Intersex as the manifestation of testicular oocytes (TO) in male gonochoristic fishes has been used as an indicator of estrogenic exposure. Here we evaluated largemouth bass (Micropterus salmoides) or smallmouth bass (Micropterus dolomieu) form 19 National Wildlife Refuges (NWRs) in the Northeast U.S. inhabiting waters on or near NWR lands for evidence of estrogenic endocrine disruption. Waterbodies sampled included rivers, lakes, impoundments, ponds, and reservoirs. Here we focus on evidence of endocrine disruption in male bass evidenced by gonad histopathology including intersex or abnormal plasma vitellogenin (Vtg) concentrations. During the fall seasons of 2008–2010, we collected male smallmouth bass (n=118) from 12 sites and largemouth bass (n=173) from 27 sites. Intersex in male smallmouth bass was observed at all sites and ranged from 60% to 100%; in male largemouth bass the range was 0–100%. Estrogenicity, as measured using a bioluminescent yeast reporter, was detected above the probable no effects concentration (0.73 ng/L) in ambient water samples from 79% of the NWR sites. Additionally, the presence of androgen receptor and glucocorticoid receptor ligands were noted as measured via novel nuclear receptor translocation assays. Mean plasma Vtg was elevated (>0.2 mg/ml) in male smallmouth bass at four sites and in male largemouth bass at one site. This is the first reconnaissance survey of this scope conducted on US National Wildlife Refuges. The baseline data collected here provide a necessary benchmark for future monitoring and justify more comprehensive NWR-specific studies.
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","language":"English","publisher":"Macmillan Publishers Limited","doi":"10.1038/sdata.2015.76","usgsCitation":"Dowsett, H.J., Robinson, M.M., and Foley, K.M., 2016, A global planktic foraminifer census data set for the Pliocene ocean: Scientific Data, v. 2, Article number: 150076 ; 6 p., https://doi.org/10.1038/sdata.2015.76.","productDescription":"Article number: 150076 ; 6 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069639","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":471412,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/sdata.2015.76","text":"Publisher Index Page"},{"id":325566,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-08","publicationStatus":"PW","scienceBaseUri":"5793443fe4b0eb1ce79e8bd0","contributors":{"authors":[{"text":"Dowsett, Harry J. 0000-0003-1983-7524 hdowsett@usgs.gov","orcid":"https://orcid.org/0000-0003-1983-7524","contributorId":949,"corporation":false,"usgs":true,"family":"Dowsett","given":"Harry","email":"hdowsett@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":643336,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robinson, Marci M. 0000-0002-9200-4097 mmrobinson@usgs.gov","orcid":"https://orcid.org/0000-0002-9200-4097","contributorId":2082,"corporation":false,"usgs":true,"family":"Robinson","given":"Marci","email":"mmrobinson@usgs.gov","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":643337,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Foley, Kevin M. 0000-0003-1013-462X kfoley@usgs.gov","orcid":"https://orcid.org/0000-0003-1013-462X","contributorId":2543,"corporation":false,"usgs":true,"family":"Foley","given":"Kevin","email":"kfoley@usgs.gov","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":643338,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70159877,"text":"70159877 - 2016 - Changes in seasonal climate outpace compensatory density-dependence in eastern brook trout","interactions":[],"lastModifiedDate":"2016-02-01T13:28:26","indexId":"70159877","displayToPublicDate":"2015-12-03T11:45:00","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":"Changes in seasonal climate outpace compensatory density-dependence in eastern brook trout","docAbstract":"Understanding how multiple extrinsic (density-independent) factors and intrinsic (density-dependent) mechanisms influence population dynamics has become increasingly urgent in the face of rapidly changing climates. It is particularly unclear how multiple extrinsic factors with contrasting effects among seasons are related to declines in population numbers and changes in mean body size and whether there is a strong role for density-dependence. The primary goal of this study was to identify the roles of seasonal variation in climate driven environmental direct effects (mean stream flow and temperature) versus density-dependence on population size and mean body size in eastern brook trout (Salvelinus fontinalis). We use data from a 10-year capture-mark-recapture study of eastern brook trout in four streams in Western Massachusetts, USA to parameterize a discrete-time population projection model. The model integrates matrix modeling techniques used to characterize discrete population structures (age, habitat type and season) with integral projection models (IPMs) that characterize demographic rates as continuous functions of organismal traits (in this case body size). Using both stochastic and deterministic analyses we show that decreases in population size are due to changes in stream flow and temperature and that these changes are larger than what can be compensated for through density-dependent responses. We also show that the declines are due mostly to increasing mean stream temperatures decreasing the survival of the youngest age class. In contrast, increases in mean body size over the same period are the result of indirect changes in density with a lesser direct role of climate-driven environmental change.
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U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, CA 95819
http://ca.water.usgs.gov
The Bell’s Vireo (Vireo bellii) is a widespread North American species of bird that has declined since the mid-1960s primarily due to habitat modification. Throughout its range, Bell’s Vireo populations are regulated under varying degrees of protection; however, the species has never been characterized genetically. Therefore, the current taxonomy used to guide management decisions may misrepresent the true evolutionary history for the species. We sequenced 86 individuals for ND2 and genotyped 48 individuals for genome-wide SNPs to identify distinct lineages within Bell’s Vireo. Phylogenetic analyses uncovered two distinct clades that are separated in the arid southwestern United States, near the border of the Chihuahuan and Sonoran Deserts. These clades diverged from each other approximately 1.11–2.04 mya. The timing of diversification, geographic location, and niche modeling of the east/west divergence suggest vicariance as a mode of diversification for these two lineages. Analyses of the SNP dataset provided additional resolution and indicated the Least Bell’s Vireo populations are a distinct evolutionary lineage. Our genetic evidence, together with information from morphology and behavior, suggests that the Bell’s Vireo complex involves two species, each containing two separate subspecies. This new information has implications for the federal, state and other listing status of Bell’s Vireo throughout its range.
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Consequently, the energy balance in urban regions is different from that of natural surfaces. To evaluate the changes in regional climate that could arise due to projected urbanization in the Phoenix-Tucson corridor, Arizona, we applied the coupled WRF-NOAH-UCM (which includes a detailed urban radiation scheme) to this region. Land cover changes were represented using land cover data for 2005 and projections to 2050, and historical North American Regional Reanalysis (NARR) data were used to specify the lateral boundary conditions. Results suggest that temperature changes will be well defined, reflecting the urban heat island (UHI) effect within areas experiencing LULCC. Changes in precipitation are less robust, but seem to indicate reductions in precipitation over the mountainous regions northeast of Phoenix and decreased evening precipitation over the newly-urbanized area.
","language":"English","publisher":"American Meteorological Society","publisherLocation":"Boston, MA","doi":"10.1175/EI-D-15-0027.1","usgsCitation":"Yang, Z., Dominguez, F., Gupta, H., Xubin Zeng, and Norman, L.M., 2016, Urban effects on regional climate: a case study in the Phoenix and Tucson ‘sun’ corridor: Earth Interactions, v. 20, Paper No. 20; 25 p., https://doi.org/10.1175/EI-D-15-0027.1.","productDescription":"Paper No. 20; 25 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064793","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":471417,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/ei-d-15-0027.1","text":"Publisher Index Page"},{"id":311785,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-16","publicationStatus":"PW","scienceBaseUri":"56602441e4b071e7ea544cba","contributors":{"authors":[{"text":"Yang, Zhao","contributorId":150143,"corporation":false,"usgs":false,"family":"Yang","given":"Zhao","email":"","affiliations":[{"id":17918,"text":"1Department of Hydrology and Water Resources, University of Arizona, Tucson, Arizona, USA","active":true,"usgs":false}],"preferred":false,"id":580825,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dominguez, Francina","contributorId":150144,"corporation":false,"usgs":false,"family":"Dominguez","given":"Francina","email":"","affiliations":[{"id":17919,"text":"Department of Atmospheric Science, University of Arizona, Tucson, Arizona, USA","active":true,"usgs":false}],"preferred":false,"id":580826,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gupta, Hoshin","contributorId":150145,"corporation":false,"usgs":false,"family":"Gupta","given":"Hoshin","email":"","affiliations":[{"id":17918,"text":"1Department of Hydrology and Water Resources, University of Arizona, Tucson, Arizona, USA","active":true,"usgs":false}],"preferred":false,"id":580827,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Xubin Zeng","contributorId":150146,"corporation":false,"usgs":false,"family":"Xubin Zeng","affiliations":[{"id":17920,"text":"2Department of Atmospheric Science, University of Arizona, Tucson, Arizona, USA","active":true,"usgs":false}],"preferred":false,"id":580828,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Norman, Laura M. 0000-0002-3696-8406 lnorman@usgs.gov","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":967,"corporation":false,"usgs":true,"family":"Norman","given":"Laura","email":"lnorman@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":580824,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70162129,"text":"70162129 - 2016 - Detection rates of geckos in visual surveys: Turning confounding variables into useful knowledge","interactions":[],"lastModifiedDate":"2016-01-14T08:45:42","indexId":"70162129","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2334,"text":"Journal of Herpetology","active":true,"publicationSubtype":{"id":10}},"title":"Detection rates of geckos in visual surveys: Turning confounding variables into useful knowledge","docAbstract":"Transect surveys without some means of estimating detection probabilities generate population size indices prone to bias because survey conditions differ in time and space. Knowing what causes such bias can help guide the collection of relevant survey covariates, correct the survey data, anticipate situations where bias might be unacceptably large, and elucidate the ecology of target species. We used negative binomial regression to evaluate confounding variables for gecko (primarily Hemidactylus frenatus and Lepidodactylus lugubris) counts on 220-m-long transects surveyed at night, primarily for snakes, on 9,475 occasions. Searchers differed in gecko detection rates by up to a factor of six. The worst and best headlamps differed by a factor of at least two. Strong winds had a negative effect potentially as large as those of searchers or headlamps. More geckos were seen during wet weather conditions, but the effect size was small. Compared with a detection nadir during waxing gibbous (nearly full) moons above the horizon, we saw 28% more geckos during waning crescent moons below the horizon. A sine function suggested that we saw 24% more geckos at the end of the wet season than at the end of the dry season. Fluctuations on a longer timescale also were verified. Disturbingly, corrected data exhibited strong short-term fluctuations that covariates apparently failed to capture. Although some biases can be addressed with measured covariates, others will be difficult to eliminate as a significant source of error in longterm monitoring programs.
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Enlisting the expertise of 284 scientists from 107 organizations throughout Canada, Mexico, and the United States, this text was developed to facilitate comparisons of fish data across regions or time. Here we describe a user-friendly web tool that automates among-sample comparisons in individual fish condition, population length-frequency distributions, and catch per unit effort (CPUE) data collected using AFS standard methods. Currently, the web tool (1) provides instantaneous summaries of almost 4,000 data sets of condition, length frequency, and CPUE of common freshwater fishes collected using standard gears in 43 states and provinces; (2) is easily appended with new standardized field data to update subsequent queries and summaries; (3) compares fish data from a particular water body with continent, ecoregion, and state data summaries; and (4) provides additional information about AFS standard fish sampling including benefits, ongoing validation studies, and opportunities to comment on specific methods. The web tool—programmed in a PHP-based Drupal framework—was supported by several AFS Sections, agencies, and universities and is freely available from the AFS website and fisheriesstandardsampling.org. With widespread use, the online tool could become an important resource for fisheries biologists.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/03632415.2015.1106944","usgsCitation":"Bonar, S.A., Mercado-Silva, N., Rahr, M., Torrey, Y.T., and Cate, A., 2016, A simple web-based tool to compare freshwater fish data collected using AFS standard methods: Fisheries, v. 40, no. 12, p. 580-589, https://doi.org/10.1080/03632415.2015.1106944.","productDescription":"10 p.","startPage":"580","endPage":"589","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059875","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":318144,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"40","issue":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-11","publicationStatus":"PW","scienceBaseUri":"56c6f93ce4b0946c6524071a","contributors":{"authors":[{"text":"Bonar, Scott A. 0000-0003-3532-4067 sbonar@usgs.gov","orcid":"https://orcid.org/0000-0003-3532-4067","contributorId":3712,"corporation":false,"usgs":true,"family":"Bonar","given":"Scott","email":"sbonar@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":619792,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mercado-Silva, Norman","contributorId":18219,"corporation":false,"usgs":true,"family":"Mercado-Silva","given":"Norman","email":"","affiliations":[],"preferred":false,"id":620808,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rahr, Matt","contributorId":167027,"corporation":false,"usgs":false,"family":"Rahr","given":"Matt","email":"","affiliations":[],"preferred":false,"id":620809,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Torrey, Yuta T.","contributorId":167028,"corporation":false,"usgs":false,"family":"Torrey","given":"Yuta","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":620810,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cate, Averill Jr.","contributorId":167030,"corporation":false,"usgs":false,"family":"Cate","given":"Averill","suffix":"Jr.","email":"","affiliations":[],"preferred":false,"id":620811,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70159802,"text":"70159802 - 2016 - A framework to assess biogeochemical response to ecosystem disturbance using nutrient partitioning ratios","interactions":[],"lastModifiedDate":"2017-11-22T17:37:32","indexId":"70159802","displayToPublicDate":"2015-11-24T13:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1478,"text":"Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"A framework to assess biogeochemical response to ecosystem disturbance using nutrient partitioning ratios","docAbstract":"Disturbances affect almost all terrestrial ecosystems, but it has been difficult to identify general principles regarding these influences. To improve our understanding of the long-term consequences of disturbance on terrestrial ecosystems, we present a conceptual framework that analyzes disturbances by their biogeochemical impacts. We posit that the ratio of soil and plant nutrient stocks in mature ecosystems represents a characteristic site property. Focusing on nitrogen (N), we hypothesize that this partitioning ratio (soil N: plant N) will undergo a predictable trajectory after disturbance. We investigate the nature of this partitioning ratio with three approaches: (1) nutrient stock data from forested ecosystems in North America, (2) a process-based ecosystem model, and (3) conceptual shifts in site nutrient availability with altered disturbance frequency. Partitioning ratios could be applied to a variety of ecosystems and successional states, allowing for improved temporal scaling of disturbance events. The generally short-term empirical evidence for recovery trajectories of nutrient stocks and partitioning ratios suggests two areas for future research. First, we need to recognize and quantify how disturbance effects can be accreting or depleting, depending on whether their net effect is to increase or decrease ecosystem nutrient stocks. Second, we need to test how altered disturbance frequencies from the present state may be constructive or destructive in their effects on biogeochemical cycling and nutrient availability. Long-term studies, with repeated sampling of soils and vegetation, will be essential in further developing this framework of biogeochemical response to disturbance.
","language":"English","publisher":"Springer","doi":"10.1007/s10021-015-9934-1","usgsCitation":"Kranabetter, J.M., McLauchlan, K.K., Enders, S.K., Fraterrigo, J.M., Higuera, P., Morris, J.L., Rastetter, E.B., Barnes, R., Buma, B., Gavin, D.G., Gerhart, L.M., Gillson, L., Hietz, P., Mack, M., McNeil, B., and Perakis, S.S., 2016, A framework to assess biogeochemical response to ecosystem disturbance using nutrient partitioning ratios: Ecosystems, v. 19, no. 3, p. 387-395, https://doi.org/10.1007/s10021-015-9934-1.","productDescription":"9 p.","startPage":"387","endPage":"395","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065126","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":471424,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/7970","text":"External Repository"},{"id":311683,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-18","publicationStatus":"PW","scienceBaseUri":"56558a2ce4b071e7ea53ded9","contributors":{"authors":[{"text":"Kranabetter, J. 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2016 - Complex mixtures, complex responses: Assessing pharmaceutical mixtures using field and laboratory approaches","interactions":[],"lastModifiedDate":"2018-08-07T12:20:06","indexId":"70159785","displayToPublicDate":"2015-11-23T11:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Complex mixtures, complex responses: Assessing pharmaceutical mixtures using field and laboratory approaches","docAbstract":"Pharmaceuticals are present in low concentrations (<100 ng/L) in most municipal wastewater effluents but may be elevated locally because of factors such as input from pharmaceutical formulation facilities. Using existing concentration data, the authors assessed pharmaceuticals in laboratory exposures of fathead minnows (Pimephales promelas) and added environmental complexity through effluent exposures. In the laboratory, larval and mature minnows were exposed to a simple opioid mixture (hydrocodone, methadone, and oxycodone), an opioid agonist (tramadol), a muscle relaxant (methocarbamol), a simple antidepressant mixture (fluoxetine, paroxetine, venlafaxine), a sleep aid (temazepam), or a complex mixture of all compounds. Larval minnow response to effluent exposure was not consistent. The 2010 exposures resulted in shorter exposed minnow larvae, whereas the larvae exposed in 2012 exhibited altered escape behavior. Mature minnows exhibited altered hepatosomatic indices, with the strongest effects in females and in mixture exposures. In addition, laboratory-exposed, mature male minnows exposed to all pharmaceuticals (except the selective serotonin reuptake inhibitor mixture) defended nest sites less rigorously than fish in the control group. Tramadol or antidepressant mixture exposure resulted in increased splenic T lymphocytes. Only male minnows exposed to whole effluent responded with increased plasma vitellogenin concentrations. Female minnows exposed to pharmaceuticals (except the opioid mixture) had larger livers, likely as a compensatory result of greater prominence of vacuoles in liver hepatocytes. The observed alteration of apical endpoints central to sustaining fish populations confirms that effluents containing waste streams from pharmaceutical formulation facilities can adversely impact fish populations but that the effects may not be temporally consistent. The present study highlights the importance of including diverse biological endpoints spanning levels of biological organization and life stages when assessing contaminant interactions.
","language":"English","publisher":"Wiley","doi":"10.1002/etc.3147","usgsCitation":"Schoenfuss, H.L., Furlong, E.T., Phillips, P., Scott, T., Kolpin, D.W., Cetkovic-Cvrlje, M., Lesteberg, K.E., and Rearick, D.C., 2016, Complex mixtures, complex responses: Assessing pharmaceutical mixtures using field and laboratory approaches: Environmental Toxicology and Chemistry, v. 35, no. 4, p. 953-965, https://doi.org/10.1002/etc.3147.","productDescription":"13 p.","startPage":"953","endPage":"965","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066098","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":311648,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","issue":"4","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-01","publicationStatus":"PW","scienceBaseUri":"565438a7e4b071e7ea53d48e","contributors":{"authors":[{"text":"Schoenfuss, Heiko L.","contributorId":76409,"corporation":false,"usgs":false,"family":"Schoenfuss","given":"Heiko","email":"","middleInitial":"L.","affiliations":[{"id":13317,"text":"Saint Cloud State University","active":true,"usgs":false}],"preferred":false,"id":580466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Furlong, Edward T. 0000-0002-7305-4603 efurlong@usgs.gov","orcid":"https://orcid.org/0000-0002-7305-4603","contributorId":740,"corporation":false,"usgs":true,"family":"Furlong","given":"Edward","email":"efurlong@usgs.gov","middleInitial":"T.","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":580467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Phillips, Patrick J. pjphilli@usgs.gov","contributorId":149753,"corporation":false,"usgs":true,"family":"Phillips","given":"Patrick J.","email":"pjphilli@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":false,"id":580468,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Scott, Tia-Marie 0000-0002-5677-0544 tia-mariescott@usgs.gov","orcid":"https://orcid.org/0000-0002-5677-0544","contributorId":5122,"corporation":false,"usgs":true,"family":"Scott","given":"Tia-Marie","email":"tia-mariescott@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":580469,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kolpin, Dana W. 0000-0002-3529-6505 dwkolpin@usgs.gov","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":1239,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana","email":"dwkolpin@usgs.gov","middleInitial":"W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":580440,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cetkovic-Cvrlje, Marina","contributorId":150029,"corporation":false,"usgs":false,"family":"Cetkovic-Cvrlje","given":"Marina","email":"","affiliations":[],"preferred":false,"id":580470,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lesteberg, Kelsey E.","contributorId":150030,"corporation":false,"usgs":false,"family":"Lesteberg","given":"Kelsey","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":580471,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rearick, Daniel C.","contributorId":38897,"corporation":false,"usgs":true,"family":"Rearick","given":"Daniel","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":580472,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70159783,"text":"70159783 - 2016 - Effect of antecedent-hydrological conditions on rainfall triggering of debris flows in ash-fall pyroclastic mantled slopes of Campania (southern Italy)","interactions":[],"lastModifiedDate":"2016-09-28T16:29:53","indexId":"70159783","displayToPublicDate":"2015-11-23T10:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2604,"text":"Landslides","active":true,"publicationSubtype":{"id":10}},"title":"Effect of antecedent-hydrological conditions on rainfall triggering of debris flows in ash-fall pyroclastic mantled slopes of Campania (southern Italy)","docAbstract":"Mountainous areas surrounding the Campanian Plain and the Somma-Vesuvius volcano (southern Italy) are among the most risky areas of Italy due to the repeated occurrence of rainfallinduced debris flows along ash-fall pyroclastic soil-mantled slopes. In this geomorphological framework, rainfall patterns, hydrological processes taking place within multi-layered ash-fall pyroclastic deposits and soil antecedent moisture status are the principal factors to be taken into account to assess triggering rainfall conditions and the related hazard. This paper presents the outcomes of an experimental study based on integrated analyses consisting of the reconstruction of physical models of landslides, in situ hydrological monitoring, and hydrological and slope stability modeling, carried out on four representative source areas of debris flows that occurred in May 1998 in the Sarno Mountain Range. The hydrological monitoring was carried out during 2011 using nests of tensiometers and Watermark pressure head sensors and also through a rainfall and air temperature recording station. Time series of measured pressure head were used to calibrate a hydrological numerical model of the pyroclastic soil mantle for 2011, which was re-run for a 12-year period beginning in 2000, given the availability of rainfall and air temperature monitoring data. Such an approach allowed us to reconstruct the regime of pressure head at a daily time scale for a long period, which is representative of about 11 hydrologic years with different meteorological conditions. Based on this simulated time series, average winter and summer hydrological conditions were chosen to carry out hydrological and stability modeling of sample slopes and to identify Intensity- Duration rainfall thresholds by a deterministic approach. Among principal results, the opposing winter and summer antecedent pressure head (soil moisture) conditions were found to exert a significant control on intensity and duration of rainfall triggering events. Going from winter to summer conditions requires a strong increase of intensity and/or duration to induce landslides. The results identify an approach to account for different hazard conditions related to seasonality of hydrological processes inside the ash-fall pyroclastic soil mantle. Moreover, they highlight another important factor of uncertainty that potentially affects rainfall thresholds triggering shallow landslides reconstructed by empirical approaches.
","language":"English","publisher":"Springer","doi":"10.1007/s10346-015-0647-5","usgsCitation":"Napolitano, E., Fusco, F., Baum, R.L., Godt, J.W., and De Vita, P., 2016, Effect of antecedent-hydrological conditions on rainfall triggering of debris flows in ash-fall pyroclastic mantled slopes of Campania (southern Italy): Landslides, v. 13, no. 5, p. 967-983, https://doi.org/10.1007/s10346-015-0647-5.","productDescription":"17 p.","startPage":"967","endPage":"983","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070130","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":311642,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Italy","state":"Campania","otherGeospatial":"Sarno Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 14.616279602050781,\n 40.84550208206526\n ],\n [\n 14.616279602050781,\n 40.89950086329285\n ],\n [\n 14.684257507324219,\n 40.89950086329285\n ],\n [\n 14.684257507324219,\n 40.84550208206526\n ],\n [\n 14.616279602050781,\n 40.84550208206526\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-18","publicationStatus":"PW","scienceBaseUri":"565438a8e4b071e7ea53d490","contributors":{"authors":[{"text":"Napolitano, E.","contributorId":97401,"corporation":false,"usgs":true,"family":"Napolitano","given":"E.","email":"","affiliations":[],"preferred":false,"id":580432,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fusco, F","contributorId":150020,"corporation":false,"usgs":false,"family":"Fusco","given":"F","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":580433,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baum, Rex L. 0000-0001-5337-1970 baum@usgs.gov","orcid":"https://orcid.org/0000-0001-5337-1970","contributorId":1288,"corporation":false,"usgs":true,"family":"Baum","given":"Rex","email":"baum@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":580434,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Godt, Jonathan W. 0000-0002-8737-2493 jgodt@usgs.gov","orcid":"https://orcid.org/0000-0002-8737-2493","contributorId":1166,"corporation":false,"usgs":true,"family":"Godt","given":"Jonathan","email":"jgodt@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":580435,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"De Vita, P.","contributorId":26207,"corporation":false,"usgs":true,"family":"De Vita","given":"P.","affiliations":[],"preferred":false,"id":580436,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70159576,"text":"70159576 - 2016 - Flexible risk metrics for identifying and monitoring conservation-priority species","interactions":[],"lastModifiedDate":"2015-12-14T13:51:40","indexId":"70159576","displayToPublicDate":"2015-11-10T16:45:00","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":"Flexible risk metrics for identifying and monitoring conservation-priority species","docAbstract":"Region-specific conservation programs should have objective, reliable metrics for species prioritization and progress evaluation that are customizable to the goals of a program, easy to comprehend and communicate, and standardized across time. Regional programs may have vastly different goals, spatial coverage, or management agendas, and one-size-fits-all schemes may not always be the best approach. We propose a quantitative and objective framework for generating metrics for prioritizing species that is straightforward to implement and update, customizable to different spatial resolutions, and based on readily available time-series data. This framework is also well-suited to handling missing-data and observer error. We demonstrate this approach using North American Breeding Bird Survey (NABBS) data to identify conservation priority species from a list of over 300 landbirds across 33 bird conservation regions (BCRs). To highlight the flexibility of the framework for different management goals and timeframes we calculate two different metrics. The first identifies species that may be inadequately monitored by NABBS protocols in the near future (TMT, time to monitoring threshold), and the other identifies species likely to decline significantly in the near future based on recent trends (TPD, time to percent decline). Within the individual BCRs we found up to 45% (mean 28%) of the species analyzed had overall declining population trajectories, which could result in up to 37 species declining below a minimum NABBS monitoring threshold in at least one currently occupied BCR within the next 50 years. Additionally, up to 26% (mean 8%) of the species analyzed within the individual BCRs may decline by 30% within the next decade. Conservation workers interested in conserving avian diversity and abundance within these BCRs can use these metrics to plan alternative monitoring schemes or highlight the urgency of those populations experiencing the fastest declines. However, this framework is adaptable to many taxa besides birds where abundance time-series data are available.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2015.10.020","usgsCitation":"Stanton, J.C., Semmens, B.X., McKann, P.C., Will, T., and Thogmartin, W.E., 2016, Flexible risk metrics for identifying and monitoring conservation-priority species: Ecological Indicators, v. 61, no. 2, p. 683-692, https://doi.org/10.1016/j.ecolind.2015.10.020.","productDescription":"10 p.","startPage":"683","endPage":"692","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066945","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":471432,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2015.10.020","text":"Publisher Index Page"},{"id":311180,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","volume":"61","issue":"2","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56431532e4b0aafbcd017fa4","chorus":{"doi":"10.1016/j.ecolind.2015.10.020","url":"http://dx.doi.org/10.1016/j.ecolind.2015.10.020","publisher":"Elsevier BV","authors":"Stanton Jessica C., Semmens Brice X., McKann Patrick C., Will Tom, Thogmartin Wayne E.","journalName":"Ecological Indicators","publicationDate":"2/2016"},"contributors":{"authors":[{"text":"Stanton, Jessica C. 0000-0002-6225-3703 jcstanton@usgs.gov","orcid":"https://orcid.org/0000-0002-6225-3703","contributorId":5634,"corporation":false,"usgs":true,"family":"Stanton","given":"Jessica","email":"jcstanton@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":579534,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Semmens, Brice X.","contributorId":149775,"corporation":false,"usgs":false,"family":"Semmens","given":"Brice","email":"","middleInitial":"X.","affiliations":[{"id":17820,"text":"Scripps Institution of Oceanography, University of California, San Diego","active":true,"usgs":false}],"preferred":false,"id":579535,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McKann, Patrick C.","contributorId":149776,"corporation":false,"usgs":false,"family":"McKann","given":"Patrick","email":"","middleInitial":"C.","affiliations":[{"id":6733,"text":"former UMESC employee, USGS","active":true,"usgs":false}],"preferred":false,"id":579536,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Will, Tom","contributorId":149777,"corporation":false,"usgs":false,"family":"Will","given":"Tom","email":"","affiliations":[{"id":17821,"text":"U.S. Fish and Wildlife Service, Division of Migratory Birds","active":true,"usgs":false}],"preferred":false,"id":579537,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":579538,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70159584,"text":"70159584 - 2016 - Density dependence, whitebark pine, and vital rates of grizzly bears","interactions":[],"lastModifiedDate":"2016-04-13T12:09:01","indexId":"70159584","displayToPublicDate":"2015-11-10T15:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Density dependence, whitebark pine, and vital rates of grizzly bears","docAbstract":"Understanding factors influencing changes in population trajectory is important for effective wildlife management, particularly for populations of conservation concern. Annual population growth of the grizzly bear (Ursus arctos) population in the Greater Yellowstone Ecosystem, USA has slowed from 4.2–7.6% during 1983–2001 to 0.3–2.2% during 2002–2011. Substantial changes in availability of a key food source and bear population density have occurred. Whitebark pine (Pinus albicaulis), the seeds of which are a valuable but variable fall food for grizzly bears, has experienced substantial mortality primarily due to a mountain pine beetle (Dendroctonus ponderosae) outbreak that started in the early 2000s. Positive growth rates of grizzly bears have resulted in populations reaching high densities in some areas and have contributed to continued range expansion. We tested research hypotheses to examine if changes in vital rates detected during the past decade were more associated with whitebark pine decline or, alternatively, increasing grizzly bear density. We focused our assessment on known-fate data to estimate survival of cubs-of-the-year (cubs), yearlings, and independent bears (≥2 yrs), and reproductive transition of females from having no offspring to having cubs. We used spatially and temporally explicit indices for grizzly bear density and whitebark pine mortality as individual covariates. Models indicated moderate support for an increase in survival of independent male bears over 1983–2012, whereas independent female survival did not change. Cub survival, yearling survival, and reproductive transition from no offspring to cubs all changed during the 30-year study period, with lower rates evident during the last 10–15 years. Cub survival and reproductive transition were negatively associated with an index of grizzly bear density, indicating greater declines where bear densities were higher. Our analyses did not support a similar relationship for the index of whitebark pine mortality. The results of our study support the interpretation that slowing of population growth during the last decade was associated more with increasing grizzly bear density than the decline in whitebark pine. Grizzly bear density and its potential effect on vital rates and population trajectory warrant consideration for management of the grizzly bear population in the Greater Yellowstone Ecosystem.
","language":"English","publisher":"Wildlife Society","doi":"10.1002/jwmg.1005","usgsCitation":"van Manen, F.T., Haroldson, M.A., Bjornlie, D., Ebinger, M.R., Thompson, D.J., Costello, C., and White, G.C., 2016, Density dependence, whitebark pine, and vital rates of grizzly bears: Journal of Wildlife Management, v. 80, no. 2, p. 300-313, https://doi.org/10.1002/jwmg.1005.","productDescription":"14 p.","startPage":"300","endPage":"313","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059669","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":471433,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.1005","text":"Publisher Index Page"},{"id":311170,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Grand Teton National Park, Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.181396484375,\n 42.44778143462245\n ],\n [\n -112.181396484375,\n 45.69083283645816\n ],\n [\n -108.62182617187499,\n 45.69083283645816\n ],\n [\n -108.62182617187499,\n 42.44778143462245\n ],\n [\n -112.181396484375,\n 42.44778143462245\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"80","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-22","publicationStatus":"PW","scienceBaseUri":"56431532e4b0aafbcd017fa0","contributors":{"authors":[{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":579577,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haroldson, Mark A. 0000-0002-7457-7676 mharoldson@usgs.gov","orcid":"https://orcid.org/0000-0002-7457-7676","contributorId":1773,"corporation":false,"usgs":true,"family":"Haroldson","given":"Mark","email":"mharoldson@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":579578,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bjornlie, Daniel D.","contributorId":145512,"corporation":false,"usgs":false,"family":"Bjornlie","given":"Daniel D.","affiliations":[{"id":16140,"text":"Wyoming Game & Fish Department, Large Carnivore Section, Lander, Wyoming 82520, USA","active":true,"usgs":false}],"preferred":false,"id":579579,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ebinger, Michael R. mebinger@usgs.gov","contributorId":5771,"corporation":false,"usgs":true,"family":"Ebinger","given":"Michael","email":"mebinger@usgs.gov","middleInitial":"R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":579580,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thompson, Daniel J.","contributorId":149795,"corporation":false,"usgs":false,"family":"Thompson","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":5116,"text":"Large Carnivore Section, Wyoming Game & Fish Department, 260 Buena Vista, Lander, WY 82520, USA","active":true,"usgs":false}],"preferred":false,"id":579581,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Costello, Cecily M.","contributorId":145510,"corporation":false,"usgs":false,"family":"Costello","given":"Cecily M.","affiliations":[{"id":5117,"text":"University of Montana, College of Forestry and Conservation, University Hall, Room 309, Missoula, MT 59812, USA","active":true,"usgs":false}],"preferred":false,"id":579582,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"White, Gary C.","contributorId":26256,"corporation":false,"usgs":true,"family":"White","given":"Gary","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":579583,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70158684,"text":"ofr20151195 - 2016 - Profiles of reservoir properties of oil-bearing plays for selected petroleum provinces in the United States","interactions":[],"lastModifiedDate":"2018-07-31T10:13:13","indexId":"ofr20151195","displayToPublicDate":"2015-11-05T14:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1195","title":"Profiles of reservoir properties of oil-bearing plays for selected petroleum provinces in the United States","docAbstract":"Profiles of reservoir properties of oil-bearing plays for selected petroleum provinces in the United States were developed to characterize the database to be used for a potential assessment by the U.S. Geological Survey (USGS) of oil that would be technically recoverable by the application of enhanced oil recovery methods using injection of carbon dioxide (CO2-EOR). The USGS assessment methodology may require reservoir-level data for the purposes of screening conventional oil reservoirs and projecting CO2-EOR performance in terms of the incremental recoverable oil. The information used in this report is based on reservoir properties from the “Significant Oil and Gas Fields of the United States Database” prepared by Nehring Associates, Inc. (2012). As described by Nehring Associates, Inc., the database “covers all producing provinces (basins) in the United States except the Appalachian Basin and the Cincinnati Arch.”
\nUnder contract to the USGS, INTEK, Inc., developed and applied algorithms to estimate variables useful in projecting EOR performance at the reservoir level and to complete some partial reservoir records of the “Significant Oil and Gas Fields of the United States Database” (Nehring Associates, Inc., 2012). The augmented database is referred to here as the “Comprehensive Resource Database” (CRD).
\nThe CRD play and province classification scheme corresponds to the definitions used in the 1995 USGS National Oil and Gas Assessment (NOGA). The profiles in this report consist of a resource table and a six-part figure showing the variation of reservoir parameters selected because of their importance in the choice of a miscible or immiscible method for CO2-EOR and in the assessment of potential oil recovery using the EOR processes. A subset of these reservoirs may be available for either miscible- or immiscible-type flooding for CO2-EOR. Plays with fewer than 10 oil reservoirs were not graphed and were omitted from the province profiles. For this report and for the purposes of screening reservoirs as candidates for the application of CO2-EOR methods, oil reservoirs must have no more than 10,000 standard cubic feet of natural gas per barrel of oil at surface conditions. Oil-bearing plays presented in this report must contain at least one oil reservoir so defined.
\nThe profile plots allow geologists to evaluate the range of empirical and default values of the oil reservoir characteristics within a play and across plays that belong to the same province in the CRD. For most plays, the default estimates can be identified by the stacking of points at a single value on strip charts in the profiles. Reasonable default values should be within the range of the reservoir parameter values assigned by Nehring Associates, Inc. (2012), to reservoirs of that particular play.
\nEach province profile figure consists of five strip charts and a boxplot. The five strip charts display for individual plays the following reservoir-fluid and reservoir properties: A, oil density (American Petroleum Institute [API] gravity in degrees); B, computed pseudo-Dykstra-Parsons coefficient; C, reservoir porosity (in percent); D, reservoir permeability (in millidarcies); and E, estimates of the original oil in place (OOIP) per unit volume of reservoir rock (in barrels per acre-foot). The OOIP per unit volume of reservoir rock is an indicator of the relative richness of the oil reservoir and is derived from estimates in the CRD of OOIP, reservoir acreage, and net pay. The net pay is the interval of productive reservoir rock. The same data for OOIP per unit volume are graphed as a strip chart (E) and a boxplot (F).
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\"}}]}","edition":"Version 1: Originally posted November 5, 2015: Version 1.1: February 2016","contact":"Eastern Energy Resources Science Center
U.S. Geological Survey
MS 956 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
http://energy.usgs.gov/GeneralInfo/
ScienceCenters/Eastern.aspx
Speed regulations of watercraft in protected areas are designed to reduce lethal collisions with wildlife but can have economic consequences. We present a quantitative framework for investigating the risk of deadly collisions between boats and wildlife.
\nWe apply encounter rate theory to demonstrate how marine mammal-boat encounter rate can be used to predict the expected number of deaths associated with management scenarios. We illustrate our approach with management scenarios for two endangered species: the Florida manatee Trichechus manatus latirostris and the North Atlantic right whale Eubalaena glacialis. We used a Monte Carlo simulation approach to demonstrate the uncertainty that is associated with our estimate of relative mortality.
\nWe show that encounter rate increased with vessel speed but that the expected number of encounters varies depending on the boating activities considered. For instance, in a scenario involving manatees and boating activities such as water skiing, the expected number of encounters in a given area (in a fixed time interval) increased with vessel speed. In another scenario in which a vessel made a transit of fixed length the expected number of encounters decreases slightly with boat speed. In both cases the expected number of encounters increased with distanced travelled by the boat. For whales, we found a slight reduction (~0.1%) in the number of encounters under a scenario where speed is unregulated; this reduction, however, is negligible, and overall expected relative mortality was ~30% lower under the scenario with speed regulation. The probability of avoidance by the animal or vessel was set to 0 because of lack of data, but we explored the importance of this parameter on the model predictions. In fact, expected relative mortality under speed regulations decreases even further when the probability of avoidance is a decreasing function of vessel speed.
\nBy applying encounter rate theory to the case of boat collisions with marine mammals, we gained new insights about encounter processes between wildlife and watercraft. Our work emphasizes the importance of considering uncertainty when estimating wildlife mortality. Finally, our findings are relevant to other systems and ecological processes involving the encounter between moving agents.
","language":"English","publisher":"Wiley","doi":"10.1111/2041-210X.12447","usgsCitation":"Martin, J., Sabatier, Q., Gowan, T.A., Giraud, C., Gurarie, E., Calleson, S., Ortega-Ortiz, J.G., Deutsch, C., Rycyk, A., and Koslovsky, S., 2016, A quantitative framework for estimating risk of collision between marine mammals and boats: Methods in Ecology and Evolution, v. 7, no. 1, p. 42-50, https://doi.org/10.1111/2041-210X.12447.","productDescription":"9 p.","startPage":"42","endPage":"50","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060059","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471437,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.12447","text":"Publisher Index Page"},{"id":310761,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"1","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-12","publicationStatus":"PW","scienceBaseUri":"5633357ce4b048076347ee95","contributors":{"authors":[{"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":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":578671,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sabatier, Quentin","contributorId":149517,"corporation":false,"usgs":false,"family":"Sabatier","given":"Quentin","email":"","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":578672,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gowan, Timothy A.","contributorId":138595,"corporation":false,"usgs":false,"family":"Gowan","given":"Timothy","email":"","middleInitial":"A.","affiliations":[{"id":12456,"text":"former USGS scientist","active":true,"usgs":false}],"preferred":false,"id":578673,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Giraud, Christophe","contributorId":149518,"corporation":false,"usgs":false,"family":"Giraud","given":"Christophe","email":"","affiliations":[{"id":17764,"text":"Universite Paris Sud","active":true,"usgs":false}],"preferred":false,"id":578674,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gurarie, Eliezer","contributorId":149519,"corporation":false,"usgs":false,"family":"Gurarie","given":"Eliezer","email":"","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":578675,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Calleson, Scott","contributorId":149520,"corporation":false,"usgs":false,"family":"Calleson","given":"Scott","email":"","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":578676,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ortega-Ortiz, Joel G.","contributorId":149521,"corporation":false,"usgs":false,"family":"Ortega-Ortiz","given":"Joel","email":"","middleInitial":"G.","affiliations":[{"id":5112,"text":"University of Miami","active":true,"usgs":false}],"preferred":false,"id":578677,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Deutsch, Charles J.","contributorId":64135,"corporation":false,"usgs":true,"family":"Deutsch","given":"Charles J.","affiliations":[],"preferred":false,"id":578678,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rycyk, Athena","contributorId":149522,"corporation":false,"usgs":false,"family":"Rycyk","given":"Athena","email":"","affiliations":[{"id":7092,"text":"Florida State University","active":true,"usgs":false}],"preferred":false,"id":578679,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Koslovsky, Stacie M.","contributorId":149523,"corporation":false,"usgs":false,"family":"Koslovsky","given":"Stacie M.","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":578680,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70159481,"text":"70159481 - 2016 - Fluid spatial dynamics of West Nile virus in the USA: Rapid spread in a permissive host environment","interactions":[],"lastModifiedDate":"2016-10-11T11:32:45","indexId":"70159481","displayToPublicDate":"2015-10-28T11:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2497,"text":"Journal of Virology","active":true,"publicationSubtype":{"id":10}},"title":"Fluid spatial dynamics of West Nile virus in the USA: Rapid spread in a permissive host environment","docAbstract":"The introduction of West Nile virus (WNV) into North America in 1999 is a classical example of viral emergence in a new environment, with its subsequent dispersion across the continent having a major impact on local bird populations. Despite the importance of this epizootic, the pattern, dynamics and determinants of WNV spread in its natural hosts remain uncertain. In particular, it is unclear whether the virus encountered major barriers to transmission, or spread in an unconstrained manner, and if specific viral lineages were favored over others indicative of intrinsic differences in fitness. To address these key questions in WNV evolution and ecology we sequenced the complete genomes of approximately 300 avian isolates sampled across the USA between 2001-2012. Phylogenetic analysis revealed a relatively ‘star-like' tree structure, indicative of explosive viral spread in US, although with some replacement of viral genotypes through time. These data are striking in that viral sequences exhibit relatively limited clustering according to geographic region, particularly for those viruses sampled from birds, and no strong phylogenetic association with well sampled avian species. The genome sequence data analysed here also contain relatively little evidence for adaptive evolution, particularly on structural proteins, suggesting that most viral lineages are of similar fitness, and that WNV is well adapted to the ecology of mosquito vectors and diverse avian hosts in the USA. In sum, the molecular evolution of WNV in North America depicts a largely unfettered expansion within a permissive host and geographic population with little evidence of major adaptive barriers.
","language":"English","publisher":"American Society for Microbiology","publisherLocation":"Baltimore, MD","doi":"10.1128/JVI.02305-15","usgsCitation":"Di Giallonardo, F., Geoghegan, J.L., Docherty, D.E., McLean, R., Zody, M.C., Qu, J., Yang, X., Birren, B.W., Malboeuf, C.M., Newman, R., Ip, S., and Holmes, E.C., 2016, Fluid spatial dynamics of West Nile virus in the USA: Rapid spread in a permissive host environment: Journal of Virology, v. 90, no. 2, p. 862-872, https://doi.org/10.1128/JVI.02305-15.","productDescription":"11 p.","startPage":"862","endPage":"872","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068684","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":471439,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1128/jvi.02305-15","text":"External 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beaches","interactions":[],"lastModifiedDate":"2021-08-25T16:49:10.727248","indexId":"70159828","displayToPublicDate":"2015-10-28T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Prototypic automated continuous recreational water quality monitoring of nine Chicago beaches","docAbstract":"Predictive empirical modeling is used in many locations worldwide as a rapid, alternative recreational water quality management tool to eliminate delayed notifications associated with traditional fecal indicator bacteria (FIB) culturing (referred to as the persistence model, PM) and to prevent errors in releasing swimming advisories. The goal of this study was to develop a fully automated water quality management system for multiple beaches using predictive empirical models (EM) and state-of-the-art technology. Many recent EMs rely on samples or data collected manually, which adds to analysis time and increases the burden to the beach manager. In this study, data from water quality buoys and weather stations were transmitted through cellular telemetry to a web hosting service. An executable program simultaneously retrieved and aggregated data for regression equations and calculated EM results each morning at 9:30 AM; results were transferred through RSS feed to a website, mapped to each beach, and received by the lifeguards to be posted at the beach. Models were initially developed for five beaches, but by the third year, 21 beaches were managed using refined and validated modeling systems. The adjusted R2 of the regressions relating Escherichia coli to hydrometeorological variables for the EMs were greater than those for the PMs, and ranged from 0.220 to 0.390 (2011) and 0.103 to 0.381 (2012). Validation results in 2013 revealed reduced predictive capabilities; however, three of the originally modeled beaches showed improvement in 2013 compared to 2012. The EMs generally showed higher accuracy and specificity than those of the PMs, and sensitivity was low for both approaches. In 2012 EM accuracy was 70–97%; specificity, 71–100%; and sensitivity, 0–64% and in 2013 accuracy was 68–97%; specificity, 73–100%; and sensitivity 0–36%. Factors that may have affected model capabilities include instrument malfunction, non-point source inputs, and sparse calibration data. The modeling system developed is the most extensive, fully-automated system for recreational water quality developed to date. Key insights for refining and improving large-scale empirical models for beach management have been developed through this multi-year effort.
","language":"English","publisher":"Elsevier","publisherLocation":"Oxford, UK","doi":"10.1016/j.jenvman.2015.10.011","usgsCitation":"Shively, D., Nevers, M., Breitenbach, C., Phanikumar, M., Przybyla-Kelly, K., Spoljaric, A., and Whitman, R.L., 2016, Prototypic automated continuous recreational water quality monitoring of nine Chicago beaches: Journal of Environmental Management, v. 166, p. 285-293, https://doi.org/10.1016/j.jenvman.2015.10.011.","productDescription":"9 p.","startPage":"285","endPage":"293","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061853","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":311747,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois","city":"Chicago","otherGeospatial":"Great Lakes, Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.65647888183594,\n 42.03552434403621\n ],\n [\n -87.62626647949217,\n 41.99011884096809\n ],\n [\n -87.615966796875,\n 41.91454130182335\n ],\n [\n -87.59193420410156,\n 41.89767733570708\n ],\n [\n -87.56309509277344,\n 41.80766096027984\n ],\n [\n -87.53700256347656,\n 41.7672146942102\n ],\n [\n -87.52601623535156,\n 41.75338543627463\n ],\n [\n -87.52670288085938,\n 41.73084248230534\n ],\n [\n -87.52395629882812,\n 41.70931682567252\n ],\n [\n -87.53837585449219,\n 41.699063978799174\n ],\n [\n -87.63107299804688,\n 41.840408844786396\n ],\n [\n -87.681884765625,\n 41.99522219923445\n ],\n [\n -87.69218444824219,\n 42.02838405374952\n ],\n [\n -87.68119812011717,\n 42.037054301883806\n ],\n [\n -87.659912109375,\n 42.03603433407788\n ],\n [\n -87.65647888183594,\n 42.03552434403621\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"166","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"565d8140e4b071e7ea543480","contributors":{"authors":[{"text":"Shively, Dawn","contributorId":150065,"corporation":false,"usgs":false,"family":"Shively","given":"Dawn","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":580618,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nevers, Meredith 0000-0001-6963-6734 mnevers@usgs.gov","orcid":"https://orcid.org/0000-0001-6963-6734","contributorId":2013,"corporation":false,"usgs":true,"family":"Nevers","given":"Meredith","email":"mnevers@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":580617,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Breitenbach, Cathy","contributorId":150066,"corporation":false,"usgs":false,"family":"Breitenbach","given":"Cathy","email":"","affiliations":[{"id":17899,"text":"Chicago Park District","active":true,"usgs":false}],"preferred":false,"id":580619,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Phanikumar, Mantha S.","contributorId":17888,"corporation":false,"usgs":true,"family":"Phanikumar","given":"Mantha S.","affiliations":[],"preferred":false,"id":580623,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Przybyla-Kelly, Kasia","contributorId":150067,"corporation":false,"usgs":false,"family":"Przybyla-Kelly","given":"Kasia","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":580620,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Spoljaric, Ashley M.","contributorId":150068,"corporation":false,"usgs":false,"family":"Spoljaric","given":"Ashley M.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":580621,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Whitman, Richard L.","contributorId":150069,"corporation":false,"usgs":false,"family":"Whitman","given":"Richard","email":"","middleInitial":"L.","affiliations":[{"id":12443,"text":"U.S. Geological Survey (retired)","active":true,"usgs":false}],"preferred":false,"id":580622,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70159410,"text":"70159410 - 2016 - Integrating spatially explicit indices of abundance and habitat quality: an applied example for greater sage-grouse management","interactions":[],"lastModifiedDate":"2016-01-11T10:54:13","indexId":"70159410","displayToPublicDate":"2015-10-27T11:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Integrating spatially explicit indices of abundance and habitat quality: an applied example for greater sage-grouse management","docAbstract":"Predictive species distributional models are a cornerstone of wildlife conservation planning. Constructing such models requires robust underpinning science that integrates formerly disparate data types to achieve effective species management.
\nGreater sage-grouse Centrocercus urophasianus, hereafter “sage-grouse” populations are declining throughout sagebrush-steppe ecosystems in North America, particularly within the Great Basin, which heightens the need for novel management tools that maximize use of available information.
\nHerein, we improve upon existing species distribution models by combining information about sage-grouse habitat quality, distribution, and abundance from multiple data sources. To measure habitat, we created spatially explicit maps depicting habitat selection indices (HSI) informed by > 35 500 independent telemetry locations from > 1600 sage-grouse collected over 15 years across much of the Great Basin. These indices were derived from models that accounted for selection at different spatial scales and seasons. A region-wide HSI was calculated using the HSI surfaces modelled for 12 independent subregions and then demarcated into distinct habitat quality classes.
\nWe also employed a novel index to describe landscape patterns of sage-grouse abundance and space use (AUI). The AUI is a probabilistic composite of: (i) breeding density patterns based on the spatial configuration of breeding leks and associated trends in male attendance; and (ii) year-round patterns of space use indexed by the decreasing probability of use with increasing distance to leks. The continuous AUI surface was then reclassified into two classes representing high and low/no use and abundance.
\nSynthesis and applications. Using the example of sage-grouse, we demonstrate how the joint application of indices of habitat selection, abundance, and space use derived from multiple data sources yields a composite map that can guide effective allocation of management intensity across multiple spatial scales. As applied to sage-grouse, the composite map identifies spatially explicit management categories within sagebrush steppe that are most critical to sustaining sage-grouse populations as well as those areas where changes in land use would likely have minimal impact. Importantly, collaborative efforts among stakeholders guide which intersections of habitat selection indices and abundance and space use classes are used to define management categories. Because sage-grouse are an umbrella species, our joint-index modelling approach can help target effective conservation for other sagebrush obligate species, and can be readily applied to species in other ecosystems with similar life histories, such as central-placed breeding.
\nThe organizers of the 2014 US National Climate Assessment (NCA) made a concerted effort to reach out to and collaborate with Indigenous peoples, resulting in the most comprehensive information to date on climate change impacts to Indigenous peoples in a US national assessment. Yet, there is still much room for improvement in assessment processes to ensure adequate recognition of Indigenous perspectives and Indigenous knowledge systems. This article discusses the process used in creating the Indigenous Peoples, Land, and Resources NCA chapter by a team comprised of tribal members, agencies, academics, and non-governmental organizations, who worked together to solicit, collect, and synthesize traditional knowledges and data from a diverse array of Indigenous communities across the US. It also discusses the synergy and discord between traditional knowledge systems and science and the emergence of cross-cutting issues and vulnerabilities for Indigenous peoples. The challenges of coalescing information about climate change and its impacts on Indigenous communities are outlined along with recommendations on the types of information to include in future assessment outputs. We recommend that future assessments – not only NCA, but other relevant local, regional, national, and international efforts aimed at the translation of climate information and assessments into meaningful actions – should support integration of Indigenous perspectives in a sustained way that builds respectful relationships and effectively engages Indigenous communities. Given the large number of tribes in the US and the current challenges and unique vulnerabilities of Indigenous communities, a special report focusing solely on climate change and Indigenous peoples is warranted.
This article is part of a special issue on “The National Climate Assessment: Innovations in Science and Engagement” edited by Katharine Jacobs, Susanne Moser, and James Buizer.
The lone star tick, Amblyomma americanum, is a disease vector of significance for human and animal health throughout much of the eastern United States. To model the potential effects of climate change on this tick, a better understanding is needed of the relative roles of temperature-dependent and temperature-independent (day-length-dependent behavioral or morphogenetic diapause) processes acting on the tick lifecycle. In this study, we explored the roles of these processes by simulating seasonal activity patterns using models with site-specific temperature and day-length-dependent processes. We first modeled the transitions from engorged larvae to feeding nymphs, engorged nymphs to feeding adults, and engorged adult females to feeding larvae. The simulated seasonal patterns were compared against field observations at three locations in United States. Simulations suggested that 1) during the larva-to-nymph transition, some larvae undergo no diapause while others undergo morphogenetic diapause of engorged larvae; 2) molted adults undergo behavioral diapause during the transition from nymph-to-adult; and 3) there is no diapause during the adult-to-larva transition. A model constructed to simulate the full lifecycle of A. americanum successfully predicted observed tick activity at the three U.S. study locations. Some differences between observed and simulated seasonality patterns were observed, however, identifying the need for research to refine some model parameters. In simulations run using temperature data for Montreal, deterministic die-out of A. americanum populations did not occur, suggesting the possibility that current climate in parts of southern Canada is suitable for survival and reproduction of this tick.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/jme/tjv150","usgsCitation":"Ludwig, A., Ginsberg, H., Hickling, G., and Ogden, N.H., 2016, A dynamic population model to investigate effects of climate and climate-independent factors on the lifecycle of the tick Amblyomma americanum (Acari: Ixodidae): Journal of Medical Entomology, v. 53, no. 1, p. 99-115, https://doi.org/10.1093/jme/tjv150.","productDescription":"17 p.","startPage":"99","endPage":"115","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-067271","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":486932,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.uri.edu/pls_facpubs/144","text":"External Repository"},{"id":312845,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-26","publicationStatus":"PW","scienceBaseUri":"567bd3bae4b0a04ef491a1ee","contributors":{"authors":[{"text":"Ludwig, Antoinette","contributorId":147666,"corporation":false,"usgs":false,"family":"Ludwig","given":"Antoinette","email":"","affiliations":[{"id":16890,"text":"Public Health Agency of Canada","active":true,"usgs":false}],"preferred":false,"id":572282,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ginsberg, Howard S. 0000-0002-4933-2466 hginsberg@usgs.gov","orcid":"https://orcid.org/0000-0002-4933-2466","contributorId":147665,"corporation":false,"usgs":true,"family":"Ginsberg","given":"Howard S.","email":"hginsberg@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":572281,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hickling, Graham J.","contributorId":88639,"corporation":false,"usgs":true,"family":"Hickling","given":"Graham J.","affiliations":[],"preferred":false,"id":572283,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ogden, Nicholas H.","contributorId":147667,"corporation":false,"usgs":false,"family":"Ogden","given":"Nicholas","email":"","middleInitial":"H.","affiliations":[{"id":16890,"text":"Public Health Agency of Canada","active":true,"usgs":false}],"preferred":false,"id":572284,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159200,"text":"70159200 - 2016 - Population trends, bend use relative to available habitat and within-river-bend habitat use of eight indicator species of Missouri and Lower Kansas River benthic fishes: 15 years after baseline assessment","interactions":[],"lastModifiedDate":"2016-01-11T10:52:23","indexId":"70159200","displayToPublicDate":"2015-10-20T11:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Population trends, bend use relative to available habitat and within-river-bend habitat use of eight indicator species of Missouri and Lower Kansas River benthic fishes: 15 years after baseline assessment","docAbstract":"A baseline assessment of the Missouri River fish community and species-specific habitat use patterns conducted from 1996 to 1998 provided the first comprehensive analysis of Missouri River benthic fish population trends and habitat use in the Missouri and Lower Yellowstone rivers, exclusive of reservoirs, and provided the foundation for the present Pallid Sturgeon Population Assessment Program (PSPAP). Data used in such studies are frequently zero inflated. To address this issue, the zero-inflated Poisson (ZIP) model was applied. This follow-up study is based on PSPAP data collected up to 15 years later along with new understanding of how habitat characteristics among and within bends affect habitat use of fish species targeted by PSPAP, including pallid sturgeon. This work demonstrated that a large-scale, large-river, PSPAP-type monitoring program can be an effective tool for assessing population trends and habitat usage of large-river fish species. Using multiple gears, PSPAP was effective in monitoring shovelnose and pallid sturgeons, sicklefin, shoal and sturgeon chubs, sand shiner, blue sucker and sauger. For all species, the relationship between environmental variables and relative abundance differed, somewhat, among river segments suggesting the importance of the overall conditions of Upper and Middle Missouri River and Lower Missouri and Kansas rivers on the habitat usage patterns exhibited. Shoal and sicklefin chubs exhibited many similar habitat usage patterns; blue sucker and shovelnose sturgeon also shared similar responses. For pallid sturgeon, the primary focus of PSPAP, relative abundance tended to increase in Upper and Middle Missouri River paralleling stocking efforts, whereas no evidence of an increasing relative abundance was found in the Lower Missouri River despite stocking.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.2846","usgsCitation":"Wildhaber, M.L., Yang, W., and Arab, A., 2016, Population trends, bend use relative to available habitat and within-river-bend habitat use of eight indicator species of Missouri and Lower Kansas River benthic fishes: 15 years after baseline assessment: River Research and Applications, v. 32, p. 36-65, https://doi.org/10.1002/rra.2846.","productDescription":"30 p.","startPage":"36","endPage":"65","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055609","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":310114,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Kansas River, Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.99414062499999,\n 45.72152152227954\n ],\n [\n -113.719482421875,\n 49.49667452747045\n ],\n [\n -99.7119140625,\n 49.01625665778159\n ],\n [\n -96.591796875,\n 45.90529985724796\n ],\n [\n -94.932861328125,\n 43.52465500687185\n ],\n [\n -93.09814453125,\n 40.60561205826018\n ],\n [\n -89.97802734375,\n 38.865374851611634\n ],\n [\n -89.835205078125,\n 36.50963615733049\n ],\n [\n -94.537353515625,\n 36.500805317604794\n ],\n [\n -102.095947265625,\n 39.99395569397331\n ],\n [\n -114.08203125,\n 43.96119063892024\n ],\n [\n -113.99414062499999,\n 45.72152152227954\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"32","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2014-11-04","publicationStatus":"PW","scienceBaseUri":"562757a8e4b0d158f5926505","contributors":{"authors":[{"text":"Wildhaber, Mark L. 0000-0002-6538-9083 mwildhaber@usgs.gov","orcid":"https://orcid.org/0000-0002-6538-9083","contributorId":1386,"corporation":false,"usgs":true,"family":"Wildhaber","given":"Mark","email":"mwildhaber@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":577837,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yang, Wen-Hsi","contributorId":45228,"corporation":false,"usgs":true,"family":"Yang","given":"Wen-Hsi","email":"","affiliations":[],"preferred":false,"id":577838,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arab, Ali","contributorId":75002,"corporation":false,"usgs":true,"family":"Arab","given":"Ali","email":"","affiliations":[],"preferred":false,"id":577839,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70159637,"text":"70159637 - 2016 - Mycobacterial infection in Northern snakehead (Channa argus) from the Potomac River catchment","interactions":[],"lastModifiedDate":"2018-08-08T10:38:02","indexId":"70159637","displayToPublicDate":"2015-10-16T03:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2286,"text":"Journal of Fish Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Mycobacterial infection in Northern snakehead (Channa argus) from the Potomac River catchment","docAbstract":"The Northern snakehead, Channa argus (Cantor), is a non-native predatory fish that has become established regionally in some temperate freshwater habitats within the United States. Over the past decade, Northern snakehead populations have developed within aquatic ecosystems throughout the eastern USA, including the Potomac River system within Virginia, Maryland and Washington, D.C. Since this species was initially observed in this region in 2002, the population has expanded considerably (Odenkirk & Owens 2007). In the Chesapeake Bay watershed, populations of Northern snakehead exist in the lower Potomac River and Rappahannock Rivers on the Western shore of the Bay, and these fish have also been found in middle or upper reaches of river systems on the Eastern shore of the Bay, including the Nanticoke and Wicomico Rivers among others. Over the past several years, many aspects of Northern snakehead life history in the Potomac River have been described, including range and dispersal patterns, microhabitat selection and diet (Lapointe, Thorson & Angermeier 2010; Saylor, Lapointe & Angermeier 2012; Lapointe, Odenkirk & Angermeier 2013). However, comparatively little is known about their health status including susceptibility to parasitism and disease and their capacity to serve as reservoirs of disease for native wildlife. Although considered hardy by fisheries biologists, snakehead fish have demonstrated susceptibility to a number of described piscine diseases within their native range and habitat in Asia. Reported pathogens of significance in snakehead species in Asia include snakehead rhabdovirus (Lio-Po et al. 2000), aeromonad bacteria (Zheng, Cao & Yang 2012), Nocardia (Wang et al. 2007) andMycobacterium spp. (Chinabut, Limsuwan & Chantatchakool 1990; ). Mycobacterial isolates recovered from another snakehead species (Channa striata) in the previous studies have included M. marinum and M. fortuitum, as identified through molecular-based diagnostics (Puttinaowarat et al. 2002). We have conducted health screenings of Northern snakehead from the Potomac River system over the past several years and have detected few associated pathogens. Typical observations have largely consisted of incidental identification of parasitism with protozoal, monogenean or trematode organisms (unpublished data). We have also identified largemouth bass virus (LMBV) in clinically normal Northern snakehead collected from the Potomac River (Iwanowicz et al. 2013). Continued research concerning these and other pathogens of this introduced species is important to fully understand the potential impacts of these fish on indigenous wildlife and aquatic ecosystems.
","language":"English","publisher":"Blackwell Science","publisherLocation":"Oxford, England","doi":"10.1111/jfd.12412","usgsCitation":"Densmore, C.L., Iwanowicz, L., Henderson, A., Iwanowicz, D.D., and Odenkirk, J., 2016, Mycobacterial infection in Northern snakehead (Channa argus) from the Potomac River catchment: Journal of Fish Diseases, v. 39, no. 6, p. 771-775, https://doi.org/10.1111/jfd.12412.","productDescription":"5 p.","startPage":"771","endPage":"775","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065068","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":311384,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Potomac River, Pohick Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.12471008300781,\n 38.6895295540336\n ],\n [\n -77.13912963867188,\n 38.6999799615129\n ],\n [\n -77.16041564941406,\n 38.70667813760075\n ],\n [\n -77.19543457031249,\n 38.6999799615129\n ],\n [\n -77.20333099365233,\n 38.674253135311496\n ],\n [\n -77.19509124755858,\n 38.662726661586646\n ],\n [\n -77.17655181884766,\n 38.65387950468725\n ],\n [\n -77.15835571289062,\n 38.64369051578083\n ],\n [\n -77.13912963867188,\n 38.628940728833264\n ],\n [\n -77.10479736328125,\n 38.622503507032874\n ],\n [\n -77.07664489746094,\n 38.626258623311166\n ],\n [\n -77.05432891845703,\n 38.64288606020925\n ],\n [\n -77.05982208251953,\n 38.67452117076055\n ],\n [\n -77.08076477050781,\n 38.691673351832996\n ],\n [\n -77.12471008300781,\n 38.6895295540336\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"39","issue":"6","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-16","publicationStatus":"PW","scienceBaseUri":"564b0c55e4b0ebfbef0d3172","contributors":{"authors":[{"text":"Densmore, Christine L. 0000-0001-6440-0781 cdensmore@usgs.gov","orcid":"https://orcid.org/0000-0001-6440-0781","contributorId":4560,"corporation":false,"usgs":true,"family":"Densmore","given":"Christine","email":"cdensmore@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":579837,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Iwanowicz, Luke R. 0000-0002-1197-6178 liwanowicz@usgs.gov","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":150383,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke R. 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This is especially true in situations where the abundance of one species may inhibit that of another, such as the intensively-farmed landscape of the Prairie Pothole Region (PPR) of the central United States, where waterfowl production is largely constrained by mesocarnivore nest predation. We used a hierarchical Bayesian approach to relate the distribution of various land-cover types to the relative abundances of four mesocarnivores in the PPR: coyote Canis latrans, raccoon Procyon lotor, red fox Vulpes vulpes, and striped skunk Mephitis mephitis. We developed models for each species at multiple spatial resolutions (41.4 km2, 10.4 km2, and 2.6 km2) to address different ecological and management-related questions. Model results for each species were similar irrespective of resolution. We found that the amount of row-crop agriculture was nearly ubiquitous in our best models, exhibiting a positive relationship with relative abundance for each species. The amount of native grassland land-cover was positively associated with coyote and raccoon relative abundance, but generally absent from models for red fox and skunk. Red fox and skunk were positively associated with each other, suggesting potential niche overlap. We found no evidence that coyote abundance limited that of other mesocarnivore species, as might be expected under a hypothesis of mesopredator release. The relationships between relative abundance and land-cover types were similar across spatial resolutions. Our results indicated that mesocarnivores in the PPR are most likely to occur in portions of the landscape with large amounts of agricultural land-cover. Further, our results indicated that track-survey data can be used in a hierarchical framework to gain inferences regarding spatial patterns in animal relative abundance.
","language":"English","publisher":"Wiley","doi":"10.1111/ecog.01179","collaboration":"Prepared in collaboration with U.S. Fish and Wildlife Service","usgsCitation":"Crimmins, S.M., Walleser, L.R., Hertel, D.R., McKann, P., Rohweder, J.J., and Thogmartin, W.E., 2016, Relating mesocarnivore relative abundance to anthropogenic land-use with a hierarchical spatial count model: Ecography, v. 39, no. 6, p. 524-532, https://doi.org/10.1111/ecog.01179.","productDescription":"9 p.","startPage":"524","endPage":"532","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057940","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":309843,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa, Minnesota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.8115234375,\n 42.71473218539458\n ],\n [\n -96.8115234375,\n 47.754097979680026\n ],\n [\n -93.71337890625,\n 47.754097979680026\n ],\n [\n -93.71337890625,\n 42.71473218539458\n ],\n [\n -96.8115234375,\n 42.71473218539458\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"39","issue":"6","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-30","publicationStatus":"PW","scienceBaseUri":"561e1d28e4b0cdb063e59ca5","contributors":{"authors":[{"text":"Crimmins, Shawn M. 0000-0001-6229-5543 scrimmins@usgs.gov","orcid":"https://orcid.org/0000-0001-6229-5543","contributorId":5498,"corporation":false,"usgs":true,"family":"Crimmins","given":"Shawn","email":"scrimmins@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":576938,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walleser, Liza R. lwalleser@usgs.gov","contributorId":4329,"corporation":false,"usgs":true,"family":"Walleser","given":"Liza","email":"lwalleser@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":576939,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hertel, Dan R.","contributorId":149113,"corporation":false,"usgs":false,"family":"Hertel","given":"Dan","email":"","middleInitial":"R.","affiliations":[{"id":17647,"text":"United States Fish and Wildlife Service, Habitat and Population Evaluation Team","active":true,"usgs":false}],"preferred":false,"id":576940,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McKann, Patrick C.","contributorId":14940,"corporation":false,"usgs":true,"family":"McKann","given":"Patrick C.","affiliations":[],"preferred":false,"id":576941,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rohweder, Jason J. jrohweder@usgs.gov","contributorId":460,"corporation":false,"usgs":true,"family":"Rohweder","given":"Jason","email":"jrohweder@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":576942,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":576937,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70158679,"text":"70158679 - 2016 - Environmental controls on spatial patterns in the long-term persistence of giant kelp in central California","interactions":[],"lastModifiedDate":"2016-03-17T13:43:39","indexId":"70158679","displayToPublicDate":"2015-10-06T14:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Environmental controls on spatial patterns in the long-term persistence of giant kelp in central California","docAbstract":"As marine management is moving towards the practice of protecting static areas, it is 44 important to make sure protected areas capture and protect persistent populations. Rocky reefs in 45 many temperate areas worldwide serve as habitat for canopy forming macroalgae and these 46 structure forming species of kelps (order Laminariales) often serve as important habitat for a great 47 diversity of species. Macrocystis pyrifera is the most common canopy forming kelp species found 48 along the coast of California but the distribution and abundance of M. pyrifera varies in space and 49 time. The purpose of this study is to determine what environmental parameters are correlated with 50 the spatial and temporal persistence of M. pyrifera along the central coast of California and how 51 well those environmental parameters can be used to predict areas where M. pyrifera is more likely 52 to persist. Nine environmental variables considered in this study included depth of the seafloor, 53 structure of the rocky reef, proportion of rocky reef, size of kelp patch, biomass of kelp within a 54 patch, distance from the edge of a kelp patch, sea surface temperature, wave orbital velocities, and 55 population connectivity of individual kelp patches. Using a generalized linear mixed effects model 56 (GLMM), the persistence of M. pyrifera was significantly associated with seven of the nine 57 variables considered: depth, complexity of the rocky reef, proportion of rock, patch biomass, 58 distance from the edge of a patch, population connectivity, and wave-orbital velocities. These 59 seven environmental variables were then used to predict the persistence of kelp across the central 60 coast and these predictions were compared to a reserved dataset of M. pyrifera persistence, which 61 was not used in the creation of the GLMM. The environmental variables were shown to accurately 62 predict the persistence of M. pyrifera within the central coast of California (r = 0.71, P<0.001). 63 Because persistence of giant kelp is important to the community structure of kelp forests, 64 understanding those factors that support persistent populations of M. pyrifera will enable more 65 effective management of these ecosystems.
","language":"English","publisher":"Ecological Society of America","doi":"10.1890/15-0267.1","collaboration":"Prepared in collaboration with University of California at Santa Cruz, University of California at Los Angeles","usgsCitation":"Young, M.A., Cavanaugh, K.C., Bell, T.W., Raimondi, P.T., Edwards, C.A., Drake, P.T., Erikson, L., and Storlazzi, C.D., 2016, Environmental controls on spatial patterns in the long-term persistence of giant kelp in central California: Ecology, v. 86, no. 1, p. 45-60, https://doi.org/10.1890/15-0267.1.","productDescription":"16 p.","startPage":"45","endPage":"60","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063935","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":502615,"rank":0,"type":{"id":41,"text":"Open Access External Repository 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