Assessments of prey fishes in the Great Lakes have been conducted annually since the 1970s by the Great Lakes Science Center, sometimes assisted by partner agencies. Prey fish assessments differ among lakes in the proportion of a lake covered, seasonal timing, bottom trawl gear used, sampling design, and the manner in which the trawl is towed (across or along bottom contours). Because each assessment is unique in one or more important aspects, a direct comparison of prey fish catches among lakes is problematic. All of the assessments, however, produce indices of abundance or biomass that can be standardized to facilitate comparisons of trends among lakes and to illustrate present status of the populations. We present indices of abundance for important prey fishes in the Great Lakes standardized to the highest value for a time series within each lake: cisco (Coregonus artedi), bloater (C. hoyi), rainbow smelt (Osmerus mordax), and alewife (Alosa pseudoharengus). We also provide indices for round goby (Neogobius melanostomus), an invasive fish presently spreading throughout the basin. Our intent is to provide a short, informal report emphasizing data presentation rather than synthesis; for this reason we intentionally avoid use of tables and cited references.
For each lake, standardized relative indices for annual biomass and density estimates of important prey fishes were calculated as the fraction relative to the largest value observed in the times series. To determine whether basin-wide trends were apparent for each species, we first ranked standardized index values within each lake. When comparing ranked index values from three or more lakes, we calculated the Kendall coefficient of concordance (W), which can range from 0 (complete discordance or disagreement among trends) to 1 (complete concordance or agreement among trends). The P-value for W provides the probability of agreement across the lakes. When comparing ranked index values from two lakes, we calculated the Kendall correlation coefficient (τ), which ranges from -1 (inverse association, perfect disagreement) to 1 (direct association, perfect agreement). Here, the P-value for τ provides the probability of either inverse or direct association between the lakes. First, we present trends in relative biomass of age-1 and older prey fishes to show changes in populations within each lake. Then, we present standardized indices of numerical abundance of a single age class to show changes in relative year-class strength within each lake. Indices of year-class strength reliably reflect the magnitude of the cohort size at subsequent ages. However, because of differences in survey timing across lakes, the age class that is used for each species to index year-class strength varies across lakes and, just as surveys differ among lakes, methods for determining fish age-class differ also. For Lake Superior cisco, bloater, smelt, and Lake Michigan alewife, year- class strengths are based on aged fish and age-length keys, and for all other combinations of lakes and species, age-classes are assigned based on fish length cut-offs. Our intent with this report is to provide a cross-lakes view of population trends but not to propose reasons for those trends.
","conferenceTitle":"Great Lakes Fishery Commission: Upper and Lower Lakes Committee Meetings","conferenceDate":"March 23-27, 2009","conferenceLocation":"Ypsilanti, MI","language":"English","publisher":"Great Lakes Fishery Commission","usgsCitation":"Gorman, O.T., and Bunnell, D., 2009, Great Lakes prey fish populations: A cross-basin overview of status and trends in 2008, Great Lakes Fishery Commission: Upper and Lower Lakes Committee Meetings, Ypsilanti, MI, March 23-27, 2009, 9 p.","productDescription":"9 p.","ipdsId":"IP-012884","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":340167,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":314249,"type":{"id":15,"text":"Index Page"},"url":"https://www.glsc.usgs.gov/products/reports/701506138"}],"country":"Canada, United States","otherGeospatial":"Great Lakes","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58ff0ea8e4b006455f2d6200","contributors":{"authors":[{"text":"Gorman, Owen T. 0000-0003-0451-110X otgorman@usgs.gov","orcid":"https://orcid.org/0000-0003-0451-110X","contributorId":2888,"corporation":false,"usgs":true,"family":"Gorman","given":"Owen","email":"otgorman@usgs.gov","middleInitial":"T.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":588500,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bunnell, David B. dbunnell@usgs.gov","contributorId":141167,"corporation":false,"usgs":true,"family":"Bunnell","given":"David B.","email":"dbunnell@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":588498,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70162071,"text":"70162071 - 2009 - Status of pelagic prey fishes and pelagic macroinvertebrates in Lake Michigan, 2008","interactions":[],"lastModifiedDate":"2017-04-25T10:39:47","indexId":"70162071","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Status of pelagic prey fishes and pelagic macroinvertebrates in Lake Michigan, 2008","docAbstract":"Acoustic surveys were conducted in late summer/early fall during the years 1992-1996 and 2001-2008 to estimate pelagic prey fish biomass in Lake Michigan. Midwater trawling during the surveys provided a measure of species and size composition of the fish community for use in scaling acoustic data and providing species-specific abundance estimates. In 2005, we began sampling Mysis diluviana during the survey. The 2008 survey provided data from 24 acoustic transects (734 km), 33 midwater tows, and 39 mysid tows. Mean total prey fish biomass was 15.3 kg/ha (relative standard error, RSE = 7.6%) or ~82 kilotonnes (kt, 1,000 metric tons), which was 1.9 times higher than the estimate for 2007 but 78% lower than the long-term mean. The increase from 2007 was because of increased biomass of age-1 and age-3 alewife. The 2008 alewife year-class contributed ~12% of total alewife biomass (11.0 kg/ha, RSE = 9.0%), while the 2007 and 2005 alewife year-classes contributed ~33% and 35%, respectively. In 2008, alewife comprised 72% of total biomass, while rainbow smelt and bloater were 11 and 17% of total biomass, respectively. Rainbow smelt biomass in 2008 (1.6 kg/ha, RSE = 10.6%) was identical to the biomass in 2007 (1.6 kg/ha). Bloater biomass was again much lower (2.6 kg/ha, RSE = 15.2%) than in the 1990s, but mean density of small bloater in 2008 (534 fish/ha, RSE = 10.9) was the highest observed in any acoustic survey on record. Prey fish biomass remained well below the Fish Community Objectives target of 500-800 kt and only alewife and small bloater are above or near long-term mean biomass levels. Mysis diluviana remains relatively abundant. Mean density ranged from 185 ind./m2 (RSE = 6.8%) in 2005 to 112 ind./m2 (RSE = 5.1%) in 2007, but there was not a statistically significant difference among years.
","conferenceTitle":"Great Lakes Fishery Commission: Lake Michigan Committee Meeting","conferenceDate":"March 26, 2009","conferenceLocation":"Ypsilanti, MI","language":"English","publisher":"Great Lakes Fishery Commission","usgsCitation":"Warner, D.M., Claramunt, R., Holuszko, J.D., and Desorcie, T.J., 2009, Status of pelagic prey fishes and pelagic macroinvertebrates in Lake Michigan, 2008, Great Lakes Fishery Commission: Lake Michigan Committee Meeting, Ypsilanti, MI, March 26, 2009, 14 p.","productDescription":"14 p.","ipdsId":"IP-012490","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":340133,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":314243,"type":{"id":15,"text":"Index Page"},"url":"https://www.glsc.usgs.gov/products/reports/265538519"}],"country":"United States","otherGeospatial":"Lake Michigan","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58ff0ea8e4b006455f2d6204","contributors":{"authors":[{"text":"Warner, David M. 0000-0003-4939-5368 dmwarner@usgs.gov","orcid":"https://orcid.org/0000-0003-4939-5368","contributorId":2986,"corporation":false,"usgs":true,"family":"Warner","given":"David","email":"dmwarner@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":588458,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Claramunt, Randall M.","contributorId":19047,"corporation":false,"usgs":true,"family":"Claramunt","given":"Randall M.","affiliations":[],"preferred":false,"id":588461,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holuszko, Jeffrey D.","contributorId":104429,"corporation":false,"usgs":true,"family":"Holuszko","given":"Jeffrey","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":588457,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Desorcie, Timothy J. 0000-0002-9965-1668 tdesorcie@usgs.gov","orcid":"https://orcid.org/0000-0002-9965-1668","contributorId":3672,"corporation":false,"usgs":true,"family":"Desorcie","given":"Timothy","email":"tdesorcie@usgs.gov","middleInitial":"J.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":588460,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70161736,"text":"70161736 - 2009 - Status and trends of prey fish populations in Lake Michigan, 2008","interactions":[],"lastModifiedDate":"2018-03-15T09:57:57","indexId":"70161736","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":5651,"text":"Great Lakes Fishery Commission, Committee Meeting Report","active":true,"publicationSubtype":{"id":4}},"title":"Status and trends of prey fish populations in Lake Michigan, 2008","docAbstract":"The Great Lakes Science Center (GLSC) has conducted lake-wide surveys of the fish community in Lake Michigan each fall since 1973 using standard 12-m bottom trawls towed along contour at depths of 9 to 110 m at each of seven index transects. The resulting data on relative abundance, size structure, and condition of individual fishes are used to estimate various population parameters that are in turn used by state and tribal agencies in managing Lake Michigan fish stocks. All seven established index transects of the survey were completed in 2008. The survey provides relative abundance and biomass estimates between the 5-m and 114-m depth contours of the lake (herein, lake-wide) for prey fish populations, as well as burbot, yellow perch, and the introduced dreissenid mussels. Lake-wide biomass of alewives in 2008 was estimated at 8.27 kilotonnes (kt) (1 kt = 1000 metric tons), which was the smallest biomass estimate in the entire time series and 29% lower than the 2007 estimate. Lake-wide biomass of bloater in 2008 was estimated at 3.33 kt, which was the lowest estimate since 1977 and 38% lower than the 2007 estimate. Rainbow smelt lake-wide biomass equaled 0.89 kt, which was only 0.01 kt higher than 2007, which is the lowest estimate in the time series. Deepwater sculpin lake-wide biomass equaled 5.23 kt, which is the fourth straight year of declining biomass. The 2008 estimate is the second smallest in the time series, and 39% lower than the 2007 estimate. Slimy sculpin lake-wide biomass remained relatively high in 2008 (2.75 kt), increasing 25% over 2007. Ninespine stickleback lake-wide biomass equaled only 0.50 kt in 2008, which was 79% lower than the 2007 estimate. The final prey fish, exotic round goby, increased two orders of magnitude between 2007 and 2008, from 0.02 to 4.65 kt. Round gobies now represent 18% of the prey fish biomass. Burbot lake-wide biomass (0.91 kt in 2008) has remained fairly constant since 2002. Numeric density of age-0 yellow perch (i.e., < 100 mm) equaled 0.7 fish per ha, which is indicative of a relatively poor year-class. Lake-wide biomass of dreissenid mussels dropped precipitously in 2008, down to 9.47 kt, and a 96% decline from the 2007 biomass estimate. Overall, the total lake-wide prey fish biomass estimate (sum of alewife, bloater, rainbow smelt, deepwater sculpin, slimy sculpin, round goby, and ninespine stickleback) in 2008 was 25.62 kt, which was the lowest observed since the survey began in 1973.","conferenceTitle":"Great Lakes Fishery Commission: Lake Michigan Committee Meeting","conferenceDate":"March 26, 2009","conferenceLocation":"Ypsilanti, MI","language":"English","publisher":"Great Lakes Fishery Commission","usgsCitation":"Bunnell, D., Madenjian, C.P., Holuszko, J.D., Desorcie, T.J., and Adams, J.V., 2009, Status and trends of prey fish populations in Lake Michigan, 2008: Great Lakes Fishery Commission, Committee Meeting Report, 13 p.","productDescription":"13 p.","ipdsId":"IP-012350","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":340117,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":313817,"type":{"id":15,"text":"Index Page"},"url":"https://www.glsc.usgs.gov/products/reports/1692671905"}],"country":"United States","otherGeospatial":"Lake Michigan","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58fdbd1be4b0074928294491","contributors":{"authors":[{"text":"Bunnell, David B. dbunnell@usgs.gov","contributorId":141167,"corporation":false,"usgs":true,"family":"Bunnell","given":"David B.","email":"dbunnell@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":587592,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Madenjian, Charles P. 0000-0002-0326-164X cmadenjian@usgs.gov","orcid":"https://orcid.org/0000-0002-0326-164X","contributorId":2200,"corporation":false,"usgs":true,"family":"Madenjian","given":"Charles","email":"cmadenjian@usgs.gov","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":587591,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holuszko, Jeffrey D.","contributorId":104429,"corporation":false,"usgs":true,"family":"Holuszko","given":"Jeffrey","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":587590,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Desorcie, Timothy J. 0000-0002-9965-1668 tdesorcie@usgs.gov","orcid":"https://orcid.org/0000-0002-9965-1668","contributorId":3672,"corporation":false,"usgs":true,"family":"Desorcie","given":"Timothy","email":"tdesorcie@usgs.gov","middleInitial":"J.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":587595,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Adams, Jean V. 0000-0002-9101-068X jvadams@usgs.gov","orcid":"https://orcid.org/0000-0002-9101-068X","contributorId":3140,"corporation":false,"usgs":true,"family":"Adams","given":"Jean","email":"jvadams@usgs.gov","middleInitial":"V.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":587593,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70159575,"text":"70159575 - 2009 - Audiomagnetotelluric investigation of Snake Valley, eastern Nevada and western Utah","interactions":[],"lastModifiedDate":"2016-06-17T10:03:22","indexId":"70159575","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5014,"text":"Geology and Geologic Resources and Issues of Western Utah","active":true,"publicationSubtype":{"id":10}},"title":"Audiomagnetotelluric investigation of Snake Valley, eastern Nevada and western Utah","docAbstract":"Audiomagnetotelluric (AMT) data along four profiles in western Snake Valley and the corresponding two-dimensional (2-D) inverse models reveal subsurface structures that may be significant to ground-water investigations in the area. The AMT method is a valuable tool for estimating the electrical resistivity of the earth over depth ranges from a few meters to less than one kilometer. The method has the potential to identify faults and stratigraphy within basins of eastern Nevada, thereby helping define the hydrogeologic framework of the region.
\nAs support for an exploratory well-drilling and hydraulic-testing program, AMT data were collected using a Geometrics Stratagem EH4 system along four profiles that extend roughly east-west from the southern Snake Range into Snake Valley. The profiles range from 3 to 5 kilometers in length, and station spacing was 200 to 400 meters. Two-dimensional inverse models were computed using the data from the transverse-electric (TE), transverse-magnetic (TM), and combined (TE+TM) mode using a conjugate gradient, finite-difference method. Interpretation of the 2-D AMT models defines several faults, some of which may influence ground-water flow in the basins, as well as identify underlying Paleozoic carbonate and clastic rocks and the thickness of basin-fill sediments. These AMT data and models, coupled with the geologic mapping and other surface geophysical methods, form the basis for identifying potential well sites and defining the subsurface structures and stratigraphy within Snake Valley.
","language":"English","publisher":"Utah Geological Association","usgsCitation":"McPhee, D., Pari, K., and Baird, F., 2009, Audiomagnetotelluric investigation of Snake Valley, eastern Nevada and western Utah: Geology and Geologic Resources and Issues of Western Utah, p. 287-298.","productDescription":"12 p.","startPage":"287","endPage":"298","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-013054","costCenters":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":311621,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":311164,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://archives.datapages.com/data/uga/data/081/081001/287_ugs810287.htm"}],"country":"United States","state":"Nevada, Utah","otherGeospatial":"Snake Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.20631408691406,\n 38.678541582058195\n ],\n [\n -114.20631408691406,\n 39.0303858632327\n ],\n [\n -113.95225524902344,\n 39.0303858632327\n ],\n [\n -113.95225524902344,\n 38.678541582058195\n ],\n [\n -114.20631408691406,\n 38.678541582058195\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5650523fe4b0f162148c5cf3","contributors":{"authors":[{"text":"McPhee, Darcy 0000-0002-5177-3068 dmcphee@usgs.gov","orcid":"https://orcid.org/0000-0002-5177-3068","contributorId":2621,"corporation":false,"usgs":true,"family":"McPhee","given":"Darcy","email":"dmcphee@usgs.gov","affiliations":[{"id":412,"text":"National Cooperative Geologic Mapping Program","active":false,"usgs":true}],"preferred":true,"id":579531,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pari, Keith","contributorId":149774,"corporation":false,"usgs":false,"family":"Pari","given":"Keith","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":579533,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Baird, Frank","contributorId":149773,"corporation":false,"usgs":false,"family":"Baird","given":"Frank","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":579532,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70148130,"text":"70148130 - 2009 - Fishing mortality in North Carolina's southern flounder fishery: direct estimates of instantaneous fishing mortality from a tag return experiment","interactions":[],"lastModifiedDate":"2015-06-03T10:19:43","indexId":"70148130","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2680,"text":"Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science","active":true,"publicationSubtype":{"id":10}},"title":"Fishing mortality in North Carolina's southern flounder fishery: direct estimates of instantaneous fishing mortality from a tag return experiment","docAbstract":"Estimation of harvest rates is often a critical component of fishery stock assessment and management. These assessments are often based on catch-at-age data sets generated over many years, but estimates of instantaneous fishing mortality (F) can also be obtained from a shorter-term tag return study. We conducted a 2-year tag return experiment to generate direct estimates of F for southern flounder Paralichthys lethostigma in a North Carolina estuary. The southern flounder supports lucrative commercial and recreational fisheries within the state and has experienced heavy fishing pressure for more than a decade. During 2005 and 2006, fish were captured and tagged with the assistance of commercial harvesters in the New River estuary. Tag returns were used to generate monthly estimates of F, which demonstrated a clear seasonal pattern that was consistent between years. Several important assumptions of the tag return model were accounted for through the use of double-tagged individuals, the distribution of both high- and standard-reward tags, and the completion of an independent controlled experiment to evaluate mortality related to tagging. Annual estimates of F exceeded the short-term management target in both years. Residual patterns suggest that the estimates may actually have been biased low, possibly due to delayed mixing of tagged fish. Thus, despite recently amended fishery regulations, F in the North Carolina southern flounder gill-net fishery still has the potential to greatly exceed targeted levels, which may delay stock recovery. Tag return studies can provide reliable (and nearly real-time) information about F and natural mortality as long as the experimental design addresses specific assumptions related to tagging-induced mortality, tag shedding, and nonreporting of tags.
","language":"English","publisher":"American Fisheries Society","doi":"10.1577/C09-009.1","usgsCitation":"Smith, W.E., Scharf, F.S., and Hightower, J.E., 2009, Fishing mortality in North Carolina's southern flounder fishery: direct estimates of instantaneous fishing mortality from a tag return experiment: Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science, v. 1, no. 1, p. 283-299, https://doi.org/10.1577/C09-009.1.","productDescription":"17 p.","startPage":"283","endPage":"299","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-010537","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":476274,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1577/c09-009.1","text":"Publisher Index Page"},{"id":301003,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"New River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.30186462402344,\n 34.548418116253366\n ],\n [\n -77.33551025390624,\n 34.57612563188475\n ],\n [\n -77.35954284667969,\n 34.58912801692681\n ],\n [\n -77.36709594726561,\n 34.59760673724307\n ],\n [\n -77.34443664550781,\n 34.61851721379668\n ],\n [\n -77.30941772460938,\n 34.63207795006471\n ],\n [\n -77.31147766113281,\n 34.64620136014535\n ],\n [\n -77.33001708984375,\n 34.65128519895413\n ],\n [\n -77.35336303710938,\n 34.67331156427795\n ],\n [\n -77.35816955566406,\n 34.69871932453228\n ],\n [\n -77.38494873046875,\n 34.713395809196285\n ],\n [\n -77.34855651855469,\n 34.71903991764788\n ],\n [\n -77.34443664550781,\n 34.741048259437335\n ],\n [\n -77.35954284667969,\n 34.74669047997149\n ],\n [\n -77.3931884765625,\n 34.73935551813357\n ],\n [\n -77.41378784179686,\n 34.74217673437265\n ],\n [\n -77.43713378906249,\n 34.75120397893155\n ],\n [\n -77.45155334472656,\n 34.75007562731471\n ],\n [\n -77.44674682617188,\n 34.73089129142625\n ],\n [\n -77.43850708007812,\n 34.72129745316466\n ],\n [\n -77.43919372558594,\n 34.70379994079758\n ],\n [\n -77.44056701660156,\n 34.681217036379266\n ],\n [\n -77.43232727050781,\n 34.67500565754207\n ],\n [\n -77.41790771484375,\n 34.68347560408202\n ],\n [\n -77.40554809570311,\n 34.66709959253004\n ],\n [\n -77.38632202148438,\n 34.64733112904415\n ],\n [\n -77.38220214843749,\n 34.6365977029715\n ],\n [\n -77.39524841308594,\n 34.619647359797185\n ],\n [\n -77.41790771484375,\n 34.62642791261892\n ],\n [\n -77.45361328125,\n 34.622472657470205\n ],\n [\n -77.45429992675781,\n 34.60269355405183\n ],\n [\n -77.43507385253906,\n 34.5710371883746\n ],\n [\n -77.40966796875,\n 34.56029389604531\n ],\n [\n -77.38357543945312,\n 34.557466483188996\n ],\n [\n -77.39524841308594,\n 34.54672143790495\n ],\n [\n -77.40211486816406,\n 34.535409364930814\n ],\n [\n -77.39593505859375,\n 34.52013562807766\n ],\n [\n -77.37945556640625,\n 34.50938576380423\n ],\n [\n -77.30186462402344,\n 34.548418116253366\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"1","issue":"1","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2009-01-01","publicationStatus":"PW","scienceBaseUri":"55702538e4b0d9246a9fd19a","contributors":{"authors":[{"text":"Smith, William E.","contributorId":141055,"corporation":false,"usgs":false,"family":"Smith","given":"William","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":548125,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scharf, Frederick S.","contributorId":140980,"corporation":false,"usgs":false,"family":"Scharf","given":"Frederick","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":548126,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hightower, Joseph E. jhightower@usgs.gov","contributorId":835,"corporation":false,"usgs":true,"family":"Hightower","given":"Joseph","email":"jhightower@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":547459,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70156061,"text":"70156061 - 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Based on a before-after-control impact (BACI) experimental design, long-term stream monitoring (1997–2006) was conducted at upstream (as control, n = 3) and downstream (as impact, n = 6) sites in the Lost River watershed of the Mid-Atlantic Highlands region, West Virginia. Monitoring data were analyzed to assess impacts of during and after highway construction on 15 water quality parameters and macroinvertebrate condition using the West Virginia stream condition index (WVSCI). Principal components analysis (PCA) identified regional primary water quality variances, and paired t tests and time series analysis detected seven highway construction-impacted water quality parameters which were mainly associated with the second principal component. In particular, impacts on turbidity, total suspended solids, and total iron during construction, impacts on chloride and sulfate during and after construction, and impacts on acidity and nitrate after construction were observed at the downstream sites. The construction had statistically significant impacts on macroinvertebrate index scores (i.e., WVSCI) after construction, but did not change the overall good biological condition. Implementing BMPs that address those construction-impacted water quality parameters can be an effective mitigation strategy for future highway construction in this highlands region.
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Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Delineation of Magnesium-rich Ultramafic Rocks Available for Mineral Carbon Sequestration in the United States","docAbstract":"The 2005 Intergovernmental Panel on Climate Change report on Carbon Dioxide Capture and Storage suggested that a major gap in mineral carbon sequestration is locating the magnesium-silicate bedrock available to sequester CO2. It is generally known that silicate minerals with high concentrations of magnesium are suitable for mineral carbonation. However, no assessment has been made covering the entire United States detailing their geographical distribution and extent, or evaluating their potential for use in mineral carbonation. Researchers at Columbia University and the U.S. Geological Survey have developed a digital geologic database of ultramafic rocks in the continental United States. Data were compiled from varied-scale geologic maps of magnesium-silicate ultramafic rocks. These rock types are potentially suitable as source material for mineral carbon-dioxide sequestration. The focus of the national-scale map is entirely on suitable ultramafic rock types, which typically consist primarily of olivine and serpentine minerals. By combining the map with digital datasets that show non-mineable lands (such as urban areas and National Parks), estimates on potential depth of a surface mine, and the predicted reactivities of the mineral deposits, one can begin to estimate the capacity for CO2 mineral sequestration within the United States. ?? 2009 Elsevier Ltd. All rights reserved.","largerWorkTitle":"Energy Procedia","conferenceTitle":"9th International Conference on Greenhouse Gas Control Technologies, GHGT-9","conferenceDate":"16 November 2008 through 20 November 2008","conferenceLocation":"Washington DC","language":"English","doi":"10.1016/j.egypro.2009.02.322","issn":"18766102","usgsCitation":"Krevor, S., Graves, C.R., Van Gosen, B.S., and McCafferty, A.E., 2009, Delineation of Magnesium-rich Ultramafic Rocks Available for Mineral Carbon Sequestration in the United States, in Energy Procedia, v. 1, no. 1, Washington DC, 16 November 2008 through 20 November 2008, p. 4915-4920, https://doi.org/10.1016/j.egypro.2009.02.322.","startPage":"4915","endPage":"4920","numberOfPages":"6","costCenters":[],"links":[{"id":487813,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.egypro.2009.02.322","text":"Publisher Index Page"},{"id":216347,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.egypro.2009.02.322"},{"id":244211,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"1","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059fe65e4b0c8380cd4ecfc","contributors":{"authors":[{"text":"Krevor, S. C.","contributorId":107389,"corporation":false,"usgs":true,"family":"Krevor","given":"S. C.","affiliations":[],"preferred":false,"id":452130,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graves, C. R.","contributorId":72482,"corporation":false,"usgs":true,"family":"Graves","given":"C.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":452127,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Van Gosen, B. S. 0000-0003-4214-3811","orcid":"https://orcid.org/0000-0003-4214-3811","contributorId":97907,"corporation":false,"usgs":true,"family":"Van Gosen","given":"B.","middleInitial":"S.","affiliations":[],"preferred":false,"id":452129,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCafferty, A. E.","contributorId":93499,"corporation":false,"usgs":true,"family":"McCafferty","given":"A.","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":452128,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70193767,"text":"70193767 - 2009 - Investigation of aquifer-estuary interaction using wavelet analysis of fiber-optic temperature data","interactions":[],"lastModifiedDate":"2019-10-21T12:30:46","indexId":"70193767","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Investigation of aquifer-estuary interaction using wavelet analysis of fiber-optic temperature data","docAbstract":"Fiber-optic distributed temperature sensing (FODTS) provides sub-minute temporal and meter-scale spatial resolution over kilometer-long cables. Compared to conventional thermistor or thermocouple-based technologies, which measure temperature at discrete (and commonly sparse) locations, FODTS offers nearly continuous spatial coverage, thus providing hydrologic information at spatiotemporal scales previously impossible. Large and information-rich FODTS datasets, however, pose challenges for data exploration and analysis. To date, FODTS analyses have focused on time-series variance as the means to discriminate between hydrologic phenomena. Here, we demonstrate the continuous wavelet transform (CWT) and cross-wavelet transform (XWT) to analyze FODTS in the context of related hydrologic time series. We apply the CWT and XWT to data from Waquoit Bay, Massachusetts to identify the location and timing of tidal pumping of submarine groundwater.
","language":"English","publisher":"Wiley","doi":"10.1029/2008GL036926","usgsCitation":"Henderson, R., Day-Lewis, F.D., and Harvey, C.F., 2009, Investigation of aquifer-estuary interaction using wavelet analysis of fiber-optic temperature data: Geophysical Research Letters, v. 36, no. 6, L06403; 6 p., https://doi.org/10.1029/2008GL036926.","productDescription":"L06403; 6 p.","ipdsId":"IP-010693","costCenters":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":488185,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2008gl036926","text":"Publisher Index Page"},{"id":348717,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"6","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2009-03-31","publicationStatus":"PW","scienceBaseUri":"5a610cfde4b06e28e9c25765","contributors":{"authors":[{"text":"Henderson, R.D.","contributorId":14269,"corporation":false,"usgs":true,"family":"Henderson","given":"R.D.","email":"","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":6619,"text":"University of Connecticutt","active":true,"usgs":false}],"preferred":false,"id":720318,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Day-Lewis, Frederick D. 0000-0003-3526-886X daylewis@usgs.gov","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":1672,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","email":"daylewis@usgs.gov","middleInitial":"D.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":720317,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harvey, Charles F.","contributorId":199836,"corporation":false,"usgs":false,"family":"Harvey","given":"Charles","email":"","middleInitial":"F.","affiliations":[{"id":12444,"text":"Massachusetts Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":720319,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70035288,"text":"70035288 - 2009 - Migratory patterns and population structure among breeding and wintering red-breasted mergansers (Mergus serrator) and common mergansers (M. merganser)","interactions":[],"lastModifiedDate":"2018-07-14T14:15:02","indexId":"70035288","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3544,"text":"The Auk","onlineIssn":"1938-4254","printIssn":"0004-8038","active":true,"publicationSubtype":{"id":10}},"title":"Migratory patterns and population structure among breeding and wintering red-breasted mergansers (Mergus serrator) and common mergansers (M. merganser)","docAbstract":"Philopatry has long been assumed to structure populations of waterfowl and other species of birds genetically, especially via maternally transmitted mitochondrial DNA (mtDNA), yet other migratory behaviors and nesting ecology (use of ground vs. cavity sites) may also contribute to population genetic structure. We investigated the effects of migration and nesting ecology on the population genetic structure of two Holarctic waterfowl, the Red-breasted Merganser (Mergus serrator) and Common Merganser (M. merganser), using mtDNA control-region sequence data. Red-breasted Mergansers (a ground-nesting species) exhibited lower levels of population differentiation across their North American range, possibly as a result of post-Pleistocene range expansion and population growth. By contrast, Common Mergansers (a cavity-nesting species) breeding in western and eastern North America were strongly differentiated, as were continental groups in North America and Europe. Our hypothesis that population differentiation of breeding female Common Mergansers results from limited migration during non-breeding periods was not supported, in that equally heterogeneous mtDNA lineages were observed in males and females on several wintering areas. The interspecific differences in mtDNA patterns for these two closely related species may have resulted from factors related to nesting ecology (ground vs. cavity nesting) and responses to historical climate change.
","language":"English","publisher":"American Ornithological Society","doi":"10.1525/auk.2009.08182","issn":"00048038","usgsCitation":"Pearce, J.M., McCracken, K.G., Christensen, T.K., and Zhuravlev, Y., 2009, Migratory patterns and population structure among breeding and wintering red-breasted mergansers (Mergus serrator) and common mergansers (M. merganser): The Auk, v. 126, no. 4, p. 784-798, https://doi.org/10.1525/auk.2009.08182.","productDescription":"15 p.","startPage":"784","endPage":"798","costCenters":[],"links":[{"id":243360,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"126","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a572ae4b0c8380cd6dacf","contributors":{"authors":[{"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":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":450030,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCracken, K. G.","contributorId":7431,"corporation":false,"usgs":true,"family":"McCracken","given":"K.","middleInitial":"G.","affiliations":[],"preferred":false,"id":450027,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Christensen, Thomas K.","contributorId":69381,"corporation":false,"usgs":false,"family":"Christensen","given":"Thomas","email":"","middleInitial":"K.","affiliations":[{"id":6963,"text":"Department of Bioscience, Aarhus University","active":true,"usgs":false}],"preferred":false,"id":450028,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhuravlev, Y.N.","contributorId":82149,"corporation":false,"usgs":true,"family":"Zhuravlev","given":"Y.N.","email":"","affiliations":[],"preferred":false,"id":450029,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70189184,"text":"70189184 - 2009 - Sensitivity analysis, calibration, and testing of a distributed hydrological model using error‐based weighting and one objective function","interactions":[],"lastModifiedDate":"2018-04-03T11:20:23","indexId":"70189184","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Sensitivity analysis, calibration, and testing of a distributed hydrological model using error‐based weighting and one objective function","docAbstract":"We evaluate the utility of three interrelated means of using data to calibrate the fully distributed rainfall‐runoff model TOPKAPI as applied to the Maggia Valley drainage area in Switzerland. The use of error‐based weighting of observation and prior information data, local sensitivity analysis, and single‐objective function nonlinear regression provides quantitative evaluation of sensitivity of the 35 model parameters to the data, identification of data types most important to the calibration, and identification of correlations among parameters that contribute to nonuniqueness. Sensitivity analysis required only 71 model runs, and regression required about 50 model runs. The approach presented appears to be ideal for evaluation of models with long run times or as a preliminary step to more computationally demanding methods. The statistics used include composite scaled sensitivities, parameter correlation coefficients, leverage, Cook's D, and DFBETAS. Tests suggest predictive ability of the calibrated model typical of hydrologic models.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2008WR007255","usgsCitation":"Foglia, L., Hill, M.C., Mehl, S.W., and Burlando, P., 2009, Sensitivity analysis, calibration, and testing of a distributed hydrological model using error‐based weighting and one objective function: Water Resources Research, v. 45, no. 6, Article W06427; 18 p., https://doi.org/10.1029/2008WR007255.","productDescription":"Article W06427; 18 p.","ipdsId":"IP-011230","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":343431,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"45","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2009-06-24","publicationStatus":"PW","scienceBaseUri":"595f4c49e4b0d1f9f057e395","contributors":{"authors":[{"text":"Foglia, L.","contributorId":6251,"corporation":false,"usgs":true,"family":"Foglia","given":"L.","affiliations":[],"preferred":false,"id":703397,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hill, Mary C. mchill@usgs.gov","contributorId":974,"corporation":false,"usgs":true,"family":"Hill","given":"Mary","email":"mchill@usgs.gov","middleInitial":"C.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":703395,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mehl, Steffen W. swmehl@usgs.gov","contributorId":975,"corporation":false,"usgs":true,"family":"Mehl","given":"Steffen","email":"swmehl@usgs.gov","middleInitial":"W.","affiliations":[],"preferred":true,"id":703396,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burlando, P.","contributorId":29209,"corporation":false,"usgs":true,"family":"Burlando","given":"P.","affiliations":[],"preferred":false,"id":703398,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70033168,"text":"70033168 - 2009 - PCDDs, PCDFs, PCBs, OC pesticides and mercury in fish and osprey eggs from Willamette River, Oregon (1993, 2001 and 2006) with calculated biomagnification factors","interactions":[],"lastModifiedDate":"2017-11-17T15:28:59","indexId":"70033168","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1479,"text":"Ecotoxicology","active":true,"publicationSubtype":{"id":10}},"title":"PCDDs, PCDFs, PCBs, OC pesticides and mercury in fish and osprey eggs from Willamette River, Oregon (1993, 2001 and 2006) with calculated biomagnification factors","docAbstract":"The osprey (Pandion haliaetus) population nesting along the main stem Willamette River and lower Santiam River was first studied to evaluate contaminants and reproductive rates in 1993 when 78 occupied nests were present. By 2001, the population increased to 234 occupied nests, a 13.7% annual rate of population increase. A sample egg was collected from each of a series of nests along the Upper River (river mile 55-187) in 1993, 2001 and 2006 to evaluate trends of persistent contaminants (organochlorine [OC] pesticides, polychlorinated biphenyls [PCBs], polychlorinated dibenzo-p-dioxins [PCDDs], and polychlorinated dibenzofurans [PCDFs]). Nearly all OC pesticide residues decreased significantly, e.g., p, p?-DDE (DDE) from 2,350 to 1,353 to 210 ??g/kg wet weight (ww). PCBs followed a similar pattern over time, e.g., ???PCBs 688 to 245 to 182 ??g/kg ww, while PCDDs and PCDFs showed a more precipitous decline (often 85-95%) between 1993 and 2001, with no egg analyses warranted in 2006. During 2001-2002, sample osprey eggs were also collected from nests at three Headwater Reservoirs and two lower reaches (Newberg Pool and Tidal Portland) of the Willamette River, as well as the lower portion of the Santiam River to evaluate spatial residue patterns. Significant differences were seldom detected among the different sampling areas for OC pesticides (probably due to small sample sizes), although higher concentrations were often seen in the lower reaches, e.g., DDE 901 ??g/kg ww (Headwater Reservoirs), 1,353 (Upper River), 1,384 (Newberg Pool) and 2,676 (Tidal Portland). PCB congener concentrations in eggs were usually higher in the Tidal Portland reach than at other locations and often significantly higher than at the Headwater Reservoirs or Upper River. Mercury (first analyzed in eggs in 2001), PCDDs and PCDFs were extremely low in 2001/2002 with no significant spatial patterns. Whole fish composite samples of largescale sucker (Catastomus macrocheilus) and northern pikeminnow (Ptychocheilus oregonensis), which account for about 90% of the biomass in the diet of this osprey population, were also collected from the Willamette River in 1993 and 2001 and analyzed for the same contaminants as osprey eggs. Contaminant residues in fish from the Upper River decreased between 1993 and 2001, paralleling findings for osprey eggs. Likewise, spatial patterns for fish residues paralleled findings for osprey eggs from the different reaches in 2001. A second empirical estimate of biomagnification factors (BMFs) from fish to osprey eggs for OC pesticides, PCBs, PCDDs and PCDFs (ww and lipid weight [lw] basis) was calculated based on residue data collected in 2001. The two independent BMF estimates (1993 and 2001) for each contaminant from the Upper River provide a measure of consistency, e.g., DDE (ww) 87 and 79, (lw) 103 and 112; ???PCBs (ww) 11 and 8.4, (lw) 13 and 12. Mercury did not biomagnify from fish to osprey eggs (BMF = 0.60). Legacy contaminants investigated had limited (perhaps only DDE), if any, effects on reproductive success of the increasing osprey population nesting along the Willamette River by 2001. ?? 2008 U.S. Government.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecotoxicology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1007/s10646-008-0268-z","issn":"09639","usgsCitation":"Henny, C.J., Kaiser, J.L., and Grove, R.A., 2009, PCDDs, PCDFs, PCBs, OC pesticides and mercury in fish and osprey eggs from Willamette River, Oregon (1993, 2001 and 2006) with calculated biomagnification factors: Ecotoxicology, v. 18, no. 2, p. 151-173, https://doi.org/10.1007/s10646-008-0268-z.","startPage":"151","endPage":"173","numberOfPages":"23","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":240985,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213367,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10646-008-0268-z"}],"volume":"18","issue":"2","noUsgsAuthors":false,"publicationDate":"2008-10-02","publicationStatus":"PW","scienceBaseUri":"505a7341e4b0c8380cd76f28","contributors":{"authors":[{"text":"Henny, Charles J.","contributorId":12578,"corporation":false,"usgs":true,"family":"Henny","given":"Charles","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":439667,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kaiser, J. L.","contributorId":27602,"corporation":false,"usgs":true,"family":"Kaiser","given":"J.","middleInitial":"L.","affiliations":[],"preferred":false,"id":439668,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grove, R. A.","contributorId":6546,"corporation":false,"usgs":false,"family":"Grove","given":"R.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":439666,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70194406,"text":"70194406 - 2009 - Vegetation classification and distribution mapping report: Mesa Verde National Park","interactions":[],"lastModifiedDate":"2021-10-27T15:57:21.342499","indexId":"70194406","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":53,"text":"Natural Resource Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"NPS/SCPN/NRR—2009/112","title":"Vegetation classification and distribution mapping report: Mesa Verde National Park","docAbstract":"The classification and distribution mapping of the vegetation of Mesa Verde National Park (MEVE) and surrounding environment was achieved through a multi-agency effort between 2004 and 2007. The National Park Service’s Southern Colorado Plateau Network facilitated the team that conducted the work, which comprised the U.S. Geological Survey’s Southwest Biological Science Center, Fort Collins Research Center, and Rocky Mountain Geographic Science Center; Northern Arizona University; Prescott College; and NatureServe.
The project team described 47 plant communities for MEVE, 34 of which were described from quantitative classification based on f eld-relevé data collected in 1993 and 2004. The team derived 13 additional plant communities from field observations during the photointerpretation phase of the project. The National Vegetation Classification Standard served as a framework for classifying these plant communities to the alliance and association level. Eleven of the 47 plant communities were classified as “park specials;” that is, plant communities with insufficient data to describe them as new alliances or associations.
The project team also developed a spatial vegetation map database representing MEVE, with three different map-class schemas: base, group, and management map classes. The base map classes represent the fi nest level of spatial detail. Initial polygons were developed using Definiens Professional (at the time of our use, this software was called eCognition), assisted by interpretation of 1:12,000 true-color digital orthophoto quarter quadrangles (DOQQs). These polygons (base map classes) were labeled using manual photo interpretation of the DOQQs and 1:12,000 true-color aerial photography. Field visits verified interpretation concepts.
The vegetation map database includes 46 base map classes, which consist of associations, alliances, and park specials classified with quantitative analysis, additional associations and park specials noted during photointerpretation, and non-vegetated land cover, such as infrastructure, land use, and geological land cover. The base map classes consist of 5,007 polygons in the project area. A field-based accuracy assessment of the base map classes showed overall accuracy to be 43.5%. Seven map classes comprise 89.1% of the park vegetated land cover.
The group map classes represent aggregations of the base map classes, approximating the group level of the National Vegetation Classification Standard, version 2 (Federal Geographic Data Committee 2007), and reflecting physiognomy and floristics. Terrestrial ecological systems, as described by NatureServe (Comer et al. 2003), were used as the fi rst approximation of the group level. The project team identified 14 group map classes for this project. The overall accuracy of the group map classes was determined using the same accuracy assessment data as for the base map classes. The overall accuracy of the group representation of vegetation was 80.3%.
In consultation with park staff , the team developed management map classes, consisting of park-defined groupings of base map classes intended to represent a balance between maintaining required accuracy and providing a focus on vegetation of particular interest or import to park managers. The 23 management map classes had an overall accuracy of 73.3%.
While the main products of this project are the vegetation classification and the vegetation map database, a number of ancillary digital geographic information system and database products were also produced that can be used independently or to augment the main products. These products include shapefiles of the locations of field-collected data and relational databases of field-collected data.
","language":"English","publisher":"National Park Service","publisherLocation":"Fort Collins, CO","usgsCitation":"Thomas, K.A., McTeague, M.L., Ogden, L., Floyd, M.L., Schulz, K., Friesen, B.A., Fancher, T.S., Waltermire, R.G., and Cully, A., 2009, Vegetation classification and distribution mapping report: Mesa Verde National Park: Natural Resource Report NPS/SCPN/NRR—2009/112, xiii, 333 p.","productDescription":"xiii, 333 p.","numberOfPages":"352","ipdsId":"IP-009848","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":349399,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":349398,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/DataStore/Reference/Profile/662650"}],"country":"United States","otherGeospatial":"Mesa Verde National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.555908203125,\n 37.15539139648255\n ],\n [\n -108.34373474121094,\n 37.15539139648255\n ],\n [\n -108.34373474121094,\n 37.351601144954785\n ],\n [\n -108.555908203125,\n 37.351601144954785\n ],\n [\n -108.555908203125,\n 37.15539139648255\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a610cfce4b06e28e9c2575b","contributors":{"authors":[{"text":"Thomas, Kathryn A. 0000-0002-7131-8564 kathryn_a_thomas@usgs.gov","orcid":"https://orcid.org/0000-0002-7131-8564","contributorId":167,"corporation":false,"usgs":true,"family":"Thomas","given":"Kathryn","email":"kathryn_a_thomas@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":723708,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McTeague, Monica L.","contributorId":82045,"corporation":false,"usgs":true,"family":"McTeague","given":"Monica","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":723709,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ogden, Lindsay","contributorId":54131,"corporation":false,"usgs":true,"family":"Ogden","given":"Lindsay","email":"","affiliations":[],"preferred":false,"id":723710,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Floyd, M. Lisa","contributorId":22569,"corporation":false,"usgs":true,"family":"Floyd","given":"M.","email":"","middleInitial":"Lisa","affiliations":[],"preferred":false,"id":723711,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schulz, Keith","contributorId":200884,"corporation":false,"usgs":false,"family":"Schulz","given":"Keith","email":"","affiliations":[],"preferred":false,"id":723712,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Friesen, Beverly A. bafriesen@usgs.gov","contributorId":3216,"corporation":false,"usgs":true,"family":"Friesen","given":"Beverly","email":"bafriesen@usgs.gov","middleInitial":"A.","affiliations":[{"id":573,"text":"Special Applications Science Center","active":true,"usgs":true}],"preferred":true,"id":723713,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fancher, Tammy S. 0000-0002-1318-3614 fanchert@usgs.gov","orcid":"https://orcid.org/0000-0002-1318-3614","contributorId":3788,"corporation":false,"usgs":true,"family":"Fancher","given":"Tammy","email":"fanchert@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":723714,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Waltermire, Robert G. waltermireb@usgs.gov","contributorId":2074,"corporation":false,"usgs":true,"family":"Waltermire","given":"Robert","email":"waltermireb@usgs.gov","middleInitial":"G.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":723715,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cully, Anne","contributorId":200885,"corporation":false,"usgs":false,"family":"Cully","given":"Anne","email":"","affiliations":[],"preferred":false,"id":723716,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70194451,"text":"70194451 - 2009 - Distributed geospatial model sharing based on open interoperability standards","interactions":[],"lastModifiedDate":"2017-11-29T12:59:09","indexId":"70194451","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5571,"text":"Journal of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Distributed geospatial model sharing based on open interoperability standards","docAbstract":"Numerous geospatial computational models have been developed based on sound principles and published in journals or presented in conferences. However modelers have made few advances in the development of computable modules that facilitate sharing during model development or utilization. Constraints hampering development of model sharing technology includes limitations on computing, storage, and connectivity; traditional stand-alone and closed network systems cannot fully support sharing and integrating geospatial models. To address this need, we have identified methods for sharing geospatial computational models using Service Oriented Architecture (SOA) techniques and open geospatial standards. The service-oriented model sharing service is accessible using any tools or systems compliant with open geospatial standards, making it possible to utilize vast scientific resources available from around the world to solve highly sophisticated application problems. The methods also allow model services to be empowered by diverse computational devices and technologies, such as portable devices and GRID computing infrastructures. Based on the generic and abstract operations and data structures required for Web Processing Service (WPS) standards, we developed an interactive interface for model sharing to help reduce interoperability problems for model use. Geospatial computational models are shared on model services, where the computational processes provided by models can be accessed through tools and systems compliant with WPS. We developed a platform to help modelers publish individual models in a simplified and efficient way. Finally, we illustrate our technique using wetland hydrological models we developed for the prairie pothole region of North America.
","language":"English","publisher":"Journal of Remote Sensing","usgsCitation":"Feng, M., Liu, S., Euliss, N.H., and Fang, Y., 2009, Distributed geospatial model sharing based on open interoperability standards: Journal of Remote Sensing, v. 13, no. 6, p. 1060-1066.","productDescription":"7 p.","startPage":"1060","endPage":"1066","ipdsId":"IP-014691","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":349530,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"6","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a610cfbe4b06e28e9c25753","contributors":{"authors":[{"text":"Feng, Min","contributorId":75370,"corporation":false,"usgs":true,"family":"Feng","given":"Min","email":"","affiliations":[],"preferred":false,"id":723906,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Shuguang 0000-0002-6027-3479 sliu@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3479","contributorId":147403,"corporation":false,"usgs":true,"family":"Liu","given":"Shuguang","email":"sliu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":723905,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Euliss, Ned H. Jr. ceuliss@usgs.gov","contributorId":2916,"corporation":false,"usgs":true,"family":"Euliss","given":"Ned","suffix":"Jr.","email":"ceuliss@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":false,"id":723904,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fang, Yin","contributorId":200996,"corporation":false,"usgs":false,"family":"Fang","given":"Yin","email":"","affiliations":[],"preferred":false,"id":724033,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70194818,"text":"70194818 - 2009 - Population trends of native Hawaiian forest birds, 1976–2008: the data and statistical analyses","interactions":[],"lastModifiedDate":"2018-01-02T14:17:03","indexId":"70194818","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"seriesTitle":{"id":414,"text":"Technical Report","active":false,"publicationSubtype":{"id":9}},"seriesNumber":"HCSU-TR012","title":"Population trends of native Hawaiian forest birds, 1976–2008: the data and statistical analyses","docAbstract":"The Hawaii Forest Bird Interagency Database Project has produced a centralized database of forest bird survey data collected in Hawai`i since the mid-1970s. The database contains over 1.1 million bird observation records of 90 species from almost 600 surveys on the main Hawaiian Islands—a dataset including nearly all surveys from that period. The primary objective has been to determine the status and trends of native Hawaiian forest birds derived from this comprehensive dataset.
We generated species-specific density estimates from each survey and tested for changes in population densities over the longest possible temporal period. Although this cumulative data set seems enormous and represents the best available information on status of Hawaiian forest birds, detecting meaningful population distribution, density, and trends for forest birds in Hawai`i has been difficult. These population parameters are best derived from long-term, large-scale, standardized monitoring programs. The basis for long-term population monitoring in Hawai`i was established by the Hawaii Forest Bird Survey of 1976-1983 (Scott et al. 1986). Since then, however, only key areas have been resurveyed, primarily to monitor rare species. The majority of surveys since the early 1980s have been conducted by numerous, independent programs, resulting in some inconsistencies in methodology and sampling that in some cases has been intermittent and usually at limited scale (temporally or spatially). Thus, despite the consolidation of data into a centralized database, our understanding of population patterns is rather limited, especially at the regional and landscape scales. To rectify their deficiency, we present a framework to improve the understanding of forest bird trends in Hawai`i through an overarching monitoring design that allocates sampling at appropriate regional and temporal scales.
Despite the limitations of the current monitoring effort, important generalities stand out vividly from the multiplicity of species-specific trends. Overall, in marginal habitats the Hawaiian passerine fauna continues to decline, with populations of most species shrinking in size and distribution. Since the early 1980s, 10 species that were rare at the time may now be extinct, although one, the `Alalā (Corvus hawaiiensis), survives in captivity. Dedicated search effort for the remaining nine species has been inadequate. Of the 22 species remaining, eight have declined, five appear to be stable, two are increasing, and the trend for seven species is unclear. On the bright side, native passerines, including endangered species, appear to be stable or increasing in areas with large tracts of native forest above 1,500 m elevation, even while decreasing in more fragmented or disturbed habitats, particularly at lower elevation. For example, all eight native species resident at Hakalau Forest National Wildlife Refuge have shown stable trends or significant increases in density over the long-term. Thus, native birds are ever more restricted to high-elevation forest and woodland refugia. It is these upland habitats that require sustained and all-out restoration to prevent further extinctions of Hawaiian forest birds.
Coolwater streams, which are intermediate in character between coldwater “trout” streams and more diverse warmwater streams, occur widely in temperate regions but are poorly understood. We used modeled water temperature data and fish assemblage samples from 371 stream sites in Michigan and Wisconsin to define, describe, and map coolwater streams and their fish assemblages. We defined coolwater streams as ones having summer water temperatures suitable for both coldwater and warmwater species and used the observed distributions of the 99 fish species at our sites to identify coolwater thermal boundaries. Coolwater streams had June-through-August mean water temperatures of 17.0–20.5°C, July mean temperatures of 17.5–21.0°C, and maximum daily mean temperatures of 20.7–24.6°C. We delineated two subclasses of coolwater streams: “cold transition” (having July mean water temperatures of 17.5–19.5°C) and “warm transition” (having July mean temperatures of 19.5–21.0°C). Fish assemblages in coolwater streams were variable and lacked diagnostic species but were generally intermediate in species richness and overlapped in composition with coldwater and warmwater streams. In cold-transition streams, coldwater (e.g., salmonids and cottids) and transitional species (e.g., creek chub Semotilus atromaculatus, eastern blacknose dace Rhynichthys atratulus, white sucker Catostomus commersonii, and johnny darter Etheostoma nigrum) were common and warmwater species (e.g., ictalurids and centrarchids) were uncommon; in warm-transition streams warmwater and transitional species were common and coldwater species were uncommon. Coolwater was the most widespread and abundant thermal class in Michigan and Wisconsin, comprising 65% of the combined total stream length in the two states (cold-transition streams being more common than warm-transition ones). Our approach can be used to identify and characterize coolwater streams elsewhere in the temperate region, benefiting many aspects of fisheries management and environmental protection.
","language":"English","publisher":"Taylor & Francis","doi":"10.1577/M08-118.1","usgsCitation":"Lyons, J., Zorn, T., Stewart, J.S., Seelbach, P.W., Wehrly, K., and Wang, L., 2009, Defining and characterizing coolwater streams and their fish assemblages in Michigan and Wisconsin, USA: North American Journal of Fisheries Management, v. 29, no. 4, p. 1130-1151, https://doi.org/10.1577/M08-118.1.","productDescription":"22 p.","startPage":"1130","endPage":"1151","ipdsId":"IP-005975","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":348550,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, 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multidisciplinary effort to assign realistic source parameters to models of volcanic ash-cloud transport and dispersion during eruptions","docAbstract":"During volcanic eruptions, volcanic ash transport and dispersion models (VATDs) are used to forecast the location and movement of ash clouds over hours to days in order to define hazards to aircraft and to communities downwind. Those models use input parameters, called “eruption source parameters”, such as plume height H, mass eruption rate Ṁ, duration D, and the mass fraction m63 of erupted debris finer than about 4ϕ or 63 μm, which can remain in the cloud for many hours or days. Observational constraints on the value of such parameters are frequently unavailable in the first minutes or hours after an eruption is detected. Moreover, observed plume height may change during an eruption, requiring rapid assignment of new parameters. This paper reports on a group effort to improve the accuracy of source parameters used by VATDs in the early hours of an eruption. We do so by first compiling a list of eruptions for which these parameters are well constrained, and then using these data to review and update previously studied parameter relationships. We find that the existing scatter in plots of H versus Ṁ yields an uncertainty within the 50% confidence interval of plus or minus a factor of four in eruption rate for a given plume height. This scatter is not clearly attributable to biases in measurement techniques or to well-recognized processes such as elutriation from pyroclastic flows. Sparse data on total grain-size distribution suggest that the mass fraction of fine debris m63 could vary by nearly two orders of magnitude between small basaltic eruptions (∼ 0.01) and large silicic ones (> 0.5). We classify eleven eruption types; four types each for different sizes of silicic and mafic eruptions; submarine eruptions; “brief” or Vulcanian eruptions; and eruptions that generate co-ignimbrite or co-pyroclastic flow plumes. For each eruption type we assign source parameters. We then assign a characteristic eruption type to each of the world's ∼ 1500 Holocene volcanoes. These eruption types and associated parameters can be used for ash-cloud modeling in the event of an eruption, when no observational constraints on these parameters are available.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2009.01.008","usgsCitation":"Mastin, L.G., Guffanti, M.C., Servranckx, R., Webley, P., Barsotti, S., Dean, K., Durant, A., Ewert, J.W., Neri, A., Rose, W., Schneider, D.J., Siebert, L., Stunder, B., Swanson, G., Tupper, A., Volentik, A., and Waythomas, C.F., 2009, A multidisciplinary effort to assign realistic source parameters to models of volcanic ash-cloud transport and dispersion during eruptions: Journal of Volcanology and Geothermal Research, v. 186, no. 1-2, p. 10-21, https://doi.org/10.1016/j.jvolgeores.2009.01.008.","productDescription":"12 p.","startPage":"10","endPage":"21","ipdsId":"IP-007193","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":347339,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"186","issue":"1-2","publishingServiceCenter":{"id":14,"text":"Menlo Park 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A.","contributorId":6294,"corporation":false,"usgs":false,"family":"Volentik","given":"A.","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":715590,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Waythomas, Christopher F. 0000-0002-3898-272X cwaythomas@usgs.gov","orcid":"https://orcid.org/0000-0002-3898-272X","contributorId":640,"corporation":false,"usgs":true,"family":"Waythomas","given":"Christopher","email":"cwaythomas@usgs.gov","middleInitial":"F.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":715591,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70190417,"text":"70190417 - 2009 - Acquiring marine data in the Canada Basin, Arctic Ocean","interactions":[],"lastModifiedDate":"2025-04-04T13:30:10.249528","indexId":"70190417","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1578,"text":"Eos, Transactions, American Geophysical Union","onlineIssn":"2324-9250","printIssn":"0096-394","active":true,"publicationSubtype":{"id":10}},"title":"Acquiring marine data in the Canada Basin, Arctic Ocean","docAbstract":"This article describes the logistical challenges and initial data sets from geophysical seismic reflection, seismic refraction, and hydrographic surveys in the Canada Basin conducted by scientists with U.S. and Canadian government agencies (Figure 1a) to fulfill the requirements of the United Nations Convention on the Law of the Sea to determine sediment thickness, geological origin, and basin evolution in this unexplored part of the world. Some of these data were collected using a single ship, but the heaviest ice conditions necessitated using two icebreakers, similar to other recent Arctic surveys [e.g., Jokat, 2003].
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/eost2009EO23","usgsCitation":"Hutchinson, D., Jackson, H., Shimeld, J., Chapman, C., Childs, J.R., Funck, T., and Rowland, R., 2009, Acquiring marine data in the Canada Basin, Arctic Ocean: Eos, Transactions, American Geophysical Union, v. 90, no. 23, p. 197-198, https://doi.org/10.1029/eost2009EO23.","productDescription":"2 p.","startPage":"197","endPage":"198","ipdsId":"IP-010812","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":488597,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/eost2009eo23","text":"Publisher Index Page"},{"id":345368,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Arctic Ocean, Canada Basin","volume":"90","issue":"23","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2013-03-21","publicationStatus":"PW","scienceBaseUri":"59a7ced6e4b0fd9b77d092d1","contributors":{"authors":[{"text":"Hutchinson, Deborah 0000-0002-2544-5466 dhutchinson@usgs.gov","orcid":"https://orcid.org/0000-0002-2544-5466","contributorId":174836,"corporation":false,"usgs":true,"family":"Hutchinson","given":"Deborah","email":"dhutchinson@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":709047,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jackson, H.R.","contributorId":196040,"corporation":false,"usgs":false,"family":"Jackson","given":"H.R.","email":"","affiliations":[{"id":36265,"text":"Geological Survey of Canada Atlantic, 1 Challenger Dr. Box 1006 Dartmouth, N.S., B2Y 4A2","active":true,"usgs":false}],"preferred":false,"id":709051,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shimeld, J.W.","contributorId":196041,"corporation":false,"usgs":false,"family":"Shimeld","given":"J.W.","affiliations":[{"id":36265,"text":"Geological Survey of Canada Atlantic, 1 Challenger Dr. Box 1006 Dartmouth, N.S., B2Y 4A2","active":true,"usgs":false}],"preferred":false,"id":709052,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chapman, C.B.","contributorId":196038,"corporation":false,"usgs":false,"family":"Chapman","given":"C.B.","email":"","affiliations":[],"preferred":false,"id":709049,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Childs, Jonathan R. jchilds@usgs.gov","contributorId":3155,"corporation":false,"usgs":true,"family":"Childs","given":"Jonathan","email":"jchilds@usgs.gov","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":709048,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Funck, T.","contributorId":196039,"corporation":false,"usgs":false,"family":"Funck","given":"T.","email":"","affiliations":[],"preferred":false,"id":709050,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rowland, R.W.","contributorId":36153,"corporation":false,"usgs":true,"family":"Rowland","given":"R.W.","email":"","affiliations":[],"preferred":false,"id":709089,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70047290,"text":"70047290 - 2009 - Standardizing electrofishing power for boat electrofishing: chapter 14","interactions":[],"lastModifiedDate":"2022-12-29T15:10:38.350514","indexId":"70047290","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Standardizing electrofishing power for boat electrofishing: chapter 14","docAbstract":"Standardization of electrofishing can help reduced the variability of survey data and potentially reduce injur of fish. Without standardization, differences among collections can be partially attributed to disparities in electrofishing methodology, intensity of the electrical field, and size of the electrical field rather than to disparities in fish abundance, population structure, or fish community composition. Such standardization is critical when electrofishing is used to monitor temporal and spatial changes of fish assemblages in waters with diverse ambient conductivities. In a field study, standardization improved predictability of electrofishing catch rates by about 15% (Burkhardt and Gutreuter 1995). In a laboratory study, standardization of power transfer allowed scientists accurate prediction of control unit settings required to immobilize fish in a wide range of ambient conductivities (Miranda and Dolan 2003). Because electrofishing is an active capture method applied to changing microenvironments that continually distort the electric field and to multiple target species that respond differently to electric fields, complete standardization is not possible with present technology, but standardization of controllable power transferred to fish is advisable.
\nStandardizing boat electrofishing entails achieving an accepted level of collection consistency by managing various brand factors, including (1) the temporal and spatial distribution of sampling effort, (2) boat operation, (3) equipment configuration, (4) characteristics of the waveform and energized field, and (5) power transferred to fish. This chapter focuses exclusively on factor 5:L factors 1-4 have been addressed in earlier chapters. Additionally, while the concepts covered in this chapter address boat electrofishing in general, the power settings discussed were developed from tests with primarily warmwater fish communities. Others (see Chapter 9) recommend lower power settings for communities consisting of primarily coldwater fishes. For reviews of basic concepts of electricity, electrofishing theory and systems, fish behavior relative to diverse waveforms, and injury matter, the reader is referred to Novotny (1990), Reynold (1996), and Snyder (2003).
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Jr. 0000-0002-3558-243X jwlane@usgs.gov","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":189168,"corporation":false,"usgs":true,"family":"Lane","given":"John","suffix":"Jr.","email":"jwlane@usgs.gov","middleInitial":"W.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":false,"id":720307,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Richard D.","contributorId":56406,"corporation":false,"usgs":false,"family":"Miller","given":"Richard","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":720310,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Clemens, Drew","contributorId":199902,"corporation":false,"usgs":false,"family":"Clemens","given":"Drew","email":"","affiliations":[],"preferred":false,"id":720308,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70188019,"text":"70188019 - 2009 - Volumetric visualization of multiple-return LIDAR data: Using voxels","interactions":[],"lastModifiedDate":"2017-05-26T13:45:45","indexId":"70188019","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3052,"text":"Photogrammetric Engineering and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Volumetric visualization of multiple-return LIDAR data: Using voxels","docAbstract":"Elevation data are an important component in the visualization and analysis of geographic information. The creation and display of 3D models representing bare earth, vegetation, and surface structures have become a major focus of light detection and ranging (lidar) remote sensing research in the past few years. Lidar is an active sensor that records the distance, or range, of a laser usually fi red from an airplane, helicopter, or satellite. By converting the millions of 3D lidar returns from a system into bare ground, vegetation, or structural elevation information, extremely accurate, high-resolution elevation models can be derived and produced to visualize and quantify scenes in three dimensions. These data can be used to produce high-resolution bare-earth digital elevation models; quantitative estimates of vegetative features such as canopy height, canopy closure, and biomass; and models of urban areas such as building footprints and 3D city models.
","language":"English","publisher":"ASPRS","usgsCitation":"Stoker, J.M., 2009, Volumetric visualization of multiple-return LIDAR data: Using voxels: Photogrammetric Engineering and Remote Sensing, v. 75, no. 2, p. 109-112.","productDescription":"4 p.","startPage":"109","endPage":"112","ipdsId":"IP-010649","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":341808,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"75","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59293e9ae4b016f7a9407723","contributors":{"authors":[{"text":"Stoker, Jason M. 0000-0003-2455-0931 jstoker@usgs.gov","orcid":"https://orcid.org/0000-0003-2455-0931","contributorId":3021,"corporation":false,"usgs":true,"family":"Stoker","given":"Jason","email":"jstoker@usgs.gov","middleInitial":"M.","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696205,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70035599,"text":"70035599 - 2009 - Genetic differentiation between sympatric and allopatric wintering populations of Snow Geese","interactions":[],"lastModifiedDate":"2012-03-12T17:21:51","indexId":"70035599","displayToPublicDate":"2009-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3784,"text":"Wilson Journal of Ornithology","active":true,"publicationSubtype":{"id":10}},"title":"Genetic differentiation between sympatric and allopatric wintering populations of Snow Geese","docAbstract":"Blackwater National Wildlife Refuge on the Delmarva Peninsula, Maryland, USA has been the wintering area of a small population of Lesser Snow Geese (Chen caerulescens caerulescens; LSGO) since the 1930s. Snow Geese primarily pair in wintering areas and gene flow could be restricted between this and other LSGO wintering populations. Winter pair formation also could facilitate interbreeding with sympatric but morphologically differentiated Greater Snow Geese (C. c. atlantica; GSGO).We sequenced 658 bp of the mitochondrial DNA control region for 68 Snow Geese from East Coast and Louisiana wintering populations to examine the level of genetic differentiation among populations and subspecies. We found no evidence for genetic differentiation between LSGO populations but, consistent with morphological differences, LSGO and GSGO were significantly differentiated. We also found a lack of genetic differentiation between different LSGO morphotypes from Louisiana. We examined available banding data and found the breeding range of Delmarva LSGO overlaps extensively with LSGO that winter in Louisiana, and documented movements between wintering populations. Our results suggest the Delmarva population of LSGO is not a unique population unit apart from Mid-Continent Snow Geese. ?? 2009 by the Wilson Ornithological Society.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Wilson Journal of Ornithology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1676/07-126.1","issn":"15594491","usgsCitation":"Humphries, E., Peters, J., Jonsson, J., Stone, R., Afton, A., and Omland, K., 2009, Genetic differentiation between sympatric and allopatric wintering populations of Snow Geese: Wilson Journal of Ornithology, v. 121, no. 4, p. 730-738, https://doi.org/10.1676/07-126.1.","startPage":"730","endPage":"738","numberOfPages":"9","costCenters":[],"links":[{"id":216213,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1676/07-126.1"},{"id":244068,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"121","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a156de4b0c8380cd54ded","contributors":{"authors":[{"text":"Humphries, E.M.","contributorId":59266,"corporation":false,"usgs":true,"family":"Humphries","given":"E.M.","email":"","affiliations":[],"preferred":false,"id":451404,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peters, J.L.","contributorId":27702,"corporation":false,"usgs":true,"family":"Peters","given":"J.L.","email":"","affiliations":[],"preferred":false,"id":451401,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jonsson, J.E.","contributorId":61623,"corporation":false,"usgs":true,"family":"Jonsson","given":"J.E.","email":"","affiliations":[],"preferred":false,"id":451405,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stone, Rachel L.","contributorId":28825,"corporation":false,"usgs":true,"family":"Stone","given":"Rachel","middleInitial":"L.","affiliations":[],"preferred":false,"id":451402,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Afton, A. 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There is a strong conceptual model of sources, sinks, and pathways of carbon within peatlands, but challenges remain both in understanding the hydrogeology and the linkages between carbon cycling and peat pore water flow. In this chapter, research findings from the glacial Lake Agassiz peatlands are used to develop a conceptual framework for peatland hydrogeology and identify four challenges related to northern peatlands yet to be addressed: (1) develop a better understanding of the extent and net impact of climate-driven groundwater flushing in peatlands; (2) quantify the complexities of heterogeneity on pore water flow and, in particular, reconcile contradictions between peatland hydrogeologic interpretations and isotopic data; (3) understand the hydrogeologic implications of free-phase methane production, entrapment, and release in peatlands; and (4) quantify the impact of arctic and subarctic warming on peatland hydrogeology and its linkage to carbon cycling.
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\nUntil now, summaries of freshwater fisheries data collected in a standard manner across North America have not been available. Length at age, length-weight relationships, and other types of detailed summary data are available in Carlander (1696-1977). However, a variety of sampling methods were used to collect these data, allowing successful comparisons among length at age and length-weight data but making it difficult or impossible to compare size distribution and catch per unit effort (CPUE) data among populations.
\nThis chapter provides North American and ecoregion (area that contains a geographically distinct assemblage of natural communities and share similar environmental conditions) averages and distributions of several commonly used sampling techniques described in this book. Biologists using the standardized sampling techniques described in this book will be able to compare their data sets to the summaries provided in the tables that follow to determine if the data from their sampled populations of fish are average, below average, or above average for a given index in their ecoregion or across North America.
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