Sakhalin taimen (Parahucho perryi) range from the Russian Far East mainland along the Sea of Japan coast, and Sakhalin, Kuril, and Hokkaido Islands and are considered to primarily be an anadromous species. We used otolith strontium-to-calcium ratios (Sr/Ca) to determine the chronology of migration between freshwater and saltwater and identify migratory contingents of taimen collected from the Koppi River, Russia. In addition, we examined taimen from the Sarufutsu River, Japan and Tumnin River, Russia that were captured in marine waters. Transects of otolith Sr/Ca for the Sarufutsu River fish were consistent with patterns observed in anadromous salmonids. Two fish from the Tumnin River appeared to be recent migrants to saltwater and one fish was characterized by an otolith Sr/Ca transect consistent with marine migration. Using these transects as benchmarks, all Koppi River taimen were classified as freshwater residents. These findings suggest more work is needed to assess life history variability among locations and the role of freshwater productivity in controlling migratory behavior in taimen.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10641-011-9908-x","usgsCitation":"Zimmerman, C.E., Rand, P., Fukushima, M., and Zolotukhin, S., 2012, Migration of Sakhalin taimen (Parahucho perryi): Evidence of freshwater resident life history types: Environmental Biology of Fishes, v. 93, no. 2, p. 223-232, https://doi.org/10.1007/s10641-011-9908-x.","productDescription":"10 p.","startPage":"223","endPage":"232","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":241727,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Japan, Russia","otherGeospatial":"Tumnin River, Koppi River, Sarufutsu River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 138.69140625,\n 46.31658418182218\n ],\n [\n 143.173828125,\n 46.31658418182218\n ],\n [\n 143.173828125,\n 54.213861000644926\n ],\n [\n 138.69140625,\n 54.213861000644926\n ],\n [\n 138.69140625,\n 46.31658418182218\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"93","issue":"2","noUsgsAuthors":false,"publicationDate":"2011-08-05","publicationStatus":"PW","scienceBaseUri":"505a5702e4b0c8380cd6d9b3","contributors":{"authors":[{"text":"Zimmerman, Christian E. 0000-0002-3646-0688 czimmerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3646-0688","contributorId":410,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Christian","email":"czimmerman@usgs.gov","middleInitial":"E.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":437030,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rand, P.S.","contributorId":17561,"corporation":false,"usgs":true,"family":"Rand","given":"P.S.","email":"","affiliations":[],"preferred":false,"id":437028,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fukushima, M.","contributorId":28082,"corporation":false,"usgs":true,"family":"Fukushima","given":"M.","email":"","affiliations":[],"preferred":false,"id":437029,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zolotukhin, S.F.","contributorId":50737,"corporation":false,"usgs":true,"family":"Zolotukhin","given":"S.F.","email":"","affiliations":[],"preferred":false,"id":437031,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70032434,"text":"70032434 - 2012 - A spatial cluster analysis of tractor overturns in Kentucky from 1960 to 2002","interactions":[],"lastModifiedDate":"2020-12-01T19:16:19.95915","indexId":"70032434","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"A spatial cluster analysis of tractor overturns in Kentucky from 1960 to 2002","docAbstract":"Background:
Agricultural tractor overturns without rollover protective structures are the leading cause of farm fatalities in the United States. To our knowledge, no studies have incorporated the spatial scan statistic in identifying high-risk areas for tractor overturns. The aim of this study was to determine whether tractor overturns cluster in certain parts of Kentucky and identify factors associated with tractor overturns.
Methods:
A spatial statistical analysis using Kulldorff's spatial scan statistic was performed to identify county clusters at greatest risk for tractor overturns. A regression analysis was then performed to identify factors associated with tractor overturns.
Results:
The spatial analysis revealed a cluster of higher than expected tractor overturns in four counties in northern Kentucky (RR = 2.55) and 10 counties in eastern Kentucky (RR = 1.97). Higher rates of tractor overturns were associated with steeper average percent slope of pasture land by county (p = 0.0002) and a greater percent of total tractors with less than 40 horsepower by county (p<0.0001).
Conclusions:
This study reveals that geographic hotspots of tractor overturns exist in Kentucky and identifies factors associated with overturns. This study provides policymakers a guide to targeted county-level interventions (e.g., roll-over protective structures promotion interventions) with the intention of reducing tractor overturns in the highest risk counties in Kentucky.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0030532","issn":"19326203","usgsCitation":"Saman, D., Cole, H., Odoi, A., Myers, M., Carey, D., and Westneat, S., 2012, A spatial cluster analysis of tractor overturns in Kentucky from 1960 to 2002: PLoS ONE, v. 7, no. 1, e30532, 9 p., https://doi.org/10.1371/journal.pone.0030532.","productDescription":"e30532, 9 p.","costCenters":[],"links":[{"id":474673,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0030532","text":"Publisher Index Page"},{"id":241716,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214029,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0030532"}],"country":"United 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\"}}]}","volume":"7","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-01-24","publicationStatus":"PW","scienceBaseUri":"5059e59fe4b0c8380cd46e98","contributors":{"authors":[{"text":"Saman, D.M.","contributorId":105924,"corporation":false,"usgs":true,"family":"Saman","given":"D.M.","email":"","affiliations":[],"preferred":false,"id":436164,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cole, H.P.","contributorId":11013,"corporation":false,"usgs":true,"family":"Cole","given":"H.P.","email":"","affiliations":[],"preferred":false,"id":436159,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Odoi, A.","contributorId":78952,"corporation":false,"usgs":true,"family":"Odoi","given":"A.","email":"","affiliations":[],"preferred":false,"id":436162,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Myers, M.L.","contributorId":104717,"corporation":false,"usgs":true,"family":"Myers","given":"M.L.","email":"","affiliations":[],"preferred":false,"id":436163,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Carey, D.I.","contributorId":12637,"corporation":false,"usgs":true,"family":"Carey","given":"D.I.","email":"","affiliations":[],"preferred":false,"id":436160,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Westneat, S.C.","contributorId":52801,"corporation":false,"usgs":true,"family":"Westneat","given":"S.C.","email":"","affiliations":[],"preferred":false,"id":436161,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70032604,"text":"70032604 - 2012 - Ocean-atmosphere dynamics during Hurricane Ida and Nor'Ida: An application of the coupled ocean-atmosphere-wave-sediment transport (COAWST) modeling system","interactions":[],"lastModifiedDate":"2017-11-05T22:24:26","indexId":"70032604","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2925,"text":"Ocean Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Ocean-atmosphere dynamics during Hurricane Ida and Nor'Ida: An application of the coupled ocean-atmosphere-wave-sediment transport (COAWST) modeling system","docAbstract":"The coupled ocean–atmosphere–wave–sediment transport (COAWST) modeling system was used to investigate atmosphere–ocean–wave interactions in November 2009 during Hurricane Ida and its subsequent evolution to Nor’Ida, which was one of the most costly storm systems of the past two decades. One interesting aspect of this event is that it included two unique atmospheric extreme conditions, a hurricane and a nor’easter storm, which developed in regions with different oceanographic characteristics. Our modeled results were compared with several data sources, including GOES satellite infrared data, JASON-1 and JASON-2 altimeter data, CODAR measurements, and wave and tidal information from the National Data Buoy Center (NDBC) and the National Tidal Database. By performing a series of numerical runs, we were able to isolate the effect of the interaction terms between the atmosphere (modeled with Weather Research and Forecasting, the WRF model), the ocean (modeled with Regional Ocean Modeling System (ROMS)), and the wave propagation and generation model (modeled with Simulating Waves Nearshore (SWAN)). Special attention was given to the role of the ocean surface roughness. Three different ocean roughness closure models were analyzed: DGHQ (which is based on wave age), TY2001 (which is based on wave steepness), and OOST (which considers both the effects of wave age and steepness). Including the ocean roughness in the atmospheric module improved the wind intensity estimation and therefore also the wind waves, surface currents, and storm surge amplitude. For example, during the passage of Hurricane Ida through the Gulf of Mexico, the wind speeds were reduced due to wave-induced ocean roughness, resulting in better agreement with the measured winds. During Nor’Ida, including the wave-induced surface roughness changed the form and dimension of the main low pressure cell, affecting the intensity and direction of the winds. The combined wave age- and wave steepness-based parameterization (OOST) provided the best results for wind and wave growth prediction. However, the best agreement between the measured (CODAR) and computed surface currents and storm surge values was obtained with the wave steepness-based roughness parameterization (TY2001), although the differences obtained with respect to DGHQ were not significant. The influence of sea surface temperature (SST) fields on the atmospheric boundary layer dynamics was examined; in particular, we evaluated how the SST affects wind wave generation, surface currents and storm surges. The integrated hydrograph and integrated wave height, parameters that are highly correlated with the storm damage potential, were found to be highly sensitive to the ocean surface roughness parameterization.
Effusion rate is a primary measurement used to judge the expected advance rate, length, and hazard potential of lava flows. At basaltic volcanoes, the rapid draining of lava stored in rootless shields and perched ponds can produce lava flows with much higher local effusion rates and advance velocities than would be expected based on the effusion rate at the vent. For several months in 2007–2008, lava stored in a series of perched ponds and rootless shields on Kīlauea Volcano, Hawai'i, was released episodically to produce fast-moving 'a'ā lava flows. Several of these lava flows approached Royal Gardens subdivision and threatened the safety of remaining residents. Using time-lapse image measurements, we show that the initial time-averaged discharge rate for one collapse-triggered lava flow was approximately eight times greater than the effusion rate at the vent. Though short-lived, the collapse-triggered 'a'ā lava flows had average advance rates approximately 45 times greater than that of the pāhoehoe flow field from which they were sourced. The high advance rates of the collapse-triggered lava flows demonstrates that recognition of lava accumulating in ponds and shields, which may be stored in a cryptic manner, is vital for accurately assessing short-term hazards at basaltic volcanoes.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Bulletin of Volcanology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s00445-011-0505-9","issn":"02588900","usgsCitation":"Patrick, M.R., and Orr, T., 2012, Rootless shield and perched lava pond collapses at Kīlauea Volcano, Hawai'i: Bulletin of Volcanology, v. 74, no. 1, p. 67-78, https://doi.org/10.1007/s00445-011-0505-9.","productDescription":"12 p.","startPage":"67","endPage":"78","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"links":[{"id":213720,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s00445-011-0505-9"},{"id":241375,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.35491943359375,\n 19.321511226817176\n ],\n [\n -155.35491943359375,\n 19.439399401246273\n ],\n [\n -155.17913818359375,\n 19.439399401246273\n ],\n [\n -155.17913818359375,\n 19.321511226817176\n ],\n [\n -155.35491943359375,\n 19.321511226817176\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"74","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-06-30","publicationStatus":"PW","scienceBaseUri":"505aae8ce4b0c8380cd87112","contributors":{"authors":[{"text":"Patrick, Matthew R. 0000-0002-8042-6639 mpatrick@usgs.gov","orcid":"https://orcid.org/0000-0002-8042-6639","contributorId":2070,"corporation":false,"usgs":true,"family":"Patrick","given":"Matthew","email":"mpatrick@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":436232,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Orr, Tim R.","contributorId":86859,"corporation":false,"usgs":true,"family":"Orr","given":"Tim R.","affiliations":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true}],"preferred":false,"id":436233,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70032251,"text":"70032251 - 2012 - Petroleum prospectivity of the Canada Basin, Arctic Ocean","interactions":[],"lastModifiedDate":"2020-12-03T21:17:52.831554","indexId":"70032251","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2682,"text":"Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"Petroleum prospectivity of the Canada Basin, Arctic Ocean","docAbstract":"Reconnaissance seismic reflection data indicate that Canada Basin is a >700,000 sq. km. remnant of the Amerasia Basin of the Arctic Ocean that lies south of the Alpha-Mendeleev Large Igneous Province, which was constructed across the northern part of the Amerasia Basin between about 127 and 89–83.5 Ma. Canada Basin was filled by Early Jurassic to Holocene detritus from the Beaufort–Mackenzie Deltaic System, which drains the northern third of interior North America, with sizable contributions from Alaska and Northwest Canada. The basin contains roughly 5 or 6 million cubic km of sediment. Three fourths or more of this volume generates low amplitude seismic reflections, interpreted to represent hemipelagic deposits, which contain lenses to extensive interbeds of moderate amplitude reflections interpreted to represent unconfined turbidite and amalgamated channel deposits.
Extrapolation from Arctic Alaska and Northwest Canada suggests that three fourths of the section in Canada Basin is correlative with stratigraphic sequences in these areas that contain intervals of hydrocarbon source rocks. In addition, worldwide heat flow averages suggest that about two thirds of Canada Basin lies in the oil or gas windows. Structural, stratigraphic and combined structural and stratigraphic features of local to regional occurrence offer exploration targets in Canada Basin, and at least one of these contains bright spots. However, deep water (to almost 4000 m), remoteness from harbors and markets, and thick accumulations of seasonal to permanent sea ice (until its possible removal by global warming later this century) will require the discovery of very large deposits for commercial success in most parts of Canada Basin.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2011.11.001","issn":"02648172","usgsCitation":"Grantz, A., and Hart, P.E., 2012, Petroleum prospectivity of the Canada Basin, Arctic Ocean: Marine and Petroleum Geology, v. 30, no. 1, p. 126-143, https://doi.org/10.1016/j.marpetgeo.2011.11.001.","productDescription":"18 p.","startPage":"126","endPage":"143","numberOfPages":"18","ipdsId":"IP-024561","costCenters":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":242442,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214694,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.marpetgeo.2011.11.001"}],"country":"United States","otherGeospatial":"Canada Basin, Arctic Ocean","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -154.68749999999997,\n 71.30079291637452\n ],\n [\n -125.859375,\n 67.33986082559095\n ],\n [\n -99.140625,\n 67.47492238478702\n ],\n [\n -62.57812500000001,\n 78.56048828398782\n ],\n [\n -53.0859375,\n 83.599030708362\n ],\n [\n -125.15625000000001,\n 84.77052832075908\n ],\n [\n -170.859375,\n 83.52016238353205\n ],\n [\n -164.8828125,\n 73.92246884621463\n ],\n [\n -154.68749999999997,\n 71.30079291637452\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a77fce4b0c8380cd785e8","contributors":{"authors":[{"text":"Grantz, Arthur agrantz@usgs.gov","contributorId":2585,"corporation":false,"usgs":true,"family":"Grantz","given":"Arthur","email":"agrantz@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":435245,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hart, Patrick E. 0000-0002-5080-1426 hart@usgs.gov","orcid":"https://orcid.org/0000-0002-5080-1426","contributorId":2879,"corporation":false,"usgs":true,"family":"Hart","given":"Patrick","email":"hart@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":435244,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70032470,"text":"70032470 - 2012 - Generation and evolution of hydrothermal fluids at Yellowstone: Insights from the Heart Lake Geyser Basin","interactions":[],"lastModifiedDate":"2019-05-30T13:00:34","indexId":"70032470","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Generation and evolution of hydrothermal fluids at Yellowstone: Insights from the Heart Lake Geyser Basin","docAbstract":"We sampled fumaroles and hot springs from the Heart Lake Geyser Basin (HLGB), measured water and gas discharge, and estimated heat and mass flux from this geothermal area in 2009. The combined data set reveals that diverse fluids share an origin by mixing of deep solute-rich parent water with dilute heated meteoric water, accompanied by subsequent boiling. A variety of chemical and isotopic geothermometers are consistent with a parent water that equilibrates with rocks at 205°C ± 10°C and then undergoes 21% ± 2% adiabatic boiling. Measured diffuse CO2 flux and fumarole compositions are consistent with an initial dissolved CO2 concentration of 21 ± 7 mmol upon arrival at the caldera boundary and prior to southeast flow, boiling, and discharge along the Witch Creek drainage. The calculated advective flow from the basin is 78 ± 16 L s−1 of parent thermal water, corresponding to 68 ± 14 MW, or –1% of the estimated thermal flux from Yellowstone. Helium and carbon isotopes reveal minor addition of locally derived crustal, biogenic, and meteoric gases as this fluid boils and degasses, reducing the He isotope ratio (Rc/Ra) from 2.91 to 1.09. The HLGB is one of the few thermal areas at Yellowstone that approaches a closed system, where a series of progressively boiled waters can be sampled along with related steam and noncondensable gas. At other Yellowstone locations, steam and gas are found without associated neutral Cl waters (e.g., Hot Spring Basin) or Cl-rich waters emerge without significant associated steam and gas (Upper Geyser Basin).","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geochemistry, Geophysics, Geosystems","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1029/2011GC003835","issn":"15252027","usgsCitation":"Lowenstern, J.B., Bergfeld, D., Evans, W.C., and Hurwitz, S., 2012, Generation and evolution of hydrothermal fluids at Yellowstone: Insights from the Heart Lake Geyser Basin: Geochemistry, Geophysics, Geosystems, v. 13, no. 1, 20 p.; Q01017, https://doi.org/10.1029/2011GC003835.","productDescription":"20 p.; Q01017","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":474808,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2011gc003835","text":"Publisher Index Page"},{"id":241719,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214032,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1029/2011GC003835"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone National Park;Heart Lake Geyser","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -110.514654,44.27994 ], [ -110.514654,44.299944 ], [ -110.494646,44.299944 ], [ -110.494646,44.27994 ], [ -110.514654,44.27994 ] ] ] } } ] }","volume":"13","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-01-28","publicationStatus":"PW","scienceBaseUri":"505a154ee4b0c8380cd54d4d","contributors":{"authors":[{"text":"Lowenstern, J. B.","contributorId":7737,"corporation":false,"usgs":true,"family":"Lowenstern","given":"J.","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":436350,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bergfeld, D.","contributorId":58053,"corporation":false,"usgs":true,"family":"Bergfeld","given":"D.","email":"","affiliations":[],"preferred":false,"id":436351,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Evans, William C.","contributorId":104903,"corporation":false,"usgs":true,"family":"Evans","given":"William","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":436353,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hurwitz, S.","contributorId":61110,"corporation":false,"usgs":true,"family":"Hurwitz","given":"S.","email":"","affiliations":[],"preferred":false,"id":436352,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70032250,"text":"70032250 - 2012 - Geostatistical modeling of the gas emission zone and its in-place gas content for Pittsburgh-seam mines using sequential Gaussian simulation","interactions":[],"lastModifiedDate":"2018-09-21T12:39:12","indexId":"70032250","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2033,"text":"International Journal of Coal Geology","active":true,"publicationSubtype":{"id":10}},"title":"Geostatistical modeling of the gas emission zone and its in-place gas content for Pittsburgh-seam mines using sequential Gaussian simulation","docAbstract":"Determination of the size of the gas emission zone, the locations of gas sources within, and especially the amount of gas retained in those zones is one of the most important steps for designing a successful methane control strategy and an efficient ventilation system in longwall coal mining. The formation of the gas emission zone and the potential amount of gas-in-place (GIP) that might be available for migration into a mine are factors of local geology and rock properties that usually show spatial variability in continuity and may also show geometric anisotropy. Geostatistical methods are used here for modeling and prediction of gas amounts and for assessing their associated uncertainty in gas emission zones of longwall mines for methane control.
This study used core data obtained from 276 vertical exploration boreholes drilled from the surface to the bottom of the Pittsburgh coal seam in a mining district in the Northern Appalachian basin. After identifying important coal and non-coal layers for the gas emission zone, univariate statistical and semivariogram analyses were conducted for data from different formations to define the distribution and continuity of various attributes. Sequential simulations performed stochastic assessment of these attributes, such as gas content, strata thickness, and strata displacement. These analyses were followed by calculations of gas-in-place and their uncertainties in the Pittsburgh seam caved zone and fractured zone of longwall mines in this mining district. Grid blanking was used to isolate the volume over the actual panels from the entire modeled district and to calculate gas amounts that were directly related to the emissions in longwall mines.
Results indicated that gas-in-place in the Pittsburgh seam, in the caved zone and in the fractured zone, as well as displacements in major rock units, showed spatial correlations that could be modeled and estimated using geostatistical methods. This study showed that GIP volumes may change up to 3 MMscf per acre and, in a multi-panel district, may total 9 Bcf of methane within the gas emission zone. Therefore, ventilation and gas capture systems should be designed accordingly. In addition, rock displacements within the gas emission zone are spatially distributed. From an engineering and practical point of view, spatial distributions of GIP and distributions of rock displacements should be correlated with in-mine emissions and gob gas venthole productions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2011.10.010","issn":"01665162","usgsCitation":"Karacan, C.O., Olea, R., and Goodman, G., 2012, Geostatistical modeling of the gas emission zone and its in-place gas content for Pittsburgh-seam mines using sequential Gaussian simulation: International Journal of Coal Geology, v. 90-91, p. 50-71, https://doi.org/10.1016/j.coal.2011.10.010.","productDescription":"22 p.","startPage":"50","endPage":"71","ipdsId":"IP-031033","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":474676,"rank":10000,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4589251","text":"External Repository"},{"id":242409,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214664,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.coal.2011.10.010"}],"volume":"90-91","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a28b3e4b0c8380cd5a320","contributors":{"authors":[{"text":"Karacan, Cevat O. 0000-0002-0947-8241","orcid":"https://orcid.org/0000-0002-0947-8241","contributorId":67742,"corporation":false,"usgs":true,"family":"Karacan","given":"Cevat","email":"","middleInitial":"O.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":435243,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olea, Ricardo A. 0000-0003-4308-0808","orcid":"https://orcid.org/0000-0003-4308-0808","contributorId":26436,"corporation":false,"usgs":true,"family":"Olea","given":"Ricardo A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":435241,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goodman, G.","contributorId":29233,"corporation":false,"usgs":true,"family":"Goodman","given":"G.","email":"","affiliations":[],"preferred":false,"id":435242,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70003924,"text":"70003924 - 2012 - Migrating birds’ use of stopover habitat in the southwestern United States","interactions":[],"lastModifiedDate":"2013-03-21T10:34:26","indexId":"70003924","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","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":"Migrating birds’ use of stopover habitat in the southwestern United States","docAbstract":"In the arid Southwest, migratory birds are known to use riparian stopover habitats; we know less about how migrants use other habitat types during migratory stopover. Using radar data and satellite land-cover data, we determined the habitats with which birds are associated during migration stopover. Bird densities differed significantly by habitat type at all sites in at least one season. In parts of Arizona and New Mexico upland forest supported high densities of migrants, especially in fall. Developed habitat, in areas with little upland forest, also supported high densities of migrants. Scrub/shrub and grassland habitats supported low to intermediate densities, but because these habitat types dominate the Southwestern landscape, they may provide stopover habitat for larger numbers of migratory birds than previously recognized. These results are complicated by continuing challenges related to target identity (i.e., distinguishing among birds, arthropods and bats). Our results suggest that it is too simplistic to (1) consider the arid West as a largely inhospitable landscape in which there are only relatively small oases of habitat that provide the resources needed by all migrants, (2) think of western riparian and upland forests as supporting the majority of migrants in all cases, and (3) consider a particular habitat unimportant for stopover solely on the basis of low densities of migrants.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"The Condor","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Cooper Ornithological Society","publisherLocation":"Waco, TX","doi":"10.1525/cond.2012.120020","usgsCitation":"Ruth, J.M., Diehl, R., and Felix, R., 2012, Migrating birds’ use of stopover habitat in the southwestern United States: The Condor, v. 114, no. 4, p. 698-710, https://doi.org/10.1525/cond.2012.120020.","productDescription":"13 p.","startPage":"698","endPage":"710","ipdsId":"IP-029588","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":269847,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":269846,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1525/cond.2012.120020"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -126.9,25.84 ], [ -126.9,49.0 ], [ -93.51,49.0 ], [ -93.51,25.84 ], [ -126.9,25.84 ] ] ] } } ] }","volume":"114","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"514c2be8e4b0cf4196fef31a","contributors":{"authors":[{"text":"Ruth, Janet M. 0000-0003-1576-5957 janet_ruth@usgs.gov","orcid":"https://orcid.org/0000-0003-1576-5957","contributorId":1408,"corporation":false,"usgs":true,"family":"Ruth","given":"Janet","email":"janet_ruth@usgs.gov","middleInitial":"M.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":349531,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diehl, R.H.","contributorId":28683,"corporation":false,"usgs":true,"family":"Diehl","given":"R.H.","email":"","affiliations":[],"preferred":false,"id":349532,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Felix, R.K. Jr.","contributorId":39669,"corporation":false,"usgs":true,"family":"Felix","given":"R.K.","suffix":"Jr.","email":"","affiliations":[],"preferred":false,"id":349533,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70005993,"text":"70005993 - 2012 - The impact of biotic/abiotic interfaces in mineral nutrient cycling: A study of soils of the Santa Cruz chronosequence, California","interactions":[],"lastModifiedDate":"2020-12-30T19:15:07.348439","indexId":"70005993","displayToPublicDate":"2011-12-25T13:43:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"The impact of biotic/abiotic interfaces in mineral nutrient cycling: A study of soils of the Santa Cruz chronosequence, California","docAbstract":"Biotic/abiotic interactions between soil mineral nutrients and annual grassland vegetation are characterized for five soils in a marine terrace chronosequence near Santa Cruz, California. A Mediterranean climate, with wet winters and dry summers, controls the annual cycle of plant growth and litter decomposition, resulting in net above-ground productivities of 280–600 g m−2 yr−1. The biotic/abiotic (A/B) interface separates seasonally reversible nutrient gradients, reflecting biological cycling in the shallower soils, from downward chemical weathering gradients in the deeper soils. The A/B interface is pedologically defined by argillic clay horizons centered at soil depths of about one meter which intensify with soil age. Below these horizons, elevated solute Na/Ca, Mg/Ca and Sr/Ca ratios reflect plagioclase and smectite weathering along pore water flow paths. Above the A/B interface, lower cation ratios denote temporal variability due to seasonal plant nutrient uptake and litter leaching. Potassium and Ca exhibit no seasonal variability beneath the A/B interface, indicating closed nutrient cycling within the root zone, whereas Mg variability below the A/B interface denotes downward leakage resulting from higher inputs of marine aerosols and lower plant nutrient requirements.
The fraction of a mineral nutrient annually cycled through the plants, compared to that lost from pore water discharge, is defined their respective fluxes Fj,plants = qj,plants/(qj,plants + qj,discharge) with average values for K and Ca (FK,plants = 0.99; FCa,plants = 0.93) much higher than for Mg and Na (FMg,plants 0.64; FNa,plants = 0.28). The discrimination against Rb and Sr by plants is described by fractionation factors (KSr/Ca = 0.86; KRb/K = 0.83) which are used in Rayleigh fractionation-mixing calculations to fit seasonal patterns in solute K and Ca cycling. KRb/K and
Site-specific temporal trends in algae, benthic invertebrate, and fish assemblages were investigated in 15 streams and rivers draining basins of varying land use in the south-central United States from 1993–2007. A multivariate approach was used to identify sites with statistically significant trends in aquatic assemblages which were then tested for correlations with assemblage metrics and abiotic environmental variables (climate, water quality, streamflow, and physical habitat). Significant temporal trends in one or more of the aquatic assemblages were identified at more than half (eight of 15) of the streams in the study. Assemblage metrics and abiotic environmental variables found to be significantly correlated with aquatic assemblages differed between land use categories. For example, algal assemblages at undeveloped sites were associated with physical habitat, while algal assemblages at more anthropogenically altered sites (agricultural and urban) were associated with nutrient and streamflow metrics. In urban stream sites results indicate that streamflow metrics may act as important controls on water quality conditions, as represented by aquatic assemblage metrics. The site-specific identification of biotic trends and abiotic–biotic relations presented here will provide valuable information that can inform interpretation of continued monitoring data and the design of future studies. In addition, the subsets of abiotic variables identified as potentially important drivers of change in aquatic assemblages provide policy makers and resource managers with information that will assist in the design and implementation of monitoring programs aimed at the protection of aquatic resources.
","language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s10750-011-0950-7","usgsCitation":"Miller, M.P., Kennen, J., Mabe, J.A., and Mize, S.V., 2012, Temporal trends in algae, benthic invertebrate, and fish assemblages in streams and rivers draining basins of varying land use in the south-central United States, 1993-2007: Hydrobiologia, v. 684, no. 1, p. 15-33, https://doi.org/10.1007/s10750-011-0950-7.","productDescription":"19 p.","startPage":"15","endPage":"33","temporalStart":"1993-01-01","temporalEnd":"2007-12-31","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":257563,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Colorado, Kansas, Kentucky, Louisiana, Mississippi, Missouri, New Mexico, Oklahoma, Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n 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0000-0002-5426-4445 jgkennen@usgs.gov","orcid":"https://orcid.org/0000-0002-5426-4445","contributorId":574,"corporation":false,"usgs":true,"family":"Kennen","given":"Jonathan G.","email":"jgkennen@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":353583,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mabe, Jeffrey A.","contributorId":65565,"corporation":false,"usgs":true,"family":"Mabe","given":"Jeffrey","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":353586,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mize, Scott V. 0000-0001-6751-5568 svmize@usgs.gov","orcid":"https://orcid.org/0000-0001-6751-5568","contributorId":2997,"corporation":false,"usgs":true,"family":"Mize","given":"Scott","email":"svmize@usgs.gov","middleInitial":"V.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":353584,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70102820,"text":"70102820 - 2012 - Programs for calibration‐based Monte Carlo simulation of recharge areas","interactions":[],"lastModifiedDate":"2019-07-03T14:25:36","indexId":"70102820","displayToPublicDate":"2011-10-11T13:24:55","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1861,"text":"Ground Water","active":true,"publicationSubtype":{"id":10}},"title":"Programs for calibration‐based Monte Carlo simulation of recharge areas","docAbstract":"One use of groundwater flow models is to simulate contributing recharge areas to wells or springs. Particle tracking can be used to simulate these recharge areas, but in many cases the modeler is not sure how accurate these recharge areas are because parameters such as hydraulic conductivity and recharge have errors associated with them. The scripts described in this article (GEN_LHS and MCDRIVER_LHS) use the Python scripting language to run a Monte Carlo simulation with Latin hypercube sampling where model parameters such as hydraulic conductivity and recharge are randomly varied for a large number of model simulations, and the probability of a particle being in the contributing area of a well is calculated based on the results of multiple simulations. Monte Carlo simulation provides one useful measure of the variability in modeled particles. The Monte Carlo method described here is unique in that it uses parameter sets derived from the optimal parameters, their standard deviations, and their correlation matrix, all of which are calculated during nonlinear regression model calibration. In addition, this method uses a set of acceptance criteria to eliminate unrealistic parameter sets.
","language":"English","publisher":"NGWA","doi":"10.1111/j.1745-6584.2011.00868.x","usgsCitation":"Starn, J., and Bagtzoglou, A.C., 2012, Programs for calibration‐based Monte Carlo simulation of recharge areas: Ground Water, v. 50, no. 3, p. 472-476, https://doi.org/10.1111/j.1745-6584.2011.00868.x.","productDescription":"5 p.","startPage":"472","endPage":"476","ipdsId":"IP-029084","costCenters":[{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true}],"links":[{"id":365284,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"50","issue":"3","noUsgsAuthors":false,"publicationDate":"2011-10-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Starn, J. Jeffrey 0000-0001-5909-0010 jjstarn@usgs.gov","orcid":"https://orcid.org/0000-0001-5909-0010","contributorId":1916,"corporation":false,"usgs":true,"family":"Starn","given":"J. Jeffrey","email":"jjstarn@usgs.gov","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":false,"id":518736,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bagtzoglou, Amvrossios C.","contributorId":211518,"corporation":false,"usgs":false,"family":"Bagtzoglou","given":"Amvrossios","email":"","middleInitial":"C.","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":765422,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70118981,"text":"70118981 - 2012 - MODFLOW-style parameters in underdetermined parameter estimation","interactions":[],"lastModifiedDate":"2024-04-24T16:19:51.813673","indexId":"70118981","displayToPublicDate":"2011-02-25T09:11:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"MODFLOW-style parameters in underdetermined parameter estimation","docAbstract":"In this article, we discuss the use of MODFLOW-Style parameters in the numerical codes MODFLOW_2005 and MODFLOW_2005-Adjoint for the definition of variables in the Layer Property Flow package. Parameters are a useful tool to represent aquifer properties in both codes and are the only option available in the adjoint version. Moreover, for overdetermined parameter estimation problems, the parameter approach for model input can make data input easier. We found that if each estimable parameter is defined by one parameter, the codes require a large computational effort and substantial gains in efficiency are achieved by removing logical comparison of character strings that represent the names and types of the parameters. An alternative formulation already available in the current implementation of the code can also alleviate the efficiency degradation due to character comparisons in the special case of distributed parameters defined through multiplication matrices. The authors also hope that lessons learned in analyzing the performance of the MODFLOW family codes will be enlightening to developers of other Fortran implementations of numerical codes.
","language":"English","publisher":"National Groundwater Association","doi":"10.1111/j.1745-6584.2011.00803.x","usgsCitation":"D’Oria, M.D., and Fienen, M., 2012, MODFLOW-style parameters in underdetermined parameter estimation: Groundwater, v. 50, no. 1, p. 149-153, https://doi.org/10.1111/j.1745-6584.2011.00803.x.","productDescription":"5 p.","startPage":"149","endPage":"153","ipdsId":"IP-016755","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":291560,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"50","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-02-25","publicationStatus":"PW","scienceBaseUri":"53e09e5be4b0beb42bdca469","contributors":{"authors":[{"text":"D’Oria, Marco D.","contributorId":22258,"corporation":false,"usgs":true,"family":"D’Oria","given":"Marco","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":497550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fienen, Michael N. 0000-0002-7756-4651 mnfienen@usgs.gov","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":893,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","email":"mnfienen@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":497549,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70227301,"text":"70227301 - 2011 - Evaluation of two forms of electroanesthesia and carbon dioxide for short-term anesthesia in walleye","interactions":[],"lastModifiedDate":"2022-01-07T17:41:42.8598","indexId":"70227301","displayToPublicDate":"2021-11-28T11:37:54","publicationYear":"2011","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":"Evaluation of two forms of electroanesthesia and carbon dioxide for short-term anesthesia in walleye","docAbstract":"Anesthetics immobilize fish, reducing physical damage and stress during aquaculture practices, stock assessment, and experimental procedures. Currently, only tricaine methanesulfonate (MS-222) is approved for use as an anesthetic for food fish in Canada and the United States; however, MS-222 can only be used with certain fish species, and treated fish must be held for a specified period of time before release into the wild. Two forms of electroanesthesia and carbon dioxide (CO2) were evaluated as anesthetics for adult walleye Sander vitreus to determine their suitability for use before intracoelomic implantation of telemetry transmitters. Walleyes were subjected to one of three treatment groups: constant direct current (CDC), pulsed direct current (PDC), and CO2. Fish subjected to these treatments were monitored for induction (where appropriate) and recovery time and whether these forms of anesthesia were conducive to implanting telemetry transmitters, that is, whether they fit a surgery threshold range of 250–350 s. Additionally, all fish were monitored for posttrial survival, and radiographs were taken to determine whether any vertebral damage was associated with the electroanesthesia treatments. Although all anesthetic treatments successfully immobilized fish for enough time to implant a transmitter, PDC electroanesthesia is recommended because of its immediate induction time, quick recovery, high immediate and short-term survival, and lack of evidence of vertebral abnormalities.
","language":"English","publisher":"American Fisheries Society","doi":"10.1080/02755947.2011.629717","usgsCitation":"Vandergoot, C.S., Murchie, K.J., Cooke, S., Dettmers, J.M., Bergstedt, R.A., and Fielder, D., 2011, Evaluation of two forms of electroanesthesia and carbon dioxide for short-term anesthesia in walleye: North American Journal of Fisheries Management, v. 31, no. 5, p. 914-922, https://doi.org/10.1080/02755947.2011.629717.","productDescription":"9 p.","startPage":"914","endPage":"922","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":394031,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"5","noUsgsAuthors":false,"publicationDate":"2011-11-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Vandergoot, Christopher S.","contributorId":71849,"corporation":false,"usgs":false,"family":"Vandergoot","given":"Christopher","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":830362,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murchie, Karen J","contributorId":149697,"corporation":false,"usgs":false,"family":"Murchie","given":"Karen","email":"","middleInitial":"J","affiliations":[{"id":17787,"text":"College of The Bahamas","active":true,"usgs":false}],"preferred":false,"id":830363,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cooke, Steven J.","contributorId":56132,"corporation":false,"usgs":false,"family":"Cooke","given":"Steven J.","affiliations":[{"id":36574,"text":"Carleton University, Ottawa, Ontario","active":true,"usgs":false}],"preferred":false,"id":830364,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dettmers, John M.","contributorId":191256,"corporation":false,"usgs":false,"family":"Dettmers","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":830365,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bergstedt, Roger A. rbergstedt@usgs.gov","contributorId":4174,"corporation":false,"usgs":true,"family":"Bergstedt","given":"Roger","email":"rbergstedt@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":830366,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fielder, David G.","contributorId":85434,"corporation":false,"usgs":true,"family":"Fielder","given":"David G.","affiliations":[],"preferred":false,"id":830367,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70203883,"text":"70203883 - 2011 - Arsenic in Chinese coals: Distribution, modes of occurrence, and environmental effects","interactions":[],"lastModifiedDate":"2019-06-18T18:27:30","indexId":"70203883","displayToPublicDate":"2019-06-18T18:25:33","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"title":"Arsenic in Chinese coals: Distribution, modes of occurrence, and environmental effects","docAbstract":"Arsenic, one of the most hazardous elements occurring in coals, can be released to the environment during coal processing and combustion. Based on the available literature and published results obtained in our laboratory, the content, distribution and the modes of occurrence of As in Chinese coals, and its environmental and impacts are reviewed in this article. With the 4763 sets of data (from the literature) rearranged, the arithmetic mean As concentration of each province and weighted mean As concentration of the entire country (using the expected coal reserves as the weighting factor) were calculated. The weighted mean As concentration in Chinese coals is 3.18 mg/kg, with As concentration increasing from northern China to southern China. The As concentration in coal varies with coal-forming ages and coal ranks. Arsenic has several modes of occurrence in coals. According to results obtained by other studies and our own experiments, As is mainly associated with mineral matter (such as pyrite and other sulfide minerals) in coals, although a significant amount of arsenic is associated with organic matter. The accumulation of As in coal is controlled by many geological factors during coal-forming processes, including plant decomposition, sedimentary environments, and epigenetic hydrothermal activity. During the combustion of coal, As is released to the air, water, and soil, causing serious environmental pollution. More than 45% of the coal consumed in China is utilized by power plants, and it is estimated that nearly 522 tonnes, 21 tonnes and 252 tonnes of As are emitted into the atmosphere by industries, residential buildings and coal-fired power plants, respectively, every year.
","language":"English","publisher":"Science of the Total Environment","doi":"10.1016/j.scitotenv.2011.10.026","usgsCitation":"Kang, Y., and Liu, G., 2011, Arsenic in Chinese coals: Distribution, modes of occurrence, and environmental effects, v. 412, p. 1-13, https://doi.org/10.1016/j.scitotenv.2011.10.026.","productDescription":"13 p.","startPage":"1","endPage":"13","costCenters":[],"links":[{"id":364805,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"412","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kang, Y.","contributorId":54431,"corporation":false,"usgs":true,"family":"Kang","given":"Y.","email":"","affiliations":[],"preferred":false,"id":764581,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Guijian","contributorId":216351,"corporation":false,"usgs":false,"family":"Liu","given":"Guijian","email":"","affiliations":[],"preferred":false,"id":764582,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70047621,"text":"70047621 - 2011 - Book review: The world of wolves: New perspectives on ecology","interactions":[],"lastModifiedDate":"2015-12-11T11:17:12","indexId":"70047621","displayToPublicDate":"2013-01-01T09:55:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2093,"text":"International Wolf","active":true,"publicationSubtype":{"id":10}},"title":"Book review: The world of wolves: New perspectives on ecology","docAbstract":"Wolf populations have proliferated in several areas and so have wolf books. The latest book is a good one. This compendium, The World of Wolves, covers a variety of fast-moving and controversial areas such as canid genetics, effects of wolves on ecosystems, climate change, hunting of wolves by snowmobile and non-lethal methods of minimizing livestock depredation. A great deal of new and interesting information resides in this book, far more than this review can cover. Several of the article authors are well experienced in their specialties: Luigi Boitani, Robert Wayne, Doug Smith, Rolf Peterson, Paul Paquet, Dean Cluff, and Olof Liberg along with numerous associates. The material reflects that.
\nReview info: The world of wolves: New perspectives on ecology. Edited by M. Musiani, L. Boitani, and P. C. Paquet, 2011. ISBN: 9781552382691, 398 pp.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"International Wolf","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"International Wolf Center","publisherLocation":"Minneapolis, MN","usgsCitation":"Mech, L.D., 2011, Book review: The world of wolves: New perspectives on ecology: International Wolf, v. 21, no. 1, p. 21-21.","productDescription":"1 p.","startPage":"21","endPage":"21","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":276626,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":312157,"type":{"id":15,"text":"Index Page"},"url":"https://www.wolf.org/wolf-info/wolf-magazine/magazine-archives/"}],"volume":"21","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"520df86ae4b08494c3cb061e","contributors":{"authors":[{"text":"Mech, L. David 0000-0003-3944-7769 david_mech@usgs.gov","orcid":"https://orcid.org/0000-0003-3944-7769","contributorId":2518,"corporation":false,"usgs":true,"family":"Mech","given":"L.","email":"david_mech@usgs.gov","middleInitial":"David","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":482550,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70042405,"text":"70042405 - 2011 - Gopherus agassizii (desert tortoise). Burrow collapse","interactions":[],"lastModifiedDate":"2013-05-31T14:09:06","indexId":"70042405","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1898,"text":"Herpetological Review","active":true,"publicationSubtype":{"id":10}},"title":"Gopherus agassizii (desert tortoise). Burrow collapse","docAbstract":"In the deserts of the southwestern U.S., burrows are utilized by the Desert Tortoise to escape environmental extremes (reviewed by Ernst and Lovich 2009. Turtles of the United States and Canada. 2nd ed. Johns Hopkins Univ. Press, Baltimore, Maryland. 827 pp.). However, the potential for mortality through burrow collapse and entrapment is poorly documented. Nicholson and Humphreys (1981. Proceedings of the Desert Tortoise Council, pp. 163−194) suggested that collapse due to livestock trampling may cause mortality. In addition, Lovich et al. (2011. Chelon. Cons. Biol. 10[1]:124–129) documented a Desert Tortoise that used a steel culvert as a burrow surrogate. The culvert filled completely with sediment following a significant rain event, entombing the animal and ultimately resulting in its death. We note that this mortality was associated with an anthropogenic structure; because tortoises are prodigious diggers, one might hypothesize that they have the ability to dig out of collapsed natural burrows in most situations. Circumstances described here presented us with an opportunity to test this hypothesis.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Herpetological Review","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Society for the Study of Amphibians and Reptiles","usgsCitation":"Loughran, C.L., Ennen, J., and Lovich, J.E., 2011, Gopherus agassizii (desert tortoise). Burrow collapse: Herpetological Review, v. 42, no. 4, p. 593-593.","productDescription":"1 p.","startPage":"593","endPage":"593","ipdsId":"IP-030092","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":273045,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":273044,"type":{"id":11,"text":"Document"},"url":"https://profile.usgs.gov/myscience/upload_folder/ci2013Mar2818141633446Burrow%20collapse%20HR%202011.pdf"}],"volume":"42","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a9c68fe4b0140a577ae6f1","contributors":{"authors":[{"text":"Loughran, Caleb L.","contributorId":26599,"corporation":false,"usgs":true,"family":"Loughran","given":"Caleb","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":471474,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ennen, Joshua","contributorId":72691,"corporation":false,"usgs":true,"family":"Ennen","given":"Joshua","affiliations":[],"preferred":false,"id":471475,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lovich, Jeffrey E. 0000-0002-7789-2831 jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":471473,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70045749,"text":"70045749 - 2011 - Variation in spring migration routes and breeding distribution of northern pintails Anas acuta that winter in Japan","interactions":[],"lastModifiedDate":"2018-07-15T18:37:00","indexId":"70045749","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2190,"text":"Journal of Avian Biology","active":true,"publicationSubtype":{"id":10}},"title":"Variation in spring migration routes and breeding distribution of northern pintails Anas acuta that winter in Japan","docAbstract":"In North America, spring migration routes and breeding distribution of northern pintails Anas acuta vary because some individuals opportunistically nest at mid-latitudes in years when ephemeral prairie wetlands are available, whereas others regularly nest in arctic and sub-arctic regions where wetland abundance is more constant. Less was known about migration routes and breeding distribution of pintails in East Asia. From 2007–2009 we marked 198 pintails on their wintering areas in Japan with satellite transmitters to: 1) document spring migration routes and summer distribution, 2) evaluate migratory connections and breeding season sympatry with North American pintails, and 3) determine if pintails used the same migration routes in fall as in spring. Most pintails (67%) migrated to the Kamchatka or Chukotka peninsulas in eastern Russia either directly from Japan or via Sakhalin Island, Russia. Remaining pintails primarily migrated to the Magadan region or Kolyma River Basin in eastern Russia via Sakhalin Island. The Chukotka Peninsula was the most common summer destination, with highest densities in the Anadyr Lowlands; a region also used by pintails that migrate from North America. One pintail migrated to St. Lawrence Island, Alaska, in spring and another briefly migrated to the western coast of Alaska in fall. Autumn migration routes generally mirrored spring migration although most pintails bypassed Sakhalin Island in fall. Compared to North American pintails, pintails that winter in Japan exhibited less variation in migration routes and breeding distribution, and nested at higher latitudes. In the Russian Far East there is no region with habitats comparable in extent to the ephemeral mid-latitude wetlands of North America. Consequently, East Asian pintails mainly nest in arctic and sub-arctic regions where annual consistency in wetlands promotes constancy in migration routes and breeding distribution. Breeding season sympatry between pintails from different continents results more from North American pintails migrating to eastern Russia than from Japanese pintails migrating to North America.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Avian Biology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/j.1600-048X.2011.05320.x","usgsCitation":"Hupp, J.W., Yamaguchi, N., Flint, P.L., Pearce, J.M., Tokita, K., Shimada, T., Ramey, A.M., Kharitonov, S., and Higuchi, H., 2011, Variation in spring migration routes and breeding distribution of northern pintails Anas acuta that winter in Japan: Journal of Avian Biology, v. 42, no. 4, p. 289-300, https://doi.org/10.1111/j.1600-048X.2011.05320.x.","productDescription":"12 p.","startPage":"289","endPage":"300","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":271744,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271743,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1600-048X.2011.05320.x"}],"volume":"42","issue":"4","noUsgsAuthors":false,"publicationDate":"2011-07-13","publicationStatus":"PW","scienceBaseUri":"51838aece4b0a21483941ad5","contributors":{"authors":[{"text":"Hupp, Jerry W. 0000-0002-6439-3910 jhupp@usgs.gov","orcid":"https://orcid.org/0000-0002-6439-3910","contributorId":127803,"corporation":false,"usgs":true,"family":"Hupp","given":"Jerry","email":"jhupp@usgs.gov","middleInitial":"W.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":478242,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yamaguchi, Noriyuki","contributorId":83397,"corporation":false,"usgs":true,"family":"Yamaguchi","given":"Noriyuki","affiliations":[],"preferred":false,"id":478249,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flint, Paul L. 0000-0002-8758-6993 pflint@usgs.gov","orcid":"https://orcid.org/0000-0002-8758-6993","contributorId":3284,"corporation":false,"usgs":true,"family":"Flint","given":"Paul","email":"pflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":478243,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pearce, John M. 0000-0002-8503-5485 jpearce@usgs.gov","orcid":"https://orcid.org/0000-0002-8503-5485","contributorId":181766,"corporation":false,"usgs":true,"family":"Pearce","given":"John","email":"jpearce@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":478241,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tokita, Ken-ichi","contributorId":9150,"corporation":false,"usgs":true,"family":"Tokita","given":"Ken-ichi","email":"","affiliations":[],"preferred":false,"id":478244,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shimada, Tetsuo","contributorId":52065,"corporation":false,"usgs":true,"family":"Shimada","given":"Tetsuo","email":"","affiliations":[],"preferred":false,"id":478246,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":478245,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kharitonov, Sergei","contributorId":70672,"corporation":false,"usgs":true,"family":"Kharitonov","given":"Sergei","email":"","affiliations":[],"preferred":false,"id":478248,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Higuchi, Hiroyoshi","contributorId":69850,"corporation":false,"usgs":true,"family":"Higuchi","given":"Hiroyoshi","email":"","affiliations":[],"preferred":false,"id":478247,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70044133,"text":"70044133 - 2011 - Contexts for change in alpine tundra","interactions":[],"lastModifiedDate":"2021-05-20T20:19:13.153547","indexId":"70044133","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3059,"text":"Physical Geography","active":true,"publicationSubtype":{"id":10}},"title":"Contexts for change in alpine tundra","docAbstract":"Because alpine tundra is responding to climate change, a need exists to understand the meaning of observed changes. To provide context for such interpretation, the relevance of niche and neutral theories of biogeography and the continuum and classification approaches to biogeographic description are assessed. Two extensive studies of alpine tundra, from the Indian Peaks area, Colorado and Glacier National Park, Montana, are combined. The data are ordinated to describe relations. The pattern that emerges is one of a continuum of vegetation, but with the distinctions one might expect from distant sites. The relationships of the similarity of vegetation on all possible pairs of sites to the environmental differences and geographic distances are analyzed using Mantel correlations. Because distance and environmental differences in climate between the two sites are correlated, partial correlations are weak but still significant. More advanced analyses are suggested for this environment prior to interpretation of monitoring efforts such as GLORIA.
","language":"English","publisher":"Taylor & Francis","publisherLocation":"Columbia, MD","doi":"10.2747/0272-3646.32.2.97","usgsCitation":"Malanson, G.P., Rose, J., Schroeder, P.J., and Fagre, D.B., 2011, Contexts for change in alpine tundra: Physical Geography, v. 32, no. 2, p. 97-113, https://doi.org/10.2747/0272-3646.32.2.97.","productDescription":"17 p.","startPage":"97","endPage":"113","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-026906","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":271336,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Montana","otherGeospatial":"Glacier National Park, Indian Peaks Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.6038818359375,\n 48.09275716032736\n ],\n [\n -114.6038818359375,\n 49.005447494058096\n ],\n [\n -113.0438232421875,\n 49.005447494058096\n ],\n [\n -113.0438232421875,\n 48.09275716032736\n ],\n [\n -114.6038818359375,\n 48.09275716032736\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.07025146484375,\n 39.72197606377427\n ],\n [\n -106.07025146484375,\n 40.348637376031725\n ],\n [\n -105.35888671875,\n 40.348637376031725\n ],\n [\n -105.35888671875,\n 39.72197606377427\n ],\n [\n -106.07025146484375,\n 39.72197606377427\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"32","issue":"2","noUsgsAuthors":false,"publicationDate":"2013-05-15","publicationStatus":"PW","scienceBaseUri":"51765be2e4b0f989f99e00b1","contributors":{"authors":[{"text":"Malanson, George P.","contributorId":36768,"corporation":false,"usgs":true,"family":"Malanson","given":"George","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":474851,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rose, Jonathan P. 0000-0003-0874-9166 jprose@usgs.gov","orcid":"https://orcid.org/0000-0003-0874-9166","contributorId":105624,"corporation":false,"usgs":true,"family":"Rose","given":"Jonathan P.","email":"jprose@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":474852,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schroeder, P. Jason","contributorId":29721,"corporation":false,"usgs":true,"family":"Schroeder","given":"P.","email":"","middleInitial":"Jason","affiliations":[],"preferred":false,"id":474850,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fagre, Daniel B. 0000-0001-8552-9461 dan_fagre@usgs.gov","orcid":"https://orcid.org/0000-0001-8552-9461","contributorId":2036,"corporation":false,"usgs":true,"family":"Fagre","given":"Daniel","email":"dan_fagre@usgs.gov","middleInitial":"B.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":474849,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70045909,"text":"70045909 - 2011 - Mineral resource of the month: copper","interactions":[],"lastModifiedDate":"2013-05-08T17:40:11","indexId":"70045909","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1419,"text":"Earth","active":true,"publicationSubtype":{"id":10}},"title":"Mineral resource of the month: copper","docAbstract":"The article provides information on copper and its various uses. It was the first metal used by humans and is considered as one of the materials that played an important role in the development of civilization. It is a major industrial metal because of its low cost, availability, electrical conductivity, high ductility and thermal conductivity. Copper has long been used in the circuitry of electronics and the distribution of electricity and is now being used in silicon-based computer chips, solar and wind power generation, and coinage.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Earth","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"AGI","usgsCitation":"Water Resources Division, U.S. Geological Survey, 2011, Mineral resource of the month: copper: Earth, v. 56, no. 2, p. 28-29.","productDescription":"2 p.","startPage":"28","endPage":"29","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":272091,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"56","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"518b73e9e4b0037667dbc82a","contributors":{"authors":[{"text":"Water Resources Division, U.S. Geological Survey","contributorId":128075,"corporation":true,"usgs":false,"organization":"Water Resources Division, U.S. Geological Survey","id":535504,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70044063,"text":"70044063 - 2011 - Infectious diseases in Yellowstone’s canid community","interactions":[],"lastModifiedDate":"2020-01-11T11:26:44","indexId":"70044063","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3802,"text":"Yellowstone Science","active":true,"publicationSubtype":{"id":10}},"title":"Infectious diseases in Yellowstone’s canid community","docAbstract":"Each summer Yellowstone Wolf Project staff visit den sites to monitor the success of wolf reproduction and pup rearing behavior. For the purposes of wolf monitoring, Yellowstone National Park (YNP) is divided into two study areas, the northern range and the interior, each distinguished by their ecological and physiographical differences. The 1,000 square kilometer northern range, characterized by lower elevations (1,500–2,200 m), serves as prime winter habitat for ungulates and supports a higher density of wolves than the interior (20–99 wolves/1,000 km2 versus 2–11 wolves/1,000 km2). The interior of the park encompasses 7,991 square kilometers, is higher in elevation, receives higher annual snowfall, and generally supports lower densities of wolves and ungulates. During the Yellowstone Wolf Project’s 2005 observations on the northern range, researchers noticed that some wolf pups were disappearing and those that remained were unusually listless. The Slough Creek pups, at first numbering 18, dwindled to three survivors. Similar findings were mirrored at other den sites across the northern range. When annual den surveys were conducted in late July, all that remained were scattered piles of bones and fur. Coyotes suffered similar setbacks in 2005, with many of the survivors exhibiting neurological shakes and tremors. The park’s canids had been affected by something, but what? Prompted by what seemed to be a disease outbreak, the Yellowstone Wolf Project, the Yellowstone Ecological Research Center (YERC), and the University of Minnesota decided to take several collaborative approaches toward improving our understanding of the presence and role of infectious disease in Yellowstone’s canid community. Several serological studies have been conducted in the past among the park’s coyotes (Gese et al. 1997) and cougars (Biek 2006), providing a helpful foundation on which to build and compare. A serological survey was conducted, using serum samples collected during routine wolf and coyote captures over a period of 18 years (Almberg et al. 2009). Simulation models were used to explore the dynamics of canine distemper virus (Almberg et al. 2010)—one of the more prominent pathogens in terms of its effects on its hosts—and several long-term pathogen surveillance projects were initiated which are intended to someday provide a foundation for more advanced genetic-based analyses of pathogen dynamics. Since these initial efforts, the group has also expanded the research to include a study of sarcoptic mange, which began affecting wolves and coyotes in YNP in 2006 and 2007.","language":"English","publisher":"National Park Service","usgsCitation":"Almberg, E., Cross, P.C., Mech, L.D., Smith, D.W., Sheldon, J.W., and Crabtree, R., 2011, Infectious diseases in Yellowstone’s canid community: Yellowstone Science, v. 19, no. 2, p. 16-24.","productDescription":"9 p.","startPage":"16","endPage":"24","ipdsId":"IP-022718","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":273422,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":273421,"type":{"id":11,"text":"Document"},"url":"https://www.greateryellowstonescience.org/sites/default/files/YS_19_2_Almberg_sm.pdf"}],"country":"United States","otherGeospatial":"Yellowstone National Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.156,44.1324 ], [ -111.156,45.109 ], [ -109.8242,45.109 ], [ -109.8242,44.1324 ], [ -111.156,44.1324 ] ] ] } } ] }","volume":"19","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51b300e4e4b01368e589e3d1","contributors":{"authors":[{"text":"Almberg, Emily S.","contributorId":101111,"corporation":false,"usgs":true,"family":"Almberg","given":"Emily S.","affiliations":[],"preferred":false,"id":474751,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cross, Paul C. 0000-0001-8045-5213 pcross@usgs.gov","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":2709,"corporation":false,"usgs":true,"family":"Cross","given":"Paul","email":"pcross@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":474747,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mech, L. David 0000-0003-3944-7769 david_mech@usgs.gov","orcid":"https://orcid.org/0000-0003-3944-7769","contributorId":2518,"corporation":false,"usgs":true,"family":"Mech","given":"L.","email":"david_mech@usgs.gov","middleInitial":"David","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":474746,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Doug W.","contributorId":9557,"corporation":false,"usgs":true,"family":"Smith","given":"Doug","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":474748,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sheldon, Jennifer W.","contributorId":56961,"corporation":false,"usgs":true,"family":"Sheldon","given":"Jennifer","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":474749,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Crabtree, Robert L.","contributorId":59712,"corporation":false,"usgs":true,"family":"Crabtree","given":"Robert L.","affiliations":[],"preferred":false,"id":474750,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70045081,"text":"70045081 - 2011 - Assessment of topographic and drainage network controls on debris-flow travel distance along the west coast of the United States","interactions":[],"lastModifiedDate":"2013-04-09T16:21:24","indexId":"70045081","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2123,"text":"Italian Journal of Engineering Geology and Environment; 5th International Conference on Debris-Flow Hazards \"Mitigation, Mechanics, Prediction and Assessment\"","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of topographic and drainage network controls on debris-flow travel distance along the west coast of the United States","docAbstract":"To better understand controls on debris-flow entrainment and travel distance, we examined topographic and drainage network characteristics of initiation locations in two separate debris-flow prone areas located 700 km apart along the west coast of the U.S. One area was located in northern California, the other in southern Oregon. In both areas, debris flows mobilized from slides during large storms, but, when stratified by number of contributing initiation locations, median debris-flow travel distances in Oregon were 5 to 8 times longer than median distances in California. Debris flows in Oregon readily entrained channel material; entrainment in California was minimal. To elucidate this difference, we registered initiation locations to high-resolution airborne LiDAR, and then examined travel distances with respect to values of slope, upslope contributing area, planform curvature, distance from initiation locations to the drainage network, and number of initiation areas that contributed to flows. Results show distinct differences in the topographic and drainage network characteristics of debris-flow initiation locations between the two study areas. Slope and planform curvature of initiation locations (landslide headscarps), commonly used to predict landslide-prone areas, were not useful for predicting debris-flow travel distances. However, a positive, power-law relation exists between median debris-flow travel distance and the number of contributing debris-flow initiation locations. Moreover, contributing area and the proximity of the initiation locations to the drainage network both influenced travel distances, but proximity to the drainage network was the better predictor of travel distance. In both study areas, flows that interacted with the drainage network flowed significantly farther than those that did not. In California, initiation sites within 60 m of the network were likely to reach the network and generate longtraveled flows; in Oregon, the threshold was 80 m.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Italian Journal of Engineering Geology and Environment; 5th International Conference on Debris-Flow Hazards \"Mitigation, Mechanics, Prediction and Assessment\"","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Research Center CERI","publisherLocation":"Rome, Italy","doi":"10.4408/IJEGE.2011-03.B-024","usgsCitation":"Coe, J.A., Reid, M.E., Brien, D.L., and Michael, J.A., 2011, Assessment of topographic and drainage network controls on debris-flow travel distance along the west coast of the United States: Italian Journal of Engineering Geology and Environment; 5th International Conference on Debris-Flow Hazards \"Mitigation, Mechanics, Prediction and Assessment\", p. 199-209, https://doi.org/10.4408/IJEGE.2011-03.B-024.","productDescription":"11 p.","startPage":"199","endPage":"209","ipdsId":"IP-024731","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":270730,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":270729,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.4408/IJEGE.2011-03.B-024"}],"country":"United States","state":"California;Oregon;Washington","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -125.75,32.5 ], [ -125.75,49.0 ], [ -116.15,49.0 ], [ -116.15,32.5 ], [ -125.75,32.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51653866e4b077fa94dadf84","contributors":{"authors":[{"text":"Coe, Jeffrey A. 0000-0002-0842-9608 jcoe@usgs.gov","orcid":"https://orcid.org/0000-0002-0842-9608","contributorId":1333,"corporation":false,"usgs":true,"family":"Coe","given":"Jeffrey","email":"jcoe@usgs.gov","middleInitial":"A.","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":476755,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reid, Mark E. 0000-0002-5595-1503 mreid@usgs.gov","orcid":"https://orcid.org/0000-0002-5595-1503","contributorId":1167,"corporation":false,"usgs":true,"family":"Reid","given":"Mark","email":"mreid@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":476754,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brien, Dainne L.","contributorId":6739,"corporation":false,"usgs":true,"family":"Brien","given":"Dainne","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":476757,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Michael, John A. jmichael@usgs.gov","contributorId":1877,"corporation":false,"usgs":true,"family":"Michael","given":"John","email":"jmichael@usgs.gov","middleInitial":"A.","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"preferred":false,"id":476756,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70042696,"text":"70042696 - 2011 - Geological impacts and implications of the 2010 tsunami along the central coast of Chile","interactions":[],"lastModifiedDate":"2013-03-09T21:50:53","indexId":"70042696","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3368,"text":"Sedimentary Geology","active":true,"publicationSubtype":{"id":10}},"title":"Geological impacts and implications of the 2010 tsunami along the central coast of Chile","docAbstract":"Geological effects of the 2010 Chilean tsunami were quantified at five near-field sites along a 200 km segment of coast located between the two zones of predominant fault slip. Field measurements, including topography, flow depths, flow directions, scour depths, and deposit thicknesses, provide insights into the processes and morphological changes associated with tsunami inundation and return flow. The superposition of downed trees recorded multiple strong onshore and alongshore flows that arrived at different times and from different directions. The most likely explanation for the diverse directions and timing of coastal inundation combines (1) variable fault rupture and asymmetrical slip displacement of the seafloor away from the epicenter with (2) resonant amplification of coastal edge waves. Other possible contributing factors include local interaction of incoming flow and return flow and delayed wave reflection by the southern coast of Peru. Coastal embayments amplified the maximum inundation distances at two sites (2.4 and 2.6 km, respectively). Tsunami vertical erosion included scour and planation of the land surface, inundation scour around the bases of trees, and channel incision from return flow. Sheets and wedges of sand and gravel were deposited at all of the sites. Locally derived boulders up to 1 m in diameter were transported as much as 400 m inland and deposited as fields of dispersed clasts. The presence of lobate bedforms at one site indicates that at least some of the late-stage sediment transport was as bed load and not as suspended load. Most of the tsunami deposits were less than 25 cm thick. Exceptions were thick deposits near open-ocean river mouths where sediment supply was abundant. Human alterations of the land surface at most of the sites provided opportunities to examine some tsunami effects that otherwise would not have been possible, including flow histories, boulder dispersion, and vegetation controls on deposit thickness.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Sedimentary Geology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.sedgeo.2011.09.004","usgsCitation":"Morton, R., Gelfenbaum, G., Buckley, M.L., and Richmond, B.M., 2011, Geological impacts and implications of the 2010 tsunami along the central coast of Chile: Sedimentary Geology, v. 242, no. 1-4, p. 34-51, https://doi.org/10.1016/j.sedgeo.2011.09.004.","productDescription":"18 p.","startPage":"34","endPage":"51","ipdsId":"IP-025743","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":268995,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":268994,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.sedgeo.2011.09.004"}],"country":"Chile","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109.5,-56.0 ], [ -109.5,17.5 ], [ -66.4,17.5 ], [ -66.4,-56.0 ], [ -109.5,-56.0 ] ] ] } } ] }","volume":"242","issue":"1-4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd5d9ee4b0b290850fb30a","contributors":{"authors":[{"text":"Morton, Robert A.","contributorId":88333,"corporation":false,"usgs":true,"family":"Morton","given":"Robert A.","affiliations":[],"preferred":false,"id":472073,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gelfenbaum, Guy","contributorId":79844,"corporation":false,"usgs":true,"family":"Gelfenbaum","given":"Guy","affiliations":[],"preferred":false,"id":472072,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buckley, Mark L.","contributorId":41385,"corporation":false,"usgs":true,"family":"Buckley","given":"Mark","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":472071,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Richmond, Bruce M. 0000-0002-0056-5832 brichmond@usgs.gov","orcid":"https://orcid.org/0000-0002-0056-5832","contributorId":2459,"corporation":false,"usgs":true,"family":"Richmond","given":"Bruce","email":"brichmond@usgs.gov","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":472070,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70044838,"text":"70044838 - 2011 - Lithium","interactions":[],"lastModifiedDate":"2013-04-28T20:48:01","indexId":"70044838","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2755,"text":"Mining Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Lithium","docAbstract":"In 2010, lithium consumption in the United States was estimated to have been about 1 kt (1,100 st) of contained lithium, a 23-percent decrease from 2009. The United States was estimated to be the fourth largest consumer of lithium. It remained the leading importer of lithium carbonate and the leading producer of value-added lithium materials. Only one company, Chemetall Foote Corp. (a subsidiary of Chemetall GmbH of Germany), produced lithium compounds from domestic resources. In 2010, world lithium consumption was estimated to have been about 21 kt (22,000 st) of lithium contained in minerals and compounds, a 12-percent increase from 2009.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Mining Engineering","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"SME","usgsCitation":"Jaskula, B., 2011, Lithium: Mining Engineering, v. 63, no. 6, p. 79-80.","productDescription":"2 p.","startPage":"79","endPage":"80","ipdsId":"IP-036623","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":271565,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"63","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"517e44ece4b0eff6bc0031d5","contributors":{"authors":[{"text":"Jaskula, B.W.","contributorId":62496,"corporation":false,"usgs":true,"family":"Jaskula","given":"B.W.","affiliations":[],"preferred":false,"id":476390,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70042031,"text":"70042031 - 2011 - Landscape models of brook trout abundance and distribution in lotic habitat with field validation","interactions":[],"lastModifiedDate":"2012-12-28T12:02:51","indexId":"70042031","displayToPublicDate":"2012-12-01T00:00:00","publicationYear":"2011","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":"Landscape models of brook trout abundance and distribution in lotic habitat with field validation","docAbstract":"Brook trout Salvelinus fontinalis are native fish in decline owing to environmental changes. Predictions of their potential distribution and a better understanding of their relationship to habitat conditions would enhance the management and conservation of this valuable species. We used over 7,800 brook trout observations throughout New York State and georeferenced, multiscale landscape condition data to develop four regionally specific artificial neural network models to predict brook trout abundance in rivers and streams. Land cover data provided a general signature of human activity, but other habitat variables were resistant to anthropogenic changes (i.e., changing on a geological time scale). The resulting models predict the potential for any stream to support brook trout. The models were validated by holding 20% of the data out as a test set and by comparison with additional field collections from a variety of habitat types. The models performed well, explaining more than 90% of data variability. Errors were often associated with small spatial displacements of predicted values. When compared with the additional field collections (39 sites), 92% of the predictions were off by only a single class from the field-observed abundances. Among “least-disturbed” field collection sites, all predictions were correct or off by a single abundance class, except for one where brown trout Salmo trutta were present. Other degrading factors were evident at most sites where brook trout were absent or less abundant than predicted. The most important habitat variables included landscape slope, stream and drainage network sizes, water temperature, and extent of forest cover. Predicted brook trout abundances were applied to all New York streams, providing a synoptic map of the distribution of brook trout habitat potential. These fish models set benchmarks of best potential for streams to support brook trout under broad-scale human influences and can assist with planning and identification of protection or rehabilitation sites.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"North American Journal of Fisheries Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Taylor & Francis Group","publisherLocation":"London, UK","doi":"10.1080/02755947.2011.593940","usgsCitation":"McKenna, J., and Johnson, J.H., 2011, Landscape models of brook trout abundance and distribution in lotic habitat with field validation: North American Journal of Fisheries Management, v. 31, no. 4, p. 742-756, https://doi.org/10.1080/02755947.2011.593940.","productDescription":"15 p.","startPage":"742","endPage":"756","ipdsId":"IP-023753","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":264883,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":264882,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/02755947.2011.593940"}],"country":"United States","state":"New York","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -79.7621,40.5 ], [ -79.7621,45.0 ], [ -71.8563,45.0 ], [ -71.8563,40.5 ], [ -79.7621,40.5 ] ] ] } } ] }","volume":"31","issue":"4","noUsgsAuthors":false,"publicationDate":"2011-09-08","publicationStatus":"PW","scienceBaseUri":"50df6e6fe4b0dfbe79e6c506","contributors":{"authors":[{"text":"McKenna, James E. Jr.","contributorId":56992,"corporation":false,"usgs":true,"family":"McKenna","given":"James E.","suffix":"Jr.","affiliations":[],"preferred":false,"id":470637,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, James H. 0000-0002-5619-3871 jhjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-5619-3871","contributorId":389,"corporation":false,"usgs":true,"family":"Johnson","given":"James","email":"jhjohnson@usgs.gov","middleInitial":"H.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":470636,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}