Bottom sediments have been regarded as memory banks for contaminant inputs to urban waterways. Bottom sediments accumulate by the addition of particles that enter the waterway from many sources (U.S. National Research Council, 1989). Sediments include solid contaminants, as well as contaminants from the water column that are adsorbed on organic matter or soil (rock) particles. Sediments from Boston Harbor and adjacent parts of Massachusetts Bay are now among the most intensively studied in the Nation in terms of chemical composition.
Scientists at the U.S. Geological Survey (USGS), Woods Hole, Mass., undertook a pioneering effort to assemble a database from all available sources of information on chemicals in sediments of the Boston Harbor study area. The database was created to help understand the distribution of sediment contaminants and their sources, transport, and other processes and to support environmental management. The work involved collaboration with the U.S. Environmental Protection Agency (USEPA), the U.S. Army Corps of Engineers (USACOE), the Massachusetts Water Resources Authority, and other organizations. More than 100,000 sediment measurements from more than 3,000 samples were gleaned from 1,500 references. New approaches were developed to scientifically edit and validate data from heterogeneous sources. The compiled data included inorganic and organic chemical information and physical parameters like sediment texture (grain size), as well as documentation to minimize a userđs need to track down hard-to-find reports.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/fs07899","usgsCitation":"Water Resources Division, U.S. Geological Survey, 1999, Contaminated-sediment database development and assessment in Boston Harbor: U.S. Geological Survey Fact Sheet 078-99, HTML document, https://doi.org/10.3133/fs07899.","productDescription":"HTML document","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":120746,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_078_99.jpg"},{"id":848,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/factsheet/fs78-99/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Massachusetts","city":"Boston","otherGeospatial":"Boston Harbor","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.11278533935547,\n 42.262319595341644\n ],\n [\n -70.90953826904297,\n 42.262319595341644\n ],\n [\n -70.90953826904297,\n 42.41306487420867\n ],\n [\n -71.11278533935547,\n 42.41306487420867\n ],\n [\n -71.11278533935547,\n 42.262319595341644\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b06e4b07f02db69a040","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":528720,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":22937,"text":"ofr98655 - 1999 - Selected ground-water-quality data of the Lockport Dolomite in Darke, Miami, Montgomery, and Preble Counties, Ohio","interactions":[],"lastModifiedDate":"2012-02-02T00:07:58","indexId":"ofr98655","displayToPublicDate":"1999-07-01T00:00:00","publicationYear":"1999","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"98-655","title":"Selected ground-water-quality data of the Lockport Dolomite in Darke, Miami, Montgomery, and Preble Counties, Ohio","docAbstract":"In 1998, 25 samples of ground water from the Lockport Dolomite in western Ohio were analyzed for major ions, trace elements, and arsenic. Samples were collected from residential wells in Darke, Miami, Montgomery, and Preble Counties. The water sampled was untreated, except perhaps for water from one well. In general, samples from the northern part of the study area had the highest concentrations of common constituents such as calcium, magnesium, potassium, sulfate, boron, and strontium. Iron and strontium concentrations were generally high throughout the study area, with median concentrations of 4,500 ?g/L (micrograms per liter) and 1,500 ?g/L, respectively. Arsenic concentrations, which ranged from less than 1 ?g/L to 29 ?g/L, did not exceed the drink ing-water standard of 50 ?g/L.","language":"ENGLISH","publisher":"U.S. Dept. of the Interior, U.S. Geological Survey ;\r\nBranch of Information Services [distributor],","doi":"10.3133/ofr98655","issn":"0094-9140","usgsCitation":"Dumouchelle, D., 1999, Selected ground-water-quality data of the Lockport Dolomite in Darke, Miami, Montgomery, and Preble Counties, Ohio: U.S. Geological Survey Open-File Report 98-655, iii, 13 p. :map ;28 cm., https://doi.org/10.3133/ofr98655.","productDescription":"iii, 13 p. :map ;28 cm.","costCenters":[],"links":[{"id":155197,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/1998/0655/report-thumb.jpg"},{"id":52338,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/1998/0655/report.pdf","linkFileType":{"id":1,"text":"pdf"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49e5e4b07f02db5e7068","contributors":{"authors":[{"text":"Dumouchelle, D.H.","contributorId":83144,"corporation":false,"usgs":true,"family":"Dumouchelle","given":"D.H.","affiliations":[],"preferred":false,"id":189162,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70206469,"text":"70206469 - 1999 - The relationship between species density and community biomass in grazed and ungrazed coastal meadows","interactions":[],"lastModifiedDate":"2019-11-06T11:05:42","indexId":"70206469","displayToPublicDate":"1999-06-30T10:59:14","publicationYear":"1999","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2939,"text":"Oikos","active":true,"publicationSubtype":{"id":10}},"title":"The relationship between species density and community biomass in grazed and ungrazed coastal meadows","docAbstract":"Previous studies have indicated that the relationship between community biomass and species density can be represented by a multivariate model in which abiotic variables influence species density both through effects on biomass and through effects on the species pool. In this paper, we use data from grazed and ungrazed coastal meadows in Finland to evaluate and extend this general conceptual model of the factors controlling species density. Structural equation analysis was used to evaluate a model for all meadows and then to perform a multigroup analysis to determine how grazed and ungrazed meadows differ. By itself, biomass could explain only 12% of the variation in species density while the multivariate model was able to explain 47% using five types of predictor variables: site, soil, flooding, grazing, and biomass. Analyses found that flooding explained the greatest amount of variability in species density, primarily through negative effects on the species pool. Grazing was also found to have a strong effect on species density and results suggest that its negative influence may be largely through reductions in the species pool in grazed meadows. The most important difference found between grazed and ungrazed meadows was that species density had a strong negative relationship to biomass in the ungrazed meadows but no significant relationship in the grazed ones. Thus, it appears that the influence of competition on species density was much greater in ungrazed meadows compared to grazed ones.
","language":"English","publisher":"Wiley","doi":"10.2307/3546689","usgsCitation":"Grace, J.B., and Jutila, H., 1999, The relationship between species density and community biomass in grazed and ungrazed coastal meadows: Oikos, v. 85, no. 3, p. 398-408, https://doi.org/10.2307/3546689.","productDescription":"11 p.","startPage":"398","endPage":"408","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":368967,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Finland","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[28.59193,69.06478],[28.44594,68.36461],[29.97743,67.6983],[29.05459,66.94429],[30.21765,65.80598],[29.54443,64.94867],[30.44468,64.20445],[30.03587,63.55281],[31.51609,62.86769],[31.13999,62.35769],[30.21111,61.78003],[28.07,60.50352],[26.25517,60.42396],[24.49662,60.05732],[22.86969,59.84637],[22.29076,60.39192],[21.32224,60.72017],[21.54487,61.70533],[21.05921,62.60739],[21.53603,63.18974],[22.44274,63.81781],[24.73051,64.90234],[25.39807,65.11143],[25.29404,65.53435],[23.90338,66.00693],[23.56588,66.39605],[23.53947,67.93601],[21.97853,68.61685],[20.64559,69.10625],[21.24494,69.37044],[22.35624,68.84174],[23.66205,68.89125],[24.73568,68.64956],[25.68921,69.09211],[26.17962,69.8253],[27.73229,70.16419],[29.01557,69.76649],[28.59193,69.06478]]]},\"properties\":{\"name\":\"Finland\"}}]}","volume":"85","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Grace, James B. 0000-0001-6374-4726 gracej@usgs.gov","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":884,"corporation":false,"usgs":true,"family":"Grace","given":"James","email":"gracej@usgs.gov","middleInitial":"B.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":774750,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jutila, H.","contributorId":42782,"corporation":false,"usgs":true,"family":"Jutila","given":"H.","email":"","affiliations":[],"preferred":false,"id":774751,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70021560,"text":"70021560 - 1999 - Epizootiology of viral hemorrhagic septicemia virus in Pacific herring from the spawn-on-kelp fishery in Prince William Sound, Alaska, USA","interactions":[],"lastModifiedDate":"2016-02-09T14:49:27","indexId":"70021560","displayToPublicDate":"1999-06-23T00:00:00","publicationYear":"1999","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1396,"text":"Diseases of Aquatic Organisms","active":true,"publicationSubtype":{"id":10}},"title":"Epizootiology of viral hemorrhagic septicemia virus in Pacific herring from the spawn-on-kelp fishery in Prince William Sound, Alaska, USA","docAbstract":"Both the prevalence and tissue titer of viral hemorrhagic septicemia virus (VHSV) increased in Pacific herring Clupea pallasi following their introduction into net pens (pounds) used in the closed pound spawn-on-kelp (SOK) fishery in Prince William Sound, Alaska. VHSV was also found in water samples from inside and outside the SOK pounds after herring had been confined for several days; however, water samples taken near wild free-ranging, spawning herring either failed to test positive or tested weakly positive for virus. Little or no virus was found in tissue samples from free-ranging, spawning herring captured from the vicinity of the pounds, nor did the prevalence of VHSV increase following spawning as it did in impounded herring. The data indicated that increased prevalences of VHSV were correlated with confinement of herring for the closed pound SOK fishery and that infection was spread within the pounds through waterborne exposure to virus particles originating from impounded fish. In addition, pounds containing predominantly young fish had higher prevalences of VHSV, suggesting that older fish may be partially immune, perhaps as a result of previous infection with the virus. Operation of SOK pounds during spawning seasons in which young herring predominate may amplify the disease and possibly exacerbate the population fluctuations observed in wild herring stocks.
","language":"English","publisher":"Inter-Research Science Center","publisherLocation":"Oldendorf/Luhe, Germany","doi":"10.3354/dao037023","issn":"01775103","usgsCitation":"Hershberger, P., Kocan, R.M., Elder, N., Meyers, T., and Winton, J., 1999, Epizootiology of viral hemorrhagic septicemia virus in Pacific herring from the spawn-on-kelp fishery in Prince William Sound, Alaska, USA: Diseases of Aquatic Organisms, v. 37, p. 23-31, https://doi.org/10.3354/dao037023.","productDescription":"9 p.","startPage":"23","endPage":"31","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":479418,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/dao037023","text":"Publisher Index Page"},{"id":229069,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a0a20e4b0c8380cd521ef","contributors":{"authors":[{"text":"Hershberger, P.K. 0000-0002-2261-7760","orcid":"https://orcid.org/0000-0002-2261-7760","contributorId":58818,"corporation":false,"usgs":true,"family":"Hershberger","given":"P.K.","affiliations":[],"preferred":false,"id":390300,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kocan, R. M.","contributorId":41783,"corporation":false,"usgs":true,"family":"Kocan","given":"R.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":390298,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elder, N.E.","contributorId":57626,"corporation":false,"usgs":true,"family":"Elder","given":"N.E.","email":"","affiliations":[],"preferred":false,"id":390299,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Meyers, T.R.","contributorId":108283,"corporation":false,"usgs":true,"family":"Meyers","given":"T.R.","email":"","affiliations":[],"preferred":false,"id":390302,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Winton, J. R. 0000-0002-3505-5509","orcid":"https://orcid.org/0000-0002-3505-5509","contributorId":82441,"corporation":false,"usgs":true,"family":"Winton","given":"J. R.","affiliations":[],"preferred":false,"id":390301,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":5223857,"text":"5223857 - 1999 - Monitoring survival rates of Swainson's Thrush Catharus ustulatus at multiple spatial scales","interactions":[],"lastModifiedDate":"2020-06-19T20:03:02.36856","indexId":"5223857","displayToPublicDate":"1999-06-16T12:18:53","publicationYear":"1999","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1052,"text":"Bird Study","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring survival rates of Swainson's Thrush Catharus ustulatus at multiple spatial scales","docAbstract":"We estimated survival rates of Swainson's Thrush, a common, neotropical, migratory landbird, at multiple spatial scales, using data collected in the western USA from the Monitoring Avian Productivity and Survivorship Programme. We evaluated statistical power to detect spatially heterogeneous survival rates and exponentially declining survival rates among spatial scales with simulated populations parameterized from results of the Swainson's Thrush analyses. Models describing survival rates as constant across large spatial scales did not fit the data. The model we chose as most appropriate to describe survival rates of Swainson's Thrush allowed survival rates to vary among Physiographic Provinces, included a separate parameter for the probability that a newly captured bird is a resident individual in the study population, and constrained capture probability to be constant across all stations. Estimated annual survival rates under this model varied from 0.42 to 0.75 among Provinces. The coefficient of variation of survival estimates ranged from 5.8 to 20% among Physiographic Provinces. Statistical power to detect exponentially declining trends was fairly low for small spatial scales, although large annual declines (3% of previous year's rate) were likely to be detected when monitoring was conducted for long periods of time (e.g. 20 years). Although our simulations and field results are based on only four years of data from a limited number and distribution of stations, it is likely that they illustrate genuine difficulties inherent to broadscale efforts to monitor survival rates of territorial landbirds. In particular, our results suggest that more attention needs to be paid to sampling schemes of monitoring programmes, particularly regarding the trade-off between precision and potential bias of parameter estimates at varying spatial scales.
","language":"English","publisher":"Taylor & Franicis","doi":"10.1080/00063659909477246","usgsCitation":"Rosenberg, D., DeSante, D., McKelvey, K., and Hines, J.E., 1999, Monitoring survival rates of Swainson's Thrush Catharus ustulatus at multiple spatial scales: Bird Study, v. 46, no. sup1, p. S198-S208, https://doi.org/10.1080/00063659909477246.","productDescription":"11 p,","startPage":"S198","endPage":"S208","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":479421,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/00063659909477246","text":"Publisher Index Page"},{"id":202274,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"46","issue":"sup1","noUsgsAuthors":false,"publicationDate":"2009-06-25","publicationStatus":"PW","scienceBaseUri":"4f4e4b01e4b07f02db698540","contributors":{"authors":[{"text":"Rosenberg, D.K.","contributorId":31505,"corporation":false,"usgs":true,"family":"Rosenberg","given":"D.K.","email":"","affiliations":[],"preferred":false,"id":339730,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeSante, D.F.","contributorId":70514,"corporation":false,"usgs":true,"family":"DeSante","given":"D.F.","affiliations":[],"preferred":false,"id":339732,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McKelvey, K.S.","contributorId":106237,"corporation":false,"usgs":true,"family":"McKelvey","given":"K.S.","email":"","affiliations":[],"preferred":false,"id":339733,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hines, James E. 0000-0001-5478-7230 jhines@usgs.gov","orcid":"https://orcid.org/0000-0001-5478-7230","contributorId":146530,"corporation":false,"usgs":true,"family":"Hines","given":"James","email":"jhines@usgs.gov","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":339731,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70209413,"text":"70209413 - 1999 - Historical trends in salinity and substrate in central and northern Florida Bay: A Paleoecological Reconstruction using modern analogue data","interactions":[],"lastModifiedDate":"2020-04-04T16:52:53.215409","indexId":"70209413","displayToPublicDate":"1999-06-04T11:51:00","publicationYear":"1999","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1583,"text":"Estuaries","active":true,"publicationSubtype":{"id":10}},"title":"Historical trends in salinity and substrate in central and northern Florida Bay: A Paleoecological Reconstruction using modern analogue data","docAbstract":"Understanding the natural spatial and temporal variability that exists within an ecosystem is a critical component of efforts to restore systems to their natural state. Analysis of benthic foraminifers and molluscs from modern monitoring sites within Florida Bay allows us to determine what environmental parameters control spatial and temporal variability of their assemblages. Faunal assemblages associated with specific environmental parameters, including salinity and substrate, serve as proxies for an interpretation of paleoecologic data. The faunal record preserved in two shallow (<2 m) cores in central Florida Bay (Russell Bank and Bob Allen Bank) provides a record of historical trends in environmental parameters for those sites. Analysis of these two cores has revealed two distinct patterns of salinity change at these sites: 1) a long-term trend of slightly increasing average salinity; and 2) a relatively rapid change to salinity fluctuations of greater frequency and amplitude, beginning around the turn of the century and becoming most pronounced after 1940. The degree of variability in substrate types at each locality limits interpretations of substrate trends to specific sites. A common sequence of change is present in the Russell Bank and Bob Allen Bank cores: from mixed grass and bare-sediment indicators at the bottom of the cores, to bare-sediment dwellers in the center, to a dominance of vegetative-cover indicators at the top of the cores. Changes in interpreted salinity patterns around the turn of the century are consistent with the timing of the construction of the Flagler Railroad from 1905 to 1912, and the Tamiami Trail and the canal and levee systems between 1915 and 1928. Beginning around 1940, the changes in the frequency and amplitude of salinity fluctuations may be related to changes in water management practices, meteorologic events (frequent hurricanes coupled with severe droughts in 1943 and 1944), or a combination of factors. The correspondence of these changes in Florida Bay with changes in the terrestrial Everglades suggests factors affecting the entire ecosystem are responsible for the salinity and substrate patterns seen in Florida Bay.
The geology of the Payette National Forest and vicinity, Idaho (Fig. 1), was mapped and compiled by Karen Lund between 1992 and 1996. The geologic data for the digital map are from original mapping as well as compilation by Lund of numerous sources of published and unpublished geologic maps that are cited in the section 'Bibliography of Geologic Map Sources.' The geology was compiled onto 1:100,000-scale topographic base maps for input into a geographic information system (GIS). The digital geologic map database can be queried in many ways to produce a variety of geologic maps. Digital base map data files are not included: they may be obtained from a variety of commercial and government sources. This database is not meant to be used or displayed at any scale larger than 1:100,000 (e.g., 1:62,500 or 1:24,000). This open-file report describes the geologic units and the methods used to convert the geologic map data into a digital format and documents the file structures. We wish to thank Gregory N. Green of the U.S. Geological Survey for reviewing the digital GIS files.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Denver, CO","doi":"10.3133/ofr98219B","issn":"0566-8174","usgsCitation":"Lund, K., Derkey, P.D., Brandt, T.R., and Oblad, J., 1999, Digital geologic map database of the Payette National Forest and vicinity, Idaho: U.S. Geological Survey Open-File Report 98-219, 45 p., https://doi.org/10.3133/ofr98219B.","productDescription":"45 p.","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":51250,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/1998/0219b/report.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":1176,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/1998/ofr-98-0219-b/","linkFileType":{"id":5,"text":"html"}},{"id":153709,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/1998/0219b/report-thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Payette National Forest and vicinity","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.57592773437499,\n 44.34742225636393\n ],\n [\n -114.85107421875,\n 44.34742225636393\n ],\n [\n -114.85107421875,\n 45.49094569262732\n ],\n [\n -116.57592773437499,\n 45.49094569262732\n ],\n [\n -116.57592773437499,\n 44.34742225636393\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a9ae4b07f02db65d4a4","contributors":{"authors":[{"text":"Lund, Karen 0000-0002-4249-3582 klund@usgs.gov","orcid":"https://orcid.org/0000-0002-4249-3582","contributorId":1235,"corporation":false,"usgs":true,"family":"Lund","given":"Karen","email":"klund@usgs.gov","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":185464,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Derkey, P. D.","contributorId":55035,"corporation":false,"usgs":true,"family":"Derkey","given":"P.","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":185465,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brandt, T. R.","contributorId":77553,"corporation":false,"usgs":true,"family":"Brandt","given":"T.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":185467,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oblad, J.R.","contributorId":59473,"corporation":false,"usgs":true,"family":"Oblad","given":"J.R.","affiliations":[],"preferred":false,"id":185466,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":3216,"text":"wsp2354B - 1999 - Surface-water-quality assessment of the Yakima River basin, Washington. Distribution of pesticides and other organic compounds in water, sediment, and aquatic biota, 1987-91: With a section on dissolved organic carbon in the Yakima River basin","interactions":[],"lastModifiedDate":"2022-12-06T21:47:03.442364","indexId":"wsp2354B","displayToPublicDate":"1999-06-01T00:00:00","publicationYear":"1999","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":341,"text":"Water Supply Paper","code":"WSP","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"2354","chapter":"B","title":"Surface-water-quality assessment of the Yakima River basin, Washington. Distribution of pesticides and other organic compounds in water, sediment, and aquatic biota, 1987-91: With a section on dissolved organic carbon in the Yakima River basin","docAbstract":"During 1987-91, chemical data were collected for pesticides and other organic compounds in surface water, streambed sediment, suspended sediment, agricultural soil, and aquatic biota to determine the occurrence, distribution, transport, and fate of organic compounds in the Yakima River basin in Washington. The report describes the chemical and physical properties of the compounds most frequently detected in the water column; organochlorine compounds including DDT, organophosphorus compounds, thiocarbamate and sulfite compounds, acetamide and triazine compounds, and chlorophenoxy-acetic acid and benzoic compounds. Concentrations are evaluated relative to chronic-toxicity water quality criteria and guidelines for the protection of human health and freshwater aquatic life.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/wsp2354B","usgsCitation":"Rinella, J.F., McKenzie, S.W., Crawford, J.K., Foreman, W., Fuhrer, G.J., Morace, J.L., and Aiken, G.R., 1999, Surface-water-quality assessment of the Yakima River basin, Washington. Distribution of pesticides and other organic compounds in water, sediment, and aquatic biota, 1987-91: With a section on dissolved organic carbon in the Yakima River basin: U.S. Geological Survey Water Supply Paper 2354, x, 180 p., https://doi.org/10.3133/wsp2354B.","productDescription":"x, 180 p.","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":30208,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/wsp/2354b/report.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":138935,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/wsp/2354b/report-thumb.jpg"},{"id":410123,"rank":2,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_19291.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Washington","otherGeospatial":"Yakima River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.493,\n 47.5833\n ],\n [\n -121.493,\n 46\n ],\n [\n -119.217,\n 46\n ],\n [\n -119.217,\n 47.5833\n ],\n [\n -121.493,\n 47.5833\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ae5e4b07f02db68a4ae","contributors":{"authors":[{"text":"Rinella, Joseph F. jrinella@usgs.gov","contributorId":1371,"corporation":false,"usgs":true,"family":"Rinella","given":"Joseph","email":"jrinella@usgs.gov","middleInitial":"F.","affiliations":[],"preferred":true,"id":146452,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McKenzie, Stuart W.","contributorId":27841,"corporation":false,"usgs":true,"family":"McKenzie","given":"Stuart","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":146454,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crawford, J. 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Kubat Government #1 well, San Juan County, Utah","interactions":[],"lastModifiedDate":"2026-04-24T16:16:28.723668","indexId":"ofr98591","displayToPublicDate":"1999-06-01T00:00:00","publicationYear":"1999","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"98-591","title":"Non-zero offset vertical seismic profile data recorded using a downhole marine airgun source and vertical- and horizontal-component surface geophones; Edward J. Kubat Government #1 well, San Juan County, Utah","docAbstract":"No abstract available.
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Kubat Government #1 well, San Juan County, Utah: U.S. Geological Survey Open-File Report 98-591, 1 computer optical disc :ill. ;4 3/4 in. in plastic box 13 x 15 x 1 cm., https://doi.org/10.3133/ofr98591.","productDescription":"1 CD-ROM","costCenters":[],"links":[{"id":503520,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/1998/0591/ofr98591.zip","text":"CD-ROM","linkFileType":{"id":6,"text":"zip"}},{"id":156669,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"}],"country":"United States","state":"Utah","county":"San Juan County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"id\":\"47\",\"properties\":{\"name\":\"Utah\",\"nation\":\"USA 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J. J.","contributorId":54588,"corporation":false,"usgs":true,"family":"Miller","given":"J.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":190922,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lee, Myung W.","contributorId":84358,"corporation":false,"usgs":true,"family":"Lee","given":"Myung","middleInitial":"W.","affiliations":[],"preferred":false,"id":190923,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Balch, A. H.","contributorId":104892,"corporation":false,"usgs":true,"family":"Balch","given":"A.","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":190924,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":32194,"text":"ofr997B - 1999 - An interpretation of the 1997 airborne electromagnetic (AEM) survey, Fort Huachuca vicinity, Cochise County, Arizona","interactions":[],"lastModifiedDate":"2023-12-11T21:27:44.152037","indexId":"ofr997B","displayToPublicDate":"1999-06-01T00:00:00","publicationYear":"1999","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"99-7","chapter":"B","title":"An interpretation of the 1997 airborne electromagnetic (AEM) survey, Fort Huachuca vicinity, Cochise County, Arizona","docAbstract":"In March of 1997, an airborne electromagnetic (AEM) survey of the Fort Huachuca Military Reservation and immediate surrounds was conducted. This survey was sponsored by the U.S. Army and contracted through the Geologic Division of the U.S. Geological Survey (USGS). Data were gathered by Geoterrex-Dighem Ltd. of Ottawa, Canada. The survey aircraft is surrounded by a coil through which a large current pulse is passed. This pulse induces currents in the Earth which are recorded by a set of three mutually perpendicular coils towed in a \"bird\" about 100 m behind and below the aircraft. The bird also records the Earth's magnetic field. The system samples the Earth response to the electromagnetic pulse about every 16 m along the aircraft flight path. For this survey, the bulk of the flightpaths were spaced about 400 m apart and oriented in a northeast-southwest direction extending from bedrock over the Huachuca Mountains to bedrock over the Tombstone Hills. A preliminary report on the unprocessed data collected in the field was delivered to the U.S. Army by USGS in July 1997 (USGS Open-File Report 97–457). The final data were delivered in March, 1998 by the contractor to USGS and thence to the U.S. Army. The present report represents the final interpretive report from USGS.
The objectives of the survey were to: 1) define the structure of the San Pedro basin in the Sierra Vista-Fort Huachuca-Huachuca City area, including the depth and shape of the basin, and to delineate large faults that may be active within the basin fill and therefore important in the hydrologic regime; 2) define near surface and subsurface areas that contain a large volume fraction of silt and clay in the basin fill and which both reduce the volume of available storage for water and reduce the permeability of the aquifer; and 3) to evaluate the use of the time domain electromagnetic method in the southwest desert setting as a means of mapping depth to water.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr997B","usgsCitation":"Bultman, M.W., Gettings, M.E., and Wynn, J., 1999, An interpretation of the 1997 airborne electromagnetic (AEM) survey, Fort Huachuca vicinity, Cochise County, Arizona: U.S. Geological Survey Open-File Report 99-7, Executive Summary; Introduction; Chapter 1; Chapter 2; Chapter 3; Appendix 1; Appendix 2, https://doi.org/10.3133/ofr997B.","productDescription":"Executive Summary; Introduction; Chapter 1; Chapter 2; Chapter 3; Appendix 1; Appendix 2","temporalStart":"1997-01-01","temporalEnd":"1997-12-31","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":423388,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_16676.htm","linkFileType":{"id":5,"text":"html"}},{"id":3150,"rank":9,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/1999/0007-b/","linkFileType":{"id":5,"text":"html"}},{"id":284860,"rank":8,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/1999/0007-b/es.html"},{"id":284861,"rank":7,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/1999/0007-b/intro.html"},{"id":284863,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/1999/0007-b/wynn/ch2.html"},{"id":284864,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/1999/0007-b/bultman/ch3.html"},{"id":284865,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/1999/0007-b/wells.txt"},{"id":284866,"rank":2,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/1999/0007-b/data.zip"},{"id":164384,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr997B.jpg"},{"id":284862,"rank":6,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/1999/0007-b/gettings/ch1.html"}],"country":"United States","state":"Arizona","county":"Cochise County","otherGeospatial":"Fort Huachuca","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -110.5,31.333333 ], [ -110.5,31.833333 ], [ -110.0,31.833333 ], [ -110.0,31.333333 ], [ -110.5,31.333333 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd4c9be4b0b290850f1157","contributors":{"authors":[{"text":"Bultman, Mark W. 0000-0001-8352-101X mbultman@usgs.gov","orcid":"https://orcid.org/0000-0001-8352-101X","contributorId":3348,"corporation":false,"usgs":true,"family":"Bultman","given":"Mark","email":"mbultman@usgs.gov","middleInitial":"W.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":207934,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gettings, Mark E. 0000-0002-2910-2321 mgetting@usgs.gov","orcid":"https://orcid.org/0000-0002-2910-2321","contributorId":602,"corporation":false,"usgs":true,"family":"Gettings","given":"Mark","email":"mgetting@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":207932,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wynn, Jeff 0000-0002-8102-3882 jwynn@usgs.gov","orcid":"https://orcid.org/0000-0002-8102-3882","contributorId":2803,"corporation":false,"usgs":true,"family":"Wynn","given":"Jeff","email":"jwynn@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":207933,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":23286,"text":"ofr98564 - 1999 - Documentation for HYDMOD; a program for extracting and processing time-series data from the U.S. Geological Survey's modular three-dimensional finite-difference ground-water flow model","interactions":[],"lastModifiedDate":"2012-02-02T00:08:03","indexId":"ofr98564","displayToPublicDate":"1999-06-01T00:00:00","publicationYear":"1999","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"98-564","title":"Documentation for HYDMOD; a program for extracting and processing time-series data from the U.S. Geological Survey's modular three-dimensional finite-difference ground-water flow model","docAbstract":"This report presents a FORTRAN computer program that generates simulated time-series data as output from the U.S. Geological Survey Modular Finite-Difference Ground-Water Flow Model at user-specified point locations or a collection of points that compose a profile through the modeled region. The program can save time-series data at user-specified locations for simulated water levels, drawdown, critical head, compaction, subsidence, streamflow, streamflow stage, and streamflow leakage. A set of locations also can be specified to create time-series profiles through the model. 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\"}}]}","edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4aa9e4b07f02db667ed8","contributors":{"editors":[{"text":"Breed, Carol S.","contributorId":100904,"corporation":false,"usgs":true,"family":"Breed","given":"Carol","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":727916,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Reheis, Marith C. 0000-0002-8359-323X mreheis@usgs.gov","orcid":"https://orcid.org/0000-0002-8359-323X","contributorId":1196,"corporation":false,"usgs":true,"family":"Reheis","given":"Marith","email":"mreheis@usgs.gov","middleInitial":"C.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":727917,"contributorType":{"id":2,"text":"Editors"},"rank":2}]}} ,{"id":32146,"text":"ofr98224D - 1999 - Map showing the potential for mineral deposits associated with Precambrian mafic and ultramafic rocks in the Blacktail and Henrys Lake Mountains and the Greenhorn and Ruby Ranges of southwestern Montana","interactions":[],"lastModifiedDate":"2021-09-13T19:31:17.233821","indexId":"ofr98224D","displayToPublicDate":"1999-05-01T00:00:00","publicationYear":"1999","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"98-224","chapter":"D","title":"Map showing the potential for mineral deposits associated with Precambrian mafic and ultramafic rocks in the Blacktail and Henrys Lake Mountains and the Greenhorn and Ruby Ranges of southwestern Montana","docAbstract":"In response to requests from the Bureau of Land Management (BLM) and the U.S. Forest Service (USFS), the U.S. Geological Survey (USGS) conducted a mineral resource assessment in the Dillon BLM Resource Area in Beaverhead and Madison Counties, southwestern Montana. These agencies use mineral resource data in creating and updating land-use management plans for federal lands for the reasonably foreseeable future. Mineral resources that have not been developed in the past may be developed in the future, based on changing commodity demands and market conditions. Therefore, federal land managers need geologic information on known mineral occurrences as well as on areas that are permissive for the occurrence of undiscovered mineral resources. This map was prepared to provide this type of geologic information for mineral deposits that can be associated with ultramafic rocks. Areas of exposed Precambrian ultramafic rocks are labeled with uppercase letters (A-F). Sources of geologic maps used to compile this map are shown on the smaller index map (\"Index to Geologic Mapping\"); lowercase letters (a-m) on the index map are keyed to the reference list.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr98224D","usgsCitation":"Hammarstrom, J.M., Van Gosen, B.S., Carlson, R.R., and Kulik, D.M., 1999, Map showing the potential for mineral deposits associated with Precambrian mafic and ultramafic rocks in the Blacktail and Henrys Lake Mountains and the Greenhorn and Ruby Ranges of southwestern Montana: U.S. Geological Survey Open-File Report 98-224, 1 Plate: 44.00 × 35.54 inches, https://doi.org/10.3133/ofr98224D.","productDescription":"1 Plate: 44.00 × 35.54 inches","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":164367,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":3106,"rank":300,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/1998/ofr-98-0224-d/98-224d.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":389170,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_22996.htm"}],"scale":"250000","country":"United States","state":"Montana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.0,\n 44.5\n ],\n [\n -111.25,\n 44.5\n ],\n [\n -111.25,\n 45.5\n ],\n [\n -113.0,\n 45.5\n ],\n [\n -113.0,\n 44.5\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e47a3e4b07f02db4963a7","contributors":{"authors":[{"text":"Hammarstrom, Jane M. 0000-0003-2742-3460 jhammars@usgs.gov","orcid":"https://orcid.org/0000-0003-2742-3460","contributorId":1226,"corporation":false,"usgs":true,"family":"Hammarstrom","given":"Jane","email":"jhammars@usgs.gov","middleInitial":"M.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":207833,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Gosen, Bradley S. 0000-0003-4214-3811 bvangose@usgs.gov","orcid":"https://orcid.org/0000-0003-4214-3811","contributorId":1174,"corporation":false,"usgs":true,"family":"Van Gosen","given":"Bradley","email":"bvangose@usgs.gov","middleInitial":"S.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":207832,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carlson, Robert R.","contributorId":71944,"corporation":false,"usgs":true,"family":"Carlson","given":"Robert","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":207834,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kulik, Dolores M.","contributorId":83091,"corporation":false,"usgs":true,"family":"Kulik","given":"Dolores","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":207835,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70021668,"text":"70021668 - 1999 - Field test of two energetic models for yellow perch","interactions":[],"lastModifiedDate":"2026-03-19T17:15:43.184943","indexId":"70021668","displayToPublicDate":"1999-05-01T00:00:00","publicationYear":"1999","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Field test of two energetic models for yellow perch","docAbstract":"Field data from a population of yellow perch Perca flavescens in Saginaw Bay, Lake Huron, were used to evaluate the ability of two energetic models to predict consumption by yellow perch. Field estimates of daily ration for age‐1–4 fish during May through October 1987 and 1988 were compared with independent predictions made by the Wisconsin energetic model and an energetic model developed by Karås and Thoresson. Predictions of daily ration using the Wisconsin model were lower than daily rations estimated from field data for all ages, primarily due to poor model–field agreement at temperatures above 22°C. This caused estimates of cumulative consumption from the Wisconsin model to be 25–50% lower than field estimates. Predictions of daily ration by the Karås–Thoresson model agreed with field estimates over a temperature range of 10–26°C for age‐1–3 yellow perch but not for older fish. Despite improvement, model predictions of cumulative consumption were 2–35% lower than field estimates. Although these tests of predicted and estimated rations may provide insight into which model produced more accurate results, it must be emphasized that field measures of daily ration are also estimates and may be in error, particularly at temperatures above 22°C where gastric evacuation rates were estimated. The Karås–Thoresson modification of the Wisconsin energetic model produced better fits to field ration data and is recommended for model applications.
","language":"English","publisher":"American Fisheries Society","doi":"10.1577/1548-8659(1999)128<0414:FTOTEM>2.0.CO;2","issn":"00028487","usgsCitation":"Schaeffer, J., Haas, R., Diana, J., and Breck, J., 1999, Field test of two energetic models for yellow perch: Transactions of the American Fisheries Society, v. 128, no. 3, p. 414-435, https://doi.org/10.1577/1548-8659(1999)128<0414:FTOTEM>2.0.CO;2.","productDescription":"22 p.","startPage":"414","endPage":"435","costCenters":[],"links":[{"id":501371,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/2027.42/142095","text":"External Repository"},{"id":229552,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Saginaw Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.35379911080491,\n 44.40622701769536\n ],\n [\n -83.86649012999017,\n 44.02265671143746\n ],\n [\n -83.96462932526535,\n 43.89022549593376\n ],\n [\n -84.01587928016657,\n 43.62261147789383\n ],\n [\n -83.63499279514937,\n 43.53345477307994\n ],\n [\n -83.30252598374528,\n 43.83924743632402\n ],\n [\n -82.90563529870151,\n 44.068965565457844\n ],\n [\n -83.03751319979332,\n 44.276344901674435\n ],\n [\n -83.35379911080491,\n 44.40622701769536\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"128","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a0fdde4b0c8380cd53a4c","contributors":{"authors":[{"text":"Schaeffer, J.S.","contributorId":42688,"corporation":false,"usgs":true,"family":"Schaeffer","given":"J.S.","email":"","affiliations":[],"preferred":false,"id":390652,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haas, R.C.","contributorId":94061,"corporation":false,"usgs":true,"family":"Haas","given":"R.C.","email":"","affiliations":[],"preferred":false,"id":390654,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Diana, J.S.","contributorId":96034,"corporation":false,"usgs":true,"family":"Diana","given":"J.S.","email":"","affiliations":[],"preferred":false,"id":390655,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Breck, J.E.","contributorId":65244,"corporation":false,"usgs":true,"family":"Breck","given":"J.E.","email":"","affiliations":[],"preferred":false,"id":390653,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70210547,"text":"70210547 - 1999 - Pool 13 drawdown: Predicting success rates and affected areas","interactions":[],"lastModifiedDate":"2022-05-27T19:13:43.921939","indexId":"70210547","displayToPublicDate":"1999-04-01T13:22:22","publicationYear":"1999","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":44,"text":"Long Term Resource Monitoring Program Technical Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"99-T002","title":"Pool 13 drawdown: Predicting success rates and affected areas","docAbstract":"The likelihood of 1- or 2-foot drawdowns, and the area affected by such alternative drawdowns, was estimated for Pool 13 on the Upper Mississippi River. Minimum water surface (elevation) requirements were compared to computed water surface profiles to determine a critical low flow that would allow a navigation channel 400 feet wide and 10.5 feet deep. An upper limit on flow was established based on the flow at which open river conditions would exist for a given drawdown. The range in flows that would allow for a drawdown was used to estimate success rates using historical daily discharge data. Success rates were determined for a variety of drawdown durations between two time periods. May 1—August 15 and June 15—August 15. The greatest effect of the drawdown would he near Lock and Dam 13. Higher discharges, as well as distance from the dam. lessen the drawdown amount. Areas that would he affected by these two drawdown scenarios were predicted by overlaying maps of water surfaces with depths using a geographic information system. Although the drawdown effects on most physical and biotic components of Pool 13 arc unknown, some general drawdown effects likely to occur because of the changes in water surface elevation are presented.
","language":"English","publisher":"U.S. Geological Survey","usgsCitation":"Rogala, J.T., Wlosinski, J.H., and Landwehr, K.J., 1999, Pool 13 drawdown: Predicting success rates and affected areas: Long Term Resource Monitoring Program Technical Report 99-T002, v, 27 p.","productDescription":"v, 27 p.","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":401314,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/unnumbered/70210547/report.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":396806,"rank":1,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_70995.htm"},{"id":396807,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/unnumbered/70210547/report-thumb.jpg"}],"country":"United States","state":"Illinois, Iowa","otherGeospatial":"Pool 13, upper Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.60699462890625,\n 41.84705871212191\n ],\n [\n -90.0384521484375,\n 41.84705871212191\n ],\n [\n -90.0384521484375,\n 42.37883631647602\n ],\n [\n -90.60699462890625,\n 42.37883631647602\n ],\n [\n -90.60699462890625,\n 41.84705871212191\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rogala, James T. 0000-0002-1954-4097 jrogala@usgs.gov","orcid":"https://orcid.org/0000-0002-1954-4097","contributorId":2651,"corporation":false,"usgs":true,"family":"Rogala","given":"James","email":"jrogala@usgs.gov","middleInitial":"T.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":837384,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wlosinski, Joseph H.","contributorId":75488,"corporation":false,"usgs":true,"family":"Wlosinski","given":"Joseph","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":837385,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Landwehr, Kevin J.","contributorId":288096,"corporation":false,"usgs":false,"family":"Landwehr","given":"Kevin","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":837386,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":1015975,"text":"1015975 - 1999 - Demography of the Yellowstone grizzly bears","interactions":[],"lastModifiedDate":"2023-12-14T15:33:37.841236","indexId":"1015975","displayToPublicDate":"1999-04-01T00:00:00","publicationYear":"1999","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Demography of the Yellowstone grizzly bears","docAbstract":"We undertook a demographic analysis of the Yellowstone grizzly bears (Ursus arctos) to identify critical environmental factors controlling grizzly bear vital rates, and thereby to help evaluate the effectiveness of past management and to identify future conservation issues. We concluded that, within the limits of uncertainty implied by the available data and our methods of data analysis, the size of the Yellowstone grizzly bear population changed little from 1975 to 1995. We found that grizzly bear mortality rates are about double in years when the whitebark pine crop fails than in mast years, and that the population probably declines when the crop fails and increases in mast years. Our model suggests that natural variation in whitebark pine crop size over the last two decades explains more of the perceived fluctuations in Yellowstone grizzly population size than do other variables.
Our analysis used demographic data from 202 radio-telemetered bears followed between 1975 and 1992 and accounted for whitebark pine (Pinus albicaulis) crop failures during 1993–1995. We used a maximum likelihood method to estimate demographic parameters and used the Akaike Information Criteria to judge the significance of various independent variables. We identified no independent variables correlated with grizzly bear fecundity. In order of importance, we found that grizzly bear mortality rates are correlated with season, whitebark pine crop size (mast vs. nonmast year), sex, management-trapping status (never management-trapped vs. mangement-trapped once or more), and age. The mortality rate of bears that were management-trapped at least once was almost double that of bears that were never management-trapped, implying a source/sink (i.e., never management-trapped/management-trapped) structure. The rate at which bears move between the source and sink, estimated as the management-trapping rate (h), is critical to estimating the finite rate of increase, λ͞. We quantified h by estimating the rate at which bears that have never been management-trapped are management-trapped for the first time. It differed across seasons, was higher in nonmast than mast years, and varied with age. We calculate that λ͞ = 1.00 from 1975 to 1983 (four mast and five nonmast years) and 1.02 from 1984 to 1995 (seven mast and five nonmast years). Overall, we find that λ͞ = 1.01 ± 0.04 (mean ± 1 se) from 1975 to 1995.
Our models suggest that future management should concentrate on the threats to whitebark pine, such as those posed by white pine blister rust, global warming, and fire suppression. As is currently widely recognized by Yellowstone land managers, our model also suggests that future management must compensate for the increased grizzly bear mortality that is likely to be caused by an increasing number of humans in Yellowstone.
","language":"English","publisher":"Ecological Society of America","doi":"10.1890/0012-9658(1999)080[0957:DOTYGB]2.0.CO;2","usgsCitation":"Pease, C.M., and Mattson, D.J., 1999, Demography of the Yellowstone grizzly bears: Ecology, v. 80, no. 3, p. 957-975, https://doi.org/10.1890/0012-9658(1999)080[0957:DOTYGB]2.0.CO;2.","productDescription":"19 p.","startPage":"957","endPage":"975","numberOfPages":"19","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":133511,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.10748291015625,\n 44.12702800650004\n ],\n [\n -109.98138427734375,\n 44.1289994645142\n ],\n [\n -109.98687744140624,\n 44.33367180085156\n ],\n [\n -110.03631591796875,\n 44.34152959888481\n ],\n [\n -110.04730224609375,\n 44.3906169787868\n ],\n [\n -110.00885009765625,\n 44.422011314236634\n ],\n [\n -109.98138427734375,\n 44.50825885600572\n ],\n [\n -110.028076171875,\n 44.52196830685208\n ],\n [\n -110.1104736328125,\n 44.50825885600572\n ],\n [\n -110.12969970703125,\n 44.53371669765759\n ],\n [\n -110.07476806640625,\n 44.56503415498704\n ],\n [\n -110.0225830078125,\n 44.58655513209543\n ],\n [\n -109.84954833984375,\n 44.61784415342067\n ],\n [\n -109.80010986328124,\n 44.71161010858431\n ],\n [\n -109.84405517578125,\n 44.75258502192499\n ],\n [\n -109.90997314453125,\n 44.813018740612776\n ],\n [\n -109.9127197265625,\n 44.89868701215517\n ],\n [\n -109.9346923828125,\n 44.97839955494438\n ],\n [\n -109.96490478515625,\n 45.017243565102596\n ],\n [\n -110.00885009765625,\n 45.06770141120143\n ],\n [\n -110.06378173828125,\n 45.05412098425883\n ],\n [\n -110.13519287109374,\n 45.042478050891546\n ],\n [\n -110.69549560546874,\n 45.04053733158769\n ],\n [\n -110.775146484375,\n 45.079339209738094\n ],\n [\n -110.82183837890625,\n 45.06964120886863\n ],\n [\n -110.86578369140625,\n 45.04635929200553\n ],\n [\n -110.89874267578124,\n 45.0502402697946\n ],\n [\n -110.928955078125,\n 45.08127861241874\n ],\n [\n -110.9619140625,\n 45.09679146394738\n ],\n [\n -111.005859375,\n 45.10842333769411\n ],\n [\n -111.0333251953125,\n 45.10260769705975\n ],\n [\n -111.060791015625,\n 45.10066901851988\n ],\n [\n -111.0992431640625,\n 45.11811475546806\n ],\n [\n -111.126708984375,\n 45.120052841530516\n ],\n [\n -111.15966796875,\n 45.089035564831036\n ],\n [\n -111.181640625,\n 45.059941562221226\n ],\n [\n -111.11846923828125,\n 45.01918507438176\n ],\n [\n -111.10748291015625,\n 44.12702800650004\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"80","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ab2e4b07f02db66ec86","contributors":{"authors":[{"text":"Pease, C. M.","contributorId":44507,"corporation":false,"usgs":false,"family":"Pease","given":"C.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":323413,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mattson, David J. david_mattson@usgs.gov","contributorId":3662,"corporation":false,"usgs":true,"family":"Mattson","given":"David","email":"david_mattson@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":323414,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":4855,"text":"ds53 - 1999 - The mineral economy of Brazil--Economia mineral do Brasil","interactions":[],"lastModifiedDate":"2012-02-02T00:05:49","indexId":"ds53","displayToPublicDate":"1999-04-01T00:00:00","publicationYear":"1999","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"53","title":"The mineral economy of Brazil--Economia mineral do Brasil","docAbstract":"This study depicts the Brazilian government structure, mineral legislation and investment policy, taxation, foreign investment policies, environmental laws and regulations, and conditions in which the mineral industry operates. The report underlines Brazil's large and diversified mineral endowment. A total of 37 mineral commodities, or groups of closely related commodities, is discussed. An overview of the geologic setting of the major mineral deposits is presented. This report is presented in English and Portuguese in pdf format.","language":"ENGLISH","publisher":"Dept. of the Interior, U.S. Geological Survey ;\r\nU.S. G.P.O.,","doi":"10.3133/ds53","usgsCitation":"Gurmendi, A.C., Barboza, F.L., and Thorman, C.H., 1999, The mineral economy of Brazil--Economia mineral do Brasil: U.S. Geological Survey Data Series 53, 1 computer optical disc ;4 3/4 in., https://doi.org/10.3133/ds53.","productDescription":"1 computer optical disc ;4 3/4 in.","costCenters":[],"links":[{"id":139943,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b32e4b07f02db6b4959","contributors":{"authors":[{"text":"Gurmendi, Alfredo C.","contributorId":78979,"corporation":false,"usgs":true,"family":"Gurmendi","given":"Alfredo","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":149951,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barboza, Frederico Lopes","contributorId":105587,"corporation":false,"usgs":true,"family":"Barboza","given":"Frederico","email":"","middleInitial":"Lopes","affiliations":[],"preferred":false,"id":149952,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thorman, Charles H. cthorman@usgs.gov","contributorId":254,"corporation":false,"usgs":false,"family":"Thorman","given":"Charles","email":"cthorman@usgs.gov","middleInitial":"H.","affiliations":[{"id":7065,"text":"USGS emeritus","active":true,"usgs":false}],"preferred":false,"id":149950,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":3674,"text":"cir1173A - 1999 - Environmental characteristics and water quality of hydrologic benchmark network stations in the Eastern United States, 1963-95","interactions":[],"lastModifiedDate":"2012-02-02T00:05:29","indexId":"cir1173A","displayToPublicDate":"1999-04-01T00:00:00","publicationYear":"1999","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1173","chapter":"A","title":"Environmental characteristics and water quality of hydrologic benchmark network stations in the Eastern United States, 1963-95","docAbstract":"The information in this report was compiled to aid in the application and interpretation of historical water-quality data collected as part of the U.S. Geological Survey Hydrologic Benchmark Network program, which was established in 1963 to provide long-term measurements of streamflow and water quality in areas that are minimally affected by human activities. This report describes the environmental characteristics and water quality at 16 benchmark basins in the Eastern United States. In most of the basins, stream-water chemistry seems to be controlled by the interaction of acidic precipitation with the underlying soils and bedrock. Land use had a minimal effect on stream-water chemistry at most of the gaging stations.","language":"ENGLISH","publisher":"U.S. G.P.O. ;\r\nU.S. Geological Survey Informations Services [distributor],","doi":"10.3133/cir1173A","usgsCitation":"Mast, M.A., and Turk, J.T., 1999, Environmental characteristics and water quality of hydrologic benchmark network stations in the Eastern United States, 1963-95: U.S. Geological Survey Circular 1173, xi, 158 p. :ill., maps ;28 cm., https://doi.org/10.3133/cir1173A.","productDescription":"xi, 158 p. :ill., maps ;28 cm.","costCenters":[],"links":[{"id":58,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/circ/circ1173","linkFileType":{"id":5,"text":"html"}},{"id":125114,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1999/1173a/report-thumb.jpg"},{"id":30722,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1999/1173a/report.pdf","linkFileType":{"id":1,"text":"pdf"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a14e4b07f02db6024d7","contributors":{"authors":[{"text":"Mast, M. Alisa 0000-0001-6253-8162 mamast@usgs.gov","orcid":"https://orcid.org/0000-0001-6253-8162","contributorId":827,"corporation":false,"usgs":true,"family":"Mast","given":"M.","email":"mamast@usgs.gov","middleInitial":"Alisa","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":147386,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Turk, John T.","contributorId":53363,"corporation":false,"usgs":true,"family":"Turk","given":"John","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":147387,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70021984,"text":"70021984 - 1999 - Structure and stability of the midsummer fish communities in Chequamegon Bay, Lake Superior, 1973-1996","interactions":[],"lastModifiedDate":"2026-03-19T18:06:22.381481","indexId":"70021984","displayToPublicDate":"1999-03-01T00:00:00","publicationYear":"1999","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Structure and stability of the midsummer fish communities in Chequamegon Bay, Lake Superior, 1973-1996","docAbstract":"We analyzed the structure and stability of the summer fish communities of Chequamegon Bay, Lake Superior, during 1973–1996 from data collected with bottom trawls at 39 stations. Fifty‐three taxa were collected during the study, but we found that relative abundances for 20 taxa described most of the internal variability of the data for all taxa. Abundance data for the 20 species showed that two communities existed in the bay; one inhabited shallow water (≤3.0 m) whereas the other inhabited deeper water (>3.0 m). No temporal patterns of change were found in the structure of the shallow‐water community, whose variation was best described by abundances of 12 taxa. The deepwater community, whose variation was best described by eight taxa, underwent three periods ofstability; 1973–1978, 1979–1988, and 1989–1996. We conclude that the shallow‐water community was stable throughout the 24 years studied. Dynamics of the deepwater community were greatly affected by changes in stocking rates of lake trout Salvelinus namaycush and splake (hybrid of brook trout S. fontinalis × lake trout) and by rehabilitation of populations of lake herring Coregonus artedi and lake whitefish C. clupeaformis. Information on the existence, structure, stability, and habitats of fish communities in the bay will be useful for assessing changes in those communities that result from further changes in the bay or lake ecosystems.
","language":"English","publisher":"American Fisheries Society","doi":"10.1577/1548-8659(1999)128<0362:SASOTM>2.0.CO;2","usgsCitation":"Hoff, M., and Bronte, C., 1999, Structure and stability of the midsummer fish communities in Chequamegon Bay, Lake Superior, 1973-1996: Transactions of the American Fisheries Society, v. 128, no. 2, p. 362-373, https://doi.org/10.1577/1548-8659(1999)128<0362:SASOTM>2.0.CO;2.","productDescription":"12 p.","startPage":"362","endPage":"373","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":229126,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Chequamegon Bay, Lake Superior","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.87854080424309,\n 46.720261632885496\n ],\n [\n -90.97923358589996,\n 46.597784806642295\n ],\n [\n -90.94537347910202,\n 46.57186055769611\n ],\n [\n -90.85827777582416,\n 46.57883268534488\n ],\n [\n -90.75527397988641,\n 46.62421897807657\n ],\n [\n -90.72401274728661,\n 46.688576820004926\n ],\n [\n -90.87854080424309,\n 46.720261632885496\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"128","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b9c2ee4b08c986b31d302","contributors":{"authors":[{"text":"Hoff, M.H.","contributorId":95439,"corporation":false,"usgs":true,"family":"Hoff","given":"M.H.","email":"","affiliations":[],"preferred":false,"id":391935,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bronte, C.R.","contributorId":20100,"corporation":false,"usgs":true,"family":"Bronte","given":"C.R.","email":"","affiliations":[],"preferred":false,"id":391934,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70186932,"text":"70186932 - 1999 - New land surface digital elevation model covers the Earth","interactions":[],"lastModifiedDate":"2017-04-14T14:31:11","indexId":"70186932","displayToPublicDate":"1999-02-01T00:00:00","publicationYear":"1999","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3879,"text":"Eos, Earth and Space Science News","active":true,"publicationSubtype":{"id":10}},"title":"New land surface digital elevation model covers the Earth","docAbstract":"Land surface elevation around the world is reaching new heights—as far as its description and measurement goes. A new global digital elevation model (DEM) is being cited as a significant improvement in the quality of topographic data available for Earth science studies.
Land surface elevation is one of the Earth's most fundamental geophysical properties, but the accuracy and detail with which it has been measured and described globally have been insufficient for many large-area studies. The new model, developed at the U.S. Geological Survey's (USGS) EROS Data Center (EDC), has changed all that.
","language":"English","publisher":"AGU","doi":"10.1029/99EO00050","usgsCitation":"Gesch, D.B., Verdin, K.L., and Greenlee, S.K., 1999, New land surface digital elevation model covers the Earth: Eos, Earth and Space Science News, v. 80, no. 6, p. 69-70, https://doi.org/10.1029/99EO00050.","productDescription":"2 p.","startPage":"69","endPage":"70","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":339743,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"80","issue":"6","noUsgsAuthors":false,"publicationDate":"2011-06-03","publicationStatus":"PW","scienceBaseUri":"58f1e0cbe4b08144348b7e2b","contributors":{"authors":[{"text":"Gesch, Dean B. 0000-0002-8992-4933 gesch@usgs.gov","orcid":"https://orcid.org/0000-0002-8992-4933","contributorId":2956,"corporation":false,"usgs":true,"family":"Gesch","given":"Dean","email":"gesch@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":691063,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Verdin, Kristine L. 0000-0002-6114-4660 kverdin@usgs.gov","orcid":"https://orcid.org/0000-0002-6114-4660","contributorId":3070,"corporation":false,"usgs":true,"family":"Verdin","given":"Kristine","email":"kverdin@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":691064,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Greenlee, Susan K. sgreenlee@usgs.gov","contributorId":3326,"corporation":false,"usgs":true,"family":"Greenlee","given":"Susan","email":"sgreenlee@usgs.gov","middleInitial":"K.","affiliations":[],"preferred":true,"id":691065,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70021820,"text":"70021820 - 1999 - How grazing and soil quality affect native and exotic plant diversity in Rocky Mountain grasslands","interactions":[],"lastModifiedDate":"2023-12-19T19:33:17.46144","indexId":"70021820","displayToPublicDate":"1999-02-01T00:00:00","publicationYear":"1999","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"How grazing and soil quality affect native and exotic plant diversity in Rocky Mountain grasslands","docAbstract":"We used multiscale plots to sample vascular plant diversity and soil characteristics in and adjacent to 26 long-term grazing exclosure sites in Colorado, Wyoming, Montana, and South Dakota, USA. The exclosures were 7–60 yr old (31.2 ± 2.5 yr, mean ± 1 se). Plots were also randomly placed in the broader landscape in open rangeland in the same vegetation type at each site to assess spatial variation in grazed landscapes. Consistent sampling in the nine National Parks, Wildlife Refuges, and other management units yielded data from 78 1000-m2 plots and 780 1-m2 subplots. We hypothesized that native species richness would be lower in the exclosures than in grazed sites, due to competitive exclusion in the absence of grazing. We also hypothesized that grazed sites would have higher native and exotic species richness compared to ungrazed areas, due to disturbance (i.e., the intermediate-disturbance hypothesis) and the conventional wisdom that grazing may accelerate weed invasion. Both hypotheses were soundly rejected. Although native species richness in 1-m2 subplots was significantly higher (P < 0.05) in grazed sites, we found nearly identical native or exotic species richness in 1000-m2 plots in exclosures (31.5 ± 2.5 native and 3.1 ± 0.5 exotic species), adjacent grazed plots (32.6 ± 2.8 native and 3.2 ± 0.6 exotic species), and randomly selected grazed plots (31.6 ± 2.9 native and 3.2 ± 0.6 exotic species). We found no significant differences in species diversity (Hill’s diversity indices, N1 and N2), evenness (Hill’s ratio of evenness, E5), cover of various life-forms (grasses, forbs, and shrubs), soil texture, or soil percentage of N and C between grazed and ungrazed sites at the 1000-m2 plot scale. The species lists of the long-ungrazed and adjacent grazed plots overlapped just 57.9 ± 2.8%. This difference in species composition is commonly attributed solely to the difference in grazing regimes. However, the species lists between pairs of grazed plots (adjacent and distant 1000-m2 plots) in the same vegetation type overlapped just 48.6 ± 3.6%, and the ungrazed plots and distant grazed plots overlapped 49.4 ± 3.6%. Differences in vegetation and soils between grazed and ungrazed sites were minimal in most cases, but soil characteristics and elevation were strongly correlated with native and exotic plant diversity in the study region. For the 78 1000-m2 plots, 59.4% of the variance in total species richness was explained by percentage of silt (coefficient = 0.647, t = 5.107, P < 0.001), elevation (coefficient = 0.012, t = 5.084, P < 0.001), and total foliar cover (coefficient = 0.110, t = 2.104, P < 0.039). Only 12.8% of the variance in exotic species cover (log10cover) was explained by percentage of clay (coefficient = −0.011, t = −2.878, P < 0.005), native species richness (coefficient = −0.011, t = −2.156, P < 0.034), and log10N (coefficient = 2.827, t = 1.860, P < 0.067). Native species cover and exotic species richness and frequency were also significantly positively correlated with percentage of soil N at the 1000-m2 plot scale. Our research led to five broad generalizations about current levels of grazing in these Rocky Mountain grasslands: (1) grazing probably has little effect on native species richness at landscape scales; (2) grazing probably has little effect on the accelerated spread of most exotic plant species at landscape scales; (3) grazing affects local plant species and life-form composition and cover, but spatial variation is considerable; (4) soil characteristics, climate, anddisturbances may have a greater effect on plant species diversity than do current levels of grazing; and (5) few plant species show consistent, directional responses to grazing or cessation of grazing.
","language":"English","publisher":"Ecological Society of America","doi":"10.1890/1051-0761(1999)009[0045:HGASQA]2.0.CO;2","usgsCitation":"Stohlgren, T.J., Schell, L.D., and Vanden Heuvel, B., 1999, How grazing and soil quality affect native and exotic plant diversity in Rocky Mountain grasslands: Ecological Applications, v. 9, no. 1, p. 45-64, https://doi.org/10.1890/1051-0761(1999)009[0045:HGASQA]2.0.CO;2.","productDescription":"20 p.","startPage":"45","endPage":"64","numberOfPages":"20","costCenters":[],"links":[{"id":229228,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a324ce4b0c8380cd5e6ba","contributors":{"authors":[{"text":"Stohlgren, Thomas J.","contributorId":213895,"corporation":false,"usgs":false,"family":"Stohlgren","given":"Thomas","email":"","middleInitial":"J.","affiliations":[{"id":38925,"text":"Natural Resource Ecology Laboratory, Colorado State University, Fort Collins","active":true,"usgs":false}],"preferred":false,"id":391302,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schell, L. D.","contributorId":75881,"corporation":false,"usgs":false,"family":"Schell","given":"L.","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":391304,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vanden Heuvel, B.","contributorId":17392,"corporation":false,"usgs":true,"family":"Vanden Heuvel","given":"B.","email":"","affiliations":[],"preferred":false,"id":391303,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":1015971,"text":"1015971 - 1999 - A GIS modeling method applied to predicting forest songbird habitat","interactions":[],"lastModifiedDate":"2023-12-19T19:30:33.62364","indexId":"1015971","displayToPublicDate":"1999-02-01T00:00:00","publicationYear":"1999","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"A GIS modeling method applied to predicting forest songbird habitat","docAbstract":"We have developed an approach for using “presence” data to construct habitat models. Presence data are those that indicate locations where the target organism is observed to occur, but that cannot be used to define locations where the organism does not occur. Surveys of highly mobile vertebrates often yield these kinds of data. Models developed through our approach yield predictions of the amount and the spatial distribution of good-quality habitat for the target species. This approach was developed primarily for use in a GIS context; thus, the models are spatially explicit and have the potential to be applied over large areas. Our method consists of two primary steps. In the first step, we identify an optimal range of values for each habitat variable to be used as a predictor in the model. To find these ranges, we employ the concept of maximizing the difference between cumulative distribution functions of (1) the values of a habitat variable at the observed presence locations of the target organism, and (2) the values of that habitat variable for all locations across a study area. In the second step, multivariate models of good habitat are constructed by combining these ranges of values, using the Boolean operators “and” and “or.” We use an approach similar to forward stepwise regression to select the best overall model.
We demonstrate the use of this method by developing species-specific habitat models for nine forest-breeding songbirds (e.g., Cerulean Warbler, Scarlet Tanager, Wood Thrush) studied in southern Ohio. These models are based on species’ microhabitat preferences for moisture and vegetation characteristics that can be predicted primarily through the use of abiotic variables. We use slope, land surface morphology, land surface curvature, water flow accumulation downhill, and an integrated moisture index, in conjunction with a land-cover classification that identifies forest/nonforest, to develop these models.
The performance of these models was evaluated with an independent data set. Our tests showed that the models performed better than random at identifying where the birds occurred and provided useful information for predicting the amount and spatial distribution of good habitat for the birds we studied. In addition, we generally found positive correlations between the amount of habitat, as predicted by the models, and the number of territories within a given area. This added component provides the possibility, ultimately, of being able to estimate population sizes. Our models represent useful tools for resource managers who are interested in assessing the impacts of alternative management plans that could alter or remove habitat for these birds.
","language":"English","publisher":"Ecological Society of America","doi":"10.1890/1051-0761(1999)009[0152:AGMMAT]2.0.CO;2","usgsCitation":"Dettmers, R., and Bart, J., 1999, A GIS modeling method applied to predicting forest songbird habitat: Ecological Applications, v. 9, no. 1, p. 152-163, https://doi.org/10.1890/1051-0761(1999)009[0152:AGMMAT]2.0.CO;2.","productDescription":"12 p.","startPage":"152","endPage":"163","numberOfPages":"12","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":135056,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b31e4b07f02db6b4120","contributors":{"authors":[{"text":"Dettmers, Randy","contributorId":48534,"corporation":false,"usgs":true,"family":"Dettmers","given":"Randy","affiliations":[],"preferred":false,"id":323401,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bart, Jonathan jon_bart@usgs.gov","contributorId":57025,"corporation":false,"usgs":true,"family":"Bart","given":"Jonathan","email":"jon_bart@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":false,"id":323402,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}