{"pageNumber":"568","pageRowStart":"14175","pageSize":"25","recordCount":46856,"records":[{"id":70048226,"text":"sir20135149 - 2013 - Geologic framework, structure, and hydrogeologic characteristics of the Knippa Gap area in eastern Uvalde and western Medina Counties, Texas","interactions":[],"lastModifiedDate":"2016-08-05T13:41:00","indexId":"sir20135149","displayToPublicDate":"2013-09-17T13:55:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5149","title":"Geologic framework, structure, and hydrogeologic characteristics of the Knippa Gap area in eastern Uvalde and western Medina Counties, Texas","docAbstract":"<p>The Edwards aquifer is the primary source of potable water for the San Antonio area in south-central Texas. The Knippa Gap was postulated to channel or restrict flow in the Edwards aquifer in eastern Uvalde County, and its existence was based on a series of numerical simulations of groundwater flow in the aquifer. To better understand the function of the area known as the Knippa Gap as it pertains to its geology and structure, the geologic framework, structure, and hydrogeologic characteristics of the area were evaluated by the U.S. Geological Survey in cooperation with the U.S. Army Corps of Engineers-Fort Worth District.</p>\n<p>The principal structural feature in the San Antonio area is the Balcones Fault Zone, which is the result of Miocene age faulting. In Medina County, the faulting of the Balcones Fault Zone has produced a relay-ramp structure that dips to the southwest from the Edwards aquifer recharge zone and extends westward and below land surface from Seco Creek.</p>\n<p>Groundwater flow paths in the Edwards aquifer are influenced by faulting and geologic structure. Some faults act as barriers to groundwater flow paths where the aquifer is offset by 50 percent or more and result in flow moving parallel to the fault. The effectiveness of a fault as a barrier to flow changes as the amount of fault displacement changes. The structurally complex area of the Balcones Fault Zone contains relay ramps, which form in extensional fault systems to allow for deformation changes along the fault block. In Medina County, the faulting of the Balcones Fault Zone has produced a relay-ramp structure that dips to the southwest from the Edwards aquifer recharge zone. Groundwater moving down the relay ramp in northern Medina County flows downgradient (downdip) to the structural low (trough) from the northeast to the southwest. In Uvalde County, the beds dip from a structural high known as the Uvalde Salient. This results in groundwater moving from the structural high and downgradient (dip) towards a structural low (trough) to the northeast. These two opposing structural dips result in a subsurface structural low (trough) locally referred to as the Knippa Gap. This trough is located in eastern Uvalde County beneath the towns of Knippa and Sabinal.</p>\n<p>By using data that were compiled and collected for this study and previous studies, a revised map was constructed depicting the geologic framework, structure, and hydrogeologic characteristics of the Knippa Gap area in eastern Uvalde and western Medina Counties, Tex. The map also shows the interpreted structural dip directions and interpreted location of a structural low (trough) in the area known as the Knippa Gap.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135149","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Clark, A.K., Pedraza, D.E., and Morris, R., 2013, Geologic framework, structure, and hydrogeologic characteristics of the Knippa Gap area in eastern Uvalde and western Medina Counties, Texas: U.S. Geological Survey Scientific Investigations Report 2013-5149, Report: viii, 36 p.; Plate: 23.00 inches x 36.00 inches, https://doi.org/10.3133/sir20135149.","productDescription":"Report: viii, 36 p.; Plate: 23.00 inches x 36.00 inches","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":277658,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135149.gif"},{"id":277657,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2013/5149/pdf/sir2013-5149_pl1.pdf","text":"Plate 1"},{"id":277655,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5149/pdf/sir2013-5149.pdf"},{"id":277656,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5149/"}],"country":"United States","state":"Texas","county":"Medina County, Uvalde County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -100.47,28.4977 ], [ -100.47,30.2733 ], [ -97.3718,30.2733 ], [ -97.3718,28.4977 ], [ -100.47,28.4977 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52396bf7e4b04b9308ae4e24","contributors":{"authors":[{"text":"Clark, Allan K. 0000-0003-0099-1521 akclark@usgs.gov","orcid":"https://orcid.org/0000-0003-0099-1521","contributorId":1279,"corporation":false,"usgs":true,"family":"Clark","given":"Allan","email":"akclark@usgs.gov","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":484050,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pedraza, Diana E. 0000-0003-4483-8094 dpedraza@usgs.gov","orcid":"https://orcid.org/0000-0003-4483-8094","contributorId":1281,"corporation":false,"usgs":false,"family":"Pedraza","given":"Diana","email":"dpedraza@usgs.gov","middleInitial":"E.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":484051,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morris, Robert R. 0000-0001-7504-3732","orcid":"https://orcid.org/0000-0001-7504-3732","contributorId":106213,"corporation":false,"usgs":true,"family":"Morris","given":"Robert R.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":484052,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70125644,"text":"70125644 - 2013 - Host range, host ecology, and distribution of more than 11800 fish parasite species","interactions":[],"lastModifiedDate":"2014-09-17T13:34:45","indexId":"70125644","displayToPublicDate":"2013-09-17T13:30:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Host range, host ecology, and distribution of more than 11800 fish parasite species","docAbstract":"Our data set includes 38 008 fish parasite records (for Acanthocephala, Cestoda, Monogenea, Nematoda, Trematoda) compiled from the scientific literature, Internet databases, and museum collections paired to the corresponding host ecological, biogeographical, and phylogenetic traits (maximum length, growth rate, life span, age at maturity, trophic level, habitat preference, geographical range size, taxonomy). The data focus on host features, because specific parasite traits are not consistently available across records. For this reason, the data set is intended as a flexible resource able to extend the principles of ecological niche modeling to the host–parasite system, providing researchers with the data to model parasite niches based on their distribution in host species and the associated host features. In this sense, the database offers a framework for testing general ecological, biogeographical, and phylogenetic hypotheses based on the identification of hosts as parasite habitat. Potential applications of the data set are, for example, the investigation of species–area relationships or the taxonomic distribution of host-specificity. The provided host–parasite list is that currently used by Fish Parasite Ecology Software Tool (FishPEST, <a href=\"http://purl.oclc.org/fishpest\" target=\"_blank\">http://purl.oclc.org/fishpest</a>), which is a website that allows researchers to model several aspects of the relationships between fish parasites and their hosts. The database is intended for researchers who wish to have more freedom to analyze the database than currently possible with FishPEST. However, for readers who have not seen FishPEST, we recommend using this as a starting point for interacting with the database.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Ecological Society of America","doi":"10.1890/12-1419.1","usgsCitation":"Strona, G., Palomares, M.L., Bailly, N., Galli, P., and Lafferty, K.D., 2013, Host range, host ecology, and distribution of more than 11800 fish parasite species: Ecology, v. 94, no. 2, https://doi.org/10.1890/12-1419.1.","productDescription":"1 p.","startPage":"544","ipdsId":"IP-041812","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":294060,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294025,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/12-1419.1"}],"volume":"94","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"541aa29ee4b01571b3d51cc2","contributors":{"authors":[{"text":"Strona, Giovanni","contributorId":62940,"corporation":false,"usgs":true,"family":"Strona","given":"Giovanni","email":"","affiliations":[],"preferred":false,"id":501528,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Palomares, Maria Lourdes D.","contributorId":16330,"corporation":false,"usgs":true,"family":"Palomares","given":"Maria","email":"","middleInitial":"Lourdes D.","affiliations":[],"preferred":false,"id":501527,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bailly, Nicholas","contributorId":99902,"corporation":false,"usgs":true,"family":"Bailly","given":"Nicholas","email":"","affiliations":[],"preferred":false,"id":501530,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Galli, Paolo","contributorId":89459,"corporation":false,"usgs":true,"family":"Galli","given":"Paolo","email":"","affiliations":[],"preferred":false,"id":501529,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":501526,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70125650,"text":"70125650 - 2013 - Predicting what helminth parasites a fish species should have using Parasite Co-occurrence Modeler (PaCo)","interactions":[],"lastModifiedDate":"2014-09-17T13:09:20","indexId":"70125650","displayToPublicDate":"2013-09-17T13:04:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2414,"text":"Journal of Parasitology","active":true,"publicationSubtype":{"id":10}},"title":"Predicting what helminth parasites a fish species should have using Parasite Co-occurrence Modeler (PaCo)","docAbstract":"Fish pathologists are often interested in which parasites would likely be present in a particular host. Parasite Co-occurrence Modeler (PaCo) is a tool for identifying a list of parasites known from fish species that are similar ecologically, phylogenetically, and geographically to the host of interest. PaCo uses data from FishBase (maximum length, growth rate, life span, age at maturity, trophic level, phylogeny, and biogeography) to estimate compatibility between a target host and parasite species–genera from the major helminth groups (Acanthocephala, Cestoda, Monogenea, Nematoda, and Trematoda). Users can include any combination of host attributes in a model. These unique features make PaCo an innovative tool for addressing both theoretical and applied questions in parasitology. In addition to predicting the occurrence of parasites, PaCo can be used to investigate how host characteristics shape parasite communities. To test the performance of the PaCo algorithm, we created 12,400 parasite lists by applying any possible combination of model parameters (248) to 50 fish hosts. We then measured the relative importance of each parameter by assessing their frequency in the best models for each host. Host phylogeny and host geography were identified as the most important factors, with both present in 88% of the best models. Habitat (64%) was identified in more than half of the best models. Among ecological parameters, trophic level (41%) was the most relevant while life span (34%), growth rate (32%), maximum length (28%), and age at maturity (20%) were less commonly linked to best models. PaCo is free to use at <a href=\"www.purl.oclc.org/fishpest\" target=\"_blank\">www.purl.oclc.org/fishpest</a>.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Parasitology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Society of Parasitologists","doi":"10.1645/GE-3147.1","usgsCitation":"Strona, G., and Lafferty, K.D., 2013, Predicting what helminth parasites a fish species should have using Parasite Co-occurrence Modeler (PaCo): Journal of Parasitology, v. 99, no. 1, p. 6-10, https://doi.org/10.1645/GE-3147.1.","productDescription":"5 p.","startPage":"6","endPage":"10","ipdsId":"IP-038365","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":294054,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294036,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1645/GE-3147.1"}],"volume":"99","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"541aa2a6e4b01571b3d51d13","contributors":{"authors":[{"text":"Strona, Giovanni","contributorId":62940,"corporation":false,"usgs":true,"family":"Strona","given":"Giovanni","email":"","affiliations":[],"preferred":false,"id":501541,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":501540,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70048198,"text":"70048198 - 2013 - Semiautomated tremor detection using a combined cross-correlation and neural network approach","interactions":[],"lastModifiedDate":"2013-10-23T14:42:43","indexId":"70048198","displayToPublicDate":"2013-09-17T11:40:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Semiautomated tremor detection using a combined cross-correlation and neural network approach","docAbstract":"Despite observations of tectonic tremor in many locations around the globe, the emergent phase arrivals, low‒amplitude waveforms, and variable event durations make automatic detection a nontrivial task. In this study, we employ a new method to identify tremor in large data sets using a semiautomated technique. The method first reduces the data volume with an envelope cross‒correlation technique, followed by a Self‒Organizing Map (SOM) algorithm to identify and classify event types. The method detects tremor in an automated fashion after calibrating for a specific data set, hence we refer to it as being “semiautomated”. We apply the semiautomated detection algorithm to a newly acquired data set of waveforms from a temporary deployment of 13 seismometers near Cholame, California, from May 2010 to July 2011. We manually identify tremor events in a 3 week long test data set and compare to the SOM output and find a detection accuracy of 79.5%. Detection accuracy improves with increasing signal‒to‒noise ratios and number of available stations. We find detection completeness of 96% for tremor events with signal‒to‒noise ratios above 3 and optimal results when data from at least 10 stations are available. We compare the SOM algorithm to the envelope correlation method of Wech and Creager and find the SOM performs significantly better, at least for the data set examined here. Using the SOM algorithm, we detect 2606 tremor events with a cumulative signal duration of nearly 55 h during the 13 month deployment. Overall, the SOM algorithm is shown to be a flexible new method that utilizes characteristics of the waveforms to identify tremor from noise or other seismic signals.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research B: Solid Earth","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Geophysical Union","doi":"10.1002/jgrb.50345","usgsCitation":"Horstmann, T., Harrington, R., and Cochran, E.S., 2013, Semiautomated tremor detection using a combined cross-correlation and neural network approach: Journal of Geophysical Research B: Solid Earth, v. 118, no. 9, p. 4827-4846, https://doi.org/10.1002/jgrb.50345.","productDescription":"20 p.","startPage":"4827","endPage":"4846","numberOfPages":"20","ipdsId":"IP-045090","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":473539,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jgrb.50345","text":"Publisher Index Page"},{"id":277626,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":277601,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jgrb.50345"}],"country":"United States","state":"California","otherGeospatial":"Cholame","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -120.6,35.6 ], [ -120.6,36.0 ], [ -120.0,36.0 ], [ -120.0,35.6 ], [ -120.6,35.6 ] ] ] } } ] }","volume":"118","issue":"9","noUsgsAuthors":false,"publicationDate":"2013-09-12","publicationStatus":"PW","scienceBaseUri":"52396bfae4b04b9308ae4e38","contributors":{"authors":[{"text":"Horstmann, Tobias","contributorId":53683,"corporation":false,"usgs":true,"family":"Horstmann","given":"Tobias","email":"","affiliations":[],"preferred":false,"id":483972,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harrington, Rebecca M.","contributorId":71089,"corporation":false,"usgs":true,"family":"Harrington","given":"Rebecca M.","affiliations":[],"preferred":false,"id":483973,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":483971,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70048215,"text":"fs20133083 - 2013 - The 3D Elevation Program: summary for Alaska","interactions":[],"lastModifiedDate":"2016-08-17T16:07:48","indexId":"fs20133083","displayToPublicDate":"2013-09-17T10:35:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-3083","title":"The 3D Elevation Program: summary for Alaska","docAbstract":"<p>Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Alaska, elevation data are critical for aviation navigation and safety, natural resources conservation, oil and gas resources, flood risk management, geologic resource assessment and hazards mitigation, forest resources management, and other business uses. Today, high-quality light detection and ranging (lidar) data and interferometric synthetic aperture radar (ifsar) are the primary sources for deriving elevation models and datasets. Federal, State, and local agencies work in partnership to (1) replace data, on a national basis, that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist.</p>\n<p>Recent mapping information for the majority of land in Alaska is not available because clouds, smoke, and remoteness have hampered data collection. Lidar data have been collected only at selected coastal areas, cities, refuges, and parks. Within the last decade, ifsar technology has become the most effective tool for overcoming the challenges to acquiring elevation data for Alaska because this technology can penetrate clouds. State efforts for the collection of ifsar data are being coordinated through Alaska&rsquo;s Statewide Digital Mapping Initiative (SDMI), a cooperative program implemented across six State of Alaska departments and the University of Alaska. Federal efforts are coordinated through the Alaska Mapping Executive Committee (AMEC), chaired by the Department of the Interior with membership from 15 Federal agencies and representatives from the State of Alaska.</p>\n<p>Coordination by SDMI and AMEC avoids duplication of effort and ensures a unified approach to consistent, statewide data acquisition; the enhancement of existing data; and support for emerging applications. The 3D Elevation Program (3DEP) initiative, managed by the U.S. Geological Survey (USGS), responds to the growing need for high-quality topographic data and a wide range of other three-dimensional representations of the Nation&rsquo;s natural and constructed features.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133083","usgsCitation":"Carswell, W., 2013, The 3D Elevation Program: summary for Alaska: U.S. Geological Survey Fact Sheet 2013-3083, 2 p., https://doi.org/10.3133/fs20133083.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":277618,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133083.PNG"},{"id":277617,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3083/pdf/fs2013-3083.pdf","text":"Report","size":"271 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Jr. carswell@usgs.gov","contributorId":1787,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":484023,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70048197,"text":"70048197 - 2013 - Mapping invasive <i>Phragmites australis</i> in the coastal Great Lakes with ALOS PALSAR satellite imagery for decision support","interactions":[],"lastModifiedDate":"2013-09-17T10:25:00","indexId":"70048197","displayToPublicDate":"2013-09-17T10:12:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Mapping invasive <i>Phragmites australis</i> in the coastal Great Lakes with ALOS PALSAR satellite imagery for decision support","docAbstract":"The invasive variety of Phragmites australis (common reed) forms dense stands that can cause negative impacts on coastal Great Lakes wetlands including habitat degradation and reduced biological diversity. Early treatment is key to controlling Phragmites, therefore a map of the current distribution is needed. ALOS PALSAR imagery was used to produce the first basin-wide distribution map showing the extent of large, dense invasive Phragmites-dominated habitats in wetlands and other coastal ecosystems along the U.S. shore of the Great Lakes. PALSAR is a satellite imaging radar sensor that is sensitive to differences in plant biomass and inundation patterns, allowing for the detection and delineation of these tall (up to 5 m), high density, high biomass invasive Phragmites stands. Classification was based on multi-season ALOS PALSAR L-band (23 cm wavelength) HH and HV polarization data. Seasonal (spring, summer, and fall) datasets were used to improve discrimination of Phragmites by taking advantage of phenological changes in vegetation and inundation patterns over the seasons. Extensive field collections of training and randomly selected validation data were conducted in 2010–2011 to aid in mapping and for accuracy assessments. Overall basin-wide map accuracy was 87%, with 86% producer's accuracy and 43% user's accuracy for invasive Phragmites. The invasive Phragmites maps are being used to identify major environmental drivers of this invader's distribution, to assess areas vulnerable to new invasion, and to provide information to regional stakeholders through a decision support tool.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Great Lakes Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2012.11.001","usgsCitation":"Bourgeau-Chavez, L., Kowalski, K., Carlson Mazur, M.L., Scarbrough, K.A., Powell, R.B., Brooks, C., Huberty, B., Jenkins, L.K., Banda, E.C., Galbraith, D.M., Laubach, Z.M., and Riordan, K., 2013, Mapping invasive <i>Phragmites australis</i> in the coastal Great Lakes with ALOS PALSAR satellite imagery for decision support: Journal of Great Lakes Research, v. 39, no. Suppl. 1, p. 65-77, https://doi.org/10.1016/j.jglr.2012.11.001.","productDescription":"13 p.","startPage":"65","endPage":"77","numberOfPages":"13","ipdsId":"IP-037101","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":277614,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":277611,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jglr.2012.11.001"}],"country":"United States","otherGeospatial":"Lake Erie;Lake Huron;Lake Michigan;Lake Ontario;Lake Superior","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92.11,41.4 ], [ -92.11,48.85 ], [ -76.3,48.85 ], [ -76.3,41.4 ], [ -92.11,41.4 ] ] ] } } ] }","volume":"39","issue":"Suppl. 1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52396bf9e4b04b9308ae4e30","contributors":{"authors":[{"text":"Bourgeau-Chavez, Laura L.","contributorId":15105,"corporation":false,"usgs":true,"family":"Bourgeau-Chavez","given":"Laura L.","affiliations":[],"preferred":false,"id":483961,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kowalski, Kurt P. 0000-0002-8424-4701 kkowalski@usgs.gov","orcid":"https://orcid.org/0000-0002-8424-4701","contributorId":3768,"corporation":false,"usgs":true,"family":"Kowalski","given":"Kurt P.","email":"kkowalski@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":483959,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carlson Mazur, Martha L.","contributorId":95377,"corporation":false,"usgs":true,"family":"Carlson Mazur","given":"Martha","email":"","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":483969,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Scarbrough, Kirk A.","contributorId":9949,"corporation":false,"usgs":true,"family":"Scarbrough","given":"Kirk","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":483960,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Powell, Richard B.","contributorId":19869,"corporation":false,"usgs":true,"family":"Powell","given":"Richard","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":483962,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brooks, Colin N.","contributorId":103961,"corporation":false,"usgs":true,"family":"Brooks","given":"Colin N.","affiliations":[],"preferred":false,"id":483970,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Huberty, Brian","contributorId":55733,"corporation":false,"usgs":true,"family":"Huberty","given":"Brian","email":"","affiliations":[],"preferred":false,"id":483966,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jenkins, Liza K.","contributorId":84657,"corporation":false,"usgs":true,"family":"Jenkins","given":"Liza","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":483967,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Banda, Elizabeth C.","contributorId":84658,"corporation":false,"usgs":true,"family":"Banda","given":"Elizabeth","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":483968,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Galbraith, David M.","contributorId":52071,"corporation":false,"usgs":true,"family":"Galbraith","given":"David","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":483964,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Laubach, Zachary M.","contributorId":33615,"corporation":false,"usgs":true,"family":"Laubach","given":"Zachary","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":483963,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Riordan, Kevin","contributorId":52877,"corporation":false,"usgs":true,"family":"Riordan","given":"Kevin","email":"","affiliations":[],"preferred":false,"id":483965,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":69344,"text":"cp52 - 2013 - Tectonic map of the Circum-Pacific region, Pacific basin sheet","interactions":[],"lastModifiedDate":"2026-05-07T16:04:05.5966","indexId":"cp52","displayToPublicDate":"2013-09-16T08:26:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":308,"text":"Circum-Pacific Map","code":"CP","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"52","title":"Tectonic map of the Circum-Pacific region, Pacific basin sheet","docAbstract":"<b>Circum-Pacific Map Project</b>:  The Circum-Pacific Map Project was a cooperative international effort designed to show the relationship of known energy and mineral resources to the major geologic features of the Pacific basin and surrounding continental areas. Available geologic, mineral, and energy-resource data are being complemented by new, project-developed data sets such as magnetic lineations, seafloor mineral deposits, and seafloor sediment. Earth scientists representing some 180 organizations from more than 40 Pacific-region countries are involved in this work. Six overlapping equal-area regional maps at a scale of 1:10,000,000 form the cartographic base for the project: the four Circum-Pacific Quadrants (Northwest, Southwest, Southeast, and Northeast), and the Antarctic and Arctic Sheets. There is also a Pacific Basin Sheet at a scale of 1:17,000,000. The Base Map Series and the Geographic Series (published from 1977 to 1990), the Plate-Tectonic Series (published in 1981 and 1982), the Geodynamic Series (published in 1984 and 1985), and the Geologic Series (published from 1984 to 1989) all include six map sheets. Other thematic map series in preparation include Mineral-Resources, Energy-Resources and Tectonic Maps. Altogether, more than 50 map sheets are planned. The maps were prepared cooperatively by the Circum-Pacific Council for Energy and Mineral Resources and the U.S. Geological Survey and are available from the Branch of Distribution, U. S. Geological Survey, Box 25286, Federal Center, Denver, Colorado 80225, U.S.A. The Circum-Pacific Map Project is organized under six panels of geoscientists representing national earth-science organizations, universities, and natural-resource companies. The six panels correspond to the basic map areas. Current panel chairmen are Tomoyuki Moritani (Northwest Quadrant), R. Wally Johnson (Southwest Quadrant), Ian W.D. Dalziel (Antarctic Region), vacant. (Southeast Quadrant), Kenneth J. Drummond (Northeast Quadrant), and George W. Moore (Arctic Region). Project coordination and final cartography was being carried out through the cooperation of the Office of the Chief Geologist of the U.S. Geological Survey, under the direction of General Chairman, George Gryc of Menlo Park, California. Project headquarters were located at 345 Middlefield Road, MS 952, Menlo Park, California 94025, U.S.A. The framework for the Circum-Pacific Map Project was developed in 1973 by a specially convened group of 12 North American geoscientists meeting in California. The project was officially launched at the First Circum-Pacific Conference on Energy and Mineral Resources, which met in Honolulu, Hawaii, in August 1974. Sponsors of the conference were the AAPG, Pacific Science Association (PSA), and the Coordinating Committee for Offshore Prospecting for Mineral Resources in Offshore Asian Areas (CCOP). The Circum-Pacific Map Project operates as an activity of the Circum-Pacific Council for Energy and Mineral Resources, a nonprofit organization that promotes cooperation among Circum-Pacific countries in the study of energy and mineral resources of the Pacific basin. Founded by Michel T. Halbouty in 1972, the Council also sponsors conferences, topical symposia, workshops and the Earth Science Series books. <b>Tectonic Map Series</b>:  The tectonic maps distinguish areas of oceanic and continental crust. Symbols in red mark active plate boundaries, and colored patterns show tectonic units (volcanic or magmatic arcs, arc-trench gaps, and interarc basins) associated with active plate margins. Well-documented inactive plate boundaries are shown by symbols in black. The tectonic development of oceanic crust is shown by episodes of seafloor spreading. These correlate with the rift and drift sequences at passive continental margins and episodes of tectonic activity at active plate margins. The recognized episodes of seafloor spreading seem to reflect major changes in plate kinematics. Oceanic plateaus and other prominences of greater than normal oceanic crustal thickness such as hotspot traces are also shown. Colored areas on the continents show the ages of deformation and metamorphism of basement rocks and the emplacement of igneous rocks. Transitional tectonic (molassic) and reactivation basins are shown by a colored boundary, and if they are deformed, a colored horizontal line pattern indicates the age of deformation. Colored bands along basin boundaries indicate age of inception, and isopachs indicate thickness of platform strata on continental crust and cover on oceanic crust. Colored patterns at separated continental margins show the age of inception of rift and drift (breakup) sequences. Symbols mark folds and faults, and special symbols show volcanoes and other structural features. Affiliations are as of compilation of the data. This map was created in quadrants and then compiled together. They are the Northwest land, Northwest Marine (different compilers), Northeast, Southwest and Southeast, and parts in plate-boundary sections.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cp52","collaboration":"In cooperation with the Circum-Pacific Council","usgsCitation":"Scheibner, E., Moore, G.W., Drummond, K.J., Dalziel, C.Q., Moritani, T., Teraoka, Y., Sato, T., and Craddock, C., 2013, Tectonic map of the Circum-Pacific region, Pacific basin sheet: U.S. Geological Survey Circum-Pacific Map 52, Pamphlet: 134 p.; 1 Map: 57.79 x 39.88 inches; Correlation of Map Units; Readme file; Metadata; Map data; CMU data; ptype explanation, https://doi.org/10.3133/cp52.","productDescription":"Pamphlet: 134 p.; 1 Map: 57.79 x 39.88 inches; Correlation of Map Units; Readme file; Metadata; Map data; CMU data; ptype explanation","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":178,"text":"Circum-Pacific Council","active":false,"usgs":true}],"links":[{"id":277590,"rank":10,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/cp52.gif"},{"id":277589,"rank":1,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/cp/52/cp52_ptype_explanation.xlsx"},{"id":277588,"rank":2,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/cp/52/cp52_cmu_gis.zip"},{"id":277587,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/cp/52/cp52_map_gis.zip"},{"id":277586,"rank":7,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/cp/52/cp52_metadata.txt"},{"id":277585,"rank":9,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/cp/52/cp52_readme.pdf"},{"id":277584,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/cp/52/cp52_cmu.pdf"},{"id":277583,"rank":8,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/cp/52/cp52_map.pdf"},{"id":277581,"rank":6,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/cp/52/"},{"id":277582,"rank":5,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/cp/52/cp52_pamphlet.pdf"},{"id":504095,"rank":11,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_98986.htm","linkFileType":{"id":5,"text":"html"}}],"otherGeospatial":"Pacific Ocean","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 128.6,-85.6 ], [ 128.6,58.2 ], [ -66.5,58.2 ], [ -66.5,-85.6 ], [ 128.6,-85.6 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52381a80e4b0c7d45ef060f7","contributors":{"authors":[{"text":"Scheibner, E.","contributorId":65371,"corporation":false,"usgs":true,"family":"Scheibner","given":"E.","affiliations":[],"preferred":false,"id":280206,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moore, G. W.","contributorId":87946,"corporation":false,"usgs":true,"family":"Moore","given":"G.","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":280208,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Drummond, K. J.","contributorId":53484,"corporation":false,"usgs":true,"family":"Drummond","given":"K.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":280202,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dalziel, Corvalan Q.J.","contributorId":55722,"corporation":false,"usgs":true,"family":"Dalziel","given":"Corvalan","email":"","middleInitial":"Q.J.","affiliations":[],"preferred":false,"id":280204,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moritani, T.","contributorId":53682,"corporation":false,"usgs":true,"family":"Moritani","given":"T.","email":"","affiliations":[],"preferred":false,"id":280203,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Teraoka, Y.","contributorId":58929,"corporation":false,"usgs":true,"family":"Teraoka","given":"Y.","email":"","affiliations":[],"preferred":false,"id":280205,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sato, T.","contributorId":65753,"corporation":false,"usgs":true,"family":"Sato","given":"T.","email":"","affiliations":[],"preferred":false,"id":280207,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Craddock, C.","contributorId":107425,"corporation":false,"usgs":true,"family":"Craddock","given":"C.","email":"","affiliations":[],"preferred":false,"id":280209,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70048190,"text":"70048190 - 2013 - Potential increases in natural disturbance rates could offset forest management impacts on ecosystem carbon stocks","interactions":[],"lastModifiedDate":"2013-09-16T12:03:47","indexId":"70048190","displayToPublicDate":"2013-09-15T11:45:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Potential increases in natural disturbance rates could offset forest management impacts on ecosystem carbon stocks","docAbstract":"Forested ecosystems contain the majority of the world’s terrestrial carbon, and forest management has implications for regional and global carbon cycling. Carbon stored in forests changes with stand age and is affected by natural disturbance and timber harvesting. We examined how harvesting and disturbance interact to influence forest carbon stocks over the Superior National Forest, in northern Minnesota. Forest inventory data from the USDA Forest Service, Forest Inventory and Analysis program were used to characterize current forest age structure and quantify the relationship between age and carbon stocks for eight forest types. Using these findings, we simulated the impact of alternative management scenarios and natural disturbance rates on forest-wide terrestrial carbon stocks over a 100-year horizon. Under low natural mortality, forest-wide total ecosystem carbon stocks increased when 0% or 40% of planned harvests were implemented; however, the majority of forest-wide carbon stocks decreased with greater harvest levels and elevated disturbance rates. Our results suggest that natural disturbance has the potential to exert stronger influence on forest carbon stocks than timber harvesting activities and that maintaining carbon stocks over the long-term may prove difficult if disturbance frequency increases in response to climate change.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Forest Ecology and Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2013.07.042","usgsCitation":"Bradford, J.B., Jensen, N.R., Domke, G., and D’Amato, A.W., 2013, Potential increases in natural disturbance rates could offset forest management impacts on ecosystem carbon stocks: Forest Ecology and Management, v. 308, p. 178-187, https://doi.org/10.1016/j.foreco.2013.07.042.","productDescription":"10 p.","startPage":"178","endPage":"187","ipdsId":"IP-044934","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":277597,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":277576,"type":{"id":15,"text":"Index Page"},"url":"https://www.sciencedirect.com/science/article/pii/S0378112713004982"},{"id":277575,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.foreco.2013.07.042"}],"country":"United States","state":"Minnesota","otherGeospatial":"Superior National Forest","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -93.0917,47.2848 ], [ -93.0917,48.4396 ], [ -89.855,48.4396 ], [ -89.855,47.2848 ], [ -93.0917,47.2848 ] ] ] } } ] }","volume":"308","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52382866e4b0c7d45ef06117","contributors":{"authors":[{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":483945,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jensen, Nicholas R.","contributorId":6755,"corporation":false,"usgs":true,"family":"Jensen","given":"Nicholas","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":483946,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Domke, Grant M.","contributorId":28891,"corporation":false,"usgs":true,"family":"Domke","given":"Grant M.","affiliations":[],"preferred":false,"id":483947,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"D’Amato, Anthony W.","contributorId":35632,"corporation":false,"usgs":true,"family":"D’Amato","given":"Anthony","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":483948,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70048183,"text":"ds777 - 2013 - Geodatabase compilation of hydrogeologic, remote sensing, and water-budget-component data for the High Plains aquifer, 2011","interactions":[],"lastModifiedDate":"2026-05-21T13:48:14.558284","indexId":"ds777","displayToPublicDate":"2013-09-13T13:39:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"777","title":"Geodatabase compilation of hydrogeologic, remote sensing, and water-budget-component data for the High Plains aquifer, 2011","docAbstract":"<p>The High Plains aquifer underlies almost 112 million acres in the central United States. It is one of the largest aquifers in the Nation in terms of annual groundwater withdrawals and provides drinking water for 2.3 million people. The High Plains aquifer has gained national and international attention as a highly stressed groundwater supply primarily because it has been appreciably depleted in some areas. The U.S. Geological Survey has an active program to monitor the changes in groundwater levels for the High Plains aquifer and has documented substantial water-level changes since predevelopment: the High Plains Groundwater Availability Study is part of a series of regional groundwater availability studies conducted to evaluate the availability and sustainability of major aquifers across the Nation. The goals of the regional groundwater studies are to quantify current groundwater resources in an aquifer system, evaluate how these resources have changed over time, and provide tools to better understand a systems response to future demands and environmental stresses. The purpose of this report is to present selected data developed and synthesized for the High Plains aquifer as part of the High Plains Groundwater Availability Study. The High Plains Groundwater Availability Study includes the development of a water-budget-component analysis for the High Plains completed in 2011 and development of a groundwater-flow model for the northern High Plains aquifer. Both of these tasks require large amounts of data about the High Plains aquifer. Data pertaining to the High Plains aquifer were collected, synthesized, and then organized into digital data containers called geodatabases. There are 8 geodatabases, 1 file geodatabase and 7 personal geodatabases, that have been grouped in three categories: hydrogeologic data, remote sensing data, and water-budget-component data. The hydrogeologic data pertaining to the northern High Plains aquifer is included in three separate geodatabases: (1) base data from a groundwater-flow model; (2) hydrogeology and hydraulic properties data; and (3) groundwater-flow model data to be used as calibration targets. The remote sensing data for this study were developed by the U. S. Geological Survey Earth Resources Observation and Science Center and include historical and predicted land-use/land-cover data and actual evapotranspiration data by using remotely sensed temperature data. The water-budget-component data contains selected raster data from maps in the &ldquo;Selected Approaches to Estimate Water-Budget Components of the High Plains, 1940 Through 1949 and 2000 Through 2009&rdquo; report completed in 2011 (<a href=\"http://pubs.usgs.gov/sir/2011/5183/\" target=\"_blank\">http://pubs.usgs.gov/sir/2011/5183/</a>). Federal Geographic Data Committee compliant metadata were created for each spatial and tabular data layer in the geodatabases.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds777","usgsCitation":"Houston, N.A., Gonzales-Bradford, S.L., Flynn, A., Qi, S.L., Peterson, S.M., Stanton, J.S., Ryter, D.W., Sohl, T.L., and Senay, G., 2013, Geodatabase compilation of hydrogeologic, remote sensing, and water-budget-component data for the High Plains aquifer, 2011: U.S. Geological Survey Data Series 777, Report: vii, 12 p.; 29 Datasets, https://doi.org/10.3133/ds777.","productDescription":"Report: vii, 12 p.; 29 Datasets","numberOfPages":"23","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":504566,"rank":4,"type":{"id":36,"text":"NGMDB Index 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,{"id":70048170,"text":"ds791 - 2013 - Hydrographs showing groundwater levels for selected wells in the Puyallup River watershed and vicinity, Pierce and King Counties, Washington","interactions":[],"lastModifiedDate":"2026-05-20T19:12:06.110078","indexId":"ds791","displayToPublicDate":"2013-09-13T11:17:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"791","title":"Hydrographs showing groundwater levels for selected wells in the Puyallup River watershed and vicinity, Pierce and King Counties, Washington","docAbstract":"<p>Hydrographs of groundwater levels for selected wells in and adjacent to the Puyallup River watershed in Pierce and King Counties, Washington, are presented using an interactive Web-based map of the study area to illustrate changes in groundwater levels on a monthly and seasonal basis. The interactive map displays well locations that link to the hydrographs, which in turn link to the U.S. Geological Survey National Water Information System, Groundwater Site Inventory System.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds791","usgsCitation":"Lane, R.C., Julich, R.J., and Justin, G., 2013, Hydrographs showing groundwater levels for selected wells in the Puyallup River watershed and vicinity, Pierce and King Counties, Washington (Originally posted September 13, 2013; Revised and reposted August 25, 2014, Version 1.1; Revised and reposted May 28, 2015, Version 1.2): U.S. Geological Survey Data Series 791, HTML Document; Conversion Factors and Datums; 2 Figures; Table 1; Interactive Map, https://doi.org/10.3133/ds791.","productDescription":"HTML Document; Conversion Factors and Datums; 2 Figures; Table 1; Interactive Map","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":277555,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/791/ds791_table1.xlsx","text":"Table 1","size":"23 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Table 1"},{"id":277554,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/791/figure2.html","text":"Figure 2","linkFileType":{"id":5,"text":"html"},"description":"Figure 2"},{"id":277552,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/791/conversions.html","text":"Conversion Factors and Datums","linkFileType":{"id":5,"text":"html"},"description":"Conversion Factors and Datums"},{"id":504580,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_98987.htm","linkFileType":{"id":5,"text":"html"}},{"id":277560,"rank":7,"type":{"id":7,"text":"Companion Files"},"url":"https://wa.water.usgs.gov/projects/puyallupgw/hydrographs.htm","text":"Interactive Map","description":"Interactive Map"},{"id":277553,"rank":2,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/791/figure1.html","text":"Figure 1","linkFileType":{"id":5,"text":"html"},"description":"Figure 1"},{"id":277549,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/791/index.html"},{"id":277556,"rank":6,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/ds791.PNG"}],"country":"United States","state":"Washington","county":"King County, Pierce County","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.47764587402344,\n              47.43319679984749\n            ],\n            [\n              -122.0972442626953,\n              47.43366127871628\n            ],\n            [\n              -122.0969009399414,\n              47.34580193235629\n            ],\n            [\n              -121.84661865234374,\n              47.34487142066085\n            ],\n            [\n              -121.8445587158203,\n              47.26292215345572\n            ],\n            [\n              -121.48681640624999,\n              47.265252010946085\n            ],\n            [\n              -121.48406982421875,\n              46.992431036151324\n            ],\n            [\n              -121.981201171875,\n              46.992431036151324\n            ],\n            [\n              -121.97982788085938,\n              46.91322000960565\n            ],\n            [\n              -122.35816955566406,\n              46.91087470241917\n            ],\n            [\n              -122.35954284667967,\n              47.08415026205488\n            ],\n            [\n              -122.4872589111328,\n              47.08321514774161\n            ],\n            [\n              -122.47764587402344,\n              47.43319679984749\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","edition":"Originally posted September 13, 2013; Revised and reposted August 25, 2014, Version 1.1; Revised and reposted May 28, 2015, Version 1.2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52342605e4b0b9e9b3336cda","contributors":{"authors":[{"text":"Lane, R. 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,{"id":70048155,"text":"pp1795B - 2013 - Lithofacies, age, depositional setting, and geochemistry of the Otuk Formation in the Red Dog District, northwestern Alaska","interactions":[],"lastModifiedDate":"2018-05-07T20:57:58","indexId":"pp1795B","displayToPublicDate":"2013-09-13T08:57:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1795","chapter":"B","title":"Lithofacies, age, depositional setting, and geochemistry of the Otuk Formation in the Red Dog District, northwestern Alaska","docAbstract":"Complete penetration of the Otuk Formation in a continuous drill core (diamond-drill hole, DDH 927) from the Red Dog District illuminates the facies, age, depositional environment, source rock potential, and isotope stratigraphy of this unit in northwestern Alaska. The section, in the Wolverine Creek plate of the Endicott Mountains Allochthon (EMA), is ~82 meters (m) thick and appears structurally uncomplicated. Bedding dips are generally low and thicknesses recorded are close to true thicknesses. Preliminary synthesis of sedimentologic, paleontologic, and isotopic data suggests that the Otuk succession in DDH 927 is a largely complete, albeit condensed, marine Triassic section in conformable contact with marine Permian and Jurassic strata. The Otuk Formation in DDH 927 gradationally overlies gray siliceous mudstone of the Siksikpuk Formation (Permian, based on regional correlations) and underlies black organic-rich mudstone of the Kingak(?) Shale (Jurassic?, based on regional correlations). The informal shale, chert, and limestone members of the Otuk are recognized in DDH 927, but the Jurassic Blankenship Member is absent. The lower (shale) member consists of 28 m of black to light gray, silty shale with as much as 6.9 weight percent total organic carbon (TOC). Thin limy layers near the base of this member contain bivalve fragments (Claraia sp.?) consistent with an Early Triassic (Griesbachian-early Smithian) age. Gray radiolarian chert dominates the middle member (25 m thick) and yields radiolarians of Middle Triassic (Anisian and Ladinian) and Late Triassic (Carnian-late middle Norian) ages. Black to light gray silty shale, like that in the lower member, forms interbeds that range from a few millimeters to 7 centimeters in thickness through much of the middle member. A distinctive, 2.4-m-thick interval of black shale and calcareous radiolarite ~17 m above the base of the member has as much as 9.8 weight percent TOC, and a 1.9-m-thick interval of limy to cherty mudstone immediately above this contains radiolarians, foraminifers, conodonts, and halobiid bivalve fragments. The upper (limestone) member (29 m thick) is lime mudstone with monotid bivalves and late Norian radiolarians, overlain by gray chert that contains Rhaetian (latest Triassic) radiolarians; Rhaetian strata have not previously been documented in the Otuk. Rare gray to black shale interbeds in the upper member have as much as 3.4 weight percent TOC. At least 35 m of black mudstone overlies the limestone member; these strata lack interbeds of oil shale and chert that are characteristic of the Blankenship, and instead they resemble the Kingak Shale. Vitrinite reflectance values (2.45 and 2.47 percent Ro) from two samples of black shale in the chert member indicate that these rocks reached a high level of thermal maturity within the dry gas window. Regional correlations indicate that lithofacies in the Otuk Formation vary with both structural and geographic position. For example, the shale member of the Otuk in the Wolverine Creek plate includes more limy layers and less barite (as blades, nodules, and lenses) than equivalent strata in the structurally higher Red Dog plate of the EMA, but it has fewer limy layers than the shale member in the EMA ~450 kilometers (km) to the east at Tiglukpuk Creek. The limestone member of the Otuk is thicker in the Wolverine Creek plate than in the Red Dog plate and differs from this member in EMA sections to the east in containing an upper cherty interval that lacks monotids; a similar interval is seen at the top of the Otuk Formation ~125 km to the west (Lisburne Peninsula). Our observations are consistent with the interpretations of previous researchers that Otuk facies become more distal in higher structural positions and that within a given structural level more distal facies occur to the west. Recent paleogeographic reconstructions indicate that the Otuk accumulated at a relatively high paleolatitude with a bivalve fauna typical of the Boreal realm. A suite of δ<sup>13</sup>C<sub>org</sub> (carbon isotopic composition of carbon) data (n=38) from the upper Siksikpuk Formation through the Otuk Formation and into the Kingak(?) Shale in DDH 927 shows a pattern of positive and negative excursions similar to those reported elsewhere in Triassic strata. In particular, a distinct negative excursion at the base of the Otuk (from ‒23.8 to ‒31.3‰ (permil, or parts per thousand)) likely correlates with a pronounced excursion that marks the Permian-Triassic boundary at many localities worldwide. Another feature of the Otuk δ<sup>13</sup>C<sub>org</sub> record that may correlate globally is a series of negative and positive excursions in the lower member. At the top of the Otuk in DDH 927, the δ<sup>13</sup>C<sub>org</sub> values are extremely low and may correlate with a negative excursion that is widely observed at the Triassic-Jurassic boundary.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1795B","collaboration":"Studies by the U.S. Geological Survey in Alaska, 2011; This report is Chapter B in <i>Studies by the U.S. Geological Survey in Alaska, 2011</i>. For more information see <a href=\"http://pubs.usgs.gov/pp/1795/index.html\" target=\"_blank\">PP 1795</a>.","usgsCitation":"Dumoulin, J.A., Burruss, R.A., and Blome, C.D., 2013, Lithofacies, age, depositional setting, and geochemistry of the Otuk Formation in the Red Dog District, northwestern Alaska: U.S. Geological Survey Professional Paper 1795, Report: iv, 32 p., https://doi.org/10.3133/pp1795B.","productDescription":"Report: iv, 32 p.","numberOfPages":"40","onlineOnly":"Y","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":277532,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/pp1795b.gif"},{"id":277529,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/pp/1795/b/"},{"id":277530,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1795/b/pp1795b.pdf"},{"id":277531,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/pp/1795/index.html"}],"country":"United States","state":"Alaska","otherGeospatial":"Red Dog District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -168,66.5 ], [ -168,69.5 ], [ -156,69.5 ], [ -156,66.5 ], [ -168,66.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52342606e4b0b9e9b3336cde","contributors":{"authors":[{"text":"Dumoulin, Julie A. 0000-0003-1754-1287 dumoulin@usgs.gov","orcid":"https://orcid.org/0000-0003-1754-1287","contributorId":203209,"corporation":false,"usgs":true,"family":"Dumoulin","given":"Julie","email":"dumoulin@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":483889,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burruss, Robert A. 0000-0001-6827-804X burruss@usgs.gov","orcid":"https://orcid.org/0000-0001-6827-804X","contributorId":558,"corporation":false,"usgs":true,"family":"Burruss","given":"Robert","email":"burruss@usgs.gov","middleInitial":"A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":483888,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blome, Charles D. 0000-0002-3449-9378 cblome@usgs.gov","orcid":"https://orcid.org/0000-0002-3449-9378","contributorId":1246,"corporation":false,"usgs":true,"family":"Blome","given":"Charles","email":"cblome@usgs.gov","middleInitial":"D.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":483890,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70048143,"text":"ds703 - 2013 - The δ2H and δ18O of tap water from 349 sites in the United States and selected territories","interactions":[],"lastModifiedDate":"2026-05-07T17:01:59.799679","indexId":"ds703","displayToPublicDate":"2013-09-12T12:40:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"703","displayTitle":"The δ<sup>2</sup>H and δ<sup>18</sup>O of tap water from 349 sites in the United States and selected territories","title":"The δ2H and δ18O of tap water from 349 sites in the United States and selected territories","docAbstract":"Because the stable isotopic compositions of hydrogen (δ<sup>2</sup>H) and oxygen (δ<sup>18</sup>O) of animal (including human) tissues, such as hair, nail, and urine, reflect the δ<sup>2</sup>H and δ<sup>18</sup>O of water and food ingested by an animal or a human and because the δ<sup>2</sup>H and δ<sup>18</sup>O of environmental waters vary geographically, δ<sup>2</sup>H and δ<sup>18</sup>O values of tap water samples collected in 2007-2008 from 349 sites in the United States and three selected U.S. territories have been measured in support of forensic science applications, creating one of the largest databases of tap water δ<sup>2</sup>H and δ<sup>18</sup>O values to date. The results of replicate isotopic measurements for these tap water samples confirm that the expanded uncertainties (U = 2μ<sub>c</sub>) obtained over a period of years by the Reston Stable Isotope Laboratory from δ<sup>2</sup>H and δ<sup>18</sup>O dual-inlet mass spectrometric measurements are conservative, at ±2‰ and ±0.2 ‰, respectively. These uncertainties are important because U.S. Geological Survey data may be needed for forensic science applications, including providing evidence in court cases. Half way through the investigation, an isotope-laser spectrometer was acquired, enabling comparison of dual-inlet isotope-ratio mass spectrometric results with isotope-laser spectrometric results. The uncertainty of the laser-based δ<sup>2</sup>H measurement results for these tap water samples is comparable to the uncertainty of the mass spectrometric method, with the laser-based method having a slightly lower uncertainty. However, the δ<sup>18</sup>O uncertainty of the laser-based method is more than a factor of ten higher than that of the dual-inlet isotoperatio mass spectrometric method.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds703","usgsCitation":"Coplen, T.B., Landwehr, J.M., Qi, H., and Lorenz, J.M., 2013, The δ<sup>2</sup>H and δ<sup>18</sup>O of tap water from 349 sites in the United States and selected territories: U.S. Geological Survey Data Series 703, iv, 113 p., https://doi.org/10.3133/ds703.","productDescription":"Report: iv, 113 p.; Appendix","numberOfPages":"117","onlineOnly":"Y","costCenters":[{"id":543,"text":"Reston Stable Isotope Laboratory","active":false,"usgs":true}],"links":[{"id":504107,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_98949.htm","linkFileType":{"id":5,"text":"html"}},{"id":277518,"rank":3,"type":{"id":15,"text":"Index 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Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":483841,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Landwehr, Jurate M. jmlandwe@usgs.gov","contributorId":2345,"corporation":false,"usgs":true,"family":"Landwehr","given":"Jurate","email":"jmlandwe@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":483842,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Qi, Haiping 0000-0002-8339-744X haipingq@usgs.gov","orcid":"https://orcid.org/0000-0002-8339-744X","contributorId":507,"corporation":false,"usgs":true,"family":"Qi","given":"Haiping","email":"haipingq@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":483840,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lorenz, Jennifer M. 0000-0002-5826-7264 jlorenz@usgs.gov","orcid":"https://orcid.org/0000-0002-5826-7264","contributorId":3558,"corporation":false,"usgs":true,"family":"Lorenz","given":"Jennifer","email":"jlorenz@usgs.gov","middleInitial":"M.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":483843,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70048114,"text":"70048114 - 2013 - Linking river management to species conservation using dynamic landscape scale models","interactions":[],"lastModifiedDate":"2013-09-12T12:56:29","indexId":"70048114","displayToPublicDate":"2013-09-12T12:39:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Linking river management to species conservation using dynamic landscape scale models","docAbstract":"Efforts to conserve stream and river biota could benefit from tools that allow managers to evaluate landscape-scale changes in species distributions in response to water management decisions. We present a framework and methods for integrating hydrology, geographic context and metapopulation processes to simulate effects of changes in streamflow on fish occupancy dynamics across a landscape of interconnected stream segments. We illustrate this approach using a 482 km<sup>2</sup> catchment in the southeastern US supporting 50 or more stream fish species. A spatially distributed, deterministic and physically based hydrologic model is used to simulate daily streamflow for sub-basins composing the catchment. We use geographic data to characterize stream segments with respect to channel size, confinement, position and connectedness within the stream network. Simulated streamflow dynamics are then applied to model fish metapopulation dynamics in stream segments, using hypothesized effects of streamflow magnitude and variability on population processes, conditioned by channel characteristics. The resulting time series simulate spatially explicit, annual changes in species occurrences or assemblage metrics (e.g. species richness) across the catchment as outcomes of management scenarios. Sensitivity analyses using alternative, plausible links between streamflow components and metapopulation processes, or allowing for alternative modes of fish dispersal, demonstrate large effects of ecological uncertainty on model outcomes and highlight needed research and monitoring. Nonetheless, with uncertainties explicitly acknowledged, dynamic, landscape-scale simulations may prove useful for quantitatively comparing river management alternatives with respect to species conservation.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"River Research and Applications","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/rra.2575","usgsCitation":"Freeman, M., Buell, G.R., Hay, L.E., Hughes, W.B., Jacobson, R.B., Jones, J., Jones, S., LaFontaine, J.H., Odom, K.R., Peterson, J., Riley, J.W., Schindler, J.S., Shea, C., and Weaver, J., 2013, Linking river management to species conservation using dynamic landscape scale models: River Research and Applications, v. 29, no. 7, p. 906-918, https://doi.org/10.1002/rra.2575.","productDescription":"13 p.","startPage":"906","endPage":"918","numberOfPages":"13","ipdsId":"IP-017718","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":277469,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/rra.2575"},{"id":277509,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","otherGeospatial":"Flint River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -87.0,29.0 ], [ -87.0,35.0 ], [ -83.0,35.0 ], [ -83.0,29.0 ], [ -87.0,29.0 ] ] ] } } ] }","volume":"29","issue":"7","noUsgsAuthors":false,"publicationDate":"2012-04-20","publicationStatus":"PW","scienceBaseUri":"5232d470e4b0b7ac626cfa2f","contributors":{"authors":[{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":483772,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buell, Gary R. grbuell@usgs.gov","contributorId":3107,"corporation":false,"usgs":true,"family":"Buell","given":"Gary","email":"grbuell@usgs.gov","middleInitial":"R.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":483770,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hay, Lauren E. 0000-0003-3763-4595 lhay@usgs.gov","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":1287,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","email":"lhay@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":483765,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hughes, W. Brian","contributorId":84353,"corporation":false,"usgs":true,"family":"Hughes","given":"W.","email":"","middleInitial":"Brian","affiliations":[],"preferred":false,"id":483778,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jacobson, Robert B. 0000-0002-8368-2064 rjacobson@usgs.gov","orcid":"https://orcid.org/0000-0002-8368-2064","contributorId":1289,"corporation":false,"usgs":true,"family":"Jacobson","given":"Robert","email":"rjacobson@usgs.gov","middleInitial":"B.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":483766,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jones, John W. 0000-0001-6117-3691 jwjones@usgs.gov","orcid":"https://orcid.org/0000-0001-6117-3691","contributorId":2220,"corporation":false,"usgs":true,"family":"Jones","given":"John","email":"jwjones@usgs.gov","middleInitial":"W.","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":483768,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jones, S.A.","contributorId":38596,"corporation":false,"usgs":true,"family":"Jones","given":"S.A.","email":"","affiliations":[],"preferred":false,"id":483776,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"LaFontaine, Jacob H. 0000-0003-4923-2630 jlafonta@usgs.gov","orcid":"https://orcid.org/0000-0003-4923-2630","contributorId":2258,"corporation":false,"usgs":true,"family":"LaFontaine","given":"Jacob","email":"jlafonta@usgs.gov","middleInitial":"H.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":483769,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Odom, Kenneth R.","contributorId":72087,"corporation":false,"usgs":true,"family":"Odom","given":"Kenneth","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":483777,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Peterson, James T. 0000-0002-7709-8590 james_peterson@usgs.gov","orcid":"https://orcid.org/0000-0002-7709-8590","contributorId":2111,"corporation":false,"usgs":true,"family":"Peterson","given":"James","email":"james_peterson@usgs.gov","middleInitial":"T.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":483767,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Riley, Jeffrey W. 0000-0001-5525-3134 jriley@usgs.gov","orcid":"https://orcid.org/0000-0001-5525-3134","contributorId":3605,"corporation":false,"usgs":true,"family":"Riley","given":"Jeffrey","email":"jriley@usgs.gov","middleInitial":"W.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":483773,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Schindler, J. Stephen 0000-0001-9550-5957 sschindl@usgs.gov","orcid":"https://orcid.org/0000-0001-9550-5957","contributorId":3270,"corporation":false,"usgs":true,"family":"Schindler","given":"J.","email":"sschindl@usgs.gov","middleInitial":"Stephen","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":483771,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Shea, C.","contributorId":36834,"corporation":false,"usgs":true,"family":"Shea","given":"C.","email":"","affiliations":[],"preferred":false,"id":483775,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Weaver, J.D.","contributorId":29466,"corporation":false,"usgs":true,"family":"Weaver","given":"J.D.","email":"","affiliations":[],"preferred":false,"id":483774,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70048141,"text":"70048141 - 2013 - Comparison of bird community indices for riparian restoration planning and monitoring","interactions":[],"lastModifiedDate":"2017-08-31T12:41:28","indexId":"70048141","displayToPublicDate":"2013-09-12T11:28:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of bird community indices for riparian restoration planning and monitoring","docAbstract":"The use of a bird community index that characterizes ecosystem integrity is very attractive to conservation planners and habitat managers, particularly in the absence of any single focal species. In riparian areas of the western USA, several attempts at arriving at a community index signifying a functioning riparian bird community have been made previously, mostly resorting to expert opinions or national conservation rankings for species weights. Because extensive local and regional bird monitoring data were available for Nevada, we were able to develop three different indices that were derived empirically, rather than from expert opinion. We formally examined the use of three species weighting schemes in comparison with simple species richness, using different definitions of riparian species assemblage size, for the purpose of predicting community response to changes in vegetation structure from riparian restoration. For the three indices, species were weighted according to the following criteria: (1) the degree of riparian habitat specialization based on regional data, (2) the relative conservation ranking of landbird species, and (3) the degree to which a species is under-represented compared to the regional species pool for riparian areas. To evaluate the usefulness of these indices for habitat restoration planning and monitoring, we modeled them using habitat variables that are expected to respond to riparian restoration efforts, using data from 64 sampling sites in the Walker River Basin in Nevada and California. We found that none of the species-weighting schemes performed any better as an index for evaluating overall habitat condition than using species richness alone as a community index. Based on our findings, the use of a fairly complete list of 30–35 riparian specialists appears to be the best indicator group for predicting the response of bird communities to the restoration of riparian vegetation.","language":"English","publisher":"Ecological Indicators","doi":"10.1016/j.ecolind.2013.05.004","usgsCitation":"Young, J.S., Ammon, E.M., Weisburg, P.J., Dilts, T.E., Newton, W.E., Wong-Kone, D.C., and Heki, L.G., 2013, Comparison of bird community indices for riparian restoration planning and monitoring: Ecological Indicators, v. 34, p. 159-167, https://doi.org/10.1016/j.ecolind.2013.05.004.","productDescription":"9 p.","startPage":"159","endPage":"167","numberOfPages":"9","ipdsId":"IP-042483","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":277504,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":277502,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.ecolind.2013.05.004"}],"country":"United States","state":"Nevada","otherGeospatial":"Walker River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119.225693,38.779163 ], [ -119.225693,39.16178 ], [ -118.715032,39.16178 ], [ -118.715032,38.779163 ], [ -119.225693,38.779163 ] ] ] } } ] }","volume":"34","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5232d46fe4b0b7ac626cfa2b","contributors":{"authors":[{"text":"Young, Jock S.","contributorId":28154,"corporation":false,"usgs":true,"family":"Young","given":"Jock","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":483833,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ammon, Elisabeth M.","contributorId":106785,"corporation":false,"usgs":true,"family":"Ammon","given":"Elisabeth","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":483838,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weisburg, Peter J.","contributorId":62912,"corporation":false,"usgs":true,"family":"Weisburg","given":"Peter","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":483835,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dilts, Thomas E.","contributorId":36833,"corporation":false,"usgs":true,"family":"Dilts","given":"Thomas","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":483834,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Newton, Wesley E. 0000-0002-1377-043X wnewton@usgs.gov","orcid":"https://orcid.org/0000-0002-1377-043X","contributorId":3661,"corporation":false,"usgs":true,"family":"Newton","given":"Wesley","email":"wnewton@usgs.gov","middleInitial":"E.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":483832,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wong-Kone, Diane C.","contributorId":79790,"corporation":false,"usgs":true,"family":"Wong-Kone","given":"Diane","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":483837,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Heki, Lisa G.","contributorId":75052,"corporation":false,"usgs":true,"family":"Heki","given":"Lisa","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":483836,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70048136,"text":"ds787 - 2013 - Surface mineral maps of Afghanistan derived from HyMap imaging spectrometer data, version 2","interactions":[],"lastModifiedDate":"2013-09-11T17:13:14","indexId":"ds787","displayToPublicDate":"2013-09-11T16:11:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"787","subseriesTitle":"USGS Afghanistan Project Product","title":"Surface mineral maps of Afghanistan derived from HyMap imaging spectrometer data, version 2","docAbstract":"This report presents a new version of surface mineral maps derived from HyMap imaging spectrometer data collected over Afghanistan in the fall of 2007. This report also describes the processing steps applied to the imaging spectrometer data. The 218 individual flight lines composing the Afghanistan dataset, covering more than 438,000 square kilometers, were georeferenced to a mosaic of orthorectified Landsat images. The HyMap data were converted from radiance to reflectance using a radiative transfer program in combination with ground-calibration sites and a network of cross-cutting calibration flight lines. The U.S. Geological Survey Material Identification and Characterization Algorithm (MICA) was used to generate two thematic maps of surface minerals: a map of iron-bearing minerals and other materials, which have their primary absorption features at the shorter wavelengths of the reflected solar wavelength range, and a map of carbonates, phyllosilicates, sulfates, altered minerals, and other materials, which have their primary absorption features at the longer wavelengths of the reflected solar wavelength range. In contrast to the original version, version 2 of these maps is provided at full resolution of 23-meter pixel size. The thematic maps, MICA summary images, and the material fit and depth images are distributed in digital files linked to this report, in a format readable by remote sensing software and Geographic Information Systems (GIS). The digital files can be downloaded from http://pubs.usgs.gov/ds/787/downloads/.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds787","usgsCitation":"Kokaly, R., King, T., and Hoefen, T.M., 2013, Surface mineral maps of Afghanistan derived from HyMap imaging spectrometer data, version 2: U.S. Geological Survey Data Series 787, Report: iv, 29 p.; Downloads Directory, https://doi.org/10.3133/ds787.","productDescription":"Report: iv, 29 p.; Downloads Directory","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[],"links":[{"id":277495,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds787.gif"},{"id":277493,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/787/pdf/DS787.pdf"},{"id":277494,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/787/"}],"projection":"Tranverse Mercator","datum":"World Geodetic System, 1984","country":"Afghanistan","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 60.5,29.39 ], [ 60.5,38.49 ], [ 74.89,38.49 ], [ 74.89,29.39 ], [ 60.5,29.39 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"523182dce4b079b6e76e60d2","contributors":{"authors":[{"text":"Kokaly, Raymond F. 0000-0003-0276-7101","orcid":"https://orcid.org/0000-0003-0276-7101","contributorId":81442,"corporation":false,"usgs":true,"family":"Kokaly","given":"Raymond F.","affiliations":[],"preferred":false,"id":483812,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"King, Trude","contributorId":29831,"corporation":false,"usgs":true,"family":"King","given":"Trude","email":"","affiliations":[],"preferred":false,"id":483811,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hoefen, Todd M. 0000-0002-3083-5987 thoefen@usgs.gov","orcid":"https://orcid.org/0000-0002-3083-5987","contributorId":403,"corporation":false,"usgs":true,"family":"Hoefen","given":"Todd","email":"thoefen@usgs.gov","middleInitial":"M.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":483810,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70048132,"text":"sir20135116 - 2013 - Sediment distribution and hydrologic conditions of the Potomac aquifer in Virginia and parts of Maryland and North Carolina","interactions":[],"lastModifiedDate":"2017-01-17T20:46:55","indexId":"sir20135116","displayToPublicDate":"2013-09-11T15:08:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5116","title":"Sediment distribution and hydrologic conditions of the Potomac aquifer in Virginia and parts of Maryland and North Carolina","docAbstract":"Sediments of the heavily used Potomac aquifer broadly contrast across major structural features of the Atlantic Coastal Plain Physiographic Province in eastern Virginia and adjacent parts of Maryland and North Carolina. Thicknesses and relative dominance of the highly interbedded fluvial sediments vary regionally. Vertical intervals in boreholes of coarse-grained sediment commonly targeted for completion of water-supply wells are thickest and most widespread across the central and southern parts of the Virginia Coastal Plain. Designated as the Norfolk arch depositional subarea, the entire sediment thickness here functions hydraulically as a single interconnected aquifer. By contrast, coarse-grained sediment intervals are thinner and less widespread across the northern part of the Virginia Coastal Plain and into southern Maryland, designated as the Salisbury embayment depositional subarea. Fine-grained intervals that are generally avoided for completion of water-supply wells are increasingly thick and widespread northward. Fine-grained intervals collectively as thick as several hundred feet comprise two continuous confining units that hydraulically separate three vertically spaced subaquifers. The subaquifers are continuous northward but merge southward into the single undivided Potomac aquifer. Lastly, far southeastern Virginia and northeastern North Carolina are designated as the Albemarle embayment depositional subarea, where both coarse- and fine-grained intervals are of only moderate thickness. The entire sediment thickness functions hydraulically as a single interconnected aquifer. A substantial hydrologic separation from overlying aquifers is imposed by the upper Cenomanian confining unit.\n\nPotomac aquifer sediments were deposited by a fluvial depositional complex spanning the Virginia Coastal Plain approximately 100 to 145 million years ago. Westward, persistently uplifted granite and gneiss source rocks sustained a supply of coarse-grained sand and gravel. Immature, high-gradient braided streams deposited longitudinal bars and channel fills across the Norfolk arch subarea. By contrast, across the Salisbury and Albemarle embayment subareas, mature, medium- to low-gradient meandering streams deposited medium- to coarse-grained channel fills and point bars segregated from fine-grained overbank deposits. The Virginia depositional complex merged northward across the Salisbury embayment subarea with another complex in Maryland. Here, additional sediments were received from schist source rocks that underwent three cycles of initial uplift and rapid erosion followed by crustal stability and erosional leveling.\n\nBecause of the predominance of coarse-grained sediments, transmissivity, hydraulic conductivity, and regional velocities of lateral flow through the Potomac aquifer are greatest across the Norfolk arch depositional subarea, but decrease progressively northward with increasingly fine-grained sediments. Confining units hydraulically separate the Potomac aquifer from overlying aquifers, as indicated by large vertical hydraulic gradients. By contrast, most of the Potomac aquifer internally functions hydraulically as a single interconnected aquifer, as indicated by uniformly small vertical gradients. Most fine-grained sediments within the aquifer do not hydraulically separate overlying and underlying coarse-grained sediments. Across the Salisbury embayment depositional subarea, however, hydraulic separation among the vertically spaced subaquifers is imposed by the intervening confining units.\n\nThe Potomac aquifer is the largest and most heavily used source of groundwater in the Virginia Coastal Plain. Water-level declines as great as 200 feet create the potential for saltwater intrusion. Conventional stratigraphic correlation has been generally ineffective at accurately characterizing complexly distributed fluvial sediments that compose the Potomac aquifer. Consequently, the aquifer’s internal hydraulic connectivity and overall hydrologic function have not been well understood. Water-supply planning and development efforts have been hampered, and interpretations of regulatory criteria for allowable water-level declines have been ambiguous.\n\nAn investigation undertaken during 2010–11 by the U.S. Geological Survey, in cooperation with the Virginia Department of Environmental Quality, provides a comprehensive regional description of the spatial distribution of Potomac aquifer sediments and their relation to hydrologic conditions. Altitudes and thicknesses of 2,725 vertical sediment intervals represent the spatial distribution of Potomac aquifer sediments in the Virginia Coastal Plain and adjacent parts of Maryland and North Carolina. Sediment intervals are designated as either dominantly coarse or fine grained and were determined by interpretation of geophysical logs and ancillary information from 456 boreholes. Sediment-interval and borehole summary statistical data indicate regional trends in sediment lithology and stratigraphic continuity, upon which three structurally based and hydrologically distinct sediment depositional subareas are designated. Broad patterns of sediment deposition over time are inferred from published sediment pollen-age data. Discrepancies in previously drawn hydrostratigraphic relations between southeastern Virginia and northeastern North Carolina are partly resolved based on borehole geophysical logs and a recently documented geologic map and corehole. A conceptual model theorizes the depositional history of the sediments and geologically accounts for their distribution. Documented pumping tests of the Potomac aquifer at 197 locations produced 336 values of transmissivity and 127 values of storativity. Based on effective aquifer thicknesses, 296 values of sediment hydraulic conductivity and 113 values of sediment specific storage are calculated. Vertical hydraulic gradients are calculated from 9,479 pairs of water levels measured between November 17, 1953, and October 4, 2011, in 129 closely spaced pairs of wells.\n\nBorehole sediment-interval and related data provide a means to achieve high yielding production wells in the Potomac aquifer by site-specific targeting of drilling operations toward water-bearing coarse-grained sand and gravel. Advance knowledge of the potential of different parts of the aquifer also aids in planning optimal groundwater-development areas. Depositional subareas further provide a possible context for resource management. Current (2013) regulatory limits on water-level declines are relative to top surfaces of subdivided upper, middle, and lower Potomac aquifers across the entire Virginia Coastal Plain, but have the potential to exceed the same limit relative to a single undivided Potomac aquifer. By contrast, designation of the sediments as a single aquifer in the Norfolk arch and Albemarle embayment subareas—and as a series of vertically spaced subaquifers and intervening confining units in the Salisbury embayment subarea—best reflects understanding of the Potomac aquifer and can avoid the potential for excessive water-level declines. Simulation modeling to evaluate effects of groundwater withdrawals could be designed similarly, including vertical discretization and (or) zonation of the Potomac aquifer based on depositional subareas and a geostatistical distribution of aquifer properties derived from borehole sediment-interval data. Further resource-management information needs extend beyond the developed part of the Potomac aquifer, particularly across the Northern Neck and Middle Peninsula where only the shallowest part of the aquifer is known, and include structural aspects such as faults, basement bedrock, and the Chesapeake Bay impact crater.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135116","collaboration":"Prepared in cooperation with the Virginia Department of Environmental Quality","usgsCitation":"McFarland, R.E., 2013, Sediment distribution and hydrologic conditions of the Potomac aquifer in Virginia and parts of Maryland and North Carolina: U.S. Geological Survey Scientific Investigations Report 2013-5116, Report: vi, 67 p.; 3 Attachments; 2 Plates: 24 x 36 inches and 36 x 40 inches, https://doi.org/10.3133/sir20135116.","productDescription":"Report: vi, 67 p.; 3 Attachments; 2 Plates: 24 x 36 inches and 36 x 40 inches","numberOfPages":"77","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":277490,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2013/5116/tables/sir2013-5116_attachment2.xlsx"},{"id":277485,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5116/"},{"id":277484,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5116/pdf/sir2013-5116.pdf"},{"id":277486,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2013/5116/tables/sir2013-5116_attachment3.xlsx"},{"id":277487,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2013/5116/plates/sir2013-5116_plate1.pdf"},{"id":277488,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2013/5116/plates/sir2013-5116_plate2.pdf"},{"id":277491,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2013/5116/tables/sir2013-5116_attachment1.xls"},{"id":277492,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135116.jpg"}],"scale":"500000","country":"United States","state":"Maryland, North Carolina, Virginia","otherGeospatial":"Potomac Aquifer","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -77.6964,35.9713 ], [ -77.6964,38.7026 ], [ -75.26,38.7026 ], [ -75.26,35.9713 ], [ -77.6964,35.9713 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f251e4b0bc0bec0a02f3","contributors":{"authors":[{"text":"McFarland, Randolph E.","contributorId":93879,"corporation":false,"usgs":true,"family":"McFarland","given":"Randolph","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":483806,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70048113,"text":"ofr20131163 - 2013 - Submergence Vulnerability Index development and application to Coastwide Reference Monitoring System Sites and Coastal Wetlands Planning, Protection and Restoration Act projects","interactions":[],"lastModifiedDate":"2013-09-10T19:40:45","indexId":"ofr20131163","displayToPublicDate":"2013-09-10T19:33:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1163","title":"Submergence Vulnerability Index development and application to Coastwide Reference Monitoring System Sites and Coastal Wetlands Planning, Protection and Restoration Act projects","docAbstract":"Since its implementation in 2003, the Coastwide Reference Monitoring System (CRMS) in Louisiana has facilitated the creation of a comprehensive dataset that includes, but is not limited to, vegetation, hydrologic, and soil metrics on a coastwide scale. The primary impetus for this data collection is to assess land management activities, including restoration efforts, across the coast. The aim of the CRMS analytical team is to provide a method to synthesize this data to enable multiscaled evaluations of activities in Louisiana’s coastal wetlands. Several indices have been developed to facilitate data synthesis and interpretation, including a Floristic Quality Index, a Hydrologic Index, and a Landscape Index. This document details the development of the Submergence Vulnerability Index, which incorporates sediment-elevation data as well as hydrologic data to determine the vulnerability of a wetland based on its ability to keep pace with sea-level rise. The objective of this document is to provide Federal and State sponsors, project managers, planners, landowners, data users, and the rest of the coastal restoration community with the following: (1) data collection and model development methods for the sediment-elevation response variables, and (2) a description of how these response variables will be used to evaluate CWPPRA project and program effectiveness.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131163","collaboration":"Prepared in cooperation with the Coastal Wetlands Planning, Protection and Restoration Act","usgsCitation":"Stagg, C.L., Sharp, L., McGinnis, T., and Snedden, G., 2013, Submergence Vulnerability Index development and application to Coastwide Reference Monitoring System Sites and Coastal Wetlands Planning, Protection and Restoration Act projects: U.S. Geological Survey Open-File Report 2013-1163, iv, 12 p., https://doi.org/10.3133/ofr20131163.","productDescription":"iv, 12 p.","numberOfPages":"19","onlineOnly":"Y","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":277468,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131163.gif"},{"id":277466,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1163/"},{"id":277467,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1163/pdf/OF13-1163.pdf"}],"country":"United States","state":"Louisiana","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -94.04,28.93 ], [ -94.04,30.99 ], [ -88.82,30.99 ], [ -88.82,28.93 ], [ -94.04,28.93 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5230315fe4b04b8e63a2060c","contributors":{"authors":[{"text":"Stagg, Camille L. 0000-0002-1125-7253 staggc@usgs.gov","orcid":"https://orcid.org/0000-0002-1125-7253","contributorId":4111,"corporation":false,"usgs":true,"family":"Stagg","given":"Camille","email":"staggc@usgs.gov","middleInitial":"L.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":483761,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sharp, Leigh A.","contributorId":43879,"corporation":false,"usgs":true,"family":"Sharp","given":"Leigh A.","affiliations":[],"preferred":false,"id":483763,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGinnis, Thomas E.","contributorId":92959,"corporation":false,"usgs":true,"family":"McGinnis","given":"Thomas E.","affiliations":[],"preferred":false,"id":483764,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Snedden, Gregg A. 0000-0001-7821-3709","orcid":"https://orcid.org/0000-0001-7821-3709","contributorId":17338,"corporation":false,"usgs":true,"family":"Snedden","given":"Gregg A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":483762,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70124023,"text":"70124023 - 2013 - Is there room for all of us? Renewable energy and <i>Xerospermophilus mohavensis</i>","interactions":[],"lastModifiedDate":"2016-07-18T22:00:26","indexId":"70124023","displayToPublicDate":"2013-09-10T14:31:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"title":"Is there room for all of us? Renewable energy and <i>Xerospermophilus mohavensis</i>","docAbstract":"<p><span>Mohave ground squirrels </span><i>Xerospermophilus mohavensis</i><span> Merriam are small ground-dwelling rodents that have a highly restricted range in the northwest Mojave Desert, California, USA. Their small natural range is further reduced by habitat loss from agriculture, urban development, military training and recreational activities. Development of wind and solar resources for renewable energy has the potential to further reduce existing habitat. We used maximum entropy habitat models with observation data to describe current potential habitat in the context of future renewable energy development in the region. While 16% of historic habitat has been impacted by, or lost to, urbanization at present, an additional 10% may be affected by renewable energy development in the near future. Our models show that </span><i>X. mohavensis</i><span> habitat suitability is higher in areas slated for renewable energy development than in surrounding areas. We provide habitat maps that can be used to develop sampling designs, evaluate conservation corridors and inform development planning in the region.</span></p>","language":"English","publisher":"Inter-Research Science Center","doi":"10.3354/esr00487","usgsCitation":"Inman, R., Esque, T., Nussear, K.E., Leitner, P., Matocq, M.D., Weisberg, P.J., Dilts, T.E., and Vandergast, A.G., 2013, Is there room for all of us? Renewable energy and <i>Xerospermophilus mohavensis</i>: Endangered Species Research, v. 20, no. 1, p. 1-18, https://doi.org/10.3354/esr00487.","productDescription":"18 p.","startPage":"1","endPage":"18","ipdsId":"IP-040938","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":473545,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr00487","text":"Publisher Index Page"},{"id":293616,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Mojave Desert","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117.9789,34.1607 ], [ -117.9789,37.5219 ], [ -114.7254,37.5219 ], [ -114.7254,34.1607 ], [ -117.9789,34.1607 ] ] ] } } ] }","volume":"20","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"541165c2e4b0fe7e184a555f","contributors":{"authors":[{"text":"Inman, Richard D.","contributorId":91201,"corporation":false,"usgs":true,"family":"Inman","given":"Richard D.","affiliations":[],"preferred":false,"id":500564,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Esque, Todd C. tesque@usgs.gov","contributorId":3221,"corporation":false,"usgs":true,"family":"Esque","given":"Todd C.","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":500559,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nussear, Kenneth E. knussear@usgs.gov","contributorId":2695,"corporation":false,"usgs":true,"family":"Nussear","given":"Kenneth","email":"knussear@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":500558,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leitner, Philip","contributorId":31319,"corporation":false,"usgs":true,"family":"Leitner","given":"Philip","email":"","affiliations":[],"preferred":false,"id":500562,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Matocq, Marjorie D.","contributorId":25482,"corporation":false,"usgs":true,"family":"Matocq","given":"Marjorie","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":500561,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Weisberg, Peter J.","contributorId":33631,"corporation":false,"usgs":true,"family":"Weisberg","given":"Peter","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":500563,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dilts, Tomas E.","contributorId":17160,"corporation":false,"usgs":true,"family":"Dilts","given":"Tomas","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":500560,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Vandergast, Amy G. 0000-0002-7835-6571","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":97617,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","email":"","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":500565,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70123871,"text":"70123871 - 2013 - A network extension of species occupancy models in a patchy environment applied to the Yosemite toad (<i>Anaxyrus canorus</i>)","interactions":[],"lastModifiedDate":"2014-09-10T11:36:43","indexId":"70123871","displayToPublicDate":"2013-09-10T11:34:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"A network extension of species occupancy models in a patchy environment applied to the Yosemite toad (<i>Anaxyrus canorus</i>)","docAbstract":"A central challenge of conservation biology is using limited data to predict rare species occurrence and identify conservation areas that play a disproportionate role in regional persistence. Where species occupy discrete patches in a landscape, such predictions require data about environmental quality of individual patches and the connectivity among high quality patches. We present a novel extension to species occupancy modeling that blends traditionalpredictions of individual patch environmental quality with network analysis to estimate connectivity characteristics using limited survey data. We demonstrate this approach using environmental and geospatial attributes to predict observed occupancy patterns of the Yosemite toad (<i>Anaxyrus (= Bufo) canorus</i>) across >2,500 meadows in Yosemite National Park (USA). <i>A. canorus</i>, a Federal Proposed Species, breeds in shallow water associated with meadows. Our generalized linear model (GLM) accurately predicted ~84% of true presence-absence data on a subset of data withheld for testing. The predicted environmental quality of each meadow was iteratively ‘boosted’ by the quality of neighbors within dispersal distance. We used this park-wide meadow connectivity network to estimate the relative influence of an individual Meadow’s ‘environmental quality’ versus its ‘network quality’ to predict: a) clusters of high quality breeding meadows potentially linked by dispersal, b) breeding meadows with high environmental quality that are isolated from other such meadows, c) breeding meadows with lower environmental quality where long-term persistence may critically depend on the network neighborhood, and d) breeding meadows with the biggest impact on park-wide breeding patterns. Combined with targeted data on dispersal, genetics, disease, and other potential stressors, these results can guide designation of core conservation areas for <i>A. canorus</i> in Yosemite National Park.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS ONE","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"PlosOne","doi":"10.1371/journal.pone.0072200","usgsCitation":"Berlow, E.L., Knapp, R.A., Ostoja, S.M., Williams, R.J., McKenny, H., Matchett, J.R., Guo, Q., Fellers, G.M., Kleeman, P., Brooks, M.L., and Joppa, L., 2013, A network extension of species occupancy models in a patchy environment applied to the Yosemite toad (<i>Anaxyrus canorus</i>): PLoS ONE, v. 8, no. 8, e72200, https://doi.org/10.1371/journal.pone.0072200.","productDescription":"e72200","ipdsId":"IP-042749","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":473546,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0072200","text":"Publisher Index Page"},{"id":293606,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":293605,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0072200"}],"country":"United States","state":"California","otherGeospatial":"Yosemite National Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119.886496,37.494762 ], [ -119.886496,38.185228 ], [ -119.195416,38.185228 ], [ -119.195416,37.494762 ], [ -119.886496,37.494762 ] ] ] } } ] }","volume":"8","issue":"8","noUsgsAuthors":false,"publicationDate":"2013-08-12","publicationStatus":"PW","scienceBaseUri":"541165bfe4b0fe7e184a5550","contributors":{"authors":[{"text":"Berlow, Eric L.","contributorId":91416,"corporation":false,"usgs":false,"family":"Berlow","given":"Eric","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":500436,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knapp, Roland A.","contributorId":69901,"corporation":false,"usgs":false,"family":"Knapp","given":"Roland","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":500435,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ostoja, Steven M. sostoja@usgs.gov","contributorId":3039,"corporation":false,"usgs":true,"family":"Ostoja","given":"Steven","email":"sostoja@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":33665,"text":"USDA California Climate Hub, UC Davis","active":true,"usgs":false}],"preferred":false,"id":500430,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, Richard J.","contributorId":34443,"corporation":false,"usgs":true,"family":"Williams","given":"Richard","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":500432,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McKenny, Heather","contributorId":103193,"corporation":false,"usgs":true,"family":"McKenny","given":"Heather","affiliations":[],"preferred":false,"id":500438,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Matchett, John R. 0000-0002-2905-6468 jmatchett@usgs.gov","orcid":"https://orcid.org/0000-0002-2905-6468","contributorId":1669,"corporation":false,"usgs":true,"family":"Matchett","given":"John","email":"jmatchett@usgs.gov","middleInitial":"R.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":500429,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Guo, Qinghau","contributorId":35248,"corporation":false,"usgs":true,"family":"Guo","given":"Qinghau","email":"","affiliations":[],"preferred":false,"id":500433,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fellers, Gary M. 0000-0003-4092-0285 gary_fellers@usgs.gov","orcid":"https://orcid.org/0000-0003-4092-0285","contributorId":3150,"corporation":false,"usgs":true,"family":"Fellers","given":"Gary","email":"gary_fellers@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":500431,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kleeman, Patrick","contributorId":101608,"corporation":false,"usgs":true,"family":"Kleeman","given":"Patrick","affiliations":[],"preferred":false,"id":500437,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Brooks, Matthew L. 0000-0002-3518-6787 mlbrooks@usgs.gov","orcid":"https://orcid.org/0000-0002-3518-6787","contributorId":393,"corporation":false,"usgs":true,"family":"Brooks","given":"Matthew","email":"mlbrooks@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":500428,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Joppa, Lucas","contributorId":66606,"corporation":false,"usgs":true,"family":"Joppa","given":"Lucas","affiliations":[],"preferred":false,"id":500434,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70123898,"text":"70123898 - 2013 - Landscape-scale effects of fire severity on mixed-conifer and red fir forest structure in Yosemite National Park","interactions":[],"lastModifiedDate":"2014-09-10T09:51:19","indexId":"70123898","displayToPublicDate":"2013-09-10T09:45:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Landscape-scale effects of fire severity on mixed-conifer and red fir forest structure in Yosemite National Park","docAbstract":"<p>While fire shapes the structure of forests and acts as a keystone process, the details of how fire modifies forest structure have been difficult to evaluate because of the complexity of interactions between fires and forests. We studied this relationship across 69.2 km2 of Yosemite National Park, USA, that was subject to 32 fires ⩾40 ha between 1984 and 2010. Forests types included ponderosa pine (<i>Pinus ponderosa</i>), white fir-sugar pine (<i>Abies concolor/Pinus lambertiana</i>), and red fir (<i>Abies magnifica</i>). We estimated and stratified burned area by fire severity using the Landsat-derived Relativized differenced Normalized Burn Ratio (RdNBR). Airborne LiDAR data, acquired in July 2010, measured the vertical and horizontal structure of canopy material and landscape patterning of canopy patches and gaps. Increasing fire severity changed structure at the scale of fire severity patches, the arrangement of canopy patches and gaps within fire severity patches, and vertically within tree clumps. Each forest type showed an individual trajectory of structural change with increasing fire severity. As a result, the relationship between estimates of fire severity such as RdNBR and actual changes appears to vary among forest types. We found three arrangements of canopy patches and gaps associated with different fire severities: canopy-gap arrangements in which gaps were enclosed in otherwise continuous canopy (typically unburned and low fire severities); patch-gap arrangements in which tree clumps and gaps alternated and neither dominated (typically moderate fire severity); and open-patch arrangements in which trees were scattered across open areas (typically high fire severity).</p>\n<br>\n<p>Compared to stands outside fire perimeters, increasing fire severity generally resulted first in loss of canopy cover in lower height strata and increased number and size of gaps, then in loss of canopy cover in higher height strata, and eventually the transition to open areas with few or no trees. However, the estimated fire severities at which these transitions occurred differed for each forest type. Our work suggests that low severity fire in red fir forests and moderate severity fire in ponderosa pine and white fir-sugar pine forests would restore vertical and horizontal canopy structures believed to have been common prior to the start of widespread fire suppression in the early 1900s. The fusion of LiDAR and Landsat data identified post-fire structural conditions that would not be identified by Landsat alone, suggesting a broad applicability of combining Landsat and LiDAR data for landscape-scale structural analysis for fire management.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Forest Ecology and Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2012.08.044","usgsCitation":"Kane, V., Lutz, J.A., Roberts, S.L., Smith, D.F., McGaughey, R.J., Povak, N., and Brooks, M.L., 2013, Landscape-scale effects of fire severity on mixed-conifer and red fir forest structure in Yosemite National Park: Forest Ecology and Management, v. 287, p. 17-31, https://doi.org/10.1016/j.foreco.2012.08.044.","productDescription":"15 p.","startPage":"17","endPage":"31","ipdsId":"IP-038395","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":293584,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":293575,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.foreco.2012.08.044"}],"country":"United States","state":"California","otherGeospatial":"Yosemite National Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119.886496,37.494762 ], [ -119.886496,38.185228 ], [ -119.195416,38.185228 ], [ -119.195416,37.494762 ], [ -119.886496,37.494762 ] ] ] } } ] }","volume":"287","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"541165c3e4b0fe7e184a5562","chorus":{"doi":"10.1016/j.foreco.2012.08.044","url":"http://dx.doi.org/10.1016/j.foreco.2012.08.044","publisher":"Elsevier BV","authors":"Kane Van R., Lutz James A., Roberts Susan L., Smith Douglas F., McGaughey Robert J., Povak Nicholas A., Brooks Matthew L.","journalName":"Forest Ecology and Management","publicationDate":"1/2013","auditedOn":"11/1/2014"},"contributors":{"authors":[{"text":"Kane, Van R.","contributorId":25873,"corporation":false,"usgs":true,"family":"Kane","given":"Van R.","affiliations":[],"preferred":false,"id":500472,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lutz, James A.","contributorId":61350,"corporation":false,"usgs":true,"family":"Lutz","given":"James","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":500475,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roberts, Susan L.","contributorId":85312,"corporation":false,"usgs":true,"family":"Roberts","given":"Susan","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":500477,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Douglas F.","contributorId":76235,"corporation":false,"usgs":true,"family":"Smith","given":"Douglas","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":500476,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McGaughey, Robert J.","contributorId":36865,"corporation":false,"usgs":true,"family":"McGaughey","given":"Robert","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":500473,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Povak, Nicholas A.","contributorId":55749,"corporation":false,"usgs":true,"family":"Povak","given":"Nicholas A.","affiliations":[],"preferred":false,"id":500474,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brooks, Matthew L. 0000-0002-3518-6787 mlbrooks@usgs.gov","orcid":"https://orcid.org/0000-0002-3518-6787","contributorId":393,"corporation":false,"usgs":true,"family":"Brooks","given":"Matthew","email":"mlbrooks@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":500471,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70048084,"text":"sir20135143 - 2013 - Distribution of indoor radon concentrations in Pennsylvania, 1990-2007","interactions":[],"lastModifiedDate":"2016-08-10T21:18:13","indexId":"sir20135143","displayToPublicDate":"2013-09-09T14:57:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5143","title":"Distribution of indoor radon concentrations in Pennsylvania, 1990-2007","docAbstract":"<p>Results from 548,507 indoor radon tests from a database compiled by the Pennsylvania Department of Environmental Protection, Bureau of Radiation Protection, Radon Division, are evaluated in this report in an effort to determine areas where concentrations of radon are highest. Indoor radon concentrations were aggregated according to geologic unit and hydrogeologic setting for spatial analysis. Indoor radon concentrations greater than or equal to the U.S. Environmental Protection Agency (USEPA) action level of 4&nbsp;picocuries per liter (pCi/L) were observed for 39 percent of the test results; the highest concentration was&nbsp;1,866.4&nbsp;pCi/L.</p>\n<p>When analyzed according to Pennsylvania&rsquo;s geologic units, 93 of the&nbsp;188 (49.5&nbsp;percent) geologic units with indoor radon concentrations had median concentrations greater than the USEPA action level of 4&nbsp;pCi/L; most of these geologic units are located in the eastern part of the State and include metamorphic rocks, limestones, sandstones, shales, and glacial deposits. When analyzed according to Pennsylvania&rsquo;s hydrogeologic settings, 5 of the&nbsp;20 (25&nbsp;percent) settings had median indoor radon concentrations greater than the USEPA action level of 4&nbsp;pCi/L; these settings are located mostly in the south-central part of the&nbsp;State.</p>\n<p>Median indoor radon concentrations aggregated according to geologic units and hydrogeologic settings are useful for drawing general conclusions about the occurrence of indoor radon in specific geologic units and hydrogeologic settings, but the associated data and maps have limitations. The aggregated indoor radon data have testing and spatial accuracy limitations due to lack of available information regarding testing conditions and the imprecision of geocoded test locations. In addition, the associated data describing geologic units and hydrogeologic settings have spatial and interpretation accuracy limitations, which are a result of using statewide data to define conditions at test locations and geologic data that represent a broad interpretation of geologic units across the State. As a result, indoor air radon concentration distributions are not proposed for use in predicting individual concentrations at specific sites nor for use as a decision-making tool for property owners to decide whether to test for indoor radon concentrations at specific property&nbsp;locations.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135143","usgsCitation":"Gross, E.L., 2013, Distribution of indoor radon concentrations in Pennsylvania, 1990-2007: U.S. Geological Survey Scientific Investigations Report 2013-5143, Report: viii, 31 p.; PARnGeo: Zip file; PARnHydroGeo: Zip file, https://doi.org/10.3133/sir20135143.","productDescription":"Report: viii, 31 p.; PARnGeo: Zip file; PARnHydroGeo: Zip file","numberOfPages":"43","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"1990-01-01","temporalEnd":"2007-12-31","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":277434,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135143.png"},{"id":277433,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5143/"},{"id":277432,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5143/pdf/sir2013-5143.pdf","text":"Report","size":"16.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"scale":"100000","projection":"Albers Equal-Area Conic","country":"United 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,{"id":70048045,"text":"sir20135033 - 2013 - Analytical properties of some commercially available nitrate reductase enzymes evaluated as replacements for cadmium in automated, semiautomated, and manual colorimetric methods for determination of nitrate plus nitrite in water","interactions":[],"lastModifiedDate":"2013-09-06T13:33:45","indexId":"sir20135033","displayToPublicDate":"2013-09-06T13:24:15","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5033","title":"Analytical properties of some commercially available nitrate reductase enzymes evaluated as replacements for cadmium in automated, semiautomated, and manual colorimetric methods for determination of nitrate plus nitrite in water","docAbstract":"A multiyear research effort at the U.S. Geological Survey (USGS) National Water Quality Laboratory (NWQL) evaluated several commercially available nitrate reductase (NaR) enzymes as replacements for toxic cadmium in longstanding automated colorimetric air-segmented continuous-flow analyzer (CFA) methods for determining nitrate plus nitrite (NO<sub>x</sub>) in water. This research culminated in USGS approved standard- and low-level enzymatic reduction, colorimetric automated discrete analyzer NO<sub>x</sub> methods that have been in routine operation at the NWQL since October 2011. The enzyme used in these methods (AtNaR2) is a product of recombinant expression of NaR from Arabidopsis thaliana (L.) Heynh. (mouseear cress) in the yeast Pichia pastoris. Because the scope of the validation report for these new automated discrete analyzer methods, published as U.S. Geological Survey Techniques and Methods 5–B8, was limited to performance benchmarks and operational details, extensive foundational research with different enzymes—primarily YNaR1, a product of recombinant expression of NaR from Pichia angusta in the yeast Pichia pastoris—remained unpublished until now. This report documents research and development at the NWQL that was foundational to development and validation of the discrete analyzer methods. It includes: (1) details of instrumentation used to acquire kinetics data for several NaR enzymes in the presence and absence of known or suspected inhibitors in relation to reaction temperature and reaction pH; and (2) validation results—method detection limits, precision and bias estimates, spike recoveries, and interference studies—for standard- and low-level automated colorimetric CFA-YNaR1 reduction NO<sub>x</sub> methods in relation to corresponding USGS approved CFA cadmium-reduction (CdR) NO<sub>x</sub> methods. The cornerstone of this validation is paired sample statistical and graphical analysis of NOx concentrations from more than 3,800 geographically and seasonally diverse surface-water and groundwater samples that were analyzed in parallel by CFA-CdR and CFA enzyme-reduction methods. Finally, (3) demonstration of a semiautomated batch procedure in which 2-milliliter analyzer cups or disposable spectrophotometer cuvettes serve as reaction vessels for enzymatic reduction of nitrate to nitrite prior to analytical determinations. After the reduction step, analyzer cups are loaded onto CFA, flow injection, or discrete analyzers for simple, rapid, automatic nitrite determinations. In the case of manual determinations, analysts dispense colorimetric reagents into cuvettes containing post-reduction samples, allow time for color to develop, insert cuvettes individually into a spectrophotometer, and record percent transmittance or absorbance in relation to a reagent blank. Data presented here demonstrate equivalent analytical performance of enzymatic reduction NO<sub>x</sub> methods in these various formats to that of benchmark CFA-CdR NO<sub>x</sub> methods.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135033","collaboration":"Prepared by the U.S. Geological Survey Office of Water Quality, National Water Quality Laboratory","usgsCitation":"Patton, C.J., and Kryskalla, J.R., 2013, Analytical properties of some commercially available nitrate reductase enzymes evaluated as replacements for cadmium in automated, semiautomated, and manual colorimetric methods for determination of nitrate plus nitrite in water: U.S. Geological Survey Scientific Investigations Report 2013-5033, vii, 36 p., https://doi.org/10.3133/sir20135033.","productDescription":"vii, 36 p.","numberOfPages":"48","costCenters":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true}],"links":[{"id":277398,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135033.gif"},{"id":277396,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5033/"},{"id":277397,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5033/pdf/sir2013-5033.pdf"}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"522aeb63e4b08fd0132e7919","contributors":{"authors":[{"text":"Patton, Charles J. cjpatton@usgs.gov","contributorId":809,"corporation":false,"usgs":true,"family":"Patton","given":"Charles","email":"cjpatton@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":483660,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kryskalla, Jennifer R.","contributorId":91563,"corporation":false,"usgs":true,"family":"Kryskalla","given":"Jennifer","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":483661,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70048038,"text":"ds790 - 2013 - Water-level data for the Albuquerque Basin and adjacent areas, central New Mexico, period of record through September 30, 2012","interactions":[],"lastModifiedDate":"2026-05-20T19:08:28.47079","indexId":"ds790","displayToPublicDate":"2013-09-06T12:54:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"790","displayTitle":"Water-Level Data for the Albuquerque Basin and Adjacent Areas, Central New Mexico, Period of Record Through September 30, 2012","title":"Water-level data for the Albuquerque Basin and adjacent areas, central New Mexico, period of record through September 30, 2012","docAbstract":"<p>The Albuquerque Basin, located in central New Mexico, is about 100 miles long and 25–40 miles wide. The basin is defined as the extent of consolidated and unconsolidated deposits of Tertiary and Quaternary age that encompasses the structural Rio Grande Rift within the basin. Drinking-water supplies throughout the basin were obtained solely from groundwater resources until December 2008, when surface water from the Rio Grande began being treated and integrated into the system. A population increase of about 20 percent in the basin from 1990 to 2000 and a 22 percent increase from 2000 to 2010 resulted in an increased demand for water. An initial network of wells was established by the U.S. Geological Survey (USGS) in cooperation with the City of Albuquerque from April 1982 through September 1983 to monitor changes in groundwater levels throughout the basin. This network consisted of 6 wells with analog-to-digital recorders and 27 wells where water levels were measured monthly in 1983. Currently (2012), the network consists of 126 wells and piezometers. (A piezometer is a specialized well open to a specific depth in the aquifer, often of small diameter and nested with other piezometers open to different depths.) The USGS, in cooperation with the Albuquerque Bernalillo County Water Utility Authority (ABCWUA), currently (2012) measures and reports water levels from the 126 wells and piezometers in the network; this report presents water-level data collected by USGS personnel at those 126 sites through water year 2012.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds790","collaboration":"Prepared in cooperation with the Albuquerque Bernalillo County Water Utility Authority","usgsCitation":"Beman, J.E., 2013, Water-level data for the Albuquerque Basin and adjacent areas, central New Mexico, period of record through September 30, 2012 (Version 1.1: August 2021): U.S. Geological Survey Data Series 790, iii, 32 p., https://doi.org/10.3133/ds790.","productDescription":"iii, 32 p.","numberOfPages":"39","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":504579,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_98941.htm","linkFileType":{"id":5,"text":"html"}},{"id":388197,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/ds/790/versionHist.txt","text":"Version History","size":"536 B","linkFileType":{"id":2,"text":"txt"},"description":"DS 790 Version History"},{"id":388196,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/790/ds790.pdf","text":"Report","size":"4.68 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 790"},{"id":388195,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/790/coverthb2.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Albuquerque Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -107.5255,33.9989 ], [ -107.5255,35.9976 ], [ -105.9864,35.9976 ], [ -105.9864,33.9989 ], [ -107.5255,33.9989 ] ] ] } } ] }","edition":"Version 1.1: August 2021","contact":"<p><a data-mce-href=\"mailto:%20dc_nm@usgs.gov\" href=\"mailto:%20dc_nm@usgs.gov\">Director</a>, <a data-mce-href=\"https://www.usgs.gov/centers/nm-water\" href=\"https://www.usgs.gov/centers/nm-water\">New Mexico Water Science Center</a><br>U.S. Geological Survey<br>6700 Edith Blvd. NE<br>Albuquerque, NM 87113<br></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Water-Level Data</li><li>References Cited</li><li>Water-Level Data for Selected Wells and Piezometers in the Albuquerque Basin</li></ul>","revisedDate":"2021-08-25","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"522aeb6be4b08fd0132e7961","contributors":{"authors":[{"text":"Beman, Joseph E. 0000-0002-0689-029X jebeman@usgs.gov","orcid":"https://orcid.org/0000-0002-0689-029X","contributorId":2619,"corporation":false,"usgs":true,"family":"Beman","given":"Joseph","email":"jebeman@usgs.gov","middleInitial":"E.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":483636,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70048035,"text":"70048035 - 2013 - A comprehensive evaluation of two MODIS evapotranspiration products over the conterminous United States: using point and gridded FLUXNET and water balance ET","interactions":[],"lastModifiedDate":"2013-09-06T12:47:19","indexId":"70048035","displayToPublicDate":"2013-09-06T12:38:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"A comprehensive evaluation of two MODIS evapotranspiration products over the conterminous United States: using point and gridded FLUXNET and water balance ET","docAbstract":"Remote sensing datasets are increasingly being used to provide spatially explicit large scale evapotranspiration (ET) estimates. Extensive evaluation of such large scale estimates is necessary before they can be used in various applications. In this study, two monthly MODIS 1 km ET products, MODIS global ET (MOD16) and Operational Simplified Surface Energy Balance (SSEBop) ET, are validated over the conterminous United States at both point and basin scales. Point scale validation was performed using eddy covariance FLUXNET ET (FLET) data (2001–2007) aggregated by year, land cover, elevation and climate zone. Basin scale validation was performed using annual gridded FLUXNET ET (GFET) and annual basin water balance ET (WBET) data aggregated by various hydrologic unit code (HUC) levels. Point scale validation using monthly data aggregated by years revealed that the MOD16 ET and SSEBop ET products showed overall comparable annual accuracies. For most land cover types, both ET products showed comparable results. However, SSEBop showed higher performance for Grassland and Forest classes; MOD16 showed improved performance in the Woody Savanna class. Accuracy of both the ET products was also found to be comparable over different climate zones. However, SSEBop data showed higher skill score across the climate zones covering the western United States. Validation results at different HUC levels over 2000–2011 using GFET as a reference indicate higher accuracies for MOD16 ET data. MOD16, SSEBop and GFET data were validated against WBET (2000–2009), and results indicate that both MOD16 and SSEBop ET matched the accuracies of the global GFET dataset at different HUC levels. Our results indicate that both MODIS ET products effectively reproduced basin scale ET response (up to 25% uncertainty) compared to CONUS-wide point-based ET response (up to 50–60% uncertainty) illustrating the reliability of MODIS ET products for basin-scale ET estimation. Results from this research would guide the additional parameter refinement required for the MOD16 and SSEBop algorithms in order to further improve their accuracy and performance for agro-hydrologic applications.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Remote Sensing of Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2013.07.013","usgsCitation":"Velpuri, N.M., Senay, G., Singh, R.K., Bohms, S., and Verdin, J.P., 2013, A comprehensive evaluation of two MODIS evapotranspiration products over the conterminous United States: using point and gridded FLUXNET and water balance ET: Remote Sensing of Environment, v. 139, p. 35-49, https://doi.org/10.1016/j.rse.2013.07.013.","productDescription":"15 p.","startPage":"35","endPage":"49","numberOfPages":"15","ipdsId":"IP-046110","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":277386,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":277383,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2013.07.013"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.8,24.5 ], [ -124.8,49.383333 ], [ -66.95,49.383333 ], [ -66.95,24.5 ], [ -124.8,24.5 ] ] ] } } ] }","volume":"139","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"522aeb52e4b08fd0132e7911","contributors":{"authors":[{"text":"Velpuri, Naga M. 0000-0002-6370-1926","orcid":"https://orcid.org/0000-0002-6370-1926","contributorId":96183,"corporation":false,"usgs":true,"family":"Velpuri","given":"Naga","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":483634,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senay, Gabriel B. 0000-0002-8810-8539","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":66808,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel B.","affiliations":[],"preferred":false,"id":483633,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Singh, Ramesh K. 0000-0002-8164-3483 rsingh@usgs.gov","orcid":"https://orcid.org/0000-0002-8164-3483","contributorId":3895,"corporation":false,"usgs":true,"family":"Singh","given":"Ramesh","email":"rsingh@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":483632,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bohms, Stefanie 0000-0002-2979-4655 sbohms@usgs.gov","orcid":"https://orcid.org/0000-0002-2979-4655","contributorId":3148,"corporation":false,"usgs":true,"family":"Bohms","given":"Stefanie","email":"sbohms@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":483631,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Verdin, James P. 0000-0003-0238-9657 verdin@usgs.gov","orcid":"https://orcid.org/0000-0003-0238-9657","contributorId":720,"corporation":false,"usgs":true,"family":"Verdin","given":"James","email":"verdin@usgs.gov","middleInitial":"P.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":483630,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70048023,"text":"ofr20121183 - 2013 - Massachusetts shoreline change project: a GIS compilation of vector shorelines and associated shoreline change data for the 2013 update","interactions":[],"lastModifiedDate":"2013-09-06T10:44:17","indexId":"ofr20121183","displayToPublicDate":"2013-09-06T10:30:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1183","title":"Massachusetts shoreline change project: a GIS compilation of vector shorelines and associated shoreline change data for the 2013 update","docAbstract":"Identifying the rates and trends associated with the position of the shoreline through time presents vital information on potential impacts these changes may have on coastal populations and infrastructure, and supports informed coastal management decisions. This report publishes the historical shoreline data used to assess the scale and timing of erosion and accretion along the Massachusetts coast from New Hampshire to Rhode Island including all of Cape Cod, Martha’s Vineyard, Nantucket and the Elizabeth Islands. This data is an update to the Massachusetts Office of Coastal Zone Management Shoreline Change Project. Shoreline positions from the past 164 years (1845 to 2009) were used to compute the shoreline change rates. These data include a combined length of 1,804 kilometers of new shoreline data derived from color orthophoto imagery collected in 2008 and 2009, and topographic lidar collected in 2007. These new shorelines have been added to previously published historic shoreline data from the Massachusetts Office of Coastal Zone Management and the U.S. Geological Survey. A detailed report containing a discussion of the shoreline change data presented here and a summary of the resulting rates is available and cited at the end of the Introduction section of this report.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121183","usgsCitation":"Smith, T.L., Himmelstoss, E., and Thieler, E.R., 2013, Massachusetts shoreline change project: a GIS compilation of vector shorelines and associated shoreline change data for the 2013 update: U.S. Geological Survey Open-File Report 2012-1183, https://doi.org/10.3133/ofr20121183.","onlineOnly":"Y","temporalStart":"1844-12-30","temporalEnd":"2009-12-31","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":277369,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20121183.gif"},{"id":277368,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1183/title_page.html"},{"id":277367,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1183/"}],"country":"United States","state":"Massachusetts","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -71.8437,41.239 ], [ -71.8437,42.8868 ], [ -69.928,42.8868 ], [ -69.928,41.239 ], [ -71.8437,41.239 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"522aeb69e4b08fd0132e7949","contributors":{"authors":[{"text":"Smith, Theresa L.","contributorId":80163,"corporation":false,"usgs":true,"family":"Smith","given":"Theresa","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":483610,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Himmelstoss, Emily A.","contributorId":24736,"corporation":false,"usgs":true,"family":"Himmelstoss","given":"Emily A.","affiliations":[],"preferred":false,"id":483609,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thieler, E. Robert 0000-0003-4311-9717 rthieler@usgs.gov","orcid":"https://orcid.org/0000-0003-4311-9717","contributorId":2488,"corporation":false,"usgs":true,"family":"Thieler","given":"E.","email":"rthieler@usgs.gov","middleInitial":"Robert","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":483608,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
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