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Models currently used to estimate patterns of species co‐occurrence while accounting for errors in detection of species can be difficult to fit when the effects of covariates on species occurrence probabilities are included. The source of the estimation problems is the particular parameterization used to specify species co‐occurrence probability. We develop a new parameterization for estimating patterns of co‐occurrence of interacting species that allows the effects of covariates to be specified quite naturally without estimation problems. In our model, the occurrence of one species is assumed to depend on the occurrence of another, but the occurrence of the second species is not assumed to depend on the presence of the first species. This pattern of co‐occurrence, wherein one species is dominant and the other is subordinate, can be produced by several types of ecological interactions (predator–prey, parasitism, and so on).

A simulation study demonstrated that estimates of species occurrence probabilities were unbiased in samples of 50–100 locations and three surveys per location, provided species are easily detected (probability of detection ≥ 0.5). Higher sample sizes (>200 locations) are needed to achieve unbiasedness when species are more difficult to detect. An analysis of data from treefrog surveys in southern Florida indicated that the occurrence of Cuban treefrogs, an invasive predator species, was highest near the point of its introduction and declined with distance from that location. Sites occupied by Cuban treefrogs were 9.0 times less likely to contain green treefrogs and 15.7 times less likely to contain squirrel treefrogs compared to sites without Cuban treefrogs. The detection probabilities of native treefrog species did not depend on the presence of Cuban treefrogs, suggesting that the native treefrog species are naive to the introduced species.

","language":"English","publisher":"Ecological Society of America","doi":"10.1890/09-0850.1","usgsCitation":"Waddle, J.H., Dorazio, R., Walls, S.C., Rice, K.G., Beauchamp, J., Schuman, M., and Mazzotti, F., 2010, A new parameterization for estimating co‐occurrence of interacting species: Ecological Applications, v. 20, no. 5, p. 1467-1475, https://doi.org/10.1890/09-0850.1.","productDescription":"9 p.","startPage":"1467","endPage":"1475","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":363092,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Waddle, J. Hardin 0000-0003-1940-2133 waddleh@usgs.gov","orcid":"https://orcid.org/0000-0003-1940-2133","contributorId":138953,"corporation":false,"usgs":true,"family":"Waddle","given":"J.","email":"waddleh@usgs.gov","middleInitial":"Hardin","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":761211,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dorazio, Robert M. bob_dorazio@usgs.gov","contributorId":140635,"corporation":false,"usgs":true,"family":"Dorazio","given":"Robert M.","email":"bob_dorazio@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":761212,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walls, Susan C. 0000-0001-7391-9155 swalls@usgs.gov","orcid":"https://orcid.org/0000-0001-7391-9155","contributorId":138952,"corporation":false,"usgs":true,"family":"Walls","given":"Susan","email":"swalls@usgs.gov","middleInitial":"C.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":761213,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rice, Kenneth G. 0000-0001-8282-1088 krice@usgs.gov","orcid":"https://orcid.org/0000-0001-8282-1088","contributorId":117,"corporation":false,"usgs":true,"family":"Rice","given":"Kenneth","email":"krice@usgs.gov","middleInitial":"G.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":761214,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beauchamp, Jeff","contributorId":175458,"corporation":false,"usgs":false,"family":"Beauchamp","given":"Jeff","email":"","affiliations":[],"preferred":false,"id":761215,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schuman, Melinda J.","contributorId":138955,"corporation":false,"usgs":false,"family":"Schuman","given":"Melinda J.","affiliations":[{"id":12592,"text":"Conservancy of Southwest Florida, Naples, FL","active":true,"usgs":false}],"preferred":false,"id":761216,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mazzotti, Frank J.","contributorId":90236,"corporation":false,"usgs":true,"family":"Mazzotti","given":"Frank J.","affiliations":[],"preferred":false,"id":761217,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70180069,"text":"70180069 - 2010 - Reply to “Comment on ‘Near-surface location, geometry, and velocities of the Santa Monica fault zone, Los Angeles, California’ by R. D. Catchings, G. Gandhok, M. R. Goldman, D. Okaya, M. J. Rymer, and G. W. Bawden” by T. L. Pratt and J. F. Dolan","interactions":[],"lastModifiedDate":"2021-04-08T15:53:29.918143","indexId":"70180069","displayToPublicDate":"2017-01-30T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Reply to “Comment on ‘Near-surface location, geometry, and velocities of the Santa Monica fault zone, Los Angeles, California’ by R. D. Catchings, G. Gandhok, M. R. Goldman, D. Okaya, M. J. Rymer, and G. W. Bawden” by T. L. Pratt and J. F. Dolan","docAbstract":"

In a comment on our 2008 paper (Catchings, Gandhok, et al., 2008) on the Santa Monica fault in Los Angeles, California, Pratt and Dolan (2010) (herein referred to as P&D) cite numerous objections to our work, inferring that our study is flawed. However, as shown in our reply, their objections contradict their own published works, published works of others, and proven seismic methodologies. Rather than responding to each repeated invalid objection, we address their objections by topic in the subsequent sections.

In Catchings, Gandhok, et al. (2008), we presented high-resolution seismic-reflection images that showed two near-surface faults in the upper 50 m beneath the grounds of the Wadsworth Veterans Administration Hospital (WVAH). Although P&D suggest we effectively duplicated their seismic acquisition, our survey was not a duplication of their efforts. Rather, we conducted a seismic-imaging survey over a similar profile as Pratt et al. (1998) but used a different data acquisition system and different data processing methods to evaluate methods of seismically imaging blind faults in the wake of the 17 January 1994 M 6.7 Northridge earthquake. We used an acquisition method that provides both tomographic seismic velocities and reflection images. Our combined-data approach allowed for shallower imaging (∼2.5 m minimum) than the ∼20-m minimum of Pratt et al. (1998), clearer images of the fault zone, and more accurate depth determinations (rather than time images). In processing the reflection images, we used prestack depth migration, which is generally accepted as the only proper imaging method for imaging subsurface structures with strong lateral velocity variations (Versteeg, 1993), a condition shown to exist at the WVAH site. We correlated our reflection images with refraction tomography images, borehole lithology, and velocity data, Interferometric Synthetic Aperture Radar images, and changes in groundwater depths. Except for some minor differences, our seismic-reflection images coincide with previously published seismic-reflection images by Dolan and Pratt (1997) and Pratt et al. (1998), and a paleoseismic study by Dolan et al. (2000). Principal differences among our interpretations and those of Pratt et al. (1998) relate to the upper 20 m and the south side of the fault, which Pratt et al. (1998) did not clearly image. In contrast, our seismic images included structures on both sides of the fault zone from about 2.5 m depth to about 100 m depth at WVAH, allowing us to interpret more details.

","language":"English","publisher":"Seismological Society of America","publisherLocation":"Stanford, CA","doi":"10.1785/0120090335","usgsCitation":"Catchings, R.D., Rymer, M.J., Goldman, M.R., and Bawden, G.W., 2010, Reply to “Comment on ‘Near-surface location, geometry, and velocities of the Santa Monica fault zone, Los Angeles, California’ by R. D. Catchings, G. Gandhok, M. R. Goldman, D. Okaya, M. J. Rymer, and G. W. Bawden” by T. L. Pratt and J. F. Dolan: Bulletin of the Seismological Society of America, v. 100, no. 5A, p. 2338-2347, https://doi.org/10.1785/0120090335.","productDescription":"10 p.","startPage":"2338","endPage":"2347","ipdsId":"IP-017151","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":334355,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Los Angeles","otherGeospatial":"Santa Monica Fault Zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.54694366455077,\n 34.00073124300159\n ],\n [\n -118.54694366455077,\n 34.09218887374251\n ],\n [\n -118.37322235107422,\n 34.09218887374251\n ],\n [\n -118.37322235107422,\n 34.00073124300159\n ],\n [\n -118.54694366455077,\n 34.00073124300159\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"100","issue":"5A","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2010-09-20","publicationStatus":"PW","scienceBaseUri":"58905ef3e4b072a7ac0cad45","contributors":{"authors":[{"text":"Catchings, Rufus D. 0000-0002-5191-6102 catching@usgs.gov","orcid":"https://orcid.org/0000-0002-5191-6102","contributorId":1519,"corporation":false,"usgs":true,"family":"Catchings","given":"Rufus","email":"catching@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":660201,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rymer, Michael J. mrymer@usgs.gov","contributorId":1522,"corporation":false,"usgs":true,"family":"Rymer","given":"Michael","email":"mrymer@usgs.gov","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":660204,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goldman, Mark R. 0000-0002-0802-829X goldman@usgs.gov","orcid":"https://orcid.org/0000-0002-0802-829X","contributorId":1521,"corporation":false,"usgs":true,"family":"Goldman","given":"Mark","email":"goldman@usgs.gov","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":660203,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bawden, Gerald W. gbawden@usgs.gov","contributorId":1071,"corporation":false,"usgs":true,"family":"Bawden","given":"Gerald","email":"gbawden@usgs.gov","middleInitial":"W.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":660202,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70042479,"text":"70042479 - 2010 - Mount Rainier National Park and Olympic National Park Elk Monitoring Program Annual Report 2010","interactions":[],"lastModifiedDate":"2017-11-22T16:05:35","indexId":"70042479","displayToPublicDate":"2015-06-22T13:15:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":52,"text":"Natural Resource Data Series","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"2011/289","title":"Mount Rainier National Park and Olympic National Park Elk Monitoring Program Annual Report 2010","docAbstract":"

Fiscal year 2010 was the third year of gathering data needed for protocol development while simultaneously implementing what is expected to be the elk monitoring protocol at Mount Rainier (MORA) and Olympic (OLYM) national parks in the North Coast and Cascades Network (NCCN). Elk monitoring in these large wilderness parks relies on aerial surveys from a helicopter. Summer surveys are planned for both parks and are intended to provide quantitative estimates of abundance, sex and age composition, and distribution of migratory elk in high elevation trend count areas. Spring surveys are planned at Olympic National Park and are intended to provide quantitative estimates of abundance of resident and migratory elk on low-elevation winter ranges within surveyed trend count areas. An unknown number of elk is not detected during surveys. The protocol under development aims to estimate the number of missed elk by applying a model that accounts for detection bias. Detection bias in elk surveys in MORA will be estimated using a double-observer sightability model that was developed based on data from surveys conducted in 2008-2010. The model was developed using elk that were previously equipped with radio collars by cooperating tribes. That model is currently in peer review. At the onset of protocol development in OLYM there were no existing radio- collars on elk. Consequently double-observer sightability models have not yet been developed for elk surveys in OLYM; the majority of the effort in OLYM has been focused on capturing and radio collaring elk to permit the development of sightability models for application in OLYM. As a result, no estimates of abundance or composition are included in this annual report, only raw counts of the numbers of elk seen in surveys. At MORA each of the two trend count areas (North Rainier herd, and South Rainier herd) were surveyed twice. 290 and 380 elk were counted on the two replicates in the North Rainier herd, and 621 and 327 elk counted on the two replicate South Rainier counts. At Olympic National Park, each of three spring trend count areas was surveyed once in March 2010. 27 elk were observed in the South Fork Hoh trend count area, 137 elk were observed in the Hoh trend count area, and 131 elk were observed in the Queets trend count area. In September 2010, 18 elk were captured and fitted with radio collars as part of a contracted animal capture, eradication and tagging of animals (ACETA) operation. These animals will be available to contribute double-observer sightability data in future spring and summer surveys. There were no summer surveys for elk in OLYM in 2010.

","language":"English","publisher":"National Park Service","publisherLocation":"Fort Collins, CO","usgsCitation":"Griffin, P., Happe, P.J., Jenkins, K.J., Reid, M., Vales, D.J., Moeller, B.J., Tirhi, M., McCorquodale, S., and Miller, P., 2010, Mount Rainier National Park and Olympic National Park Elk Monitoring Program Annual Report 2010: Natural Resource Data Series 2011/289, 42 p.","productDescription":"42 p.","numberOfPages":"42","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-030477","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":310896,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://fresc.usgs.gov/products/ProductDetails.aspx?ProductNumber=2759"},{"id":310897,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mt. Rainier National Park, Olympic National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.55749511718749,\n 47.111261437080344\n ],\n [\n -124.55749511718749,\n 48.36537369040198\n ],\n [\n -122.728271484375,\n 48.36537369040198\n ],\n [\n -122.728271484375,\n 47.111261437080344\n ],\n [\n -124.55749511718749,\n 47.111261437080344\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.39044189453124,\n 46.164614496897094\n ],\n [\n -122.39044189453124,\n 47.253135632244216\n ],\n [\n -120.4815673828125,\n 47.253135632244216\n ],\n [\n -120.4815673828125,\n 46.164614496897094\n ],\n [\n -122.39044189453124,\n 46.164614496897094\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56389759e4b0d6133fe72fcf","contributors":{"authors":[{"text":"Griffin, Paul pgriffin@usgs.gov","contributorId":140575,"corporation":false,"usgs":true,"family":"Griffin","given":"Paul","email":"pgriffin@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":578989,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Happe, Patricia J.","contributorId":50983,"corporation":false,"usgs":false,"family":"Happe","given":"Patricia","email":"","middleInitial":"J.","affiliations":[{"id":16133,"text":"National Park Service, Olympic National Park","active":true,"usgs":false}],"preferred":false,"id":578990,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jenkins, Kurt J. 0000-0003-1415-6607 kurt_jenkins@usgs.gov","orcid":"https://orcid.org/0000-0003-1415-6607","contributorId":3415,"corporation":false,"usgs":true,"family":"Jenkins","given":"Kurt","email":"kurt_jenkins@usgs.gov","middleInitial":"J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":578991,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reid, Mason","contributorId":51639,"corporation":false,"usgs":true,"family":"Reid","given":"Mason","affiliations":[],"preferred":false,"id":578992,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vales, David J.","contributorId":74662,"corporation":false,"usgs":true,"family":"Vales","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":578993,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Moeller, Barbara J.","contributorId":87446,"corporation":false,"usgs":true,"family":"Moeller","given":"Barbara","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":578994,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tirhi, Michelle","contributorId":28168,"corporation":false,"usgs":false,"family":"Tirhi","given":"Michelle","affiliations":[{"id":13269,"text":"Washington Department of Fish & Wildlife","active":true,"usgs":false}],"preferred":false,"id":578995,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McCorquodale, Scott","contributorId":28515,"corporation":false,"usgs":true,"family":"McCorquodale","given":"Scott","affiliations":[],"preferred":false,"id":578996,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Miller, Pat","contributorId":149627,"corporation":false,"usgs":false,"family":"Miller","given":"Pat","email":"","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":578997,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70038618,"text":"70038618 - 2010 - Development of inferential sensors for real-time quality control of water-level data for the Everglades Depth Estimation Network","interactions":[],"lastModifiedDate":"2015-10-29T12:33:43","indexId":"70038618","displayToPublicDate":"2015-06-08T08:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":12,"text":"Conference publication"},"title":"Development of inferential sensors for real-time quality control of water-level data for the Everglades Depth Estimation Network","docAbstract":"

The Everglades Depth Estimation Network (EDEN) is an integrated network of real-time water-level gaging stations, ground-elevation models, and watersurface models designed to provide scientists, engineers, and water-resource managers with current (2000-present) water-depth information for the entire freshwater portion of the greater Everglades. The generation of EDEN waterlevel surfaces is derived from real-time data. Real-time data are automatically checked for outliers using minimum, maximum, and rate-of-change thresholds for each station. Smaller errors in the real-time data, such as gradual drift of malfunctioning pressure transducers, are more difficult to immediately identify with visual inspection of time-series plots and may only be identified during on-site inspections of the gages. Correcting smaller errors in the data often is time consuming and water-level data may not be finalized for several months. To provide water-level surfaces on a daily basis, EDEN needed an automated process to identify errors in water-level data and to provide estimates for missing or erroneous waterlevel data.

\n

A technology often used for industrial applications is “inferential sensor.” Rather than installing a redundant sensor to measure a process, such as an additional waterlevel gage, an inferential sensor, or virtual sensor, is developed that estimates the processes measured by the physical sensor. The advantage of an inferential sensor is that it provides a redundant signal to the sensor in the field but without exposure to environmental threats. In the event that a gage does malfunction, the inferential sensor provides an estimate for the period of missing data. The inferential sensor also can be used in the quality assurance and quality control of the data. Inferential sensors for gages in the EDEN network are currently (2010) under development. The inferential sensors will be automated so that the real-time EDEN data will continuously be compared to the inferential sensor signal and digital reports of the status of the real-time data will be sent periodically to the appropriate support personnel. The development and application of inferential sensors is easily transferable to other real-time hydrologic monitoring networks.

","conferenceTitle":"Proceedings of the 2010 South Carolina Water Resources Conference","conferenceDate":"October 13-14, 2010","conferenceLocation":"Columbia, South Carolina","language":"English","usgsCitation":"Daamen, R.C., Edwin A. Roehl, J., and Conrads, P., 2010, Development of inferential sensors for real-time quality control of water-level data for the Everglades Depth Estimation Network, Proceedings of the 2010 South Carolina Water Resources Conference, Columbia, South Carolina, October 13-14, 2010, 4 p.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-022769","costCenters":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"links":[{"id":310764,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.84814453125,\n 24.958670130576788\n ],\n [\n -81.84814453125,\n 26.56396337134019\n ],\n [\n -80.19195556640625,\n 26.56396337134019\n ],\n [\n -80.19195556640625,\n 24.958670130576788\n ],\n [\n -81.84814453125,\n 24.958670130576788\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56334337e4b048076347eebd","contributors":{"authors":[{"text":"Daamen, Ruby C.","contributorId":105391,"corporation":false,"usgs":true,"family":"Daamen","given":"Ruby","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":578705,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Edwin A. Roehl, Jr.","contributorId":121477,"corporation":false,"usgs":true,"family":"Edwin A. Roehl","given":"Jr.","affiliations":[],"preferred":false,"id":578706,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Conrads, Paul 0000-0003-0408-4208 pconrads@usgs.gov","orcid":"https://orcid.org/0000-0003-0408-4208","contributorId":764,"corporation":false,"usgs":true,"family":"Conrads","given":"Paul","email":"pconrads@usgs.gov","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":578707,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70120779,"text":"70120779 - 2010 - The use of genetics for the management of a recovering population: temporal assessment of migratory peregrine falcons in North America","interactions":[],"lastModifiedDate":"2018-08-20T18:22:50","indexId":"70120779","displayToPublicDate":"2013-08-18T09:30:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"The use of genetics for the management of a recovering population: temporal assessment of migratory peregrine falcons in North America","docAbstract":"

Background:Our ability to monitor populations or species that were once threatened or endangered and in the process of recovery is enhanced by using genetic methods to assess overall population stability and size over time. This can be accomplished most directly by obtaining genetic measures from temporally-spaced samples that reflect the overall stability of the population as given by changes in genetic diversity levels (allelic richness and heterozygosity), degree of population differentiation (FST and DEST), and effective population size (Ne). The primary goal of any recovery effort is to produce a long-term self-sustaining population, and these measures provide a metric by which we can gauge our progress and help make important management decisions.

\n
\n

Methodology/Principal Findings:The peregrine falcon in North America (Falco peregrinus tundrius and anatum) was delisted in 1994 and 1999, respectively, and its abundance will be monitored by the species Recovery Team every three years until 2015. Although the United States Fish and Wildlife Service makes a distinction between tundrius and anatum subspecies, our genetic results based on eleven microsatellite loci, including those from Brown et al. (2007), suggest no differentiation and warrant delineation of a subspecies in its northern latitudinal distribution from Alaska through Canada into Greenland. Using temporal samples collected at Padre Island, Texas during migration (seven temporal time periods between 1985-2007), no significant differences in genetic diversity or significant population differentiation in allele frequencies between time periods were observed and were indistinguishable from those obtained from tundrius/anatum breeding locations throughout their northern distribution. Estimates of harmonic mean Ne were variable and imprecise, but always greater than 500 when employing multiple temporal genetic methods.

\n
\n

These results, including those from simulations to assess the power of each method to estimate Ne, suggest a stable population consistent with data from field-based monitoring indicating that this species is stable or continuing to increase in abundance. Therefore, historic and continuing efforts to prevent the extinction of the peregrine falcon in North America appear successful, further highlighting the importance of archiving samples for continual assessment of population recovery and long-term viability.

","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS ONE","largerWorkSubtype":{"id":10,"text":"Journal Article"},"publisher":"PloS ONE","doi":"10.1371/journal.pone.0014042","usgsCitation":"Johnson, J., Talbot, S.L., Sage, G.K., Burnham, K.K., Brown, J.W., Maechtle, T.L., Seegar, W.S., Yates, M.A., Anderson, B., and Mindell, D.P., 2010, The use of genetics for the management of a recovering population: temporal assessment of migratory peregrine falcons in North America: PLoS ONE, v. 5, no. 11, e14042; 15 p., https://doi.org/10.1371/journal.pone.0014042.","productDescription":"e14042; 15 p.","ipdsId":"IP-022106","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":475457,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0014042","text":"Publisher Index Page"},{"id":292376,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":292350,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0014042"}],"volume":"5","issue":"11","noUsgsAuthors":false,"publicationDate":"2010-11-18","publicationStatus":"PW","scienceBaseUri":"53f25ff3e4b033341871897a","contributors":{"authors":[{"text":"Johnson, Jeff A.","contributorId":107208,"corporation":false,"usgs":true,"family":"Johnson","given":"Jeff A.","affiliations":[],"preferred":false,"id":498450,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Talbot, Sandra L. 0000-0002-3312-7214 stalbot@usgs.gov","orcid":"https://orcid.org/0000-0002-3312-7214","contributorId":140512,"corporation":false,"usgs":true,"family":"Talbot","given":"Sandra","email":"stalbot@usgs.gov","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":498441,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sage, George K. 0000-0003-1431-2286 ksage@usgs.gov","orcid":"https://orcid.org/0000-0003-1431-2286","contributorId":87833,"corporation":false,"usgs":true,"family":"Sage","given":"George","email":"ksage@usgs.gov","middleInitial":"K.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":498446,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burnham, Kurt K.","contributorId":94221,"corporation":false,"usgs":true,"family":"Burnham","given":"Kurt","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":498447,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brown, Joseph W.","contributorId":66179,"corporation":false,"usgs":true,"family":"Brown","given":"Joseph","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":498444,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Maechtle, Tom L.","contributorId":102804,"corporation":false,"usgs":true,"family":"Maechtle","given":"Tom","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":498449,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Seegar, William S.","contributorId":97013,"corporation":false,"usgs":true,"family":"Seegar","given":"William","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":498448,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Yates, Michael A.","contributorId":77058,"corporation":false,"usgs":true,"family":"Yates","given":"Michael","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":498445,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Anderson, Bud","contributorId":30920,"corporation":false,"usgs":true,"family":"Anderson","given":"Bud","email":"","affiliations":[],"preferred":false,"id":498443,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Mindell, David P.","contributorId":16762,"corporation":false,"usgs":false,"family":"Mindell","given":"David","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":498442,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70120726,"text":"70120726 - 2010 - Overview of selected surrogate technologies for high-temporal resolution suspended-sediment monitoring","interactions":[],"lastModifiedDate":"2014-08-15T15:52:36","indexId":"70120726","displayToPublicDate":"2013-08-15T15:49:00","publicationYear":"2010","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Overview of selected surrogate technologies for high-temporal resolution suspended-sediment monitoring","docAbstract":"

Traditional methods for characterizing selected properties of suspended sediments in rivers are being augmented and in some cases replaced by cost-effective surrogate instruments and methods that produce a temporally dense time series of quantifiably accurate data for use primarily in sediment-flux computations. Turbidity is the most common such surrogate technology, and the first to be sanctioned by the U.S. Geological Survey for use in producing data used in concert with water-discharge data to compute sediment concentrations and fluxes for storage in the National Water Information System. Other technologies, including laser-diffraction, digital photo-optic, acoustic-attenuation and backscatter, and pressure-difference techniques are being evaluated for producing reliable sediment concentration and, in some cases, particle-size distribution data. Each technology addresses a niche for sediment monitoring. Their performances range from compelling to disappointing. Some of these technologies have the potential to revolutionize fluvial-sediment data collection, analysis, and availability.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the Joint Federal Interagency Conference 2010: Hydrology and Sedimentation for a Changing Future: Existing and Emerging Issues: Las Vegas, NV, June 27-July 1, 2010","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","usgsCitation":"Gray, J.R., and Gartner, J.W., 2010, Overview of selected surrogate technologies for high-temporal resolution suspended-sediment monitoring, in Proceedings of the Joint Federal Interagency Conference 2010: Hydrology and Sedimentation for a Changing Future: Existing and Emerging Issues: Las Vegas, NV, June 27-July 1, 2010, 12 p.","productDescription":"12 p.","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":292341,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":292340,"type":{"id":15,"text":"Index Page"},"url":"https://acwi.gov/sos/pubs/2ndJFIC/"},{"id":292339,"type":{"id":11,"text":"Document"},"url":"https://acwi.gov/sos/pubs/2ndJFIC/Contents/3C_Gray_surrogates_3_3_2010_paper.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ef1ed6e4b0bfa1f993efe1","contributors":{"authors":[{"text":"Gray, John R. 0000-0002-8817-3701 jrgray@usgs.gov","orcid":"https://orcid.org/0000-0002-8817-3701","contributorId":1158,"corporation":false,"usgs":true,"family":"Gray","given":"John","email":"jrgray@usgs.gov","middleInitial":"R.","affiliations":[{"id":5058,"text":"Office of the Chief Scientist for Water","active":true,"usgs":true}],"preferred":true,"id":498430,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gartner, Jeffrey W.","contributorId":77524,"corporation":false,"usgs":true,"family":"Gartner","given":"Jeffrey","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":498431,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70120715,"text":"70120715 - 2010 - Development of a national, dynamic reservoir-sedimentation database","interactions":[],"lastModifiedDate":"2019-06-04T09:11:49","indexId":"70120715","displayToPublicDate":"2013-08-15T15:21:00","publicationYear":"2010","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Development of a national, dynamic reservoir-sedimentation database","docAbstract":"

The importance of dependable, long-term water supplies, coupled with the need to quantify rates of capacity loss of the Nation’s re servoirs due to sediment deposition, were the most compelling reasons for developing the REServoir- SEDimentation survey information (RESSED) database and website. Created under the auspices of the Advisory Committee on Water Information’s Subcommittee on Sedimenta ion by the U.S. Geological Survey and the Natural Resources Conservation Service, the RESSED database is the most comprehensive compilation of data from reservoir bathymetric and dry-basin surveys in the United States. As of March 2010, the database, which contains data compiled on the 1950s vintage Soil Conservation Service’s Form SCS-34 data sheets, contained results from 6,616 surveys on 1,823 reservoirs in the United States and two surveys on one reservoir in Puerto Rico. The data span the period 1755–1997, with 95 percent of the surveys performed from 1930–1990. The reservoir surface areas range from sub-hectare-scale farm ponds to 658 km2 Lake Powell. The data in the RESSED database can be useful for a number of purposes, including calculating changes in reservoir-storage characteristics, quantifying sediment budgets, and estimating erosion rates in a reservoir’s watershed.


The March 2010 version of the RESSED database has a number of deficiencies, including a cryptic and out-of-date database architecture; some geospatial inaccuracies (although most have been corrected); other data errors; an inability to store all data in a readily retrievable manner; and an inability to store all data types that currently exist. Perhaps most importantly, the March 2010 version of RESSED database provides no publicly available means to submit new data and corrections to existing data. To address these and other deficiencies, the Subcommittee on Sedimentation, through the U.S. Geological Survey and the U.S. Army Corps of Engineers, began a collaborative project in November 2009 to modernize the RESSED database architecture; provide public online input capability; and produce online reports. The ultimate goal of the Subcommittee on Sedimentation is to build a comprehensive, quality-assured database describing capacity changes over time for the largest suite of the Nation’s reservoirs.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the Joint Federal Interagency Conference 2010: Hydrology and Sedimentation for a Changing Future: Existing and Emerging Issues: Las Vegas, NV, June 27-July 1, 2010","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Joint Federal Interagency Conference 2010: Hydrology and Sedimentation for a Changing Future: Existing and Emerging Issues","conferenceDate":"June 27-July 1, 2010","conferenceLocation":"Las Vegas, Nevada","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","usgsCitation":"Gray, J.R., Bernard, J., Stewart, D.W., McFaul, E., Laurent, K., Schwarz, G., Stinson, J., Jonas, M., Randle, T., and Webb, J., 2010, Development of a national, dynamic reservoir-sedimentation database, in Proceedings of the Joint Federal Interagency Conference 2010: Hydrology and Sedimentation for a Changing Future: Existing and Emerging Issues: Las Vegas, NV, June 27-July 1, 2010, Las Vegas, Nevada, June 27-July 1, 2010, 12 p.","productDescription":"12 p.","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":292330,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":292327,"type":{"id":15,"text":"Index Page"},"url":"https://acwi.gov/sos/pubs/2ndJFIC/"},{"id":294561,"type":{"id":11,"text":"Document"},"url":"https://acwi.gov/sos/pubs/2ndJFIC/Contents/7C_Gray_ressed_3_4_2010_paper.pdf"}],"country":"United States;Puerto Rico","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 144.616667,13.233333 ], [ 144.616667,71.833333 ], [ -64.566667,71.833333 ], [ -64.566667,13.233333 ], [ 144.616667,13.233333 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ef1ec6e4b0bfa1f993ef07","contributors":{"authors":[{"text":"Gray, J. R.","contributorId":63372,"corporation":false,"usgs":true,"family":"Gray","given":"J.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":498419,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bernard, J.M.","contributorId":43999,"corporation":false,"usgs":true,"family":"Bernard","given":"J.M.","email":"","affiliations":[],"preferred":false,"id":498416,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stewart, D. W.","contributorId":86194,"corporation":false,"usgs":true,"family":"Stewart","given":"D.","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":498420,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McFaul, E.J.","contributorId":8465,"corporation":false,"usgs":true,"family":"McFaul","given":"E.J.","email":"","affiliations":[],"preferred":false,"id":498411,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Laurent, K.W.","contributorId":55351,"corporation":false,"usgs":true,"family":"Laurent","given":"K.W.","affiliations":[],"preferred":false,"id":498417,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schwarz, G. E. 0000-0002-9239-4566","orcid":"https://orcid.org/0000-0002-9239-4566","contributorId":14852,"corporation":false,"usgs":true,"family":"Schwarz","given":"G. E.","affiliations":[],"preferred":false,"id":498412,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stinson, J.T.","contributorId":22700,"corporation":false,"usgs":true,"family":"Stinson","given":"J.T.","email":"","affiliations":[],"preferred":false,"id":498413,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jonas, M.M.","contributorId":42143,"corporation":false,"usgs":true,"family":"Jonas","given":"M.M.","email":"","affiliations":[],"preferred":false,"id":498415,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Randle, T. J.","contributorId":59074,"corporation":false,"usgs":true,"family":"Randle","given":"T. J.","affiliations":[],"preferred":false,"id":498418,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Webb, J.W.","contributorId":40134,"corporation":false,"usgs":true,"family":"Webb","given":"J.W.","email":"","affiliations":[],"preferred":false,"id":498414,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70120689,"text":"70120689 - 2010 - Computing time-series suspended-sediment concentrations and loads from in-stream turbidity-sensor and streamflow data","interactions":[],"lastModifiedDate":"2014-08-15T14:14:44","indexId":"70120689","displayToPublicDate":"2013-08-15T14:07:00","publicationYear":"2010","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Computing time-series suspended-sediment concentrations and loads from in-stream turbidity-sensor and streamflow data","docAbstract":"

Over the last decade, use of a method for computing suspended-sediment concentration and loads using turbidity sensors—primarily nephelometry, but also optical backscatter—has proliferated. Because an in- itu turbidity sensor is capa le of measuring turbidity instantaneously, a turbidity time series can be recorded and related directly to time-varying suspended-sediment concentrations. Depending on the suspended-sediment characteristics of the measurement site, this method can be more reliable and, in many cases, a more accurate means for computing suspended-sediment concentrations and loads than traditional U.S. Geological Survey computational methods.


Guidelines and procedures for estimating time s ries of suspended-sediment concentration and loading as a function of turbidity and streamflow data have been published in a U.S. Geological Survey Techniques and Methods Report, Book 3, Chapter C4. This paper is a summary of these guidelines and discusses some of the concepts, s atistical procedures, and techniques used to maintain a multiyear suspended sediment time series.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the Joint Federal Interagency Conference 2010: Hydrology and Sedimentation for a Changing Future: Existing and Emerging Issues: Las Vegas, NV, June 27-July 1, 2010","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","usgsCitation":"Rasmussen, P.P., Gray, J.R., Glysson, G.D., and Ziegler, A., 2010, Computing time-series suspended-sediment concentrations and loads from in-stream turbidity-sensor and streamflow data, in Proceedings of the Joint Federal Interagency Conference 2010: Hydrology and Sedimentation for a Changing Future: Existing and Emerging Issues: Las Vegas, NV, June 27-July 1, 2010, 14 p.","productDescription":"14 p.","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":292317,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":292315,"type":{"id":15,"text":"Index Page"},"url":"https://acwi.gov/sos/pubs/2ndJFIC/"},{"id":292316,"type":{"id":11,"text":"Document"},"url":"https://acwi.gov/sos/pubs/2ndJFIC/Contents/8B_Rasmussen_03_01_10_paper.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ef1ec4e4b0bfa1f993eef6","contributors":{"authors":[{"text":"Rasmussen, Patrick P. 0000-0002-3287-6010 pras@usgs.gov","orcid":"https://orcid.org/0000-0002-3287-6010","contributorId":3530,"corporation":false,"usgs":true,"family":"Rasmussen","given":"Patrick","email":"pras@usgs.gov","middleInitial":"P.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":498387,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gray, John R. 0000-0002-8817-3701 jrgray@usgs.gov","orcid":"https://orcid.org/0000-0002-8817-3701","contributorId":1158,"corporation":false,"usgs":true,"family":"Gray","given":"John","email":"jrgray@usgs.gov","middleInitial":"R.","affiliations":[{"id":5058,"text":"Office of the Chief Scientist for Water","active":true,"usgs":true}],"preferred":true,"id":498386,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Glysson, G. Doug","contributorId":10340,"corporation":false,"usgs":true,"family":"Glysson","given":"G.","email":"","middleInitial":"Doug","affiliations":[],"preferred":false,"id":498388,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ziegler, Andrew C. aziegler@usgs.gov","contributorId":433,"corporation":false,"usgs":true,"family":"Ziegler","given":"Andrew C.","email":"aziegler@usgs.gov","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":498385,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70204141,"text":"70204141 - 2010 - Landscape indicators and land cover change in the Mid-Atlantic Region of the United States, 1973-2001","interactions":[],"lastModifiedDate":"2019-07-10T09:59:37","indexId":"70204141","displayToPublicDate":"2013-05-15T09:56:42","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1722,"text":"GIScience and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Landscape indicators and land cover change in the Mid-Atlantic Region of the United States, 1973-2001","docAbstract":"

Landscape indicators, derived from land use and land cover data as well as other data, were used to calculate the ecological consequences of land cover change in terms of nitrate loading and physical bird habitat. Both were modeled from 1973, 1992, and 2001 land cover data in the Mid-Atlantic region of the United States. Land cover statistics and trends are calculated for three time periods. In general, forest gain and agricultural loss was found in areas of improving landscape indicators and forest loss and agricultural gain was found to occur in areas of declining indicators, which was confirmed by high-resolution aerial photographic analysis.

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Terrence 0000-0002-5793-0503 tslonecker@usgs.gov","orcid":"https://orcid.org/0000-0002-5793-0503","contributorId":168591,"corporation":false,"usgs":true,"family":"Slonecker","given":"E.","email":"tslonecker@usgs.gov","middleInitial":"Terrence","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":36171,"text":"National Civil Applications Center","active":true,"usgs":true}],"preferred":true,"id":765690,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Milheim, Lesley lmilheim@usgs.gov","contributorId":168592,"corporation":false,"usgs":true,"family":"Milheim","given":"Lesley","email":"lmilheim@usgs.gov","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":765691,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Claggett, Peter R. 0000-0002-5335-2857 pclaggett@usgs.gov","orcid":"https://orcid.org/0000-0002-5335-2857","contributorId":176287,"corporation":false,"usgs":true,"family":"Claggett","given":"Peter","email":"pclaggett@usgs.gov","middleInitial":"R.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":765692,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70046817,"text":"70046817 - 2010 - Creation of next generation U.S. Geological Survey topographic maps","interactions":[],"lastModifiedDate":"2013-08-26T13:31:54","indexId":"70046817","displayToPublicDate":"2013-01-01T13:15:00","publicationYear":"2010","noYear":false,"publicationType":{"id":4,"text":"Book"},"publicationSubtype":{"id":12,"text":"Conference publication"},"title":"Creation of next generation U.S. Geological Survey topographic maps","docAbstract":"The U.S. Geological Survey (USGS) is 2 years into a 3-year cycle to create new digital topographic map products for the conterminous United States from data acquired and maintained as part of The National Map databases. These products are in the traditional, USGS topographic quadrangle, 7.5-minute (latitude and longitude) cell format. The 3-year cycle was conceived to follow the acquisition of National Aerial Imagery Program (NAIP) orthorectified imagery, a key layer in the new product. In fiscal year (FY) 2009 (ending September 30, 2009), the first year of the 3-year cycle, the USGS produced 13,200 products. These initial products of the “Digital MapBeta” series had limited feature content, including only the NAIP image, some roads, geographic names, and grid and collar information. The products were created in layered georegistered Portable Document Format (PDF) files, allowing users with freely available Adobe® Reader® software to view, print, and perform simple Geographic Information System-like functions. In FY 2010 (ending September 30, 2010), the USGS produced 20,380 products. These products of the “US Topo” series added hydrography (surface water features), contours, and some boundaries. In FY 2011 (ending September 30, 2011), the USGS will complete the initial coverage with US Topo products and will add additional feature content to the maps. The design, development, and production associated with the US Topo products provide management and technical challenges for the USGS and its public and private sector partners. One challenge is the acquisition and maintenance of nationally consistent base map data from multiple sources. Another is the use of these data to create a consistent, current series of cartographic products that can be used by the broad spectrum of traditional topographic map users. Although the USGS and its partners have overcome many of these challenges, many, such as establishing and funding a sustainable base data-maintenance program, remain to be resolved for the long term.","conferenceTitle":"ASPRS/CaGIS 2010 Fall Specialty Conference","conferenceDate":"2010-11-01T00:00:00","conferenceLocation":"Orlando, FL","language":"English","publisher":"ISPRS Technical Commission","usgsCitation":"Craun, K.J., 2010, Creation of next generation U.S. Geological Survey topographic maps, 4 p.","productDescription":"4 p.","numberOfPages":"4","ipdsId":"IP-024012","costCenters":[],"links":[{"id":277004,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":277002,"type":{"id":11,"text":"Document"},"url":"https://www.isprs.org/proceedings/XXXVIII/part4/files/Craun.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"521c78e4e4b01458f7842920","contributors":{"authors":[{"text":"Craun, Kari J. 0000-0001-7875-2809 kcraun@usgs.gov","orcid":"https://orcid.org/0000-0001-7875-2809","contributorId":3526,"corporation":false,"usgs":true,"family":"Craun","given":"Kari","email":"kcraun@usgs.gov","middleInitial":"J.","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true},{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":480359,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70047163,"text":"70047163 - 2010 - Making lidar more photogenic: creating band combinations from lidar information","interactions":[],"lastModifiedDate":"2013-07-23T12:46:44","indexId":"70047163","displayToPublicDate":"2013-01-01T12:32:00","publicationYear":"2010","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":"Making lidar more photogenic: creating band combinations from lidar information","docAbstract":"Over the past five to ten years the use and applicability of light detection and ranging (lidar) technology has increased dramatically. As a result, an almost exponential amount of lidar data is being collected across the country for a wide range of applications, and it is currently the technology of choice for high resolution terrain model creation, 3-dimensional city and infrastructure modeling, forestry and a wide range of scientific applications (Lin and Mills, 2010). The amount of data that is being delivered across the country is impressive. For example, the U.S. Geological Survey’s (USGS) Center for Lidar Information Coordination and Knowledge (CLICK), which is a National repository of USGS and partner lidar point cloud datasets (Stoker et al., 2006), currently has 3.5 percent of the United States covered by lidar, and has approximately another 5 percent in the processing queue. The majority of data being collected by the commercial sector are from discrete-return systems, which collect billions of lidar points in an average project. There are also a lot of discussions involving a potential National-scale Lidar effort (Stoker et al., 2008).","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Photogrammetric Engineering and Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Photogrammetric Engineering and Remote Sensing","usgsCitation":"Stoker, J.M., 2010, Making lidar more photogenic: creating band combinations from lidar information: Photogrammetric Engineering and Remote Sensing, v. 76, no. 3, p. 216-220.","productDescription":"5 p.","startPage":"216","endPage":"220","ipdsId":"IP-018975","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":275295,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275294,"type":{"id":11,"text":"Document"},"url":"https://digital.ipcprintservices.com/publication/?i=32898&&l=&m=&ver=&pp=&p=15"}],"volume":"76","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51efa5f2e4b0b09fbe58f199","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":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":481196,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70043234,"text":"70043234 - 2010 - A procedure for radiometric recalibration of Landsat 5 TM reflective-band data","interactions":[],"lastModifiedDate":"2013-02-27T17:49:39","indexId":"70043234","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1944,"text":"IEEE Transactions on Geoscience and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"A procedure for radiometric recalibration of Landsat 5 TM reflective-band data","docAbstract":"From the Landsat program's inception in 1972 to the present, the Earth science user community has been benefiting from a historical record of remotely sensed data. The multispectral data from the Landsat 5 (L5) Thematic Mapper (TM) sensor provide the backbone for this extensive archive. Historically, the radiometric calibration procedure for the L5 TM imagery used the detectors' response to the internal calibrator (IC) on a scene-by-scene basis to determine the gain and offset for each detector. The IC system degraded with time, causing radiometric calibration errors up to 20%. In May 2003, the L5 TM data processed and distributed by the U.S. Geological Survey (USGS) Earth Resources Observation and Science Center through the National Landsat Archive Production System (NLAPS) were updated to use a lifetime lookup-table (LUT) gain model to radiometrically calibrate TM data instead of using scene-specific IC gains. Further modification of the gain model was performed in 2007. The L5 TM data processed using IC prior to the calibration update do not benefit from the recent calibration revisions. A procedure has been developed to give users the ability to recalibrate their existing level-1 products. The best recalibration results are obtained if the work-order report that was included in the original standard data product delivery is available. However, if users do not have the original work-order report, the IC trends can be used for recalibration. The IC trends were generated using the radiometric gain trends recorded in the NLAPS database. This paper provides the details of the recalibration procedure for the following: 1) data processed using IC where users have the work-order file; 2) data processed using IC where users do not have the work-order file; 3) data processed using prelaunch calibration parameters; and 4) data processed using the previous version of the LUT (e.g., LUT03) that was released before April 2, 2007.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"IEEE Transactions on Geoscience and Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"IEEE","publisherLocation":"Washington, D.C.","doi":"10.1109/TGRS.2009.2026166","usgsCitation":"Chander, G., Haque, M., Micijevic, E., and Barsi, J., 2010, A procedure for radiometric recalibration of Landsat 5 TM reflective-band data: IEEE Transactions on Geoscience and Remote Sensing, v. 48, no. 1, p. 556-574, https://doi.org/10.1109/TGRS.2009.2026166.","productDescription":"19 p.","startPage":"556","endPage":"574","ipdsId":"IP-010187","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":268420,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":268395,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1109/TGRS.2009.2026166"}],"volume":"48","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"512f38f3e4b0cad81a732d8e","contributors":{"authors":[{"text":"Chander, G.","contributorId":51449,"corporation":false,"usgs":true,"family":"Chander","given":"G.","affiliations":[],"preferred":false,"id":473203,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haque, M.O. 0000-0002-0914-1446","orcid":"https://orcid.org/0000-0002-0914-1446","contributorId":73087,"corporation":false,"usgs":true,"family":"Haque","given":"M.O.","affiliations":[],"preferred":false,"id":473205,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Micijevic, E. 0000-0002-3828-9239","orcid":"https://orcid.org/0000-0002-3828-9239","contributorId":59939,"corporation":false,"usgs":true,"family":"Micijevic","given":"E.","affiliations":[],"preferred":false,"id":473204,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barsi, J. A.","contributorId":24085,"corporation":false,"usgs":true,"family":"Barsi","given":"J. A.","affiliations":[],"preferred":false,"id":473202,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70043685,"text":"70043685 - 2010 - Improving inferences from fisheries capture-recapture studies through remote detection of PIT tags","interactions":[],"lastModifiedDate":"2013-06-06T13:58:33","indexId":"70043685","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1657,"text":"Fisheries","onlineIssn":"1548-8446","printIssn":"0363-2415","active":true,"publicationSubtype":{"id":10}},"title":"Improving inferences from fisheries capture-recapture studies through remote detection of PIT tags","docAbstract":"Models for capture-recapture data are commonly used in analyses of the dynamics of fish and wildlife populations, especially for estimating vital parameters such as survival. Capture-recapture methods provide more reliable inferences than other methods commonly used in fisheries studies. However, for rare or elusive fish species, parameter estimation is often hampered by small probabilities of re-encountering tagged fish when encounters are obtained through traditional sampling methods. We present a case study that demonstrates how remote antennas for passive integrated transponder (PIT) tags can increase encounter probabilities and the precision of survival estimates from capture-recapture models. Between 1999 and 2007, trammel nets were used to capture and tag over 8,400 endangered adult Lost River suckers (Deltistes luxatus) during the spawning season in Upper Klamath Lake, Oregon. Despite intensive sampling at relatively discrete spawning areas, encounter probabilities from Cormack-Jolly-Seber models were consistently low (< 0.2) and the precision of apparent annual survival estimates was poor. Beginning in 2005, remote PIT tag antennas were deployed at known spawning locations to increase the probability of re-encountering tagged fish. We compare results based only on physical recaptures with results based on both physical recaptures and remote detections to demonstrate the substantial improvement in estimates of encounter probabilities (approaching 100%) and apparent annual survival provided by the remote detections. The richer encounter histories provided robust inferences about the dynamics of annual survival and have made it possible to explore more realistic models and hypotheses about factors affecting the conservation and recovery of this endangered species. Recent advances in technology related to PIT tags have paved the way for creative implementation of large-scale tagging studies in systems where they were previously considered impracticable.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Fisheries","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Taylor & Francis","doi":"10.1577/1548-8446-35.5.217","usgsCitation":"Hewitt, D.A., Janney, E.C., Hayes, B., and Shively, R.S., 2010, Improving inferences from fisheries capture-recapture studies through remote detection of PIT tags: Fisheries, v. 35, no. 5, p. 217-231, https://doi.org/10.1577/1548-8446-35.5.217.","productDescription":"15 p.","startPage":"217","endPage":"231","ipdsId":"IP-016069","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":273408,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":273407,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1577/1548-8446-35.5.217"}],"volume":"35","issue":"5","noUsgsAuthors":false,"publicationDate":"2010-05-01","publicationStatus":"PW","scienceBaseUri":"51b1bbd3e4b022a6a540f9e4","contributors":{"authors":[{"text":"Hewitt, David A. 0000-0002-5387-0275 dhewitt@usgs.gov","orcid":"https://orcid.org/0000-0002-5387-0275","contributorId":3767,"corporation":false,"usgs":false,"family":"Hewitt","given":"David","email":"dhewitt@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":474070,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Janney, Eric C. 0000-0002-0228-2174","orcid":"https://orcid.org/0000-0002-0228-2174","contributorId":83629,"corporation":false,"usgs":true,"family":"Janney","given":"Eric","email":"","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":474072,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hayes, Brian S. 0000-0001-8229-4070","orcid":"https://orcid.org/0000-0001-8229-4070","contributorId":37022,"corporation":false,"usgs":true,"family":"Hayes","given":"Brian S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":474071,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shively, Rip S. rsshively@usgs.gov","contributorId":233,"corporation":false,"usgs":true,"family":"Shively","given":"Rip","email":"rsshively@usgs.gov","middleInitial":"S.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":474069,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70044273,"text":"70044273 - 2010 - Correction for the 17O interference in δ(13C) measurements when analyzing CO2 with stable isotope mass spectrometry","interactions":[],"lastModifiedDate":"2021-03-31T15:35:16.846487","indexId":"70044273","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3207,"text":"Pure and Applied Chemistry","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Correction for the 17O interference in δ(13C) measurements when analyzing CO2 with stable isotope mass spectrometry","title":"Correction for the 17O interference in δ(13C) measurements when analyzing CO2 with stable isotope mass spectrometry","docAbstract":"Measurements of δ(13C) determined on CO2 with an isotope-ratio mass spectrometer (IRMS) must be corrected for the amount of 17O in the CO2. For data consistency, this must be done using identical methods by different laboratories. This report aims at unifying data treatment for CO2 IRMS by proposing (i) a unified set of numerical values, and (ii) a unified correction algorithm, based on a simple, linear approximation formula. Because the oxygen of natural CO2 is derived mostly from the global water pool, it is recommended that a value of 0.528 be employed for the factor λ, which relates differences in 17O and 18O abundances. With the currently accepted N(13C)/N(12C) of 0.011 180(28) in VPDB (Vienna Peedee belemnite) reevaluation of data yields a value of 0.000 393(1) for the oxygen isotope ratio N(17O)/N(16O) of the evolved CO2. The ratio of these quantities, a ratio of isotope ratios, is essential for the 17O abundance correction: [N(17O)/N(16O)]/[N(13C)/N(12C)] = 0.035 16(8). The equation [δ(13C) ≈ 45δVPDB-CO2 + 2 17R/13R (45δVPDB-CO2 – λ46δVPDB-CO2)] closely approximates δ(13C) values with less than 0.010 ‰ deviation for normal oxygen-bearing materials and no more than 0.026 ‰ in extreme cases. Other materials containing oxygen of non-mass-dependent isotope composition require a more specific data treatment. A similar linear approximation is also suggested for δ(18O). The linear approximations are easy to implement in a data spreadsheet, and also help in generating a simplified uncertainty budget.","language":"English","publisher":"IUPAC","publisherLocation":"Research Triangle Park, NC","doi":"10.1351/PAC-REP-09-01-05","usgsCitation":"Brand, W., Assonov, S.S., and Coplen, T.B., 2010, Correction for the 17O interference in δ(13C) measurements when analyzing CO2 with stable isotope mass spectrometry: Pure and Applied Chemistry, v. 82, no. 8, p. 1719-1733, https://doi.org/10.1351/PAC-REP-09-01-05.","productDescription":"15 p.","startPage":"1719","endPage":"1733","ipdsId":"IP-010248","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":475469,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1351/pac-rep-09-01-05","text":"Publisher Index Page"},{"id":271349,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"82","issue":"8","noUsgsAuthors":false,"publicationDate":"2010-05-26","publicationStatus":"PW","scienceBaseUri":"51765be5e4b0f989f99e00c8","contributors":{"authors":[{"text":"Brand, Willi A.","contributorId":38866,"corporation":false,"usgs":true,"family":"Brand","given":"Willi A.","affiliations":[],"preferred":false,"id":475226,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Assonov, Sergey S.","contributorId":13511,"corporation":false,"usgs":true,"family":"Assonov","given":"Sergey","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":475225,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coplen, Tyler B. 0000-0003-4884-6008 tbcoplen@usgs.gov","orcid":"https://orcid.org/0000-0003-4884-6008","contributorId":508,"corporation":false,"usgs":true,"family":"Coplen","given":"Tyler","email":"tbcoplen@usgs.gov","middleInitial":"B.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":475224,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70043232,"text":"70043232 - 2010 - An overview of sensor calibration inter-comparison and applications","interactions":[],"lastModifiedDate":"2013-04-08T20:29:34","indexId":"70043232","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1707,"text":"Frontiers of Earth Science in China","active":true,"publicationSubtype":{"id":10}},"title":"An overview of sensor calibration inter-comparison and applications","docAbstract":"Long-term climate data records (CDR) are often constructed using observations made by multiple Earth observing sensors over a broad range of spectra and a large scale in both time and space. These sensors can be of the same or different types operated on the same or different platforms. They can be developed and built with different technologies and are likely operated over different time spans. It has been known that the uncertainty of climate models and data records depends not only on the calibration quality (accuracy and stability) of individual sensors, but also on their calibration consistency across instruments and platforms. Therefore, sensor calibration inter-comparison and validation have become increasingly demanding and will continue to play an important role for a better understanding of the science product quality. This paper provides an overview of different methodologies, which have been successfully applied for sensor calibration inter-comparison. Specific examples using different sensors, including MODIS, AVHRR, and ETM+, are presented to illustrate the implementation of these methodologies.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Frontiers of Earth Science in China","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s11707-010-0002-z","usgsCitation":"Xiong, X., Cao, C., and Chander, G., 2010, An overview of sensor calibration inter-comparison and applications: Frontiers of Earth Science in China, v. 4, no. 2, p. 237-252, https://doi.org/10.1007/s11707-010-0002-z.","productDescription":"16 p.","startPage":"237","endPage":"252","ipdsId":"IP-017283","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":270674,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":270673,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s11707-010-0002-z"}],"volume":"4","issue":"2","noUsgsAuthors":false,"publicationDate":"2010-02-12","publicationStatus":"PW","scienceBaseUri":"5163e6e7e4b0b7010f820160","contributors":{"authors":[{"text":"Xiong, Xiaoxiong","contributorId":15088,"corporation":false,"usgs":true,"family":"Xiong","given":"Xiaoxiong","email":"","affiliations":[],"preferred":false,"id":473195,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cao, Changyong","contributorId":24663,"corporation":false,"usgs":true,"family":"Cao","given":"Changyong","email":"","affiliations":[],"preferred":false,"id":473196,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chander, Gyanesh gchander@usgs.gov","contributorId":3013,"corporation":false,"usgs":true,"family":"Chander","given":"Gyanesh","email":"gchander@usgs.gov","affiliations":[],"preferred":true,"id":473194,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70042228,"text":"70042228 - 2010 - Relationship and variation of qPCR and culturable enterococci estimates in ambient surface waters are predictable","interactions":[],"lastModifiedDate":"2013-03-10T15:13:13","indexId":"70042228","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Relationship and variation of qPCR and culturable enterococci estimates in ambient surface waters are predictable","docAbstract":"The quantitative polymerase chain reaction (qPCR) method provides rapid estimates of fecal indicator bacteria densities that have been indicated to be useful in the assessment of water quality. Primarily because this method provides faster results than standard culture-based methods, the U.S. Environmental Protection Agency is currently considering its use as a basis for revised ambient water quality criteria. In anticipation of this possibility, we sought to examine the relationship between qPCR-based and culture-based estimates of enterococci in surface waters. Using data from several research groups, we compared enterococci estimates by the two methods in water samples collected from 37 sites across the United States. A consistent linear pattern in the relationship between cell equivalents (CCE), based on the qPCR method, and colony-forming units (CFU), based on the traditional culturable method, was significant (P < 0.05) at most sites. A linearly decreasing variance of CCE with increasing CFU levels was significant (P < 0.05) or evident for all sites. Both marine and freshwater sites under continuous influence of point-source contamination tended to reveal a relatively constant proportion of CCE to CFU. The consistency in the mean and variance patterns of CCE versus CFU indicates that the relationship of results based on these two methods is more predictable at high CFU levels (e.g., log10CFU > 2.0/100 mL) while uncertainty increases at lower CFU values. It was further noted that the relative error in replicated qPCR estimates was generally higher than that in replicated culture counts even at relatively high target levels, suggesting a greater need for replicated analyses in the qPCR method to reduce relative error. Further studies evaluating the relationship between culture and qPCR should take into account analytical uncertainty as well as potential differences in results of these methods that may arise from sample variability, different sources of pollution, and environmental factors.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Science and Technology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"ACS Publications","publisherLocation":"Washington, D.C.","doi":"10.1021/es9028974","usgsCitation":"Whitman, R.L., Ge, Z., Nevers, M.B., Boehm, A., Chern, E.C., Haugland, R.A., Lukasik, A.M., Molina, M., Przybyla-Kelly, K., Shively, D.A., White, E.M., Zepp, R.G., and Byappanahalli, M., 2010, Relationship and variation of qPCR and culturable enterococci estimates in ambient surface waters are predictable: Environmental Science & Technology, v. 44, no. 13, p. 5049-5054, https://doi.org/10.1021/es9028974.","productDescription":"6 p.","startPage":"5049","endPage":"5054","ipdsId":"IP-019709","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":269039,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":269038,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/es9028974"}],"volume":"44","issue":"13","noUsgsAuthors":false,"publicationDate":"2010-06-08","publicationStatus":"PW","scienceBaseUri":"53cd7027e4b0b29085106e04","contributors":{"authors":[{"text":"Whitman, Richard L. rwhitman@usgs.gov","contributorId":542,"corporation":false,"usgs":true,"family":"Whitman","given":"Richard","email":"rwhitman@usgs.gov","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":471036,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ge, Zhongfu","contributorId":29709,"corporation":false,"usgs":true,"family":"Ge","given":"Zhongfu","affiliations":[],"preferred":false,"id":471039,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nevers, Meredith B.","contributorId":91803,"corporation":false,"usgs":true,"family":"Nevers","given":"Meredith","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":471046,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boehm, Alexandria B.","contributorId":51616,"corporation":false,"usgs":true,"family":"Boehm","given":"Alexandria B.","affiliations":[],"preferred":false,"id":471043,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chern, Eunice C.","contributorId":42500,"corporation":false,"usgs":true,"family":"Chern","given":"Eunice","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":471041,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Haugland, Richard A.","contributorId":102439,"corporation":false,"usgs":true,"family":"Haugland","given":"Richard","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":471048,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lukasik, Ashley M.","contributorId":32421,"corporation":false,"usgs":true,"family":"Lukasik","given":"Ashley","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":471040,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Molina, Marirosa","contributorId":102356,"corporation":false,"usgs":true,"family":"Molina","given":"Marirosa","affiliations":[],"preferred":false,"id":471047,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Przybyla-Kelly, Kasia","contributorId":79004,"corporation":false,"usgs":true,"family":"Przybyla-Kelly","given":"Kasia","affiliations":[],"preferred":false,"id":471045,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Shively, Dawn A. dshively@usgs.gov","contributorId":2051,"corporation":false,"usgs":true,"family":"Shively","given":"Dawn","email":"dshively@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":471037,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"White, Emily M.","contributorId":24664,"corporation":false,"usgs":true,"family":"White","given":"Emily","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":471038,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Zepp, Richard G.","contributorId":59703,"corporation":false,"usgs":true,"family":"Zepp","given":"Richard","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":471044,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Byappanahalli, Muruleedhara N.","contributorId":47335,"corporation":false,"usgs":true,"family":"Byappanahalli","given":"Muruleedhara N.","affiliations":[],"preferred":false,"id":471042,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70046093,"text":"70046093 - 2010 - Current challenges using models to forecast seawater intrusion: lessons from the Eastern Shore of Virginia, USA","interactions":[],"lastModifiedDate":"2018-10-11T17:47:42","indexId":"70046093","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Current challenges using models to forecast seawater intrusion: lessons from the Eastern Shore of Virginia, USA","docAbstract":"A three-dimensional model of the aquifer system of the Eastern Shore of Virginia, USA was calibrated to reproduce historical water levels and forecast the potential for saltwater intrusion. Future scenarios were simulated with two pumping schemes to predict potential areas of saltwater intrusion. Simulations suggest that only a few wells would be threatened with detectable salinity increases before 2050. The objective was to examine whether salinity increases can be accurately forecast for individual wells with such a model, and to address what the challenges are in making such model forecasts given current (2009) simulation capabilities. The analysis suggests that even with current computer capabilities, accurate simulations of concentrations within a regional-scale (many km) transition zone are computationally prohibitive. The relative paucity of data that is typical for such regions relative to what is needed for accurate transport simulations suggests that even with an infinitely powerful computer, accurate forecasting for a single well would still be elusive. Useful approaches may include local-grid refinement near wells and geophysical surveys, but it is important to keep expectations for simulated forecasts at wells in line with chloride concentration and other data that can be obtained at that local scale.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Hydrogeology Journal","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s10040-009-0513-4","usgsCitation":"Sanford, W.E., and Pope, J.P., 2010, Current challenges using models to forecast seawater intrusion: lessons from the Eastern Shore of Virginia, USA: Hydrogeology Journal, v. 18, no. 1, p. 73-93, https://doi.org/10.1007/s10040-009-0513-4.","productDescription":"21 p.","startPage":"73","endPage":"93","ipdsId":"IP-011118","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":272784,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294165,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10040-009-0513-4"}],"country":"United States","state":"Virginia","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -83.6754,36.5408 ], [ -83.6754,39.466 ], [ -75.2422,39.466 ], [ -75.2422,36.5408 ], [ -83.6754,36.5408 ] ] ] } } ] }","volume":"18","issue":"1","noUsgsAuthors":false,"publicationDate":"2009-08-25","publicationStatus":"PW","scienceBaseUri":"51a08be0e4b0e42455806566","contributors":{"authors":[{"text":"Sanford, Ward E. 0000-0002-6624-0280 wsanford@usgs.gov","orcid":"https://orcid.org/0000-0002-6624-0280","contributorId":2268,"corporation":false,"usgs":true,"family":"Sanford","given":"Ward","email":"wsanford@usgs.gov","middleInitial":"E.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":478893,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pope, Jason P. 0000-0003-3199-993X jpope@usgs.gov","orcid":"https://orcid.org/0000-0003-3199-993X","contributorId":2044,"corporation":false,"usgs":true,"family":"Pope","given":"Jason","email":"jpope@usgs.gov","middleInitial":"P.","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true},{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478892,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70045703,"text":"70045703 - 2010 - Prevalence of antibodies to type A influenza virus in wild avian species using two serologic assays","interactions":[],"lastModifiedDate":"2018-01-03T14:46:56","indexId":"70045703","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Prevalence of antibodies to type A influenza virus in wild avian species using two serologic assays","docAbstract":"

Serologic testing to detect antibodies to avian influenza (AI) virus has been an underused tool for the study of these viruses in wild bird populations, which traditionally has relied on virus isolation and reverse transcriptase-polymerase chain reaction (RT-PCR). In a preliminary study, a recently developed commercial blocking enzyme-linked immunosorbent assay (bELISA) had sensitivity and specificity estimates of 82% and 100%, respectively, for detection of antibodies to AI virus in multiple wild bird species after experimental infection. To further evaluate the efficacy of this commercial bELISA and the agar gel immunodiffusion (AGID) test for AI virus antibody detection in wild birds, we tested 2,249 serum samples collected from 62 wild bird species, representing 10 taxonomic orders. Overall, the bELISA detected 25.4% positive samples, whereas the AGID test detected 14.8%. At the species level, the bELISA detected as many or more positive serum samples than the AGID in all 62 avian species. The majority of positive samples, detected by both assays, were from species that use aquatic habitats, with the highest prevalence from species in the orders Anseriformes and Charadriiformes. Conversely, antibodies to AI virus were rarely detected in the terrestrial species. The serologic data yielded by both assays are consistent with the known epidemiology of AI virus in wild birds and published reports of host range based on virus isolation and RT-PCR. The results of this research are also consistent with the aforementioned study, which evaluated the performance of the bELISA and AGID test on experimental samples. Collectively, the data from these two studies indicate that the bELISA is a more sensitive serologic assay than the AGID test for detecting prior exposure to AI virus in wild birds. Based on these results, the bELISA is a reliable species-independent assay with potentially valuable applications for wild bird AI surveillance.

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Conventional triaxial compression tests were conducted at 40 MPa effective normal stress on saturated saw cut samples containing binary and ternary mixtures of quartz, montmorillonite, and illite. In all cases, frictional strengths of mixtures fall between the end-members of pure quartz (strongest) and clay (weakest). The overall trend was a decrease in strength with increasing clay content. In the illite/quartz mixture the trend was nearly linear, while in the montmorillonite mixtures a sigmoidal trend with three strength regimes was noted. Microstructural observations were performed on the deformed samples to characterize the geometric attributes of shear localization within the gouge layers. Two micromechanical models were used to analyze the critical clay fractions for the two-regime transitions on the basis of clay porosity and packing of the quartz grains. The transition from regime 1 (high strength) to 2 (intermediate strength) is associated with the shift from a stress-supporting framework of quartz grains to a clay matrix embedded with disperse quartz grains, manifested by the development of P-foliation and reduction in Riedel shear angle. The transition from regime 2 (intermediate strength) to 3 (low strength) is attributed to the development of shear localization in the clay matrix, occurring only when the neighboring layers of quartz grains are separated by a critical clay thickness. Our mixture data relating strength degradation to clay content agree well with strengths of natural shear zone materials obtained from scientific deep drilling projects.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research B: Solid Earth","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"AGU","doi":"10.1029/2009JB006383","usgsCitation":"Tembe, S., Lockner, D.A., and Wong, T., 2010, Effect of clay content and mineralogy on frictional sliding behavior of simulated gouges: binary and ternary mixtures of quartz, illite, and montmorillonite: Journal of Geophysical Research B: Solid Earth, v. 115, no. 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Water resources data are published annually for use by engineers, scientists, managers, educators, and the general public. These archival products supplement direct access to current and historical water data provided by NWISWeb. Beginning with Water Year 2006, annual water data reports are available as individual electronic Site Data Sheets for the entire Nation for retrieval, download, and localized printing on demand. National distribution includes tabular and map interfaces for search, query, display and download of data. From 1962 until 2005, reports were published by State as paper documents, although most reports since the mid-1990s are also available in electronic form through this web page. Reports prior to 1962 were published in occasional USGS Water-Supply Papers and other reports.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/wdr2010","usgsCitation":"Water Resources Division, U.S. Geological Survey, 2010, Water-resources data for the United States: water year 2010: U.S. Geological Survey Water Data Report 2010, HTML Document, https://doi.org/10.3133/wdr2010.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[],"links":[{"id":269341,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/wdr2010.jpg"},{"id":269339,"type":{"id":15,"text":"Index Page"},"url":"https://wdr.water.usgs.gov/wy2010/search.jsp","text":"Water-resources data for the United States Water Year 2010"},{"id":269340,"type":{"id":7,"text":"Companion Files"},"url":"https://wdr.water.usgs.gov/","text":"Annual Water Data Reports"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 172.5,18.9 ], [ 172.5,71.4 ], [ -66.9,71.4 ], [ -66.9,18.9 ], [ 172.5,18.9 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5142f18ce4b073a963ff6625","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":535454,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70045705,"text":"70045705 - 2010 - Model-based evaluation of highly and low pathogenic avian influenza dynamics in wild birds","interactions":[],"lastModifiedDate":"2013-04-30T10:54:26","indexId":"70045705","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Model-based evaluation of highly and low pathogenic avian influenza dynamics in wild birds","docAbstract":"There is growing interest in avian influenza (AI) epidemiology to predict disease risk in wild and domestic birds, and prevent transmission to humans. However, understanding the epidemic dynamics of highly pathogenic (HPAI) viruses remains challenging because they have rarely been detected in wild birds. We used modeling to integrate available scientific information from laboratory and field studies, evaluate AI dynamics in individual hosts and waterfowl populations, and identify key areas for future research. We developed a Susceptible-Exposed-Infectious-Recovered (SEIR) model and used published laboratory challenge studies to estimate epidemiological parameters (rate of infection, latency period, recovery and mortality rates), considering the importance of age classes, and virus pathogenicity. Infectious contact leads to infection and virus shedding within 1–2 days, followed by relatively slower period for recovery or mortality. We found a shorter infectious period for HPAI than low pathogenic (LP) AI, which may explain that HPAI has been much harder to detect than LPAI during surveillance programs. Our model predicted a rapid LPAI epidemic curve, with a median duration of infection of 50–60 days and no fatalities. In contrast, HPAI dynamics had lower prevalence and higher mortality, especially in young birds. Based on field data from LPAI studies, our model suggests to increase surveillance for HPAI in post-breeding areas, because the presence of immunologically naïve young birds is predicted to cause higher HPAI prevalence and bird losses during this season. Our results indicate a better understanding of the transmission, infection, and immunity-related processes is required to refine predictions of AI risk and spread, improve surveillance for HPAI in wild birds, and develop disease control strategies to reduce potential transmission to domestic birds and/or humans.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS ONE","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Public Library of Science","usgsCitation":"Hénaux, V., Samuel, M.D., and Bunck, C.M., 2010, Model-based evaluation of highly and low pathogenic avian influenza dynamics in wild birds: PLoS ONE, v. 5, no. 6, e10997.","productDescription":"e10997","costCenters":[{"id":675,"text":"Wisconsin Cooperative Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":271638,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5180e7e8e4b0df838b924d75","contributors":{"authors":[{"text":"Hénaux, Viviane","contributorId":47670,"corporation":false,"usgs":true,"family":"Hénaux","given":"Viviane","affiliations":[],"preferred":false,"id":478120,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Samuel, Michael D. msamuel@usgs.gov","contributorId":1419,"corporation":false,"usgs":true,"family":"Samuel","given":"Michael","email":"msamuel@usgs.gov","middleInitial":"D.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":478119,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bunck, Christine M. cbunck@usgs.gov","contributorId":731,"corporation":false,"usgs":true,"family":"Bunck","given":"Christine","email":"cbunck@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":478118,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70043486,"text":"70043486 - 2010 - Longitudinal structure in temperate stream fish communities: evaluating conceptual models with temporal data","interactions":[],"lastModifiedDate":"2013-03-26T14:31:33","indexId":"70043486","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Longitudinal structure in temperate stream fish communities: evaluating conceptual models with temporal data","docAbstract":"Five conceptual models of longitudinal fish community organization in streams were examined: (1) niche diversity model (NDM), (2) stream continuum model (SCM), (3) immigrant accessibility model (IAM), (4) environmental stability model (ESM), and (5) adventitious stream model (ASM). We used differences among models in their predictions about temporal species turnover, along with five spatiotemporal fish community data sets, to evaluate model applicability. Models were similar in predicting a positive species richness–stream size relationship and longitudinal species nestedness, but differed in predicting either similar temporal species turnover throughout the stream continuum (NDM, SCM), higher turnover upstream (IAM, ESM), or higher turnover downstream (ASM). We calculated measures of spatial and temporal variation from spatiotemporal fish data in five wadeable streams in central and eastern North America spanning 34–68 years (French Creek [New York], Piasa Creek [Illinois], Spruce Run [Virginia], Little Stony Creek [Virginia], and Sinking Creek [Virginia]). All streams exhibited substantial species turnover (i.e., at least 27% turnover in stream-scale species pools), in contrast to the predictions of the SCM. Furthermore, community change was greater in downstream than upstream reaches in four of five streams. This result is most consistent with the ASM and suggests that downstream communities are strongly influenced by migrants to and from species pools outside the focal stream. In Sinking Creek, which is isolated from external species pools, temporal species turnover (via increased richness) was higher upstream than downstream, which is a pattern most consistent with the IAM or ESM. These results corroborate the hypothesis that temperate stream habitats and fish communities are temporally dynamic and that fish migration and environmental disturbances play fundamental roles in stream fish community organization.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Community ecology of stream fishes : concepts, approaches, and techniques; American Fisheries Symposium 73","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"American Fisheries Society","publisherLocation":"Bethesda, MD","usgsCitation":"Roberts, J.H., and Hitt, N.P., 2010, Longitudinal structure in temperate stream fish communities: evaluating conceptual models with temporal data, in Community ecology of stream fishes : concepts, approaches, and techniques; American Fisheries Symposium 73, 19 p.","productDescription":"19 p.","ipdsId":"IP-024159","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":270191,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5152c398e4b01197b08e9cb5","contributors":{"authors":[{"text":"Roberts, James H.","contributorId":83811,"corporation":false,"usgs":true,"family":"Roberts","given":"James","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":473692,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hitt, Nathaniel P. 0000-0002-1046-4568 nhitt@usgs.gov","orcid":"https://orcid.org/0000-0002-1046-4568","contributorId":4435,"corporation":false,"usgs":true,"family":"Hitt","given":"Nathaniel","email":"nhitt@usgs.gov","middleInitial":"P.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":473691,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70042315,"text":"70042315 - 2010 - Low-altitude aerial color digital photographic survey of the San Andreas Fault","interactions":[],"lastModifiedDate":"2019-06-03T13:30:12","indexId":"70042315","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Low-altitude aerial color digital photographic survey of the San Andreas Fault","docAbstract":"

Ever since 1858, when Gaspard-Félix Tournachon (pen name Félix Nadar) took the first aerial photograph (Professional Aerial Photographers Association 2009), the scientific value and popular appeal of such pictures have been widely recognized. Indeed, Nadar patented the idea of using aerial photographs in mapmaking and surveying. Since then, aerial imagery has flourished, eventually making the leap to space and to wavelengths outside the visible range. Yet until recently, the availability of such surveys has been limited to technical organizations with significant resources. Geolocation required extensive time and equipment, and distribution was costly and slow. While these situations still plague older surveys, modern digital photography and lidar systems acquire well-calibrated and easily shared imagery, although expensive, platform-specific software is sometimes still needed to manage and analyze the data. With current consumer-level electronics (cameras and computers) and broadband internet access, acquisition and distribution of large imaging data sets are now possible for virtually anyone. In this paper we demonstrate a simple, low-cost means of obtaining useful aerial imagery by reporting two new, high-resolution, low-cost, color digital photographic surveys of selected portions of the San Andreas fault in California. All pictures are in standard jpeg format. The first set of imagery covers a 92-km-long section of the fault in Kern and San Luis Obispo counties and includes the entire Carrizo Plain. The second covers the region from Lake of the Woods to Cajon Pass in Kern, Los Angeles, and San Bernardino counties (151 km) and includes Lone Pine Canyon soon after the ground was largely denuded by the Sheep Fire of October 2009. The first survey produced a total of 1,454 oblique digital photographs (4,288 x 2,848 pixels, average 6 Mb each) and the second produced 3,762 nadir images from an elevation of approximately 150 m above ground level (AGL) on the southeast leg and 300 m AGL on the northwest leg. Spatial resolution (pixel size or ground sample distance) is a few centimeters. Time and geographic coordinates of the aircraft were automatically written into the exchangeable image file format (EXIF) data within each jpeg photograph. A few hours after acquisition and validation, the photographs were uploaded to a publicly accessible Web page. The goal was to obtain quick-turnaround, low-cost, high-resolution, overlapping, and contiguous imagery for use in planning field operations, and to provide imagery for a wide variety of land use and educational studies. This work was carried out in support of ongoing geological research on the San Andreas fault, but the technique is widely applicable beyond geology.

","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Seismological Research Letters","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"SSA","doi":"10.1785/gssrl.81.3.453","usgsCitation":"Lynch, D.K., Hudnut, K.W., and Dearborn, D.S., 2010, Low-altitude aerial color digital photographic survey of the San Andreas Fault: Seismological Research Letters, v. 81, no. 3, p. 453-459, https://doi.org/10.1785/gssrl.81.3.453.","productDescription":"7 p.","startPage":"453","endPage":"459","ipdsId":"IP-018453","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":274098,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":274097,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1785/gssrl.81.3.453"}],"country":"United States","state":"California","otherGeospatial":"San Andreas Fault","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.41,32.53 ], [ -124.41,42.01 ], [ -114.13,42.01 ], [ -114.13,32.53 ], [ -124.41,32.53 ] ] ] } } ] }","volume":"81","issue":"3","noUsgsAuthors":false,"publicationDate":"2010-05-13","publicationStatus":"PW","scienceBaseUri":"51c96a69e4b0a50a6e8f5825","contributors":{"authors":[{"text":"Lynch, David K.","contributorId":88600,"corporation":false,"usgs":true,"family":"Lynch","given":"David","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":471265,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hudnut, Kenneth W. 0000-0002-3168-4797 hudnut@usgs.gov","orcid":"https://orcid.org/0000-0002-3168-4797","contributorId":2550,"corporation":false,"usgs":true,"family":"Hudnut","given":"Kenneth","email":"hudnut@usgs.gov","middleInitial":"W.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":471263,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dearborn, David S.P.","contributorId":27343,"corporation":false,"usgs":true,"family":"Dearborn","given":"David","email":"","middleInitial":"S.P.","affiliations":[],"preferred":false,"id":471264,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70043823,"text":"70043823 - 2010 - Diel behavior of rearing fall Chinook salmon","interactions":[],"lastModifiedDate":"2013-04-25T09:39:29","indexId":"70043823","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2901,"text":"Northwestern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Diel behavior of rearing fall Chinook salmon","docAbstract":"In fisheries science, habitat use is often inferred when fish are sampled or observed in a particular location. Physical habitat is typically measured where fish are found, and thus deemed important to habitat use. Although less common, a more informative approach is to measure or observe fish behavior within given habitats to more thoroughly assess their use of those locations. While this approach better reflects how fish use habitat, fish behavior can be difficult to quantify, particularly at night. For example, Tiffan and others (2002, 2006) were able to quantify habitat availability and characteristics that were important for rearing juvenile fall Chinook Salmon (Oncorhynchus tshawytscha) in the Hanford Reach of the Columbia River. The authors, however, could only speculate as to how juvenile salmon use habitat and respond to changes in water level fluctuations. Conversely, in this study we provide data on the diel activities of rearing juvenile wild fall Chinook Salmon which provides a better understanding of how fish “use” these rearing habitats. Diel behavior patterns are important because fish in the Hanford Reach are often stranded on shorelines when the water level rapidly recedes because of hydroelectric power generation at upriver dams (Nugent and others 2002; Anglin and others 2006). We hypothesize that juvenile salmon are at greater risk of stranding at night because they are less active and occupy habitat differently than during the day. We used underwater videography to collect behavioral information during the day and night to determine if juvenile fall Chinook Salmon are more susceptible to stranding when water level fluctuations occur at night.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Northwestern Naturalist","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Society for Northwestern Vertebrate Biology","doi":"10.1898/NWN10-11.1","usgsCitation":"Tiffan, K.F., Kock, T.J., and Skalicky, J., 2010, Diel behavior of rearing fall Chinook salmon: Northwestern Naturalist, v. 91, no. 3, p. 342-345, https://doi.org/10.1898/NWN10-11.1.","productDescription":"4 p.","startPage":"342","endPage":"345","ipdsId":"IP-019739","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":271451,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271450,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1898/NWN10-11.1"}],"volume":"91","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"517a5066e4b072c16ef14b04","contributors":{"authors":[{"text":"Tiffan, Kenneth F. 0000-0002-5831-2846 ktiffan@usgs.gov","orcid":"https://orcid.org/0000-0002-5831-2846","contributorId":3200,"corporation":false,"usgs":true,"family":"Tiffan","given":"Kenneth","email":"ktiffan@usgs.gov","middleInitial":"F.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":474275,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kock, Tobias J. 0000-0001-8976-0230 tkock@usgs.gov","orcid":"https://orcid.org/0000-0001-8976-0230","contributorId":3038,"corporation":false,"usgs":true,"family":"Kock","given":"Tobias","email":"tkock@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":474274,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Skalicky, Joseph J.","contributorId":91386,"corporation":false,"usgs":true,"family":"Skalicky","given":"Joseph J.","affiliations":[],"preferred":false,"id":474276,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70044492,"text":"70044492 - 2010 - Aviation response to a widely dispersed volcanic ash and gas cloud from the August 2008 eruption of Kasatochi, Alaska, USA","interactions":[],"lastModifiedDate":"2013-04-10T22:29:28","indexId":"70044492","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2316,"text":"Journal of Geophysical Research D: Atmospheres","active":true,"publicationSubtype":{"id":10}},"title":"Aviation response to a widely dispersed volcanic ash and gas cloud from the August 2008 eruption of Kasatochi, Alaska, USA","docAbstract":"The extensive volcanic cloud from Kasatochi's 2008 eruption caused widespread disruptions to aviation operations along Pacific oceanic, Canadian, and U.S. air routes. Based on aviation hazard warnings issued by the National Oceanic and Atmospheric Administration, U.S. Geological Survey, the Federal Aviation Administration, and Meteorological Service of Canada, air carriers largely avoided the volcanic cloud over a 5 day period by route modifications and flight cancellations. Comparison of time coincident GOES thermal infrared (TIR) data for ash detection with Ozone Monitoring Instrument (OMI) ultraviolet data for SO2 detection shows congruent areas of ash and gas in the volcanic cloud in the 2 days following onset of ash production. After about 2.5 days, the area of SO2 detected by OMI was more extensive than the area of ash indicated by TIR data, indicating significant ash depletion by fall out had occurred. Pilot reports of visible haze at cruise altitudes over Canada and the northern United States suggested that SO2 gas had converted to sulfate aerosols. Uncertain about the hazard potential of the aging cloud, airlines coped by flying over, under, or around the observed haze layer. Samples from a nondamaging aircraft encounter with Kasatochi's nearly 3 day old cloud contained volcanic silicate particles, confirming that some fine ash is present in predominantly gas clouds. The aircraft's exposure to ash was insufficient to cause engine damage; however, slightly damaging encounters with volcanic clouds from eruptions of Reventador in 2002 and Hekla in 2000 indicate the possibility of lingering hazards associated with old and/or diffuse volcanic clouds.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research D: Atmospheres","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"AGU","publisherLocation":"Washington, D.C.","doi":"10.1029/2010JD013868","usgsCitation":"Guffanti, M., Schneider, D.J., Wallace, K., Hall, T., Bensimon, D.R., and Salinas, L.J., 2010, Aviation response to a widely dispersed volcanic ash and gas cloud from the August 2008 eruption of Kasatochi, Alaska, USA: Journal of Geophysical Research D: Atmospheres, v. 115, no. D2, D00L19, https://doi.org/10.1029/2010JD013868.","productDescription":"D00L19","ipdsId":"IP-018797","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":270802,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":270801,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1029/2010JD013868"}],"country":"United States","state":"Alaska","otherGeospatial":"Kasatochi","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -175.53276,52.159789 ], [ -175.53276,52.190495 ], [ -175.482788,52.190495 ], [ -175.482788,52.159789 ], [ -175.53276,52.159789 ] ] ] } } ] }","volume":"115","issue":"D2","noUsgsAuthors":false,"publicationDate":"2010-11-23","publicationStatus":"PW","scienceBaseUri":"516689e0e4b0bba30b388bbf","contributors":{"authors":[{"text":"Guffanti, Marianne","contributorId":68257,"corporation":false,"usgs":true,"family":"Guffanti","given":"Marianne","affiliations":[],"preferred":false,"id":475724,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schneider, David J. 0000-0001-9092-1054 djschneider@usgs.gov","orcid":"https://orcid.org/0000-0001-9092-1054","contributorId":633,"corporation":false,"usgs":true,"family":"Schneider","given":"David","email":"djschneider@usgs.gov","middleInitial":"J.","affiliations":[{"id":121,"text":"Alaska Volcano Observatory","active":false,"usgs":true}],"preferred":false,"id":475721,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wallace, Kristi L.","contributorId":20054,"corporation":false,"usgs":true,"family":"Wallace","given":"Kristi L.","affiliations":[],"preferred":false,"id":475722,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hall, Tony","contributorId":29284,"corporation":false,"usgs":true,"family":"Hall","given":"Tony","email":"","affiliations":[],"preferred":false,"id":475723,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bensimon, Dov R.","contributorId":99852,"corporation":false,"usgs":true,"family":"Bensimon","given":"Dov","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":475726,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Salinas, Leonard J.","contributorId":86660,"corporation":false,"usgs":true,"family":"Salinas","given":"Leonard","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":475725,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}