{"pageNumber":"603","pageRowStart":"15050","pageSize":"25","recordCount":40828,"records":[{"id":70100415,"text":"ofr20141031 - 2014 - Nutrient budgets, marsh inundation under sea-level rise scenarios, and sediment chronologies for the Bass Harbor Marsh estuary at Acadia National Park","interactions":[],"lastModifiedDate":"2014-05-07T09:15:10","indexId":"ofr20141031","displayToPublicDate":"2014-05-07T09:04:00","publicationYear":"2014","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":"2014-1031","title":"Nutrient budgets, marsh inundation under sea-level rise scenarios, and sediment chronologies for the Bass Harbor Marsh estuary at Acadia National Park","docAbstract":"<p>Eutrophication in the Bass Harbor Marsh estuary on Mount Desert Island, Maine, is an ongoing problem manifested by recurring annual blooms of green macroalgae species, principally Enteromorpha prolifera and Enteromorpha flexuosa, blooms that appear in the spring and summer. These blooms are unsightly and impair the otherwise natural beauty of this estuarine ecosystem. The macroalgae also threaten the integrity of the estuary and its inherent functions. The U.S. Geological Survey and Acadia National Park have collaborated for several years to better understand the factors related to this eutrophication problem with support from the U.S. Geological Survey and National Park Service Water Quality Assessment and Monitoring Program. The current study involved the collection of hydrologic and water-quality data necessary to investigate the relative contribution of nutrients from oceanic and terrestrial sources during summer 2011 and summer 2012. This report provides data on nutrient budgets for this estuary, sedimentation chronologies for the estuary and fringing marsh, and estuary bathymetry. The report also includes data, based on aerial photographs, on historical changes from 1944 to 2010 in estuary surface area and data, based on surface-elevation details, on changes in marsh area that may accompany sea-level rise.</p>\n<br/>\n<p>The LOADEST regression model was used to calculate nutrient loads into and out of the estuary during summer 2011 and summer 2012. During these summers, tidal inputs of ammonium to the estuary were more than seven times greater than the combined inputs in watershed runoff and precipitation. In 2011 tidal inputs of nitrate were about four times greater than watershed plus precipitation inputs, and in 2012 tidal inputs were only slightly larger than watershed plus precipitation inputs. In 2011, tidal inputs of total organic nitrogen were larger than watershed input by a factor of 1.6. By contrast, in 2012 inputs of total organic nitrogen in watershed runoff were much larger than tidal inputs, by a factor of 3.6. During the 2011 and 2012 summers, tidal inputs of total dissolved phosphorus to the estuary were more than seven times greater than inputs in watershed runoff. It is evident that during the summer tidal inputs of inorganic nitrogen and total dissolved phosphorus to the estuary exceed inputs from watershed runoff and precipitation.</p>\n<br/>\n<p>Projected sea-level rise associated with ongoing climate warming will affect the area of land within the Bass Harbor Marsh estuary watershed that is inundated during conditions of mean higher high water and during mean lower low water and hence will affect the vegetation and marsh area. Given 100-centimeter sea-level rise, the inundated area would increase from 25.7 hectares at the current condition to 77.5 hectares at mean higher high water and from 21.6 hectares to 26.7 hectares at mean lower low water. Given 50-centimeter sea-level rise, flooding of the entire marsh surface, which currently occurs only under the highest spring tides, would occur on average every other day.</p>\n<br/>\n<p>Radioisotope analysis of sediment cores from the estuary indicates that the sediment accumulation rate increased markedly from 1930 to 1980 and was relatively constant (0.4 to 0.5 centimeter per year) from 1980 to 2009. Similarly, from 1980 to 2009 there was a consistently high mass accumulation rate of 0.09 to 0.11 grams per square centimeter per year. The sediment accretion rates determined for the five cores collected from the marsh surface (east and west sides of the estuary) in 2011 show generally higher rates of 0.20 to 0.29 centimeter per year for the period between 1980 to 2011 than for the period before 1980, when sediment accretion rates were 0.06 to 0.25 centimeter per year.</p>\n<br/>\n<p>The data in this report provide resource managers at Acadia National Park with a baseline that can be used to evaluate future conditions within the estuary. Climate change, sea-level rise, and land-use change within the estuary’s watershed may influence nutrient dynamics, sedimentation, and eutrophication, and these potential effects can be studied in relation to the baseline data provided in this report. The Route 102 Bridge in Tremont, Maine is constructed over a sill that controls the amount of tidal flushing by restricting the duration of the flood tide, and structural changes to the bridge could alter tidal nutrient inputs and residence times for watershed and ocean-derived nutrients in the estuary. Ongoing sea-level rise is likely increasing ocean-derived nutrients and their residence time in the estuary on the one hand and decreasing the residence time of watershed-derived nutrients on the other.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141031","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Huntington, T.G., Culbertson, C.W., Fuller, C.C., Glibert, P., and Sturtevant, L., 2014, Nutrient budgets, marsh inundation under sea-level rise scenarios, and sediment chronologies for the Bass Harbor Marsh estuary at Acadia National Park: U.S. Geological Survey Open-File Report 2014-1031, xii, 108 p., https://doi.org/10.3133/ofr20141031.","productDescription":"xii, 108 p.","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-049630","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":286945,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141031.jpg"},{"id":285165,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1031"},{"id":286944,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1031/pdf/ofr2014-1031.pdf"}],"scale":"24000","country":"United States","state":"Maine","otherGeospatial":"Acadia National Park;Bass Harbor Marsh;Mount Desert Island","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -68.375,44.25 ], [ -68.375,44.291667 ], [ -68.333333,44.291667 ], [ -68.333333,44.25 ], [ -68.375,44.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"536b47d3e4b0a51a87c4b134","contributors":{"authors":[{"text":"Huntington, Thomas G. 0000-0002-9427-3530 thunting@usgs.gov","orcid":"https://orcid.org/0000-0002-9427-3530","contributorId":1884,"corporation":false,"usgs":true,"family":"Huntington","given":"Thomas","email":"thunting@usgs.gov","middleInitial":"G.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"preferred":true,"id":492191,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Culbertson, Charles W. cculbert@usgs.gov","contributorId":1607,"corporation":false,"usgs":true,"family":"Culbertson","given":"Charles","email":"cculbert@usgs.gov","middleInitial":"W.","affiliations":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"preferred":true,"id":492189,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fuller, Christopher C. 0000-0002-2354-8074 ccfuller@usgs.gov","orcid":"https://orcid.org/0000-0002-2354-8074","contributorId":1831,"corporation":false,"usgs":true,"family":"Fuller","given":"Christopher","email":"ccfuller@usgs.gov","middleInitial":"C.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":492190,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Glibert, Patricia","contributorId":94593,"corporation":false,"usgs":true,"family":"Glibert","given":"Patricia","email":"","affiliations":[],"preferred":false,"id":492192,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sturtevant, Luke","contributorId":99893,"corporation":false,"usgs":true,"family":"Sturtevant","given":"Luke","affiliations":[],"preferred":false,"id":492193,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70103569,"text":"70103569 - 2014 - Lack of sex-biased dispersal promotes fine-scale genetic structure in alpine ungulates","interactions":[],"lastModifiedDate":"2018-08-20T18:15:29","indexId":"70103569","displayToPublicDate":"2014-05-06T14:50:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"Lack of sex-biased dispersal promotes fine-scale genetic structure in alpine ungulates","docAbstract":"Identifying patterns of fine-scale genetic structure in natural populations can advance understanding of critical ecological processes such as dispersal and gene flow across heterogeneous landscapes. Alpine ungulates generally exhibit high levels of genetic structure due to female philopatry and patchy configuration of mountain habitats. We assessed the spatial scale of genetic structure and the amount of gene flow in 301 Dall’s sheep (<i>Ovis dalli dalli</i>) at the landscape level using 15 nuclear microsatellites and 473 base pairs of the mitochondrial (mtDNA) control region. Dall’s sheep exhibited significant genetic structure within contiguous mountain ranges, but mtDNA structure occurred at a broader geographic scale than nuclear DNA within the study area, and mtDNA structure for other North American mountain sheep populations. No evidence of male-mediated gene flow or greater philopatry of females was observed; there was little difference between markers with different modes of inheritance (pairwise nuclear DNA F <sub>ST</sub> = 0.004–0.325; mtDNA F <sub>ST</sub> = 0.009–0.544), and males were no more likely than females to be recent immigrants. Historical patterns based on mtDNA indicate separate northern and southern lineages and a pattern of expansion following regional glacial retreat. Boundaries of genetic clusters aligned geographically with prominent mountain ranges, icefields, and major river valleys based on Bayesian and hierarchical modeling of microsatellite and mtDNA data. Our results suggest that fine-scale genetic structure in Dall’s sheep is influenced by limited dispersal, and structure may be weaker in populations occurring near ancestral levels of density and distribution in continuous habitats compared to other alpine ungulates that have experienced declines and marked habitat fragmentation.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Conservation Genetics","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s10592-014-0583-2","usgsCitation":"Roffler, G.H., Talbot, S.L., Luikart, G., Sage, G.K., Pilgrim, K.L., Adams, L., and Schwartz, M.K., 2014, Lack of sex-biased dispersal promotes fine-scale genetic structure in alpine ungulates: Conservation Genetics, v. 15, no. 4, p. 837-851, https://doi.org/10.1007/s10592-014-0583-2.","productDescription":"15 p.","startPage":"837","endPage":"851","numberOfPages":"15","ipdsId":"IP-049059","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":286931,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10592-014-0583-2"},{"id":286936,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -146.0,60.5 ], [ -146.0,63.0 ], [ -140.0,63.0 ], [ -140.0,60.5 ], [ -146.0,60.5 ] ] ] } } ] }","volume":"15","issue":"4","noUsgsAuthors":false,"publicationDate":"2014-02-17","publicationStatus":"PW","scienceBaseUri":"5369f650e4b063fb73c0a9d3","contributors":{"authors":[{"text":"Roffler, Gretchen H. groffler@usgs.gov","contributorId":1946,"corporation":false,"usgs":true,"family":"Roffler","given":"Gretchen","email":"groffler@usgs.gov","middleInitial":"H.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":493394,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Talbot, Sandra L. 0000-0002-3312-7214 stalbot@usgs.gov","orcid":"https://orcid.org/0000-0002-3312-7214","contributorId":140512,"corporation":false,"usgs":true,"family":"Talbot","given":"Sandra","email":"stalbot@usgs.gov","middleInitial":"L.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":493393,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Luikart, Gordon","contributorId":97409,"corporation":false,"usgs":false,"family":"Luikart","given":"Gordon","affiliations":[{"id":6580,"text":"University of Montana, Flathead Lake Biological Station, Polson, Montana 59860, USA","active":true,"usgs":false}],"preferred":false,"id":493398,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sage, George K. 0000-0003-1431-2286 ksage@usgs.gov","orcid":"https://orcid.org/0000-0003-1431-2286","contributorId":87833,"corporation":false,"usgs":true,"family":"Sage","given":"George","email":"ksage@usgs.gov","middleInitial":"K.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":493397,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pilgrim, Kristy L.","contributorId":45222,"corporation":false,"usgs":true,"family":"Pilgrim","given":"Kristy","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":493396,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Adams, Layne G. 0000-0001-6212-2896 ladams@usgs.gov","orcid":"https://orcid.org/0000-0001-6212-2896","contributorId":2776,"corporation":false,"usgs":true,"family":"Adams","given":"Layne G.","email":"ladams@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":493395,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schwartz, Michael K.","contributorId":102326,"corporation":false,"usgs":true,"family":"Schwartz","given":"Michael","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":493399,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70102111,"text":"70102111 - 2014 - Modeling nitrate at domestic and public-supply well depths in the Central Valley, California","interactions":[],"lastModifiedDate":"2018-09-26T09:54:48","indexId":"70102111","displayToPublicDate":"2014-05-06T11:59:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Modeling nitrate at domestic and public-supply well depths in the Central Valley, California","docAbstract":"Aquifer vulnerability models were developed to map groundwater nitrate concentration at domestic and public-supply well depths in the Central Valley, California. We compared three modeling methods for ability to predict nitrate concentration >4 mg/L: logistic regression (LR), random forest classification (RFC), and random forest regression (RFR). All three models indicated processes of nitrogen fertilizer input at the land surface, transmission through coarse-textured, well-drained soils, and transport in the aquifer to the well screen. The total percent correct predictions were similar among the three models (69–82%), but RFR had greater sensitivity (84% for shallow wells and 51% for deep wells). The results suggest that RFR can better identify areas with high nitrate concentration but that LR and RFC may better describe bulk conditions in the aquifer. A unique aspect of the modeling approach was inclusion of outputs from previous, physically based hydrologic and textural models as predictor variables, which were important to the models. Vertical water fluxes in the aquifer and percent coarse material above the well screen were ranked moderately high-to-high in the RFR models, and the average vertical water flux during the irrigation season was highly significant (p < 0.0001) in logistic regression.","language":"English","publisher":"American Chemical Society","doi":"10.1021/es405452q","usgsCitation":"Nolan, B.T., Gronberg, J.M., Faunt, C., Eberts, S., and Belitz, K., 2014, Modeling nitrate at domestic and public-supply well depths in the Central Valley, California: Environmental Science & Technology, v. 48, no. 10, p. 5643-5651, https://doi.org/10.1021/es405452q.","productDescription":"9 p.","startPage":"5643","endPage":"5651","ipdsId":"IP-053144","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":286937,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286929,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/es405452q"}],"country":"United States","state":"California","otherGeospatial":"Central Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.41,32.53 ], [ -124.41,42.01 ], [ -114.13,42.01 ], [ -114.13,32.53 ], [ -124.41,32.53 ] ] ] } } ] }","volume":"48","issue":"10","noUsgsAuthors":false,"publicationDate":"2014-04-29","publicationStatus":"PW","scienceBaseUri":"5369f651e4b063fb73c0a9e2","contributors":{"authors":[{"text":"Nolan, Bernard T. 0000-0002-6945-9659 btnolan@usgs.gov","orcid":"https://orcid.org/0000-0002-6945-9659","contributorId":2190,"corporation":false,"usgs":true,"family":"Nolan","given":"Bernard","email":"btnolan@usgs.gov","middleInitial":"T.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":492828,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gronberg, JoAnn M. 0000-0003-4822-7434 jmgronbe@usgs.gov","orcid":"https://orcid.org/0000-0003-4822-7434","contributorId":3548,"corporation":false,"usgs":true,"family":"Gronberg","given":"JoAnn","email":"jmgronbe@usgs.gov","middleInitial":"M.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":492830,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Faunt, Claudia C. 0000-0001-5659-7529 ccfaunt@usgs.gov","orcid":"https://orcid.org/0000-0001-5659-7529","contributorId":1491,"corporation":false,"usgs":true,"family":"Faunt","given":"Claudia C.","email":"ccfaunt@usgs.gov","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":492827,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eberts, Sandra M. smeberts@usgs.gov","contributorId":2264,"corporation":false,"usgs":true,"family":"Eberts","given":"Sandra M.","email":"smeberts@usgs.gov","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":false,"id":492829,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Belitz, Ken 0000-0003-4481-2345","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":108032,"corporation":false,"usgs":true,"family":"Belitz","given":"Ken","affiliations":[],"preferred":false,"id":492831,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70060527,"text":"70060527 - 2014 - Mechanisms of drift-feeding behavior in juvenile Chinook salmon and the role of inedible debris in a clear water Alaskan stream","interactions":[],"lastModifiedDate":"2014-05-06T11:43:59","indexId":"70060527","displayToPublicDate":"2014-05-06T10:23:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1528,"text":"Environmental Biology of Fishes","active":true,"publicationSubtype":{"id":10}},"title":"Mechanisms of drift-feeding behavior in juvenile Chinook salmon and the role of inedible debris in a clear water Alaskan stream","docAbstract":"Drift-feeding fish are challenged to discriminate between prey and similar-sized particles of debris, which are ubiquitous even in clear-water streams. Spending time and energy pursuing debris mistaken as prey could affect fish growth and the fitness potential of different foraging strategies. Our goal was to determine the extent to which debris influences drift-feeding fish in clear water under low-flow conditions when the distracting effect of debris should be at a minimum. We used high-definition video to measure the reactions of drift-feeding juvenile Chinook salmon (Oncorhynchus tshawytscha) to natural debris and prey in situ in the Chena River, Alaska. Among all potential food items fish pursued, 52 % were captured and quickly expelled from the mouth, 39 % were visually inspected but not captured, and only 9 % were ingested. Foraging attempt rate was only moderately correlated with ingestion rate (Kendall’s τ = 0.55), raising concerns about the common use of foraging attempts as a presumed index of foraging success. The total time fish spent handling debris increased linearly with foraging attempt rate and ranged between 4 and 25 % of total foraging time among observed groups. Our results help motivate a revised theoretical view of drift feeding that emphasizes prey detection and discrimination, incorporating ideas from signal detection theory and the study of visual attention in cognitive ecology. We discuss how these ideas could lead to better explanations and predictions of the spatial behavior, prey selection, and energy intake of drift-feeding fish.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Biology of Fishes","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s10641-014-0227-x","usgsCitation":"Neuswanger, J.R., Wipfli, M.S., Rosenberger, A.E., and Hughes, N.F., 2014, Mechanisms of drift-feeding behavior in juvenile Chinook salmon and the role of inedible debris in a clear water Alaskan stream: Environmental Biology of Fishes, v. 97, no. 5, p. 489-503, https://doi.org/10.1007/s10641-014-0227-x.","productDescription":"15 p.","startPage":"489","endPage":"503","numberOfPages":"15","ipdsId":"IP-045976","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":286926,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286925,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10641-014-0227-x"}],"country":"United States","state":"Alaska","otherGeospatial":"Chena River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -147.915305,64.784024 ], [ -147.915305,64.857769 ], [ -146.995475,64.857769 ], [ -146.995475,64.784024 ], [ -147.915305,64.784024 ] ] ] } } ] }","volume":"97","issue":"5","noUsgsAuthors":false,"publicationDate":"2014-01-29","publicationStatus":"PW","scienceBaseUri":"5369f650e4b063fb73c0a9d8","contributors":{"authors":[{"text":"Neuswanger, Jason R.","contributorId":15530,"corporation":false,"usgs":true,"family":"Neuswanger","given":"Jason","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":487896,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wipfli, Mark S. 0000-0002-4856-6068 mwipfli@usgs.gov","orcid":"https://orcid.org/0000-0002-4856-6068","contributorId":1425,"corporation":false,"usgs":true,"family":"Wipfli","given":"Mark","email":"mwipfli@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":487894,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenberger, Amanda E. 0000-0002-5520-8349 arosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5520-8349","contributorId":5581,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Amanda","email":"arosenberger@usgs.gov","middleInitial":"E.","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":487895,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hughes, Nicholas F.","contributorId":40497,"corporation":false,"usgs":true,"family":"Hughes","given":"Nicholas","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":487897,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70101481,"text":"ofr20141074 - 2014 - Sediment-hosted gold deposits of the world: Database and grade and tonnage models","interactions":[],"lastModifiedDate":"2023-05-26T15:29:00.030413","indexId":"ofr20141074","displayToPublicDate":"2014-05-06T10:06:00","publicationYear":"2014","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":"2014-1074","title":"Sediment-hosted gold deposits of the world: Database and grade and tonnage models","docAbstract":"All sediment-hosted gold deposits (as a single population) share one characteristic—they all have disseminated micron-sized invisible gold in sedimentary rocks. Sediment-hosted gold deposits are recognized in the Great Basin province of the western United States and in China along with a few recognized deposits in Indonesia, Iran, and Malaysia. Three new grade and tonnage models for sediment-hosted gold deposits are presented in this paper: (1) a general sediment-hosted gold type model, (2) a Carlin subtype model, and (3) a Chinese subtype model. These models are based on grade and tonnage data from a database compilation of 118 sediment-hosted gold deposits including a total of 123 global deposits. The new general grade and tonnage model for sediment-hosted gold deposits (n=118) has a median tonnage of 5.7 million metric tonnes (Mt) and a gold grade of 2.9 grams per tonne (g/t). This new grade and tonnage model is remarkable in that the estimated parameters of the resulting grade and tonnage distributions are comparable to the previous model of Mosier and others (1992). A notable change is in the reporting of silver in more than 10 percent of deposits; moreover, the previous model had not considered deposits in China. From this general grade and tonnage model, two significantly different subtypes of sediment-hosted gold deposits are differentiated: Carlin and Chinese. The Carlin subtype includes 88 deposits in the western United States, Indonesia, Iran, and Malaysia, with median tonnage and grade of 7.1 Mt and 2.0 g/t Au, respectively. The silver grade is 0.78 g/t Ag for the 10th percentile of deposits. The Chinese subtype represents 30 deposits in China, with a median tonnage of 3.9 Mt and medium grade of 4.6 g/t Au. Important differences are recognized in the mineralogy and alteration of the two sediment-hosted gold subtypes such as: increased sulfide minerals in the Chinese subtype and decalcification alteration dominant in the Carlin type. We therefore recommend using the appropriate grade and tonnage model presented in this study for mineral resource assessments depending on the geologic and mineralogical data available for a region. Tonnage and contained gold within the general sediment-hosted gold model are analyzed based on major geologic features such as tectonic setting and magmatic (dikes, sills, and stocks) or amagmatic environment. The results show a significant difference in tonnage and contained gold, with higher median values in deposits spatially associated with igneous rocks, regardless of structural style of the deposit. These results suggest that magmatic environments control mineralization intensity—an important consideration in the regional assessment of prospective areas for sediment-hosted gold deposits.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141074","usgsCitation":"Berger, V.I., Mosier, D.L., Bliss, J.D., and Moring, B.C., 2014, Sediment-hosted gold deposits of the world: Database and grade and tonnage models (Originally posted May 5, 2014; Version 1.1 June 19, 2014): U.S. Geological Survey Open-File Report 2014-1074, Report: v, 46 p.; Appendixes 1-6, https://doi.org/10.3133/ofr20141074.","productDescription":"Report: v, 46 p.; Appendixes 1-6","numberOfPages":"51","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-046320","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":417504,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_100014.htm","linkFileType":{"id":5,"text":"html"}},{"id":286923,"rank":1,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2014/1074/downloads/ofr2014-1074_appendixes.zip"},{"id":286228,"rank":3,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1074/"},{"id":286924,"rank":4,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141074.GIF"},{"id":286922,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1074/pdf/ofr2014-1074.pdf"}],"edition":"Originally posted May 5, 2014; Version 1.1 June 19, 2014","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5369f652e4b063fb73c0a9f6","contributors":{"authors":[{"text":"Berger, Vladimir I.","contributorId":15246,"corporation":false,"usgs":true,"family":"Berger","given":"Vladimir","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":492718,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mosier, Dan L.","contributorId":42593,"corporation":false,"usgs":true,"family":"Mosier","given":"Dan","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":492719,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bliss, James D. jbliss@usgs.gov","contributorId":2790,"corporation":false,"usgs":true,"family":"Bliss","given":"James","email":"jbliss@usgs.gov","middleInitial":"D.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":492716,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moring, Barry C. 0000-0001-6797-9258 moring@usgs.gov","orcid":"https://orcid.org/0000-0001-6797-9258","contributorId":2794,"corporation":false,"usgs":true,"family":"Moring","given":"Barry","email":"moring@usgs.gov","middleInitial":"C.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":492717,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70173908,"text":"70173908 - 2014 - Estimating habitat carrying capacity for migrating and wintering waterfowl: Considerations, pitfalls and improvements","interactions":[],"lastModifiedDate":"2016-06-22T13:35:54","indexId":"70173908","displayToPublicDate":"2014-05-06T05:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3764,"text":"Wildfowl","onlineIssn":"2052-6458","printIssn":"0954-6324","active":true,"publicationSubtype":{"id":10}},"title":"Estimating habitat carrying capacity for migrating and wintering waterfowl: Considerations, pitfalls and improvements","docAbstract":"<p>Population-based habitat conservation planning for migrating and wintering waterfowl&nbsp;in North America is carried out by habitat Joint Venture (JV) initiatives and is based on&nbsp;the premise that food can limit demography (i.e. food limitation hypothesis).&nbsp;Consequently, planners use bioenergetic models to estimate food (energy) availability&nbsp;and population-level energy demands at appropriate spatial and temporal scales, and&nbsp;translate these values into regional habitat objectives. While simple in principle, there&nbsp;are both empirical and theoretical challenges associated with calculating energy supply&nbsp;and demand including: 1) estimating food availability, 2) estimating the energy content&nbsp;of specific foods, 3) extrapolating site-specific estimates of food availability to&nbsp;landscapes for focal species, 4) applicability of estimates from a single species to other&nbsp;species, 5) estimating resting metabolic rate, 6) estimating cost of daily behaviours, and&nbsp;7) estimating costs of thermoregulation or tissue synthesis. Most models being used are&nbsp;daily ration models (DRMs) whose set of simplifying assumptions are well established&nbsp;and whose use is widely accepted and feasible given the empirical data available to&nbsp;populate such models. However, DRMs do not link habitat objectives to metrics of&nbsp;ultimate ecological importance such as individual body condition or survival, and&nbsp;largely only consider food-producing habitats. Agent-based models (ABMs) provide a&nbsp;possible alternative for creating more biologically realistic models under some&nbsp;conditions; however, ABMs require different types of empirical inputs, many of which&nbsp;have yet to be estimated for key North American waterfowl. Decisions about how JVs&nbsp;can best proceed with habitat conservation would benefit from the use of sensitivity&nbsp;analyses that could identify the empirical and theoretical uncertainties that have the&nbsp;greatest influence on efforts to estimate habitat carrying capacity. Development of&nbsp;ABMs at restricted, yet biologically relevant spatial scales, followed by comparisons of&nbsp;their outputs to those generated from more simplistic, deterministic models can&nbsp;provide a means of assessing degrees of dissimilarity in how alternative models&nbsp;describe desired landscape conditions for migrating and wintering waterfowl.</p>","language":"English","publisher":"InterMedia Outdoors","usgsCitation":"Williams, C., Dugger, B., Brasher, M., Coluccy, J.M., Cramer, D.M., Eadie, J.M., Gray, M., Hagy, H.M., Livolsi, M., McWilliams, S.R., Petrie, M., Soulliere, G.J., Tirpak, J.M., and Webb, E.B., 2014, Estimating habitat carrying capacity for migrating and wintering waterfowl: Considerations, pitfalls and improvements: Wildfowl, no. 4, p. 407-435.","productDescription":"29 p.","startPage":"407","endPage":"435","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055427","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":324226,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":324227,"type":{"id":15,"text":"Index Page"},"url":"https://wildfowl.wwt.org.uk/index.php/wildfowl/article/view/2614"}],"issue":"4","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576bb6b3e4b07657d1a2289f","contributors":{"authors":[{"text":"Williams, Christopher","contributorId":36592,"corporation":false,"usgs":true,"family":"Williams","given":"Christopher","affiliations":[],"preferred":false,"id":640344,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dugger, Bruce D.","contributorId":81236,"corporation":false,"usgs":true,"family":"Dugger","given":"Bruce D.","affiliations":[],"preferred":false,"id":640345,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brasher, Michael G.","contributorId":17139,"corporation":false,"usgs":true,"family":"Brasher","given":"Michael G.","affiliations":[],"preferred":false,"id":640346,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coluccy, John M.","contributorId":111382,"corporation":false,"usgs":true,"family":"Coluccy","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":640347,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cramer, Dane M.","contributorId":172325,"corporation":false,"usgs":false,"family":"Cramer","given":"Dane","email":"","middleInitial":"M.","affiliations":[{"id":13073,"text":"Ducks Unlimited, Inc.","active":true,"usgs":false}],"preferred":false,"id":640348,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Eadie, John M.","contributorId":65219,"corporation":false,"usgs":false,"family":"Eadie","given":"John","email":"","middleInitial":"M.","affiliations":[{"id":7082,"text":"University of California - Davis","active":true,"usgs":false}],"preferred":false,"id":640349,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gray, Matthew J.","contributorId":101343,"corporation":false,"usgs":true,"family":"Gray","given":"Matthew J.","affiliations":[],"preferred":false,"id":640350,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hagy, Heath M.","contributorId":172326,"corporation":false,"usgs":false,"family":"Hagy","given":"Heath","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":640351,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Livolsi, Mark","contributorId":172327,"corporation":false,"usgs":false,"family":"Livolsi","given":"Mark","email":"","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":640352,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"McWilliams, Scott R.","contributorId":172328,"corporation":false,"usgs":false,"family":"McWilliams","given":"Scott","email":"","middleInitial":"R.","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":640353,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Petrie, Matthew mpetrie@usgs.gov","contributorId":167013,"corporation":false,"usgs":true,"family":"Petrie","given":"Matthew","email":"mpetrie@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":640354,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Soulliere, Gregory J.","contributorId":172329,"corporation":false,"usgs":false,"family":"Soulliere","given":"Gregory","email":"","middleInitial":"J.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":640355,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Tirpak, John M.","contributorId":85704,"corporation":false,"usgs":true,"family":"Tirpak","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":640356,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Webb, Elisabeth B. 0000-0003-3851-6056 ewebb@usgs.gov","orcid":"https://orcid.org/0000-0003-3851-6056","contributorId":3981,"corporation":false,"usgs":true,"family":"Webb","given":"Elisabeth","email":"ewebb@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":638956,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70156135,"text":"70156135 - 2014 - Using nuclear magnetic resonance and transient electromagnetics to characterise water distribution beneath an ice covered volcanic crater: The case of Sherman Crater Mt. Baker Washington.","interactions":[],"lastModifiedDate":"2019-03-11T14:03:42","indexId":"70156135","displayToPublicDate":"2014-05-06T01:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2850,"text":"Near Surface Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Using nuclear magnetic resonance and transient electromagnetics to characterise water distribution beneath an ice covered volcanic crater: The case of Sherman Crater Mt. Baker Washington.","docAbstract":"<p>Surface and laboratory Nuclear Magnetic Resonance (NMR) measurements combined with transient electromagnetic (TEM) data are powerful tools for subsurface water detection. Surface NMR (sNMR) and TEM soundings, laboratory NMR, complex resistivity, and X-Ray Diffraction (XRD) analysis were all conducted to characterise the distribution of water within Sherman Crater on Mt. Baker, WA. Clay rich rocks, particularly if water saturated, can weaken volcanoes, thereby increasing the potential for catastrophic sector collapses that can lead to far-travelled, destructive debris flows. Detecting the presence and volume of shallow groundwater is critical for evaluating these landslide hazards. The TEM data identified a low resistivity layer (&lt;10 ohm-m), under 60 m of glacial ice related to water saturated clays. The TEM struggles to resolve the presence or absence of a plausible thin layer of bulk liquid water on top of the clay. The sNMR measurements did not produce any observable signal, indicating the lack of substantial accumulated bulk water below the ice. Laboratory analysis on a sample from the crater wall that likely represented the clays beneath the ice confirmed that the controlling factor for the lack of sNMR signal was the fine-grained nature of the media. The laboratory measurements further indicated that small pores in clays detected by the XRD contain as much as 50% water, establishing an upper bound on the water content in the clay layer. Forward modelling of geologic scenarios revealed that bulk water layers as thin as &frac12; m between the ice and clay layer would have been detectable using sNMR. The instrumentation conditions which would allow for sNMR detection of the clay layer are investigated. Using current instrumentation the combined analysis of the TEM and sNMR data allow for valuable characterisation of the groundwater system in the crater. The sNMR is able to reduce the uncertainty of the TEM in regards to the presence of a bulk water layer, a valuable piece of information in hazard assessment.</p>","language":"English","publisher":"European Association of Geoscientists & Engineers","doi":"10.3997/1873-0604.2014009","usgsCitation":"Irons, T.P., Martin, K., Finn, C.A., Bloss, B.R., and Horton, R., 2014, Using nuclear magnetic resonance and transient electromagnetics to characterise water distribution beneath an ice covered volcanic crater: The case of Sherman Crater Mt. Baker Washington.: Near Surface Geophysics, v. 12, no. 2, p. 285-296, https://doi.org/10.3997/1873-0604.2014009.","productDescription":"12 p.","startPage":"285","endPage":"296","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053051","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"links":[{"id":306810,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mount Baker, Sherman Crater","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.05947875976562,\n              48.62110864256238\n            ],\n            [\n              -122.05947875976562,\n              48.89722676235673\n            ],\n            [\n              -121.55548095703125,\n              48.89722676235673\n            ],\n            [\n              -121.55548095703125,\n              48.62110864256238\n            ],\n            [\n              -122.05947875976562,\n              48.62110864256238\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"12","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55d305bce4b0518e35468d35","contributors":{"authors":[{"text":"Irons, Trevor P. tirons@usgs.gov","contributorId":4851,"corporation":false,"usgs":true,"family":"Irons","given":"Trevor","email":"tirons@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":567909,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Kathryn","contributorId":146449,"corporation":false,"usgs":false,"family":"Martin","given":"Kathryn","email":"","affiliations":[{"id":16695,"text":"Army Corps of Engineers","active":true,"usgs":false}],"preferred":false,"id":567910,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Finn, Carol A. 0000-0002-6178-0405 cfinn@usgs.gov","orcid":"https://orcid.org/0000-0002-6178-0405","contributorId":1326,"corporation":false,"usgs":true,"family":"Finn","given":"Carol","email":"cfinn@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":567908,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bloss, Benjamin R. 0000-0002-1678-8571 bbloss@usgs.gov","orcid":"https://orcid.org/0000-0002-1678-8571","contributorId":139981,"corporation":false,"usgs":true,"family":"Bloss","given":"Benjamin","email":"bbloss@usgs.gov","middleInitial":"R.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":567911,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Horton, Robert 0000-0001-5578-3733 rhorton@usgs.gov","orcid":"https://orcid.org/0000-0001-5578-3733","contributorId":612,"corporation":false,"usgs":true,"family":"Horton","given":"Robert","email":"rhorton@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":567912,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70056060,"text":"70056060 - 2014 - Lipid and moisture content modeling of amphidromous Dolly Varden using bioelectrical impedance analysis","interactions":[],"lastModifiedDate":"2014-05-06T09:49:15","indexId":"70056060","displayToPublicDate":"2014-05-05T16:06:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Lipid and moisture content modeling of amphidromous Dolly Varden using bioelectrical impedance analysis","docAbstract":"The physiological well-being or condition of fish is most commonly estimated from aspects of individual morphology. However, these metrics may be only weakly correlated with nutritional reserves stored as lipid, the primary form of accumulated energy in fish. We constructed and evaluated bioelectrical impedance analysis (BIA) models as an alternative method of assessing condition in amphidromous Dolly Varden Salvelinus malma collected from nearshore estuarine and lotic habitats of the Alaskan Arctic. Data on electrical resistance and reactance were collected from the lateral and ventral surfaces of 192 fish, and whole-body percent lipid and moisture content were determined using standard laboratory methods. Significant inverse relationships between temperature and resistance and reactance prompted the standardization of these data to a constant temperature using corrective equations developed herein. No significant differences in resistance or reactance were detected among spawning and nonspawning females after accounting for covariates, suggesting that electrical pathways do not intersect the gonads. Best-fit BIA models incorporating electrical variables calculated from the lateral and ventral surfaces produced the strongest associations between observed and model-predicted estimates of proximate content. These models explained between 6% and 20% more of the variability in laboratory-derived estimates of proximate content than models developed from single-surface BIA data and 32% more than models containing only length and weight data. While additional research is required to address the potential effects of methodological variation, bioelectrical impedance analysis shows promise as a way to provide high-quality, minimally invasive estimates of Dolly Varden lipid or moisture content in the field with only small increases in handling time.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"North American Journal of Fisheries Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Taylor & Francis","doi":"10.1080/02755947.2014.880764","usgsCitation":"Stolarski, J., Margraf, F., Carlson, J., and Sutton, T., 2014, Lipid and moisture content modeling of amphidromous Dolly Varden using bioelectrical impedance analysis: North American Journal of Fisheries Management, v. 34, no. 3, p. 471-481, https://doi.org/10.1080/02755947.2014.880764.","productDescription":"11 p.","startPage":"471","endPage":"481","numberOfPages":"11","ipdsId":"IP-044095","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":286920,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286919,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/02755947.2014.880764"}],"country":"United States","state":"Alaska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -145.1541,69.6619 ], [ -145.1541,70.1599 ], [ -141.6989,70.1599 ], [ -141.6989,69.6619 ], [ -145.1541,69.6619 ] ] ] } } ] }","volume":"34","issue":"3","noUsgsAuthors":false,"publicationDate":"2014-04-15","publicationStatus":"PW","scienceBaseUri":"536a0463e4b063fb73c0aa10","contributors":{"authors":[{"text":"Stolarski, J.T.","contributorId":96487,"corporation":false,"usgs":true,"family":"Stolarski","given":"J.T.","affiliations":[],"preferred":false,"id":486315,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Margraf, F.J.","contributorId":47738,"corporation":false,"usgs":true,"family":"Margraf","given":"F.J.","email":"","affiliations":[],"preferred":false,"id":486312,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carlson, J.G.","contributorId":74681,"corporation":false,"usgs":true,"family":"Carlson","given":"J.G.","email":"","affiliations":[],"preferred":false,"id":486314,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sutton, T.M.","contributorId":72193,"corporation":false,"usgs":true,"family":"Sutton","given":"T.M.","email":"","affiliations":[],"preferred":false,"id":486313,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70103370,"text":"ofr20141087 - 2014 - Characterization of potential transport pathways and implications for groundwater management near an anticline in the Central Basin area, Los Angeles County, California","interactions":[],"lastModifiedDate":"2014-05-05T15:36:05","indexId":"ofr20141087","displayToPublicDate":"2014-05-05T15:11:14","publicationYear":"2014","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":"2014-1087","title":"Characterization of potential transport pathways and implications for groundwater management near an anticline in the Central Basin area, Los Angeles County, California","docAbstract":"The Central Groundwater Basin (Central Basin) of southern Los Angeles County includes ~280 mi<sup>2</sup> of the Los Angeles Coastal Plain and serves as the primary source of water for more than two million residents. In the Santa Fe Springs–Whittier–Norwalk area, located in the northeastern part of the basin, several sources of volatile organic compounds have been identified. The volatile organic compunds are thought to have contributed to a large, commingled contaminant plume in groundwater that extends south-southwest downgradient from the Omega Chemical Corporation Superfund Site across folded geologic strata, known as the Santa Fe Springs Anticline. A multifaceted study—that incorporated a three-dimensional sequence-stratigraphic geologic model, two-dimensional groundwater particle-tracking simulations, and new groundwater chemistry data—was conducted to gain insight into the geologic and hydrologic controls on contaminant migration in the study area and to assess the potential for this shallow groundwater contamination to migrate into producing aquifer zones. Conceptual flow models were developed along a flow-parallel cross section based on the modeled stratigraphic architecture, observed geochemistry, and numerical model simulations that generally agree with observed water levels and contaminant distributions. These models predict that contaminants introduced into groundwater at shallow depths near the Omega Chemical Corporation Superfund Site and along the study cross section will likely migrate downgradient to depths intercepted by public supply wells. These conclusions, however, are subject to limitations and simplifications inherent in the modeling approaches used, as well as a significant scarcity of available geologic and hydrogeochemical information at depth and in the downgradient parts of the study area.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141087","collaboration":"Prepared in cooperation with the Water Replenishment District of Southern California","usgsCitation":"Ponti, D.J., Wagner, B.J., Land, M., and Landon, M.K., 2014, Characterization of potential transport pathways and implications for groundwater management near an anticline in the Central Basin area, Los Angeles County, California: U.S. Geological Survey Open-File Report 2014-1087, Report: vii, 75 p.; Appendix A: 49 p.; 1 Plate: 28.00 x 19.50 inches; Tables 1,4,7; High resolution figures, https://doi.org/10.3133/ofr20141087.","productDescription":"Report: vii, 75 p.; Appendix A: 49 p.; 1 Plate: 28.00 x 19.50 inches; Tables 1,4,7; High resolution figures","numberOfPages":"84","onlineOnly":"Y","ipdsId":"IP-037058","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":286913,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141087.jpg"},{"id":286906,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1087/pdf/ofr2014-1087.pdf"},{"id":286907,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2014/1087/pdf/ofr2014-1087_appendixA.pdf"},{"id":286905,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1087/"},{"id":286909,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1087/downloads/ofr2014-1087_table4.xlsx"},{"id":286908,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1087/downloads/ofr2014-1087_table1.xlsx"},{"id":286910,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1087/downloads/ofr2014-1087_table7.xlsx"},{"id":286911,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1087/downloads/figures/"},{"id":286912,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2014/1087/pdf/ofr2014-1087_plate1.pdf"}],"country":"United States","state":"California","county":"Los Angeles County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -118.5,33.583 ], [ -118.5,34.25 ], [ -117.66,34.25 ], [ -117.66,33.583 ], [ -118.5,33.583 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5368a4d0e4b059f7e82882f5","contributors":{"authors":[{"text":"Ponti, Daniel J. 0000-0002-2437-5144 dponti@usgs.gov","orcid":"https://orcid.org/0000-0002-2437-5144","contributorId":1020,"corporation":false,"usgs":true,"family":"Ponti","given":"Daniel","email":"dponti@usgs.gov","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":493274,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wagner, Brian J. bjwagner@usgs.gov","contributorId":427,"corporation":false,"usgs":true,"family":"Wagner","given":"Brian","email":"bjwagner@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":493273,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Land, Michael 0000-0001-5141-0307","orcid":"https://orcid.org/0000-0001-5141-0307","contributorId":56613,"corporation":false,"usgs":true,"family":"Land","given":"Michael","affiliations":[],"preferred":false,"id":493275,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Landon, Matthew K. 0000-0002-5766-0494 landon@usgs.gov","orcid":"https://orcid.org/0000-0002-5766-0494","contributorId":392,"corporation":false,"usgs":true,"family":"Landon","given":"Matthew","email":"landon@usgs.gov","middleInitial":"K.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":493272,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70104357,"text":"70104357 - 2014 - Reservoir controls on the occurrence and production of gas hydrates in nature","interactions":[],"lastModifiedDate":"2014-07-31T10:02:01","indexId":"70104357","displayToPublicDate":"2014-05-05T11:38:00","publicationYear":"2014","noYear":false,"publicationType":{"id":4,"text":"Book"},"publicationSubtype":{"id":12,"text":"Conference publication"},"title":"Reservoir controls on the occurrence and production of gas hydrates in nature","docAbstract":"<p>Gas hydrates in both arctic permafrost regions and deep marine settings can occur at high concentrations in sand-dominated reservoirs, which have been the focus of gas hydrate exploration and production studies in\nnorthern Alaska and Canada, and offshore in the Gulf of Mexico, off the southeastern coast of Japan, in the Ulleung Basin off the east coast of the Korean Peninsula, and along the eastern margin of India. Production testing and\nmodeling has shown that concentrated gas hydrate occurrences in sand reservoirs are conducive to existing well-based production technologies. The resource potential of gas hydrate accumulations in sand-dominated reservoirs have been assessed for several polar terrestrial basins. In 1995, the U.S. Geological Survey (USGS) assigned an in-place resource of 16.7 trillion cubic meters of gas for hydrates in sand-dominated reservoirs on the Alaska North Slope. In a more recent assessment, the USGS indicated that there are about 2.42 trillion cubic meters of technically recoverable gas resources within concentrated, sand-dominated, gas hydrate accumulations in northern Alaska. Estimates of the amount of in-place gas in the sand dominated gas hydrate accumulations of the Mackenzie Delta Beaufort Sea region of the Canadian arctic range from 1.0 to 10 trillion cubic meters of gas. Another prospective gas hydrate resources are those of moderate-to-high concentrations within sandstone reservoirs in marine environments. In 2008, the Bureau of Ocean Energy Management estimated that the Gulf of Mexico contains about 190 trillion cubic meters of gas in highly concentrated hydrate accumulations within sand reservoirs. In 2008, the Japan Oil, Gas and Metals National Corporation reported on a resource assessment of gas hydrates in which they estimated that the volume of gas within the hydrates of the eastern Nankai Trough at about 1.1 trillion cubic meters, with about half concentrated in sand reservoirs. Because conventional production technologies favor sand-dominated gas hydrate reservoirs, sand reservoirs are considered to be the most viable economic target for gas hydrate production and will be the prime focus of most future gas hydrate exploration and development projects.</p>","conferenceTitle":"Offshore Technology Conference","conferenceDate":"2014-05-04T00:00:00","conferenceLocation":"Houston, TX","language":"English","publisher":"Offshore Technology Conference","publisherLocation":"Houston, TX","doi":"10.4043/25242-MS","usgsCitation":"Collett, T.S., 2014, Reservoir controls on the occurrence and production of gas hydrates in nature, 12 p., https://doi.org/10.4043/25242-MS.","productDescription":"12 p.","numberOfPages":"12","ipdsId":"IP-053730","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":289374,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":289373,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.4043/25242-MS"}],"noUsgsAuthors":false,"publicationDate":"2014-05-05","publicationStatus":"PW","scienceBaseUri":"53b7b205e4b0388651d918b3","contributors":{"authors":[{"text":"Collett, Timothy Scott 0000-0002-7598-4708","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":90640,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"","middleInitial":"Scott","affiliations":[],"preferred":false,"id":493719,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70103477,"text":"70103477 - 2014 - A probabilistic method for constructing wave time-series at inshore locations using model scenarios","interactions":[],"lastModifiedDate":"2014-05-05T11:10:07","indexId":"70103477","displayToPublicDate":"2014-05-05T11:08:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1262,"text":"Coastal Engineering","active":true,"publicationSubtype":{"id":10}},"title":"A probabilistic method for constructing wave time-series at inshore locations using model scenarios","docAbstract":"Continuous time-series of wave characteristics (height, period, and direction) are constructed using a base set of model scenarios and simple probabilistic methods. This approach utilizes an archive of computationally intensive, highly spatially resolved numerical wave model output to develop time-series of historical or future wave conditions without performing additional, continuous numerical simulations. The archive of model output contains wave simulations from a set of model scenarios derived from an offshore wave climatology. Time-series of wave height, period, direction, and associated uncertainties are constructed at locations included in the numerical model domain. The confidence limits are derived using statistical variability of oceanographic parameters contained in the wave model scenarios. The method was applied to a region in the northern Gulf of Mexico and assessed using wave observations at 12 m and 30 m water depths. Prediction skill for significant wave height is 0.58 and 0.67 at the 12 m and 30 m locations, respectively, with similar performance for wave period and direction. The skill of this simplified, probabilistic time-series construction method is comparable to existing large-scale, high-fidelity operational wave models but provides higher spatial resolution output at low computational expense. The constructed time-series can be developed to support a variety of applications including climate studies and other situations where a comprehensive survey of wave impacts on the coastal area is of interest.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Coastal Engineering","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.coastaleng.2014.03.008","usgsCitation":"Long, J.W., Plant, N.G., Dalyander, P., and Thompson, D.M., 2014, A probabilistic method for constructing wave time-series at inshore locations using model scenarios: Coastal Engineering, v. 89, p. 53-62, https://doi.org/10.1016/j.coastaleng.2014.03.008.","productDescription":"10 p.","startPage":"53","endPage":"62","numberOfPages":"10","ipdsId":"IP-050932","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":286871,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286859,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.coastaleng.2014.03.008"}],"otherGeospatial":"Gulf Of Mexico","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -89.0,29.0 ], [ -89.0,31.0 ], [ -85.0,31.0 ], [ -85.0,29.0 ], [ -89.0,29.0 ] ] ] } } ] }","volume":"89","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5368a4cfe4b059f7e82882f0","contributors":{"authors":[{"text":"Long, Joseph W. 0000-0003-2912-1992 jwlong@usgs.gov","orcid":"https://orcid.org/0000-0003-2912-1992","contributorId":3303,"corporation":false,"usgs":true,"family":"Long","given":"Joseph","email":"jwlong@usgs.gov","middleInitial":"W.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":493347,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":493349,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dalyander, P. Soupy 0000-0001-9583-0872","orcid":"https://orcid.org/0000-0001-9583-0872","contributorId":65177,"corporation":false,"usgs":true,"family":"Dalyander","given":"P. Soupy","affiliations":[],"preferred":false,"id":493350,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, David M. 0000-0002-7103-5740 dthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-7103-5740","contributorId":3502,"corporation":false,"usgs":true,"family":"Thompson","given":"David","email":"dthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":493348,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70104147,"text":"70104147 - 2014 - Assessing the potential effects of fungicides on nontarget gut fungi (trichomycetes) and their associated larval black fly hosts","interactions":[],"lastModifiedDate":"2018-09-14T16:08:30","indexId":"70104147","displayToPublicDate":"2014-05-03T09:07:32","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the potential effects of fungicides on nontarget gut fungi (trichomycetes) and their associated larval black fly hosts","docAbstract":"Fungicides are moderately hydrophobic and have been detected in water and sediment, particularly in agricultural watersheds, but typically are not included in routine water quality monitoring efforts. This is despite their widespread use and frequent application to combat fungal pathogens. Although the efficacy of these compounds on fungal pathogens is well documented, little is known about their effects on nontarget fungi. This pilot study, a field survey in southwestern Idaho from April to December 2010 on four streams with varying pesticide inputs (two agricultural and two reference sites), was conducted to assess nontarget impact of fungicides on gut fungi, or trichomycetes. Tissues of larval black flies (Diptera: Simuliidae), hosts of gut fungi, were analyzed for pesticide accumulation. Fungicides were detected in hosts from streams within agricultural watersheds but were not detected in hosts from reference streams. Gut fungi from agricultural sites exhibited decreased percent infestation, density and sporulation within the gut, and black fly tissues had elevated pesticide concentrations. Differences observed between the sites demonstrate a potential effect on this symbiotic system. Future research is needed to parse out the details of the complex biotic and abiotic relationships; however, these preliminary results indicate that impacts to nontarget organisms could have far-reaching consequences within aquatic ecosystems.","language":"English","publisher":"Wiley","doi":"10.1111/jawr.12166","usgsCitation":"Wilson, E.R., Smalling, K., Reilly, T.J., Gray, E., Bond, L., Steele, L., Kandel, P., Chamberlin, A., Gause, J., Reynolds, N., Robertson, I., Novak, S., Feris, K., and White, M.M., 2014, Assessing the potential effects of fungicides on nontarget gut fungi (trichomycetes) and their associated larval black fly hosts: Journal of the American Water Resources Association, v. 50, no. 2, p. 420-433, https://doi.org/10.1111/jawr.12166.","productDescription":"14 p.","startPage":"420","endPage":"433","ipdsId":"IP-034388","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":473004,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://doi.org/10.1111/jawr.12166","text":"External Repository"},{"id":287044,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287043,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/jawr.12166"}],"country":"United States","volume":"50","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5371ed67e4b08449547883f7","contributors":{"authors":[{"text":"Wilson, Emma R.","contributorId":58499,"corporation":false,"usgs":true,"family":"Wilson","given":"Emma","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":493555,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smalling, Kelly L.","contributorId":16105,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L.","affiliations":[],"preferred":false,"id":493553,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reilly, Timothy J. 0000-0002-2939-3050 tjreilly@usgs.gov","orcid":"https://orcid.org/0000-0002-2939-3050","contributorId":1858,"corporation":false,"usgs":true,"family":"Reilly","given":"Timothy","email":"tjreilly@usgs.gov","middleInitial":"J.","affiliations":[{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":493551,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gray, Elmer","contributorId":9969,"corporation":false,"usgs":true,"family":"Gray","given":"Elmer","email":"","affiliations":[],"preferred":false,"id":493552,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bond, Laura","contributorId":89103,"corporation":false,"usgs":true,"family":"Bond","given":"Laura","affiliations":[],"preferred":false,"id":493561,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Steele, Lance","contributorId":99052,"corporation":false,"usgs":true,"family":"Steele","given":"Lance","email":"","affiliations":[],"preferred":false,"id":493563,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kandel, Prasanna","contributorId":80196,"corporation":false,"usgs":true,"family":"Kandel","given":"Prasanna","email":"","affiliations":[],"preferred":false,"id":493559,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Chamberlin, Alison","contributorId":64163,"corporation":false,"usgs":true,"family":"Chamberlin","given":"Alison","email":"","affiliations":[],"preferred":false,"id":493556,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gause, Justin","contributorId":64574,"corporation":false,"usgs":true,"family":"Gause","given":"Justin","email":"","affiliations":[],"preferred":false,"id":493557,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Reynolds, Nicole","contributorId":20260,"corporation":false,"usgs":true,"family":"Reynolds","given":"Nicole","email":"","affiliations":[],"preferred":false,"id":493554,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Robertson, Ian","contributorId":71103,"corporation":false,"usgs":true,"family":"Robertson","given":"Ian","affiliations":[],"preferred":false,"id":493558,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Novak, Stephen","contributorId":98639,"corporation":false,"usgs":true,"family":"Novak","given":"Stephen","affiliations":[],"preferred":false,"id":493562,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Feris, Kevin","contributorId":80197,"corporation":false,"usgs":true,"family":"Feris","given":"Kevin","affiliations":[],"preferred":false,"id":493560,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"White, Merlin M.","contributorId":104819,"corporation":false,"usgs":true,"family":"White","given":"Merlin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":493564,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70103309,"text":"70103309 - 2014 - Selection of anthropogenic features and vegetation characteristics by nesting Common Ravens in the sagebrush ecosystem","interactions":[],"lastModifiedDate":"2014-05-02T14:58:35","indexId":"70103309","displayToPublicDate":"2014-05-02T14:52:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3551,"text":"The Condor","active":true,"publicationSubtype":{"id":10}},"title":"Selection of anthropogenic features and vegetation characteristics by nesting Common Ravens in the sagebrush ecosystem","docAbstract":"Common Raven (<i>Corvus corax</i>) numbers and distribution are increasing throughout the sagebrush steppe, influencing avian communities in complex ways. Anthropogenic structures are thought to increase raven populations by providing food and nesting subsidies, which is cause for concern because ravens are important nest predators of sensitive species, including Greater Sage-Grouse (<i>Centrocercus urophasianus</i>). During 2007–2009, we located raven nests in southeastern Idaho and conducted a resource selection analysis. We measured variables at multiple spatial scales for 72 unique nest locations, including landscape-level vegetation characteristics and anthropogenic structures. Using generalized linear mixed models and an information-theoretic approach, we found a 31% decrease in the odds of nesting by ravens for every 1 km increase in distance away from a transmission line. Furthermore, a 100-m increase in distance away from the edge of two different land cover types decreased the odds of nesting by 20%, and an increase in the amount of edge by 1 km within an area of 102.1 ha centered on the nest increased the odds of nesting by 49%. A post hoc analysis revealed that ravens were most likely to nest near edges of adjoining big sagebrush (<i>Artemisia tridentata</i>) and land cover types that were associated with direct human disturbance or fire. These findings contribute to our understanding of raven expansion into rural environments and could be used to make better-informed conservation decisions, especially in the face of increasing renewable energy development.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"The Condor","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Cooper Ornithological Society","doi":"10.1650/CONDOR-13-115-R2.1","usgsCitation":"Howe, K., Coates, P.S., and Delehanty, D.J., 2014, Selection of anthropogenic features and vegetation characteristics by nesting Common Ravens in the sagebrush ecosystem: The Condor, v. 116, no. 1, p. 35-49, https://doi.org/10.1650/CONDOR-13-115-R2.1.","productDescription":"15 p.","startPage":"35","endPage":"49","numberOfPages":"15","ipdsId":"IP-042615","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":473006,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1650/condor-13-115-r2.1","text":"Publisher Index Page"},{"id":286850,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286825,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1650/CONDOR-13-115-R2.1"}],"country":"United States","state":"Idaho","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -113.135529,43.424288 ], [ -113.135529,43.887645 ], [ -112.601072,43.887645 ], [ -112.601072,43.424288 ], [ -113.135529,43.424288 ] ] ] } } ] }","volume":"116","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5365918ae4b05b5c4c6db12e","contributors":{"authors":[{"text":"Howe, Kristy B.","contributorId":59354,"corporation":false,"usgs":true,"family":"Howe","given":"Kristy B.","affiliations":[],"preferred":false,"id":493255,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":493254,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Delehanty, David J.","contributorId":80811,"corporation":false,"usgs":true,"family":"Delehanty","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":493256,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70057889,"text":"70057889 - 2014 - Reducing bias in survival under non-random temporary emigration","interactions":[],"lastModifiedDate":"2014-06-27T13:46:08","indexId":"70057889","displayToPublicDate":"2014-05-01T15:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Reducing bias in survival under non-random temporary emigration","docAbstract":"Despite intensive monitoring, temporary emigration from the sampling area can induce bias severe enough for managers to discard life-history parameter estimates toward the terminus of the times series (terminal bias). Under random temporary emigration unbiased parameters can be estimated with CJS models. However, unmodeled Markovian temporary emigration causes bias in parameter estimates and an unobservable state is required to model this type of emigration. The robust design is most flexible when modeling temporary emigration, and partial solutions to mitigate bias have been identified, nonetheless there are conditions were terminal bias prevails. Long-lived species with high adult survival and highly variable non-random temporary emigration present terminal bias in survival estimates, despite being modeled with the robust design and suggested constraints. Because this bias is due to uncertainty about the fate of individuals that are undetected toward the end of the time series, solutions should involve using additional information on survival status or location of these individuals at that time. Using simulation, we evaluated the performance of models that jointly analyze robust design data and an additional source of ancillary data (predictive covariate on temporary emigration, telemetry, dead recovery, or auxiliary resightings) in reducing terminal bias in survival estimates. The auxiliary resighting and predictive covariate models reduced terminal bias the most. Additional telemetry data was effective at reducing terminal bias only when individuals were tracked for a minimum of two years. High adult survival of long-lived species made the joint model with recovery data ineffective at reducing terminal bias because of small-sample bias. The naïve constraint model (last and penultimate temporary emigration parameters made equal), was the least efficient, though still able to reduce terminal bias when compared to an unconstrained model. Joint analysis of several sources of data improved parameter estimates and reduced terminal bias. Efforts to incorporate or acquire such data should be considered by researchers and wildlife managers, especially in the years leading up to status assessments of species of interest. Simulation modeling is a very cost effective method to explore the potential impacts of using different sources of data to produce high quality demographic data to inform management.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecological Applications","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Ecological Society of America","doi":"10.1890/13-0558.1","usgsCitation":"Peñaloza, C., Kendall, W.L., and Langtimm, C.A., 2014, Reducing bias in survival under non-random temporary emigration: Ecological Applications, v. 24, no. 5, p. 1155-1166, https://doi.org/10.1890/13-0558.1.","productDescription":"12 p.","startPage":"1155","endPage":"1166","numberOfPages":"12","ipdsId":"IP-044788","costCenters":[{"id":189,"text":"Colorado Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":287158,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287157,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/13-0558.1"}],"volume":"24","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53749074e4b0870f4d23cfe2","contributors":{"authors":[{"text":"Peñaloza, Claudia L.","contributorId":107201,"corporation":false,"usgs":true,"family":"Peñaloza","given":"Claudia L.","affiliations":[],"preferred":false,"id":486921,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kendall, William L. wkendall@usgs.gov","contributorId":406,"corporation":false,"usgs":true,"family":"Kendall","given":"William","email":"wkendall@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":486919,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Langtimm, Catherine Ann 0000-0001-8499-5743","orcid":"https://orcid.org/0000-0001-8499-5743","contributorId":33223,"corporation":false,"usgs":true,"family":"Langtimm","given":"Catherine","email":"","middleInitial":"Ann","affiliations":[],"preferred":false,"id":486920,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70103367,"text":"70103367 - 2014 - Amphibians in the climate vise: loss and restoration of resilience of montane wetland ecosystems in the western US","interactions":[],"lastModifiedDate":"2014-05-02T14:54:31","indexId":"70103367","displayToPublicDate":"2014-05-01T14:49:14","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1701,"text":"Frontiers in Ecology and the Environment","active":true,"publicationSubtype":{"id":10}},"title":"Amphibians in the climate vise: loss and restoration of resilience of montane wetland ecosystems in the western US","docAbstract":"Wetlands in the remote mountains of the western US have undergone two massive ecological “experiments” spanning the 20th century. Beginning in the late 1800s and expanding after World War II, fish and wildlife managers intentionally introduced millions of predatory trout (primarily Oncorhynchus spp) into fishless mountain ponds and lakes across the western states. These new top predators, which now occupy 95% of large mountain lakes, have limited the habitat distributions of native frogs, salamanders, and wetland invertebrates to smaller, more ephemeral ponds where trout do not survive. Now a second “experiment” – anthropogenic climate change – threatens to eliminate many of these ephemeral habitats and shorten wetland hydroperiods. Caught between climate-induced habitat loss and predation from introduced fish, native mountain lake fauna of the western US – especially amphibians – are at risk of extirpation. Targeted fish removals, guided by models of how wetlands will change under future climate scenarios, provide innovative strategies for restoring resilience of wetland ecosystems to climate change.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Frontiers in Ecology and the Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Ecological Society of America","doi":"10.1890/130145","usgsCitation":"Ryan, M., Palen, W.J., Adams, M.J., and Rochefort, R.M., 2014, Amphibians in the climate vise: loss and restoration of resilience of montane wetland ecosystems in the western US: Frontiers in Ecology and the Environment, v. 12, p. 232-240, https://doi.org/10.1890/130145.","productDescription":"9 p.","startPage":"232","endPage":"240","ipdsId":"IP-050609","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":286849,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286829,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/130145"}],"country":"United States","otherGeospatial":"Western United States","volume":"12","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53659150e4b05b5c4c6daff1","contributors":{"authors":[{"text":"Ryan, Maureen E.","contributorId":45628,"corporation":false,"usgs":true,"family":"Ryan","given":"Maureen E.","affiliations":[],"preferred":false,"id":493269,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Palen, Wendy J.","contributorId":69513,"corporation":false,"usgs":true,"family":"Palen","given":"Wendy","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":493270,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adams, M. J. 0000-0001-8844-042X mjadams@usgs.gov","orcid":"https://orcid.org/0000-0001-8844-042X","contributorId":3133,"corporation":false,"usgs":false,"family":"Adams","given":"M.","email":"mjadams@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":493268,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rochefort, Regina M.","contributorId":91459,"corporation":false,"usgs":true,"family":"Rochefort","given":"Regina","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":493271,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70112938,"text":"70112938 - 2014 - BatTool: an R package with GUI for assessing the effect of White-nose syndrome and other take events on <i>Myotis</i> spp. of bats","interactions":[],"lastModifiedDate":"2014-06-18T14:17:51","indexId":"70112938","displayToPublicDate":"2014-05-01T14:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3433,"text":"Source Code for Biology and Medicine","active":true,"publicationSubtype":{"id":10}},"title":"BatTool: an R package with GUI for assessing the effect of White-nose syndrome and other take events on <i>Myotis</i> spp. of bats","docAbstract":"<p>Background:</p> \n<p>Myotis species of bats such as the Indiana Bat and Little Brown Bat are facing population declines because of White-nose syndrome (WNS). These species also face threats from anthropogenic activities such as wind energy development. Population models may be used to provide insights into threats facing these species. We developed a population model, BatTool, as an R package to help decision makers and natural resource managers examine factors influencing the dynamics of these species. The R package includes two components: 1) a deterministic and stochastic model that are accessible from the command line and 2) a graphical user interface (GUI).</p>\n<br>\n<p>Results:</p> \n<p>BatTool is an R package allowing natural resource managers and decision makers to understand Myotis spp. population dynamics. Through the use of a GUI, the model allows users to understand how WNS and other take events may affect the population. The results are saved both graphically and as data files. Additionally, R-savvy users may access the population functions through the command line and reuse the code as part of future research. This R package could also be used as part of a population dynamics or wildlife management course.</p>\n<br>\n<p>Conclusions:</p> \n<p>BatTool provides access to a Myotis spp. population model. This tool can help natural resource managers and decision makers with the Endangered Species Act deliberations for these species and with issuing take permits as part of regulatory decision making. The tool is available online as part of this publication.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Source Code for Biology and Medicine","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"BioMed Central","doi":"10.1186/1751-0473-9-9","usgsCitation":"Erickson, R.A., Thogmartin, W.E., and Szymanski, J.A., 2014, BatTool: an R package with GUI for assessing the effect of White-nose syndrome and other take events on <i>Myotis</i> spp. of bats: Source Code for Biology and Medicine, v. 9, no. 9, 10 p., https://doi.org/10.1186/1751-0473-9-9.","productDescription":"10 p.","numberOfPages":"10","onlineOnly":"Y","ipdsId":"IP-055439","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":473009,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/1751-0473-9-9","text":"Publisher Index Page"},{"id":288829,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288820,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1186/1751-0473-9-9"}],"volume":"9","issue":"9","noUsgsAuthors":false,"publicationDate":"2014-05-06","publicationStatus":"PW","scienceBaseUri":"53ae7644e4b0abf75cf2beef","contributors":{"authors":[{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":494958,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":494957,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Szymanski, Jennifer A.","contributorId":51593,"corporation":false,"usgs":true,"family":"Szymanski","given":"Jennifer","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":494959,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70049028,"text":"fs20133108 - 2014 - Estimating magnitude and frequency of floods using the PeakFQ 7.0 program","interactions":[],"lastModifiedDate":"2014-05-01T14:33:56","indexId":"fs20133108","displayToPublicDate":"2014-05-01T14:14:26","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-3108","title":"Estimating magnitude and frequency of floods using the PeakFQ 7.0 program","docAbstract":"<p>Flood-frequency analysis provides information about the magnitude and frequency of flood discharges based on records of annual maximum instantaneous peak discharges collected at streamgages. The information is essential for defining flood-hazard areas, for managing floodplains, and for designing bridges, culverts, dams, levees, and other flood-control structures.</p>\n\n<br>\n\n<p>Bulletin 17B (B17B) of the Interagency Advisory Committee on Water Data (IACWD; 1982) codifies the standard methodology for conducting flood-frequency studies in the United States. B17B specifies that annual peak-flow data are to be fit to a log-Pearson Type III distribution. Specific methods are also prescribed for improving skew estimates using regional skew information, tests for high and low outliers, adjustments for low outliers and zero flows, and procedures for incorporating historical flood information.</p>\n\n<br>\n\n<p>The authors of B17B identified various needs for methodological improvement and recommended additional study. In response to these needs, the Advisory Committee on Water Information (ACWI, successor to IACWD; <a href=\" http://acwi.gov/\" target=\"_blank\"> http://acwi.gov/</a>, Subcommittee on Hydrology (SOH), Hydrologic Frequency Analysis Work Group (HFAWG), has recommended modest changes to B17B. These changes include adoption of a generalized method-of-moments estimator denoted the Expected Moments Algorithm (EMA) (Cohn and others, 1997) and a generalized version of the Grubbs-Beck test for low outliers (Cohn and others, 2013). The SOH requested that the USGS implement these changes in a user-friendly, publicly accessible program.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133108","usgsCitation":"Veilleux, A.G., Cohn, T., Flynn, K.M., Mason, and Hummel, P.R., 2014, Estimating magnitude and frequency of floods using the PeakFQ 7.0 program: U.S. Geological Survey Fact Sheet 2013-3108, 2 p., https://doi.org/10.3133/fs20133108.","productDescription":"2 p.","onlineOnly":"Y","ipdsId":"IP-049306","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":286834,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133108.jpg"},{"id":286832,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3108/"},{"id":286833,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3108/pdf/fs2013-3108.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53635ecfe4b08180b01424fa","contributors":{"authors":[{"text":"Veilleux, Andrea G. aveilleux@usgs.gov","contributorId":4404,"corporation":false,"usgs":true,"family":"Veilleux","given":"Andrea","email":"aveilleux@usgs.gov","middleInitial":"G.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":486049,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cohn, Timothy A. tacohn@usgs.gov","contributorId":2927,"corporation":false,"usgs":true,"family":"Cohn","given":"Timothy A.","email":"tacohn@usgs.gov","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":486048,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flynn, Kathleen M.","contributorId":43756,"corporation":false,"usgs":true,"family":"Flynn","given":"Kathleen","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":486050,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mason, Jr. 0000-0002-3998-3468 rrmason@usgs.gov","orcid":"https://orcid.org/0000-0002-3998-3468","contributorId":2090,"corporation":false,"usgs":true,"family":"Mason","suffix":"Jr.","email":"rrmason@usgs.gov","affiliations":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"preferred":true,"id":486047,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hummel, Paul R.","contributorId":58728,"corporation":false,"usgs":true,"family":"Hummel","given":"Paul","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":486051,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70126738,"text":"70126738 - 2014 - Response to heavy, non-floating oil spilled in a Great Lakes river environment: a multiple-lines-of-evidence approach for submerged oil assessment and recovery","interactions":[],"lastModifiedDate":"2017-06-30T13:53:36","indexId":"70126738","displayToPublicDate":"2014-05-01T14:06:00","publicationYear":"2014","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Response to heavy, non-floating oil spilled in a Great Lakes river environment: a multiple-lines-of-evidence approach for submerged oil assessment and recovery","docAbstract":"<p>The Enbridge Line 6B pipeline release of diluted bitumen into the Kalamazoo River downstream of Marshall, MI in July 2010 is one of the largest freshwater oil spills in North American history. The unprecedented scale of impact and massive quantity of oil released required the development and implementation of new approaches for detection and recovery. At the onset of cleanup, conventional recovery techniques were employed for the initially floating oil and were successful. However, volatilization of the lighter diluent, along with mixing of the oil with sediment during flooded, turbulent river conditions caused the oil to sink and collect in natural deposition areas in the river. For more than three years after the spill, recovery of submerged oil has remained the predominant operational focus of the response.</p>\n<br>\n<p>The recovery complexities for submerged oil mixed with sediment in depositional areas and long-term oil sheening along approximately 38 miles of the Kalamazoo River led to the development of a multiple-lines-of-evidence approach comprising six major components: geomorphic mapping, field assessments of submerged oil (poling), systematic tracking and mapping of oil sheen, hydrodynamic and sediment transport modeling, forensic oil chemistry, and net environmental benefit analysis. The Federal On-Scene Coordinator (FOSC) considered this information in determining the appropriate course of action for each impacted segment of the river.</p>\n<br>\n<p>New sources of heavy crude oils like diluted bitumen and increasing transportation of those oils require changes in the way emergency personnel respond to oil spills in the Great Lakes and other freshwater ecosystems. Strategies to recover heavy oils must consider that the oils may suspend or sink in the water column, mix with fine-grained sediment, and accumulate in depositional areas. Early understanding of the potential fate and behavior of diluted bitumen spills when combined with timely, strong conventional recovery methods can significantly influence response success.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"International Oil Spill Conference Proceedings","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"International Oil Spill Conference","publisherLocation":"Washington D.C.","doi":"10.7901/2169-3358-2014.1.434","usgsCitation":"Dollhopf, R.H., Fitzpatrick, F.A., Kimble, J.W., Capone, D.M., Graan, T.P., Zelt, R.B., and Johnson, R., 2014, Response to heavy, non-floating oil spilled in a Great Lakes river environment: a multiple-lines-of-evidence approach for submerged oil assessment and recovery, <i>in</i> International Oil Spill Conference Proceedings, v. 2014, no. 1, p. 434-448, https://doi.org/10.7901/2169-3358-2014.1.434.","productDescription":"15 p.","startPage":"434","endPage":"448","numberOfPages":"15","ipdsId":"IP-053313","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":294549,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294548,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.7901/2169-3358-2014.1.434"}],"country":"United States","state":"Michigan","otherGeospatial":"Kalamazoo River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -85.663515,42.215564 ], [ -85.663515,42.406311 ], [ -84.915548,42.406311 ], [ -84.915548,42.215564 ], [ -85.663515,42.215564 ] ] ] } } ] }","volume":"2014","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54252ec9e4b0e641df8a7110","contributors":{"authors":[{"text":"Dollhopf, Ralph H.","contributorId":31323,"corporation":false,"usgs":true,"family":"Dollhopf","given":"Ralph","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":502146,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fitzpatrick, Faith A. fafitzpa@usgs.gov","contributorId":1182,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Faith","email":"fafitzpa@usgs.gov","middleInitial":"A.","affiliations":[{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":502145,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kimble, Jeffrey W.","contributorId":58961,"corporation":false,"usgs":true,"family":"Kimble","given":"Jeffrey","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":502147,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Capone, Daniel M.","contributorId":64167,"corporation":false,"usgs":true,"family":"Capone","given":"Daniel","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":502148,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Graan, Thomas P.","contributorId":97021,"corporation":false,"usgs":true,"family":"Graan","given":"Thomas","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":502149,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zelt, Ronald B. 0000-0001-9024-855X rbzelt@usgs.gov","orcid":"https://orcid.org/0000-0001-9024-855X","contributorId":300,"corporation":false,"usgs":true,"family":"Zelt","given":"Ronald","email":"rbzelt@usgs.gov","middleInitial":"B.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":502144,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Johnson, Rex","contributorId":104374,"corporation":false,"usgs":true,"family":"Johnson","given":"Rex","affiliations":[],"preferred":false,"id":502150,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70098087,"text":"ofr20131293 - 2014 - Geodesy- and geology-based slip-rate models for the Western United States (excluding California) national seismic hazard maps","interactions":[],"lastModifiedDate":"2014-05-01T14:01:26","indexId":"ofr20131293","displayToPublicDate":"2014-05-01T13:48:01","publicationYear":"2014","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":"2013-1293","title":"Geodesy- and geology-based slip-rate models for the Western United States (excluding California) national seismic hazard maps","docAbstract":"The 2014 National Seismic Hazard Maps for the conterminous United States incorporate additional uncertainty in fault slip-rate parameter that controls the earthquake-activity rates than was applied in previous versions of the hazard maps. This additional uncertainty is accounted for by new geodesy- and geology-based slip-rate models for the Western United States. Models that were considered include an updated geologic model based on expert opinion and four combined inversion models informed by both geologic and geodetic input. The two block models considered indicate significantly higher slip rates than the expert opinion and the two fault-based combined inversion models. For the hazard maps, we apply 20 percent weight with equal weighting for the two fault-based models. Off-fault geodetic-based models were not considered in this version of the maps. Resulting changes to the hazard maps are generally less than 0.05 g (acceleration of gravity). Future research will improve the maps and interpret differences between the new models.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131293","usgsCitation":"Petersen, M.D., Zeng, Y., Haller, K., McCaffrey, R., Hammond, W.C., Bird, P., Moschetti, M., Shen, Z., Bormann, J., and Thatcher, W., 2014, Geodesy- and geology-based slip-rate models for the Western United States (excluding California) national seismic hazard maps: U.S. Geological Survey Open-File Report 2013-1293, vi, 80 p., https://doi.org/10.3133/ofr20131293.","productDescription":"vi, 80 p.","numberOfPages":"86","onlineOnly":"Y","ipdsId":"IP-051654","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":286831,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131293.jpg"},{"id":286828,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1293/"},{"id":286830,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1293/pdf/ofr2013-1293.pdf"}],"country":"United States","state":"Arizona;Colorado;Idaho;Montana;New Mexico;Nevada;Oregon;Utah;Washington;Wyoming","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -125.5,8.333333333333334E-4 ], [ -125.5,0.001388888888888889 ], [ -0.016666666666666666,0.001388888888888889 ], [ -0.016666666666666666,8.333333333333334E-4 ], [ -125.5,8.333333333333334E-4 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53635ed0e4b08180b01424fe","contributors":{"authors":[{"text":"Petersen, Mark D. 0000-0001-8542-3990 mpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8542-3990","contributorId":1163,"corporation":false,"usgs":true,"family":"Petersen","given":"Mark","email":"mpetersen@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":491552,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zeng, Yuehua zeng@usgs.gov","contributorId":1623,"corporation":false,"usgs":true,"family":"Zeng","given":"Yuehua","email":"zeng@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":491554,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haller, Kathleen M. haller@usgs.gov","contributorId":1331,"corporation":false,"usgs":true,"family":"Haller","given":"Kathleen M.","email":"haller@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":491553,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCaffrey, Robert","contributorId":51207,"corporation":false,"usgs":true,"family":"McCaffrey","given":"Robert","affiliations":[],"preferred":false,"id":491557,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hammond, William C.","contributorId":73735,"corporation":false,"usgs":true,"family":"Hammond","given":"William","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":491559,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bird, Peter","contributorId":78643,"corporation":false,"usgs":true,"family":"Bird","given":"Peter","affiliations":[],"preferred":false,"id":491560,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Moschetti, Morgan","contributorId":69479,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","affiliations":[],"preferred":false,"id":491558,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Shen, Zhengkang","contributorId":31680,"corporation":false,"usgs":true,"family":"Shen","given":"Zhengkang","affiliations":[],"preferred":false,"id":491555,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bormann, Jayne","contributorId":85093,"corporation":false,"usgs":true,"family":"Bormann","given":"Jayne","email":"","affiliations":[],"preferred":false,"id":491561,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Thatcher, Wayne","contributorId":35325,"corporation":false,"usgs":true,"family":"Thatcher","given":"Wayne","affiliations":[],"preferred":false,"id":491556,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70150435,"text":"70150435 - 2014 - Effects of smallmouth buffalo, <i>Ictiobus bubalus</i> biomass on water transparency, nutrients, and productivity in shallow experimental ponds","interactions":[],"lastModifiedDate":"2015-06-26T11:34:32","indexId":"70150435","displayToPublicDate":"2014-05-01T12:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1103,"text":"Bulletin of Environmental Contamination and Toxicology","active":true,"publicationSubtype":{"id":10}},"title":"Effects of smallmouth buffalo, <i>Ictiobus bubalus</i> biomass on water transparency, nutrients, and productivity in shallow experimental ponds","docAbstract":"<p>The smallmouth buffalo <i>Ictiobus bubalus</i> is a native benthivore to floodplain lakes in the Yazoo River Basin, USA. Based on evidence from other benthivorous fish studies we hypothesized high biomasses of <i>I. bubalus</i> contribute to poor water quality conditions. We tested this hypothesis in shallow (&lt; 1.5 m) 0.05 ha earthen ponds at three stocking biomasses over a 10-week period during the summer of 2012. The most notable results from the permutational multivariate analysis of variance suggest <i>I. bubalus</i> at high and moderate biomasses significantly (p &lt; 0.05) enhanced turbidity and suspended solid levels while decreasing Secchi depth. Our results suggest that effects of <i>I. bubalus</i> on water clarity may have considerable ecological implications in natural habitats such as shallow floodplain lakes.</p>","language":"English","publisher":"Springer-Verlag","publisherLocation":"New York, NY","doi":"10.1007/s00128-014-1231-8","usgsCitation":"Goetz, D.B., Kroger, R., and Miranda, L.E., 2014, Effects of smallmouth buffalo, <i>Ictiobus bubalus</i> biomass on water transparency, nutrients, and productivity in shallow experimental ponds: Bulletin of Environmental Contamination and Toxicology, v. 92, no. 5, p. 503-508, https://doi.org/10.1007/s00128-014-1231-8.","productDescription":"6 p.","startPage":"503","endPage":"508","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054941","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":302420,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"92","issue":"5","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2014-02-14","publicationStatus":"PW","scienceBaseUri":"558e77b5e4b0b6d21dd6594e","contributors":{"authors":[{"text":"Goetz, Daniel B.","contributorId":143784,"corporation":false,"usgs":false,"family":"Goetz","given":"Daniel","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":557066,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kroger, Robert","contributorId":143701,"corporation":false,"usgs":false,"family":"Kroger","given":"Robert","email":"","affiliations":[],"preferred":false,"id":557067,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miranda, Leandro E. 0000-0002-2138-7924 smiranda@usgs.gov","orcid":"https://orcid.org/0000-0002-2138-7924","contributorId":531,"corporation":false,"usgs":true,"family":"Miranda","given":"Leandro","email":"smiranda@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":556878,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70148701,"text":"70148701 - 2014 - Influence of drift and admixture on population structure of American black bears (<i>Ursus americanus</i>) in the Central Interior Highlands, USA, 50 years after translocation","interactions":[],"lastModifiedDate":"2015-06-22T11:08:05","indexId":"70148701","displayToPublicDate":"2014-05-01T12:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2774,"text":"Molecular Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Influence of drift and admixture on population structure of American black bears (<i>Ursus americanus</i>) in the Central Interior Highlands, USA, 50 years after translocation","docAbstract":"<p>Bottlenecks, founder events, and genetic drift often result in decreased genetic diversity and increased population differentiation. These events may follow abundance declines due to natural or anthropogenic perturbations, where translocations may be an effective conservation strategy to increase population size. American black bears (<i>Ursus americanus</i>) were nearly extirpated from the Central Interior Highlands, USA by 1920. In an effort to restore bears, 254 individuals were translocated from Minnesota, USA, and Manitoba, Canada, into the Ouachita and Ozark Mountains from 1958 to 1968. Using 15 microsatellites and mitochondrial haplotypes, we observed contemporary genetic diversity and differentiation between the source and supplemented populations. We inferred four genetic clusters: Source, Ouachitas, Ozarks, and a cluster in Missouri where no individuals were translocated. Coalescent models using approximate Bayesian computation identified an admixture model as having the highest posterior probability (0.942) over models where the translocation was unsuccessful or acted as a founder event. Nuclear genetic diversity was highest in the source (A<sub>R</sub> = 9.11) and significantly lower in the translocated populations (A<sub>R</sub> = 7.07-7.34; <i>P</i> = 0.004). The Missouri cluster had the lowest genetic diversity (A<sub>R</sub> = 5.48) and served as a natural experiment showing the utility of translocations to increase genetic diversity following demographic bottlenecks. Differentiation was greater between the two admixed populations than either compared to the source, suggesting that genetic drift acted strongly over the eight generations since the translocation. The Ouachitas and Missouri were previously hypothesized to be remnant lineages. We observed a pretranslocation remnant signature in Missouri but not in the Ouachitas.</p>","language":"English","publisher":"Blackwell Science","publisherLocation":"Oxford","doi":"10.1111/mec.12748","collaboration":"Oklahoma Department of Wildlife Conservation; Missouri Department of Conservation; Arkansas Game and Fish Commission; Federal Aid in Wildlife Restoration program; Safari Club International Foundation; University of Missouri Life Sciences Fellowship; Univ Missouri, Div Biol Sci","usgsCitation":"Puckett, E.E., Kristensen, T.V., Wilton, C.M., Lyda, S.B., Noyce, K.V., Holahan, P.M., Leslie, D.M., Beringer, J., Belant, J.L., White, D., and Eggert, L.S., 2014, Influence of drift and admixture on population structure of American black bears (<i>Ursus americanus</i>) in the Central Interior Highlands, USA, 50 years after translocation: Molecular Ecology, v. 23, no. 10, p. 2414-2427, https://doi.org/10.1111/mec.12748.","productDescription":"14 p.","startPage":"2414","endPage":"2427","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052399","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":301484,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","issue":"10","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2014-05-05","publicationStatus":"PW","scienceBaseUri":"558931c8e4b0b6d21dd61bed","contributors":{"authors":[{"text":"Puckett, Emily E.","contributorId":141457,"corporation":false,"usgs":false,"family":"Puckett","given":"Emily","email":"","middleInitial":"E.","affiliations":[{"id":13494,"text":"Division of Biological Sciences, University of Missouri, Columbia, MO","active":true,"usgs":false}],"preferred":false,"id":549584,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kristensen, Thea V.","contributorId":141458,"corporation":false,"usgs":false,"family":"Kristensen","given":"Thea","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":549585,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilton, Clay M.","contributorId":141459,"corporation":false,"usgs":false,"family":"Wilton","given":"Clay","email":"","middleInitial":"M.","affiliations":[{"id":12944,"text":"Carnivore Ecology Laboratory, Forest and Wildlife Research Center, Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":549586,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lyda, Sara B.","contributorId":141460,"corporation":false,"usgs":false,"family":"Lyda","given":"Sara","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":549587,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Noyce, Karen V.","contributorId":141461,"corporation":false,"usgs":false,"family":"Noyce","given":"Karen","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":549588,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Holahan, Paula M.","contributorId":141462,"corporation":false,"usgs":false,"family":"Holahan","given":"Paula","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":549589,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Leslie, David M. Jr. 0000-0002-3884-1484 cleslie@usgs.gov","orcid":"https://orcid.org/0000-0002-3884-1484","contributorId":2483,"corporation":false,"usgs":true,"family":"Leslie","given":"David","suffix":"Jr.","email":"cleslie@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":549068,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Beringer, J.","contributorId":25274,"corporation":false,"usgs":true,"family":"Beringer","given":"J.","email":"","affiliations":[],"preferred":false,"id":549590,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Belant, Jerrold L.","contributorId":108394,"corporation":false,"usgs":false,"family":"Belant","given":"Jerrold","email":"","middleInitial":"L.","affiliations":[{"id":35599,"text":"Carnivore Ecology Laboratory, Mississippi State University, Mississippi State, MS","active":true,"usgs":false}],"preferred":false,"id":549591,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"White, D. Jr.","contributorId":81267,"corporation":false,"usgs":true,"family":"White","given":"D.","suffix":"Jr.","affiliations":[],"preferred":false,"id":549592,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Eggert, Lori S.","contributorId":106325,"corporation":false,"usgs":false,"family":"Eggert","given":"Lori","email":"","middleInitial":"S.","affiliations":[{"id":13259,"text":"USDA Forest Service Northern Research Station","active":true,"usgs":false}],"preferred":false,"id":549593,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70112919,"text":"70112919 - 2014 - From theoretical to actual ecosystem services: mapping beneficiaries and spatial flows in ecosystem service assessments","interactions":[],"lastModifiedDate":"2014-06-18T12:40:06","indexId":"70112919","displayToPublicDate":"2014-05-01T11:58:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1468,"text":"Ecology and Society","active":true,"publicationSubtype":{"id":10}},"title":"From theoretical to actual ecosystem services: mapping beneficiaries and spatial flows in ecosystem service assessments","docAbstract":"Ecosystem services mapping and modeling has focused more on supply than demand, until recently. Whereas the potential provision of economic benefits from ecosystems to people is often quantified through ecological production functions, the use of and demand for ecosystem services has received less attention, as have the spatial flows of services from ecosystems to people. However, new modeling approaches that map and quantify service-specific sources (ecosystem capacity to provide a service), sinks (biophysical or anthropogenic features that deplete or alter service flows), users (user locations and level of demand), and spatial flows can provide a more complete understanding of ecosystem services. Through a case study in Puget Sound, Washington State, USA, we quantify and differentiate between the theoretical or in situ provision of services, i.e., ecosystems’ capacity to supply services, and their actual provision when accounting for the location of beneficiaries and the spatial connections that mediate service flows between people and ecosystems. Our analysis includes five ecosystem services: carbon sequestration and storage, riverine flood regulation, sediment regulation for reservoirs, open space proximity, and scenic viewsheds. Each ecosystem service is characterized by different beneficiary groups and means of service flow. Using the ARtificial Intelligence for Ecosystem Services (ARIES) methodology we map service supply, demand, and flow, extending on simpler approaches used by past studies to map service provision and use. With the exception of the carbon sequestration service, regions that actually provided services to people, i.e., connected to beneficiaries via flow paths, amounted to 16-66% of those theoretically capable of supplying services, i.e., all ecosystems across the landscape. These results offer a more complete understanding of the spatial dynamics of ecosystem services and their effects, and may provide a sounder basis for economic valuation and policy applications than studies that consider only theoretical service provision and/or use.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecology and Society","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Resilience Alliance","doi":"10.5751/ES-06523-190264","usgsCitation":"Bagstad, K.J., Villa, F., Batker, D., Harrison-Cox, J., Voigt, B., and Johnson, G.W., 2014, From theoretical to actual ecosystem services: mapping beneficiaries and spatial flows in ecosystem service assessments: Ecology and Society, v. 19, no. 2, 14 p., https://doi.org/10.5751/ES-06523-190264.","productDescription":"14 p.","numberOfPages":"14","onlineOnly":"Y","ipdsId":"IP-051221","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":473012,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/es-06523-190264","text":"Publisher Index Page"},{"id":288808,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288807,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.5751/ES-06523-190264"}],"country":"United States","state":"Washington","otherGeospatial":"Puget Sound","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.8767,46.0676 ], [ -124.8767,48.9997 ], [ -119.7523,48.9997 ], [ -119.7523,46.0676 ], [ -124.8767,46.0676 ] ] ] } } ] }","volume":"19","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae76cfe4b0abf75cf2c02a","contributors":{"authors":[{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":494924,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Villa, Ferdinando","contributorId":84249,"corporation":false,"usgs":true,"family":"Villa","given":"Ferdinando","affiliations":[],"preferred":false,"id":494927,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Batker, David","contributorId":39288,"corporation":false,"usgs":true,"family":"Batker","given":"David","email":"","affiliations":[],"preferred":false,"id":494925,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harrison-Cox, Jennifer","contributorId":68225,"corporation":false,"usgs":true,"family":"Harrison-Cox","given":"Jennifer","email":"","affiliations":[],"preferred":false,"id":494926,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Voigt, Brian","contributorId":102962,"corporation":false,"usgs":true,"family":"Voigt","given":"Brian","affiliations":[],"preferred":false,"id":494929,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Gary W.","contributorId":90618,"corporation":false,"usgs":true,"family":"Johnson","given":"Gary","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":494928,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70103374,"text":"70103374 - 2014 - The digital global geologic map of Mars: Chronostratigraphic ages, topographic and crater morphologic characteristics, and updated resurfacing history","interactions":[],"lastModifiedDate":"2019-12-10T12:39:00","indexId":"70103374","displayToPublicDate":"2014-05-01T11:02:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3083,"text":"Planetary and Space Science","active":true,"publicationSubtype":{"id":10}},"title":"The digital global geologic map of Mars: Chronostratigraphic ages, topographic and crater morphologic characteristics, and updated resurfacing history","docAbstract":"A new global geologic map of Mars has been completed in a digital, geographic information system (GIS) format using geospatially controlled altimetry and image data sets. The map reconstructs the geologic history of Mars, which includes many new findings collated in the quarter century since the previous, Viking-based global maps were published, as well as other discoveries that were made during the course of the mapping using new data sets. The technical approach enabled consistent and regulated mapping that is appropriate not only for the map's 1:20,000,000 scale but also for its widespread use by diverse audiences. Each geologic unit outcrop includes basic attributes regarding identity, location, area, crater densities, and chronostratigraphic age. In turn, units are grouped by geographic and lithologic types, which provide synoptic global views of material ages and resurfacing character for the Noachian, Hesperian, and Amazonian periods. As a consequence of more precise and better quality topographic and morphologic data and more complete crater-density dating, our statistical comparisons identify significant refinements for how Martian geologic terrains are characterized. Unit groups show trends in mean elevation and slope that relate to geographic occurrence and geologic origin. In comparison with the previous global geologic map series based on Viking data, the new mapping consists of half the number of units due to simpler, more conservative and globally based approaches to discriminating units. In particular, Noachian highland surfaces overall have high percentages of their areas now dated as an epoch older than in the Viking mapping. Minimally eroded (i.e., pristine) impact craters ≥3 km in diameter occur in greater proportion on Hesperian surfaces. This observation contrasts with a deficit of similarly sized craters on heavily cratered and otherwise degraded Noachian terrain as well as on young Amazonian surfaces. We interpret these as reflecting the relatively stronger, lava-rich, yet less-impacted materials making up much of the younger units. Reconstructions of resurfacing of Mars by its eight geologic epochs using the Hartmann and Neukum chronology models indicate high rates of highland resurfacing during the Noachian (peaking at 0.3 km<sip>2</sup>/yr during the Middle Noachian), modest rates of volcanism and transition zone and lowland resurfacing during the Hesperian (∼0.1 km<sup>2</sup>/yr), and low rates of mainly volcanic and polar resurfacing (∼0.01 km<sup>2</sup>/yr) for most of the Amazonian. Apparent resurfacing increased in the Late Amazonian (∼0.03 km<sup>2</sup>/yr), perhaps due to better preservation of this latest record.","language":"English","publisher":"Elsevier","doi":"10.1016/j.pss.2013.03.006","usgsCitation":"Tanaka, K.L., Robbins, S., Fortezzo, C.M., Skinner, J., and Hare, T.M., 2014, The digital global geologic map of Mars: Chronostratigraphic ages, topographic and crater morphologic characteristics, and updated resurfacing history: Planetary and Space Science, v. 95, p. 11-24, https://doi.org/10.1016/j.pss.2013.03.006.","productDescription":"14 p.","startPage":"11","endPage":"24","numberOfPages":"14","ipdsId":"IP-040880","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":286845,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars","volume":"95","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5365918de4b05b5c4c6db169","contributors":{"authors":[{"text":"Tanaka, Kenneth L. ktanaka@usgs.gov","contributorId":610,"corporation":false,"usgs":true,"family":"Tanaka","given":"Kenneth","email":"ktanaka@usgs.gov","middleInitial":"L.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":777040,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robbins, S.J.","contributorId":44835,"corporation":false,"usgs":true,"family":"Robbins","given":"S.J.","email":"","affiliations":[],"preferred":false,"id":493283,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fortezzo, Corey M. 0000-0001-8188-5530 cfortezzo@usgs.gov","orcid":"https://orcid.org/0000-0001-8188-5530","contributorId":3185,"corporation":false,"usgs":true,"family":"Fortezzo","given":"Corey","email":"cfortezzo@usgs.gov","middleInitial":"M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":777041,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Skinner, J.A. Jr.","contributorId":80395,"corporation":false,"usgs":true,"family":"Skinner","given":"J.A.","suffix":"Jr.","email":"","affiliations":[],"preferred":false,"id":493284,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hare, Trent M. 0000-0001-8842-389X thare@usgs.gov","orcid":"https://orcid.org/0000-0001-8842-389X","contributorId":3188,"corporation":false,"usgs":true,"family":"Hare","given":"Trent","email":"thare@usgs.gov","middleInitial":"M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":777042,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70136301,"text":"70136301 - 2014 - Identifying stakeholder-relevant climate change impacts: a case study in the Yakima River Basin, Washington, USA","interactions":[],"lastModifiedDate":"2014-12-30T10:49:40","indexId":"70136301","displayToPublicDate":"2014-05-01T11:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1252,"text":"Climatic Change","active":true,"publicationSubtype":{"id":10}},"title":"Identifying stakeholder-relevant climate change impacts: a case study in the Yakima River Basin, Washington, USA","docAbstract":"<p>Designing climate-related research so that study results will be useful to natural resource managers is a unique challenge. While decision makers increasingly recognize the need to consider climate change in their resource management plans, and climate scientists recognize the importance of providing locally-relevant climate data and projections, there often remains a gap between management needs and the information that is available or is being collected. We used decision analysis concepts to bring decision-maker and stakeholder perspectives into the applied research planning process. In 2009 we initiated a series of studies on the impacts of climate change in the Yakima River Basin (YRB) with a four-day stakeholder workshop, bringing together managers, stakeholders, and scientists to develop an integrated conceptual model of climate change and climate change impacts in the YRB. The conceptual model development highlighted areas of uncertainty that limit the understanding of the potential impacts of climate change and decision alternatives by those who will be most directly affected by those changes, and pointed to areas where additional study and engagement of stakeholders would be beneficial. The workshop and resulting conceptual model highlighted the importance of numerous different outcomes to stakeholders in the basin, including social and economic outcomes that go beyond the physical and biological outcomes typically reported in climate impacts studies. Subsequent studies addressed several of those areas of uncertainty, including changes in water temperatures, habitat quality, and bioenergetics of salmonid populations.</p>","language":"English","publisher":"Kluwer Academic Publishers","publisherLocation":"Dordrecht","doi":"10.1007/s10584-013-0806-4","usgsCitation":"Jenni, K., Graves, D., Hardiman, J.M., Hatten, J.R., Mastin, M.C., Mesa, M.G., Montag, J., Nieman, T., Voss, F.D., and Maule, A.G., 2014, Identifying stakeholder-relevant climate change impacts: a case study in the Yakima River Basin, Washington, USA: Climatic Change, v. 124, no. 1-2, p. 371-384, https://doi.org/10.1007/s10584-013-0806-4.","productDescription":"14 p.","startPage":"371","endPage":"384","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-037460","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":473015,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10.1007/s10584-013-0806-4","text":"External Repository"},{"id":296924,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":296907,"type":{"id":15,"text":"Index Page"},"url":"https://link.springer.com/article/10.1007%2Fs10584-013-0806-4"}],"country":"United States","state":"Washington","otherGeospatial":"Yakima River Basin","volume":"124","issue":"1-2","noUsgsAuthors":false,"publicationDate":"2013-06-20","publicationStatus":"PW","scienceBaseUri":"54dd2bcee4b08de9379b34e6","contributors":{"authors":[{"text":"Jenni, K.","contributorId":131113,"corporation":false,"usgs":false,"family":"Jenni","given":"K.","email":"","affiliations":[{"id":7250,"text":"Insight Decisions LCC, 2200 Quitman Street, Denver, CO 80212","active":true,"usgs":false}],"preferred":false,"id":537318,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graves, D.","contributorId":15393,"corporation":false,"usgs":true,"family":"Graves","given":"D.","email":"","affiliations":[],"preferred":false,"id":537316,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hardiman, Jill M. 0000-0002-3661-9695 jhardiman@usgs.gov","orcid":"https://orcid.org/0000-0002-3661-9695","contributorId":2672,"corporation":false,"usgs":true,"family":"Hardiman","given":"Jill","email":"jhardiman@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":537310,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hatten, James R. 0000-0003-4676-8093 jhatten@usgs.gov","orcid":"https://orcid.org/0000-0003-4676-8093","contributorId":3431,"corporation":false,"usgs":true,"family":"Hatten","given":"James","email":"jhatten@usgs.gov","middleInitial":"R.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":537311,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mastin, Mark C. 0000-0003-4018-7861 mcmastin@usgs.gov","orcid":"https://orcid.org/0000-0003-4018-7861","contributorId":1652,"corporation":false,"usgs":true,"family":"Mastin","given":"Mark","email":"mcmastin@usgs.gov","middleInitial":"C.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":537313,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mesa, Matthew G. mmesa@usgs.gov","contributorId":3423,"corporation":false,"usgs":true,"family":"Mesa","given":"Matthew","email":"mmesa@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":537314,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Montag, J.","contributorId":10124,"corporation":false,"usgs":true,"family":"Montag","given":"J.","affiliations":[],"preferred":false,"id":537315,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nieman, Timothy","contributorId":91965,"corporation":false,"usgs":true,"family":"Nieman","given":"Timothy","affiliations":[],"preferred":false,"id":537317,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Voss, Frank D. fdvoss@usgs.gov","contributorId":1651,"corporation":false,"usgs":true,"family":"Voss","given":"Frank","email":"fdvoss@usgs.gov","middleInitial":"D.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":537309,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Maule, Alec G. amaule@usgs.gov","contributorId":2606,"corporation":false,"usgs":true,"family":"Maule","given":"Alec","email":"amaule@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":537308,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70112455,"text":"70112455 - 2014 - Looking for age-related growth decline in natural forests: unexpected biomass patterns from tree rings and simulated mortality","interactions":[],"lastModifiedDate":"2014-06-16T10:45:11","indexId":"70112455","displayToPublicDate":"2014-05-01T10:40:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2932,"text":"Oecologia","active":true,"publicationSubtype":{"id":10}},"title":"Looking for age-related growth decline in natural forests: unexpected biomass patterns from tree rings and simulated mortality","docAbstract":"Forest biomass growth is almost universally assumed to peak early in stand development, near canopy closure, after which it will plateau or decline. The chronosequence and plot remeasurement approaches used to establish the decline pattern suffer from limitations and coarse temporal detail. We combined annual tree ring measurements and mortality models to address two questions: first, how do assumptions about tree growth and mortality influence reconstructions of biomass growth? Second, under what circumstances does biomass production follow the model that peaks early, then declines? We integrated three stochastic mortality models with a census tree-ring data set from eight temperate forest types to reconstruct stand-level biomass increments (in Minnesota, USA). We compared growth patterns among mortality models, forest types and stands. Timing of peak biomass growth varied significantly among mortality models, peaking 20–30 years earlier when mortality was random with respect to tree growth and size, than when mortality favored slow-growing individuals. Random or u-shaped mortality (highest in small or large trees) produced peak growth 25–30 % higher than the surviving tree sample alone. Growth trends for even-aged, monospecific Pinus banksiana or Acer saccharum forests were similar to the early peak and decline expectation. However, we observed continually increasing biomass growth in older, low-productivity forests of Quercus rubra, Fraxinus nigra, and Thuja occidentalis. Tree-ring reconstructions estimated annual changes in live biomass growth and identified more diverse development patterns than previous methods. These detailed, long-term patterns of biomass development are crucial for detecting recent growth responses to global change and modeling future forest dynamics.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Oecologia","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s00442-014-2881-2","usgsCitation":"Foster, J.R., D’Amato, A.W., and Bradford, J.B., 2014, Looking for age-related growth decline in natural forests: unexpected biomass patterns from tree rings and simulated mortality: Oecologia, v. 175, no. 1, p. 363-374, https://doi.org/10.1007/s00442-014-2881-2.","productDescription":"12 p.","startPage":"363","endPage":"374","numberOfPages":"12","ipdsId":"IP-042931","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":288623,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288611,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s00442-014-2881-2"}],"country":"United States","state":"Minnesota","otherGeospatial":"Superior National Forest","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -96.0,44.0 ], [ -96.0,50.0 ], [ -87.0,50.0 ], [ -87.0,44.0 ], [ -96.0,44.0 ] ] ] } } ] }","volume":"175","issue":"1","noUsgsAuthors":false,"publicationDate":"2014-01-18","publicationStatus":"PW","scienceBaseUri":"53ae776ce4b0abf75cf2c11e","contributors":{"authors":[{"text":"Foster, Jane R.","contributorId":27792,"corporation":false,"usgs":true,"family":"Foster","given":"Jane","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":494744,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"D’Amato, Anthony W.","contributorId":28140,"corporation":false,"usgs":false,"family":"D’Amato","given":"Anthony","email":"","middleInitial":"W.","affiliations":[{"id":6735,"text":"University of Vermont, Rubenstein School of Environment and Natural Resources","active":true,"usgs":false},{"id":13478,"text":"Department of Forest Resources, University of Minnesota, St. Paul, Minnesota (Correspondence to: russellm@umn.edu)","active":true,"usgs":false}],"preferred":false,"id":494745,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":494743,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
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