usgs":true,"family":"Holm","given":"Guerry O.","affiliations":[],"preferred":false,"id":627337,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perez, Brian C.","contributorId":42286,"corporation":false,"usgs":true,"family":"Perez","given":"Brian","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":627338,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McWhorter, David E.","contributorId":168801,"corporation":false,"usgs":false,"family":"McWhorter","given":"David","email":"","middleInitial":"E.","affiliations":[{"id":18062,"text":"CH2MHILL, Austin, TX","active":true,"usgs":false}],"preferred":false,"id":627339,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":627336,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Darren J.","contributorId":100291,"corporation":false,"usgs":true,"family":"Johnson","given":"Darren J.","affiliations":[],"preferred":false,"id":627340,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Raynie, Richard C.","contributorId":168802,"corporation":false,"usgs":false,"family":"Raynie","given":"Richard","email":"","middleInitial":"C.","affiliations":[{"id":13608,"text":"Louisiana Coastal Protection and Restoration Authority","active":true,"usgs":false}],"preferred":false,"id":627341,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Killebrew, Charles J.","contributorId":168803,"corporation":false,"usgs":false,"family":"Killebrew","given":"Charles","email":"","middleInitial":"J.","affiliations":[{"id":13608,"text":"Louisiana Coastal Protection and Restoration Authority","active":true,"usgs":false}],"preferred":false,"id":627342,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70170099,"text":"70170099 - 2016 - Influence of manatees' diving on their risk of collision with watercraft","interactions":[],"lastModifiedDate":"2016-07-11T15:44:59","indexId":"70170099","displayToPublicDate":"2016-04-07T10:30:00","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":"Influence of manatees' diving on their risk of collision with watercraft","docAbstract":"<p><span>Watercraft pose a threat to endangered Florida manatees (</span><i>Trichechus manatus latirostris</i><span>). Mortality from watercraft collisions has adversely impacted the manatee population&rsquo;s growth rate, therefore reducing this threat is an important management goal. To assess factors that contribute to the risk of watercraft strikes to manatees, we studied the diving behavior of nine manatees carrying GPS tags and time&ndash;depth recorders in Tampa Bay, Florida, during winters 2002&ndash;2006. We applied a Bayesian formulation of generalized linear mixed models to depth data to model the probability (</span><i>P</i><sub><i>t</i></sub><span>) that manatees would be no deeper than 1.25 m from the water&rsquo;s surface as a function of behavioral and habitat covariates. Manatees above this threshold were considered to be within striking depth of a watercraft. Seventy-eight percent of depth records (individual range 62&ndash;86%) were within striking depth (mean = 1.09 m, max = 16.20 m), illustrating how vulnerable manatees are to strikes. In some circumstances manatees made consecutive dives to the bottom while traveling, even in areas &gt;14 m, possibly to conserve energy. This is the first documentation of potential cost-efficient diving behavior in manatees. Manatees were at higher risk of being within striking depth in shallow water (&lt;0.91 m), over seagrass, at night, and while stationary or moving slowly; they were less likely to be within striking depth when &le;50 m from a charted waterway. In shallow water the probability of a manatee being within striking depth was 0.96 (CI = 0.93&ndash;0.98) and decreased as water depth increased. The probability was greater over seagrass (</span><i>P</i><sub><i>t</i></sub><span><span class=\"Apple-converted-space\">&nbsp;</span></span><i>=</i><span><span class=\"Apple-converted-space\">&nbsp;</span>0.96, CI = 0.93&ndash;0.98) than over other substrates (</span><i>P</i><sub><i>t</i></sub><span><span class=\"Apple-converted-space\">&nbsp;</span>= 0.73, CI = 0.58&ndash;0.84). Quantitative approaches to assessing risk can improve the effectiveness of manatee conservation measures by helping identify areas for protection.</span></p>","language":"English","publisher":"PLos One","doi":"10.1371/journal.pone.0151450","usgsCitation":"Edwards, H.H., Martin, J., Deutsch, C., Muller, R.G., Koslovsky, S.M., Smith, A., and Barlas, M., 2016, Influence of manatees' diving on their risk of collision with watercraft: PLoS ONE, v. 11, no. 4, 15 p., https://doi.org/10.1371/journal.pone.0151450.","productDescription":"15 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060636","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471085,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0151450","text":"Publisher Index Page"},{"id":319882,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -82.76275634765625,\n              28.13133880763851\n            ],\n            [\n              -82.4139404296875,\n              28.06228599981216\n            ],\n            [\n              -82.3260498046875,\n              27.81357174811185\n            ],\n            [\n              -82.47299194335936,\n              27.410785702577023\n            ],\n            [\n              -82.72018432617188,\n              27.42297612892041\n            ],\n            [\n              -82.84790039062499,\n              27.847576211806295\n            ],\n            [\n              -82.85888671875,\n              28.02592458049937\n            ],\n            [\n              -82.84515380859375,\n              28.13133880763851\n            ],\n            [\n              -82.77374267578125,\n              28.13739395116007\n            ],\n            [\n              -82.76275634765625,\n              28.13133880763851\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"11","issue":"4","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-06","publicationStatus":"PW","scienceBaseUri":"5710bf30e4b0ef3b7ca55149","contributors":{"authors":[{"text":"Edwards, Holly H.","contributorId":66419,"corporation":false,"usgs":true,"family":"Edwards","given":"Holly","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":626165,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Julien 0000-0002-7375-129X julienmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-7375-129X","contributorId":5785,"corporation":false,"usgs":true,"family":"Martin","given":"Julien","email":"julienmartin@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":626164,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Deutsch, Charles J.","contributorId":64135,"corporation":false,"usgs":true,"family":"Deutsch","given":"Charles J.","affiliations":[],"preferred":false,"id":626166,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muller, Robert G","contributorId":168507,"corporation":false,"usgs":false,"family":"Muller","given":"Robert","email":"","middleInitial":"G","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":626167,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Koslovsky, Stacie M.","contributorId":168508,"corporation":false,"usgs":false,"family":"Koslovsky","given":"Stacie","email":"","middleInitial":"M.","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":626168,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, Alexander J.","contributorId":140345,"corporation":false,"usgs":false,"family":"Smith","given":"Alexander J.","affiliations":[{"id":13464,"text":"Environmental Analyst, NY State Dept of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":626169,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Barlas, Margie E.","contributorId":168510,"corporation":false,"usgs":false,"family":"Barlas","given":"Margie E.","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":626170,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70170086,"text":"70170086 - 2016 - Effect of variable annual precipitation and nutrient input on nitrogen and phosphorus transport from two Midwestern agricultural watersheds","interactions":[],"lastModifiedDate":"2016-08-17T11:01:21","indexId":"70170086","displayToPublicDate":"2016-04-06T11:45:00","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":"Effect of variable annual precipitation and nutrient input on nitrogen and phosphorus transport from two Midwestern agricultural watersheds","docAbstract":"<p><span>Precipitation patterns and nutrient inputs affect transport of nitrate (NO</span><sub>3</sub><span>-N) and phosphorus (TP) from Midwest watersheds. Nutrient concentrations and yields from two subsurface-drained watersheds, the Little Cobb River (LCR) in southern Minnesota and the South Fork Iowa River (SFIR) in northern Iowa, were evaluated during 1996&ndash;2007 to document relative differences in timings and amounts of nutrients transported. Both watersheds are located in the prairie pothole region, but the SFIR exhibits a longer growing season and more livestock production. The SFIR yielded significantly more NO</span><sub>3</sub><span>-N than the LCR watershed (31.2 versus 21.3&nbsp;kg&nbsp;NO</span><sub>3</sub><span>-N&nbsp;ha</span><sup>&minus;&nbsp;1</sup><span>&nbsp;y</span><sup>&minus;&nbsp;1</sup><span>). The SFIR watershed also yielded more TP than the LCR watershed (1.13 versus 0.51&nbsp;kg&nbsp;TP&nbsp;ha</span><sup>&minus;&nbsp;1</sup><span>&nbsp;yr</span><sup>&minus;&nbsp;1</sup><span>), despite greater TP concentrations in the LCR. About 65% of NO</span><sub>3</sub><span>-N and 50% of TP loads were transported during April&ndash;June, and &lt;&nbsp;20% of the annual loads were transported later in the growing season from July&ndash;September. Monthly NO</span><sub>3</sub><span>-N and TP loads peaked in April from the LCR but peaked in June from the SFIR; this difference was attributed to greater snowmelt runoff in the LCR. The annual NO</span><sub>3</sub><span>-N yield increased with increasing annual runoff at a similar rate in both watersheds, but the LCR watershed yielded less annual NO</span><sub>3</sub><span>-N than the SFIR for a similar annual runoff. These two watersheds are within 150 km of one another and have similar dominant agricultural systems, but differences in climate and cropping inputs affected amounts and timing of nutrient transport.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.03.127","usgsCitation":"Kalkhoff, S.J., Hubbard, L.E., Tomer, M.D., and James, D., 2016, Effect of variable annual precipitation and nutrient input on nitrogen and phosphorus transport from two Midwestern agricultural watersheds: Science of the Total Environment, v. 559, p. 53-62, https://doi.org/10.1016/j.scitotenv.2016.03.127.","productDescription":"10 p.","startPage":"53","endPage":"62","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066764","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"links":[{"id":471088,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.03.127","text":"Publisher Index Page"},{"id":319818,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"559","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"572477a5e4b0b13d3914e070","chorus":{"doi":"10.1016/j.scitotenv.2016.03.127","url":"http://dx.doi.org/10.1016/j.scitotenv.2016.03.127","publisher":"Elsevier BV","authors":"Kalkhoff S.J., Hubbard L.E., Tomer M.D., James D.E.","journalName":"Science of The Total Environment","publicationDate":"7/2016","publiclyAccessibleDate":"4/5/2017"},"contributors":{"authors":[{"text":"Kalkhoff, Stephen J. 0000-0003-4110-1716 sjkalkho@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-1716","contributorId":1731,"corporation":false,"usgs":true,"family":"Kalkhoff","given":"Stephen","email":"sjkalkho@usgs.gov","middleInitial":"J.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":626084,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hubbard, Laura E. 0000-0003-3813-1500 lhubbard@usgs.gov","orcid":"https://orcid.org/0000-0003-3813-1500","contributorId":4221,"corporation":false,"usgs":true,"family":"Hubbard","given":"Laura","email":"lhubbard@usgs.gov","middleInitial":"E.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":626085,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tomer, Mark D.","contributorId":168489,"corporation":false,"usgs":false,"family":"Tomer","given":"Mark","email":"","middleInitial":"D.","affiliations":[{"id":25309,"text":"U.S. Department of Agriculture Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":626086,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"James, D.E.","contributorId":22927,"corporation":false,"usgs":true,"family":"James","given":"D.E.","email":"","affiliations":[],"preferred":false,"id":626087,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
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