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For the State of Texas, elevation data are critical for natural resources conservation; wildfire management, planning, and response; flood risk management; agriculture and precision farming; infrastructure and construction management; water supply and quality; and other business uses. Today, high-quality light detection and ranging (lidar) data are the source for creating elevation models and other elevation datasets. Federal, State, and local agencies work in partnership to (1) replace data, on a national basis, that are (on average) 30 years old and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The new 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.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133097","usgsCitation":"Carswell, W., 2013, The 3D Elevation Program: summary for Texas: U.S. Geological Survey Fact Sheet 2013-3097, 2 p., https://doi.org/10.3133/fs20133097.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":278281,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133097.gif"},{"id":278279,"type":{"id":15,"text":"Index 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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":485000,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70048529,"text":"sim3257 - 2013 - Geologic map of the Washougal quadrangle, Clark County, Washington, and Multnomah County, Oregon","interactions":[],"lastModifiedDate":"2023-06-02T16:53:15.721814","indexId":"sim3257","displayToPublicDate":"2013-10-18T12:13:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3257","title":"Geologic map of the Washougal quadrangle, Clark County, Washington, and Multnomah County, Oregon","docAbstract":"The Washougal 7.5’ quadrangle spans the boundary between the Portland Basin and the Columbia River Gorge, approximately 30 km east of Portland, Oregon. The map area contains the westernmost portion of the Columbia River Gorge National Scenic area as well as the rapidly growing areas surrounding the Clark County, Washington, cities of Camas and Washougal. The Columbia River transects the map area, and two major tributaries, the Washougal River in Washington and the Sandy River in Oregon, also flow through the quadrangle. The Columbia, Washougal, and Sandy Rivers have all cut deep valleys through hilly uplands, exposing Oligocene volcanic bedrock in the north part of the map area and lava flows of the Miocene Columbia River Basalt Group in the western Columbia River Gorge. Elsewhere in the map area, these older rocks are buried beneath weakly consolidated to well-consolidated Neogene and younger basin-fill sedimentary rocks and Quaternary volcanic and sedimentary deposits. The Portland Basin is part of the Coastal Lowland that separates the Cascade Range from the Oregon Coast Range. The basin has been interpreted as a pull-apart basin located in the releasing stepover between two en echelon, northwest-striking, right-lateral fault zones. These fault zones are thought to reflect regional transpression, transtension, and dextral shear within the forearc in response to oblique subduction of the Pacific plate along the Cascadia Subduction Zone. The southwestern margin of the Portland Basin is a well-defined topographic break along the base of the Tualatin Mountains, an asymmetric anticlinal ridge that is bounded on its northeast flank by the Portland Hills Fault Zone, which is probably an active structure. The nature of the corresponding northeastern margin of the basin is less clear, but a series of poorly defined and partially buried dextral extensional structures has been hypothesized from topography, microseismicity, potential-field anomalies, and reconnaissance geologic mapping. This map is a contribution to a program designed to improve the geologic database for the Portland Basin region of the Pacific Northwest urban corridor, the densely populated Cascadia forearc region of western Washington and Oregon. Updated, more detailed information on the bedrock and surficial geology of the basin and its surrounding area will facilitate improved assessments of seismic risk, and resource availability in this rapidly growing region.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3257","usgsCitation":"Evarts, R.C., O'Connor, J., and Tolan, T.L., 2013, Geologic map of the Washougal quadrangle, Clark County, Washington, and Multnomah County, Oregon: U.S. Geological Survey Scientific Investigations Map 3257, Pamphlet: iii, 46 p.; 1 Plate: 54.84 x 36.00 inches; Metadata; Readme, https://doi.org/10.3133/sim3257.","productDescription":"Pamphlet: iii, 46 p.; 1 Plate: 54.84 x 36.00 inches; Metadata; Readme","numberOfPages":"49","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"links":[{"id":398883,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_99068.htm","linkFileType":{"id":5,"text":"html"}},{"id":278248,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3257/pdf/sim3257_map.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":278250,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3257/downloads/washougal_metadata.txt","linkFileType":{"id":1,"text":"pdf"}},{"id":278247,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3257/pdf/sim3257_pamphlet.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":278249,"rank":6,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3257/pdf/washougal_readme.pdf"},{"id":278251,"rank":1,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3257/downloads/sim3257_db.zip"},{"id":278252,"rank":2,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3257/downloads/sim3257_shp.zip"},{"id":278253,"rank":7,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3257.gif"}],"scale":"24000","country":"United States","state":"Oregon","county":"Clark County, Multnomah County","otherGeospatial":"Washougal quadrangle","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.375,\n              45.5\n            ],\n            [\n              -122.25,\n              45.5\n            ],\n            [\n              -122.25,\n              45.625\n            ],\n            [\n              -122.375,\n              45.625\n            ],\n            [\n              -122.375,\n              45.5\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52624a67e4b079a99629a0e2","contributors":{"authors":[{"text":"Evarts, Russell C. revarts@usgs.gov","contributorId":1974,"corporation":false,"usgs":true,"family":"Evarts","given":"Russell","email":"revarts@usgs.gov","middleInitial":"C.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":484973,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O'Connor, Jim E. 0000-0002-7928-5883 oconnor@usgs.gov","orcid":"https://orcid.org/0000-0002-7928-5883","contributorId":140771,"corporation":false,"usgs":true,"family":"O'Connor","given":"Jim E.","email":"oconnor@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":484975,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tolan, Terry L.","contributorId":31029,"corporation":false,"usgs":true,"family":"Tolan","given":"Terry","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":484974,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70073512,"text":"70073512 - 2013 - Bayes and empirical Bayes estimators of abundance and density from spatial capture-recapture data","interactions":[],"lastModifiedDate":"2014-01-21T09:22:44","indexId":"70073512","displayToPublicDate":"2013-10-15T09:16:00","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":"Bayes and empirical Bayes estimators of abundance and density from spatial capture-recapture data","docAbstract":"In capture-recapture and mark-resight surveys, movements of individuals both within and between sampling periods can alter the susceptibility of individuals to detection over the region of sampling. In these circumstances spatially explicit capture-recapture (SECR) models, which incorporate the observed locations of individuals, allow population density and abundance to be estimated while accounting for differences in detectability of individuals. In this paper I propose two Bayesian SECR models, one for the analysis of recaptures observed in trapping arrays and another for the analysis of recaptures observed in area searches. In formulating these models I used distinct submodels to specify the distribution of individual home-range centers and the observable recaptures associated with these individuals. This separation of ecological and observational processes allowed me to derive a formal connection between Bayes and empirical Bayes estimators of population abundance that has not been established previously. I showed that this connection applies to every Poisson point-process model of SECR data and provides theoretical support for a previously proposed estimator of abundance based on recaptures in trapping arrays. To illustrate results of both classical and Bayesian methods of analysis, I compared Bayes and empirical Bayes esimates of abundance and density using recaptures from simulated and real populations of animals. Real populations included two iconic datasets: recaptures of tigers detected in camera-trap surveys and recaptures of lizards detected in area-search surveys. In the datasets I analyzed, classical and Bayesian methods provided similar – and often identical – inferences, which is not surprising given the sample sizes and the noninformative priors used in the analyses.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS ONE","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"PLoS ONE","doi":"10.1371/journal.pone.0084017","usgsCitation":"Dorazio, R.M., 2013, Bayes and empirical Bayes estimators of abundance and density from spatial capture-recapture data: PLoS ONE, v. 8, no. 12, 12 p., https://doi.org/10.1371/journal.pone.0084017.","productDescription":"12 p.","ipdsId":"IP-044554","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":473484,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0084017","text":"Publisher Index Page"},{"id":281302,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281301,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0084017"}],"volume":"8","issue":"12","noUsgsAuthors":false,"publicationDate":"2013-12-27","publicationStatus":"PW","scienceBaseUri":"53cd4efae4b0b290850f26cb","contributors":{"authors":[{"text":"Dorazio, Robert M. 0000-0003-2663-0468 bob_dorazio@usgs.gov","orcid":"https://orcid.org/0000-0003-2663-0468","contributorId":1668,"corporation":false,"usgs":true,"family":"Dorazio","given":"Robert","email":"bob_dorazio@usgs.gov","middleInitial":"M.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":488864,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70048807,"text":"70048807 - 2013 - Classification of freshwater ice conditions on the Alaskan Arctic Coastal Plain using ground penetrating radar and TerraSAR-X satellite data","interactions":[],"lastModifiedDate":"2013-11-06T10:27:00","indexId":"70048807","displayToPublicDate":"2013-10-11T09:37:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2068,"text":"International Journal of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Classification of freshwater ice conditions on the Alaskan Arctic Coastal Plain using ground penetrating radar and TerraSAR-X satellite data","docAbstract":"Arctic freshwater ecosystems have responded rapidly to climatic changes over the last half century. Lakes and rivers are experiencing a thinning of the seasonal ice cover, which may increase potential over-wintering freshwater habitat, winter water supply for industrial withdrawal, and permafrost degradation. Here, we combined the use of ground penetrating radar (GPR) and high-resolution (HR) spotlight TerraSAR-X (TSX) satellite data (1.25 m resolution) to identify and characterize floating ice and grounded ice conditions in lakes, ponds, beaded stream pools, and an alluvial river channel. Classified ice conditions from the GPR and the TSX data showed excellent agreement: 90.6% for a predominantly floating ice lake, 99.7% for a grounded ice lake, 79.0% for a beaded stream course, and 92.1% for the alluvial river channel. A GIS-based analysis of 890 surface water features larger than 0.01 ha showed that 42% of the total surface water area potentially provided over-wintering habitat during the 2012/2013 winter. Lakes accounted for 89% of this area, whereas the alluvial river channel accounted for 10% and ponds and beaded stream pools each accounted for <1%. Identification of smaller landscape features such as beaded stream pools may be important because of their distribution and role in connecting other water bodies on the landscape. These findings advance techniques for detecting and knowledge associated with potential winter habitat distribution for fish and invertebrates at the local scale in a region of the Arctic with increasing stressors related to climate and land use change.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"International Journal of Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Taylor & Francis","doi":"10.1080/2150704X.2013.834392","usgsCitation":"Jones, B.M., Gusmeroli, A., Arp, C.D., Strozzi, T., Grosse, G., Gaglioti, B.V., and Whitman, M.S., 2013, Classification of freshwater ice conditions on the Alaskan Arctic Coastal Plain using ground penetrating radar and TerraSAR-X satellite data: International Journal of Remote Sensing, v. 34, no. 23, p. 8267-8279, https://doi.org/10.1080/2150704X.2013.834392.","productDescription":"13 p.","startPage":"8267","endPage":"8279","numberOfPages":"13","ipdsId":"IP-049177","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":278875,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278874,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/2150704X.2013.834392"}],"country":"United States","state":"Alaska","otherGeospatial":"Arctic Coastal Plain;Fish Creek;Judy Creek;Ublutuoch River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -151.599998,70.199529 ], [ -151.599998,70.335093 ], [ -151.259422,70.335093 ], [ -151.259422,70.199529 ], [ -151.599998,70.199529 ] ] ] } } ] }","volume":"34","issue":"23","noUsgsAuthors":false,"publicationDate":"2013-09-23","publicationStatus":"PW","scienceBaseUri":"527b72f5e4b0a7295d9b85b5","contributors":{"authors":[{"text":"Jones, Benjamin M. 0000-0002-1517-4711 bjones@usgs.gov","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":2286,"corporation":false,"usgs":true,"family":"Jones","given":"Benjamin","email":"bjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":true,"id":485676,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gusmeroli, Alessio","contributorId":106003,"corporation":false,"usgs":true,"family":"Gusmeroli","given":"Alessio","affiliations":[],"preferred":false,"id":485682,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arp, Christopher D.","contributorId":17330,"corporation":false,"usgs":false,"family":"Arp","given":"Christopher","email":"","middleInitial":"D.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":485678,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Strozzi, Tazio","contributorId":64547,"corporation":false,"usgs":true,"family":"Strozzi","given":"Tazio","email":"","affiliations":[],"preferred":false,"id":485679,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grosse, Guido","contributorId":101475,"corporation":false,"usgs":true,"family":"Grosse","given":"Guido","affiliations":[{"id":34291,"text":"University of Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":485681,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gaglioti, Benjamin V. 0000-0003-0591-5253 bgaglioti@usgs.gov","orcid":"https://orcid.org/0000-0003-0591-5253","contributorId":4521,"corporation":false,"usgs":true,"family":"Gaglioti","given":"Benjamin","email":"bgaglioti@usgs.gov","middleInitial":"V.","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":485677,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Whitman, Matthew S.","contributorId":67961,"corporation":false,"usgs":false,"family":"Whitman","given":"Matthew","email":"","middleInitial":"S.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":485680,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70048761,"text":"70048761 - 2013 - A model of strength","interactions":[],"lastModifiedDate":"2014-05-30T14:43:23","indexId":"70048761","displayToPublicDate":"2013-10-11T07:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3338,"text":"Science","active":true,"publicationSubtype":{"id":10}},"title":"A model of strength","docAbstract":"In her AAAS News & Notes piece \"Can the Southwest manage its thirst?\" (26 July, p. 362), K. Wren quotes Ajay Kalra, who advocates a particular method for predicting Colorado River streamflow \"because it eschews complex physical climate models for a statistical data-driven modeling approach.\" A preference for data-driven models may be appropriate in this individual situation, but it is not so generally, Data-driven models often come with a warning against extrapolating beyond the range of the data used to develop the models. When the future is like the past, data-driven models can work well for prediction, but it is easy to over-model local or transient phenomena, often leading to predictive inaccuracy (1). Mechanistic models are built on established knowledge of the process that connects the response variables with the predictors, using information obtained outside of an extant data set. One may shy away from a mechanistic approach when the underlying process is judged to be too complicated, but good predictive models can be constructed with statistical components that account for ingredients missing in the mechanistic analysis. Models with sound mechanistic components are more generally applicable and robust than data-driven models.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Science","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Science","doi":"10.1126/science.342.6155.192","usgsCitation":"Johnson, D.H., and Cook, R., 2013, A model of strength: Science, v. 342, p. 192-193, https://doi.org/10.1126/science.342.6155.192.","productDescription":"2 p.","startPage":"192","endPage":"193","numberOfPages":"2","ipdsId":"IP-051404","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":285051,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":285050,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1126/science.342.6155.192"}],"volume":"342","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53558fc0e4b0120853e8be06","contributors":{"authors":[{"text":"Johnson, Douglas H. 0000-0002-7778-6641 douglas_h_johnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7778-6641","contributorId":1387,"corporation":false,"usgs":true,"family":"Johnson","given":"Douglas","email":"douglas_h_johnson@usgs.gov","middleInitial":"H.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":485583,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cook, R.D.","contributorId":6371,"corporation":false,"usgs":true,"family":"Cook","given":"R.D.","email":"","affiliations":[],"preferred":false,"id":485584,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70047120,"text":"70047120 - 2013 - Segmenting images automatically for granulometry and sedimentology: a martian case study","interactions":[],"lastModifiedDate":"2014-02-05T15:03:23","indexId":"70047120","displayToPublicDate":"2013-10-09T10:16:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"Segmenting images automatically for granulometry and sedimentology: a martian case study","docAbstract":"In a companion work, we bridge the gap between mature segmentation software used in terrestrial sedimentology\nand emergent planetary segmentation with an original algorithm optimized to segment\nwhole images from the Microscopic Imager (MI) of the Mars Exploration Rovers (MER). In this work,\nwe compare its semi-automated outcome with manual photoanalyses using unconsolidated sediment\nat Gusev and Meridiani Planum sites for geologic context. On average, our code and manual segmentation\nconverge to within ~\u000210% in the number and total area of identified grains in a pseudo-random, single\nblind comparison of 50 samples. Unlike manual segmentation, it also locates finer grains in an image with\ninternal consistency, enabling robust comparisons across geologic contexts. When implemented in Mathematica-\n8, the algorithm segments an entire MI image within minutes, surpassing the extent and speed\npossible with manual segmentation by about a factor of ten. These results indicate that our algorithm\nenables not only new sedimentological insight from the MER MI data, but also detailed sedimentology\nwith the Mars Science Laboratory’s Mars Hand Lens Instrument.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Icarus","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2013.09.021","usgsCitation":"Karunatillake, S., McLennan, S.M., Herkenhoff, K.E., Husch, J.M., Hardgrove, C., and Skok, J., 2013, Segmenting images automatically for granulometry and sedimentology: a martian case study: Icarus, p. 408-417, https://doi.org/10.1016/j.icarus.2013.09.021.","productDescription":"10 p.","startPage":"408","endPage":"417","ipdsId":"IP-034002","costCenters":[],"links":[{"id":282053,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":282051,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.icarus.2013.09.021"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd71fde4b0b29085108048","contributors":{"authors":[{"text":"Karunatillake, Suniti","contributorId":40125,"corporation":false,"usgs":true,"family":"Karunatillake","given":"Suniti","email":"","affiliations":[],"preferred":false,"id":481114,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McLennan, Scott M.","contributorId":95388,"corporation":false,"usgs":true,"family":"McLennan","given":"Scott","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":481116,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herkenhoff, Kenneth E. 0000-0002-3153-6663 kherkenhoff@usgs.gov","orcid":"https://orcid.org/0000-0002-3153-6663","contributorId":2275,"corporation":false,"usgs":true,"family":"Herkenhoff","given":"Kenneth","email":"kherkenhoff@usgs.gov","middleInitial":"E.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":481111,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Husch, Jonathan M.","contributorId":69061,"corporation":false,"usgs":true,"family":"Husch","given":"Jonathan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":481115,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hardgrove, Craig","contributorId":13546,"corporation":false,"usgs":false,"family":"Hardgrove","given":"Craig","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":481113,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Skok, J.R.","contributorId":11509,"corporation":false,"usgs":true,"family":"Skok","given":"J.R.","email":"","affiliations":[],"preferred":false,"id":481112,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70186187,"text":"70186187 - 2013 - Phylogenetic conservatism in plant phenology","interactions":[],"lastModifiedDate":"2017-03-31T10:18:38","indexId":"70186187","displayToPublicDate":"2013-10-08T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2242,"text":"Journal of Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Phylogenetic conservatism in plant phenology","docAbstract":"Phenological events – defined points in the life cycle of a plant or animal – have been regarded as highly plastic traits, reflecting flexible responses to various environmental cues.\nThe ability of a species to track, via shifts in phenological events, the abiotic environment through time might dictate its vulnerability to future climate change. Understanding the predictors and drivers of phenological change is therefore critical. \nHere, we evaluated evidence for phylogenetic conservatism – the tendency for closely related spe-cies to share similar ecological and biological attributes – in phenological traits across flowering plants. We aggregated published and unpublished data on timing of first flower and first leaf, encompassing ~4000 species at 23 sites across the Northern Hemisphere. We reconstructed the phylogeny for the setof included species, first, using the software program Phylomatic, and second, from DNA data. We then quantified phylogenetic conservatism in plant phenology within and across sites.\nWe show that more closely related species tend to flower and leaf at similar times. By contrastingmean flowering times within and across sites, however, we illustrate that it is not the time of yearthat is conserved, but rather the phenological responses to a common set of abiotic cues.\nOur findings suggest that species cannot be treated as statistically independent when modelling phenological responses.\nSynthesis. Closely related species tend to resemble each other in the timing of their life-history events, a likely product of evolutionarily conser ved responses to environmental cues. The search for the underlying drivers of phenology must therefore account for species’ shared evolutionary histories.","language":"English","publisher":"Wiley","doi":"10.1111/1365-2745.12154","usgsCitation":"Davies, T.J., Wolkovich, E.M., Kraft, N.J., Salamin, N., Allen, J.M., Ault, T.R., Betancourt, J.L., Bolmgren, K., Cleland, E.E., Cook, B.I., Crimmins, T.M., Mazer, S.J., McCabe, G., Pau, S., Regetz, J., Schwartz, M.D., and Travers, S.E., 2013, Phylogenetic conservatism in plant phenology: Journal of Ecology, v. 101, no. 6, p. 1520-1530, https://doi.org/10.1111/1365-2745.12154.","productDescription":"11 p.","startPage":"1520","endPage":"1530","ipdsId":"IP-049157","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":473490,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/1365-2745.12154","text":"External Repository"},{"id":338920,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":338878,"type":{"id":15,"text":"Index Page"},"url":"https://onlinelibrary.wiley.com/doi/10.1111/1365-2745.12154/full"}],"volume":"101","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2013-10-08","publicationStatus":"PW","scienceBaseUri":"58df6ac7e4b02ff32c6aea69","contributors":{"authors":[{"text":"Davies, T. Jonathan","contributorId":190201,"corporation":false,"usgs":false,"family":"Davies","given":"T.","email":"","middleInitial":"Jonathan","affiliations":[],"preferred":false,"id":687797,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wolkovich, Elizabeth M.","contributorId":190202,"corporation":false,"usgs":false,"family":"Wolkovich","given":"Elizabeth","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":687798,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kraft, Nathan J. B.","contributorId":190203,"corporation":false,"usgs":false,"family":"Kraft","given":"Nathan","email":"","middleInitial":"J. B.","affiliations":[],"preferred":false,"id":687799,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Salamin, Nicolas","contributorId":146424,"corporation":false,"usgs":false,"family":"Salamin","given":"Nicolas","email":"","affiliations":[],"preferred":false,"id":687800,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Allen, Jenica M.","contributorId":146420,"corporation":false,"usgs":false,"family":"Allen","given":"Jenica","email":"","middleInitial":"M.","affiliations":[{"id":13006,"text":"Department of Ecology and Evolutionary Biology, University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":687801,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ault, Toby R.","contributorId":146164,"corporation":false,"usgs":false,"family":"Ault","given":"Toby","email":"","middleInitial":"R.","affiliations":[{"id":6624,"text":"University of Arizona, Laboratory of Tree-Ring Research","active":true,"usgs":false}],"preferred":false,"id":687802,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Betancourt, Julio L. 0000-0002-7165-0743 jlbetanc@usgs.gov","orcid":"https://orcid.org/0000-0002-7165-0743","contributorId":3376,"corporation":false,"usgs":true,"family":"Betancourt","given":"Julio","email":"jlbetanc@usgs.gov","middleInitial":"L.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":687796,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bolmgren, Kjell","contributorId":190204,"corporation":false,"usgs":false,"family":"Bolmgren","given":"Kjell","email":"","affiliations":[],"preferred":false,"id":687803,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cleland, Elsa E.","contributorId":190205,"corporation":false,"usgs":false,"family":"Cleland","given":"Elsa","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":687804,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cook, Benjamin I.","contributorId":190206,"corporation":false,"usgs":false,"family":"Cook","given":"Benjamin","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":687805,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Crimmins, Theresa M.","contributorId":178236,"corporation":false,"usgs":false,"family":"Crimmins","given":"Theresa","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":687806,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Mazer, Susan J.","contributorId":190207,"corporation":false,"usgs":false,"family":"Mazer","given":"Susan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":687807,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":167116,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory J.","email":"gmccabe@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":687808,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Pau, Stephanie","contributorId":190208,"corporation":false,"usgs":false,"family":"Pau","given":"Stephanie","email":"","affiliations":[],"preferred":false,"id":687809,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Regetz, Jim","contributorId":190209,"corporation":false,"usgs":false,"family":"Regetz","given":"Jim","affiliations":[],"preferred":false,"id":687810,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Schwartz, Mark D.","contributorId":175228,"corporation":false,"usgs":false,"family":"Schwartz","given":"Mark","email":"","middleInitial":"D.","affiliations":[{"id":18038,"text":"University of Wisconsin, Milwaukee","active":true,"usgs":false}],"preferred":false,"id":687811,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Travers, Steven E.","contributorId":146419,"corporation":false,"usgs":false,"family":"Travers","given":"Steven","email":"","middleInitial":"E.","affiliations":[{"id":16604,"text":"Department of Biological Sciences, North Dakota State University, Fargo, ND","active":true,"usgs":false}],"preferred":false,"id":687812,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}}
,{"id":70148189,"text":"70148189 - 2013 - Network modularity reveals critical scales for connectivity in ecology and evolution","interactions":[],"lastModifiedDate":"2015-05-26T09:58:34","indexId":"70148189","displayToPublicDate":"2013-10-07T11:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Network modularity reveals critical scales for connectivity in ecology and evolution","docAbstract":"<p>For nearly a century, biologists have emphasized the profound importance of spatial scale for ecology, evolution and conservation. Nonetheless, objectively identifying critical scales has proven incredibly challenging. Here we extend new techniques from physics and social sciences that estimate modularity on networks to identify critical scales for movement and gene flow in animals. Using four species that vary widely in dispersal ability and include both mark-recapture and population genetic data, we identify significant modularity in three species, two of which cannot be explained by geographic distance alone. Importantly, the inclusion of modularity in connectivity and population viability assessments alters conclusions regarding patch importance to connectivity and suggests higher metapopulation viability than when ignoring this hidden spatial scale. We argue that network modularity reveals critical meso-scales that are probably common in populations, providing a powerful means of identifying fundamental scales for biology and for conservation strategies aimed at recovering imperilled species.</p>","language":"English","publisher":"Nature Publishing Group","publisherLocation":"London","doi":"10.1038/ncomms3572","usgsCitation":"Fletcher, R., Revell, A., Reichert, B.E., Kitchens, W.M., Dixon, J., and Austin, J.D., 2013, Network modularity reveals critical scales for connectivity in ecology and evolution: Nature Communications, v. 4, p. 1-7, https://doi.org/10.1038/ncomms3572.","productDescription":"7 p.","startPage":"1","endPage":"7","numberOfPages":"7","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-046185","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":473491,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/ncomms3572","text":"Publisher Index Page"},{"id":300771,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2013-10-07","publicationStatus":"PW","scienceBaseUri":"5565994fe4b0d9246a9eb637","contributors":{"authors":[{"text":"Fletcher, Robert J.","contributorId":81785,"corporation":false,"usgs":true,"family":"Fletcher","given":"Robert J.","affiliations":[],"preferred":false,"id":547580,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Revell, Andre","contributorId":140922,"corporation":false,"usgs":false,"family":"Revell","given":"Andre","email":"","affiliations":[],"preferred":false,"id":547581,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reichert, Brian E. 0000-0002-9640-0695","orcid":"https://orcid.org/0000-0002-9640-0695","contributorId":22166,"corporation":false,"usgs":true,"family":"Reichert","given":"Brian","email":"","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":547582,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kitchens, Wiley M. kitchensw@usgs.gov","contributorId":2851,"corporation":false,"usgs":true,"family":"Kitchens","given":"Wiley","email":"kitchensw@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":547548,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dixon, J.","contributorId":98132,"corporation":false,"usgs":true,"family":"Dixon","given":"J.","affiliations":[],"preferred":false,"id":547583,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Austin, James D.","contributorId":57584,"corporation":false,"usgs":true,"family":"Austin","given":"James","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":547584,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70127934,"text":"70127934 - 2013 - Estimated global nitrogen deposition using NO<sub>2</sub> column density","interactions":[],"lastModifiedDate":"2014-10-02T15:50:54","indexId":"70127934","displayToPublicDate":"2013-10-01T15:48:51","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2068,"text":"International Journal of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Estimated global nitrogen deposition using NO<sub>2</sub> column density","docAbstract":"Global nitrogen deposition has increased over the past 100 years. Monitoring and simulation studies of  nitrogen deposition have evaluated nitrogen deposition at both the global and regional scale. With the development of remote-sensing instruments, tropospheric NO<sub>2</sub> column density retrieved from Global Ozone Monitoring Experiment (GOME) and Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) sensors now provides us with a new opportunity to understand changes in reactive nitrogen in the atmosphere. The concentration of NO<sub>2</sub> in the atmosphere has a significant effect on atmospheric nitrogen deposition. According to the general nitrogen deposition calculation method, we use the principal component regression method to evaluate global nitrogen deposition based on global NO2 column density and meteorological data. From the accuracy of the simulation, about 70% of the land area of the Earth passed a significance test of regression. In addition, NO2 column density has a significant influence on regression results over 44% of global land. The simulated results show that global average nitrogen deposition was 0.34 g m<sup>−2</sup> yr<sup>−1</sup> from 1996 to 2009 and is increasing at about 1% per year. Our simulated results show that China, Europe, and the USA are the three hotspots of nitrogen deposition according to previous research findings. In this study, Southern Asia was found to be another hotspot of nitrogen deposition (about 1.58 g m<sup>−2</sup> yr<sup>−1</sup> and maintaining a high growth rate). As nitrogen deposition increases, the number of regions threatened by high nitrogen deposits is also increasing. With N emissions continuing to increase in the future, areas whose ecosystem is affected by high level nitrogen deposition will increase.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"International Journal of Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Taylor & Francis","doi":"10.1080/01431161.2013.853894","usgsCitation":"Lu, X., Jiang, H., Zhang, X., Liu, J., Zhang, Z., Jin, J., Wang, Y., Xu, J., and Cheng, M., 2013, Estimated global nitrogen deposition using NO<sub>2</sub> column density: International Journal of Remote Sensing, v. 34, no. 24, p. 8893-8906, https://doi.org/10.1080/01431161.2013.853894.","productDescription":"14 p.","startPage":"8893","endPage":"8906","numberOfPages":"14","ipdsId":"IP-060188","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":294882,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294874,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/01431161.2013.853894"}],"volume":"34","issue":"24","noUsgsAuthors":false,"publicationDate":"2013-10-30","publicationStatus":"PW","scienceBaseUri":"542e6952e4b092f17df5a812","contributors":{"authors":[{"text":"Lu, Xuehe","contributorId":73517,"corporation":false,"usgs":true,"family":"Lu","given":"Xuehe","affiliations":[],"preferred":false,"id":502706,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jiang, Hong","contributorId":108417,"corporation":false,"usgs":true,"family":"Jiang","given":"Hong","affiliations":[],"preferred":false,"id":502709,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhang, Xiuying","contributorId":63739,"corporation":false,"usgs":true,"family":"Zhang","given":"Xiuying","affiliations":[],"preferred":false,"id":502705,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Liu, Jinxun 0000-0003-0561-8988 jxliu@usgs.gov","orcid":"https://orcid.org/0000-0003-0561-8988","contributorId":3414,"corporation":false,"usgs":true,"family":"Liu","given":"Jinxun","email":"jxliu@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":502701,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhang, Zhen","contributorId":88286,"corporation":false,"usgs":true,"family":"Zhang","given":"Zhen","affiliations":[],"preferred":false,"id":502708,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jin, Jiaxin","contributorId":13561,"corporation":false,"usgs":true,"family":"Jin","given":"Jiaxin","affiliations":[],"preferred":false,"id":502702,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wang, Ying","contributorId":76237,"corporation":false,"usgs":true,"family":"Wang","given":"Ying","email":"","affiliations":[],"preferred":false,"id":502707,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Xu, Jianhui","contributorId":60139,"corporation":false,"usgs":true,"family":"Xu","given":"Jianhui","email":"","affiliations":[],"preferred":false,"id":502704,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cheng, Miaomiao","contributorId":45234,"corporation":false,"usgs":true,"family":"Cheng","given":"Miaomiao","email":"","affiliations":[],"preferred":false,"id":502703,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70047104,"text":"70047104 - 2013 - Effects of dreissenids on monitoring and management of fisheries in western Lake Erie","interactions":[],"lastModifiedDate":"2014-02-05T15:39:57","indexId":"70047104","displayToPublicDate":"2013-10-01T15:39:00","publicationYear":"2013","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Effects of dreissenids on monitoring and management of fisheries in western Lake Erie","docAbstract":"Water clarity increased in nearshore areas of western Lake Erie by the early-1990s mainly as a result of the filtering activities of dreissenid mussels (Dreissena spp.), which invaded in the mid-1980s. We hypothesized that increased water clarity would result in greater trawl avoidance and thus reduced ability to capture fish in bottom trawls during daytime compared to nighttime. We examined this hypothesis by summarizing three analyses on fish data collected in western Lake Erie. First, we used a two-tiered modeling approach on the ration (R) of catch per hour (CPH) of age-0 yellow perch (Perca flavencens Mitchell) at night to CPH during daytime in 1961-2005. The best a priori and a posteriori models indicated a shift to higher CPH at night (R > 1) between 1990 and 1991, which corresponded to 3 years after the dreissenid invasion and when water clarity noticeably increased at nearshore sites. Secondly, we examined effects of nighttime sampling on estimates of abundance of age-2 and older yellow perch, which form the basis for recommended allowable harvest (RAH). When data from night sampling were included in models that predict abundance of age-2 yellow perch from indices of abundance of age-0 and age-1 yellow perch, predicted abundance was lower and model precision, as measured by r-squared, was higher compared to models that excluded data collected at night. Furthermore, the use of only CPH data collected at night typically resulted in lower estimates of abundance and more precise models compared to models that included CPH data collected during both daytime and nighttime. Thirdly, we used presence/absence data from paired bottom trawl samples to calculate an index of capture probability (or catchability) to determine if our ability to capture the four most common benthic species in western Lake Erie was affected by dreissenid-caused increased water clarity. Three species of fish(white perch, Morone americana Gmelin; yellow perch; and trout-perch, Percopsis omiscomaycus Walbaum) had lower mean daytime catchability than nighttime catchability after dreissenids became established, which supported the hypothesis of greater trawl avoidance during daytime following establishment of dreissenids. Results from freshwater drum (Aplodinotus grunniens Rafinesque) were opposite those of the other three species, which may be a result of behavioral shifts due to freshwater drum feeding on dreissenids mussels. Collectively, these three studies suggest that dreissenids indirectly affected our ability to assess fish populations, which further affects estimates of fish densities and relationships between indices of abundance and true abundance.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Quagga and zebra mussels: biology, impacts, and control","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"CRC Press","publisherLocation":"Hoboken, NJ","isbn":"9781439854372","usgsCitation":"Stapanian, M.A., and Kocovsky, P., 2013, Effects of dreissenids on monitoring and management of fisheries in western Lake Erie, chap. <i>of</i> Quagga and zebra mussels: biology, impacts, and control, p. 681-692.","productDescription":"12 p.","startPage":"681","endPage":"692","numberOfPages":"12","ipdsId":"IP-027862","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":282058,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Erie","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -83.4797,41.3815 ], [ -83.4797,42.6773 ], [ -81.0731,42.6773 ], [ -81.0731,41.3815 ], [ -83.4797,41.3815 ] ] ] } } ] }","edition":"2nd","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd56bbe4b0b290850f7190","contributors":{"authors":[{"text":"Stapanian, Martin A. 0000-0001-8173-4273 mstapanian@usgs.gov","orcid":"https://orcid.org/0000-0001-8173-4273","contributorId":3425,"corporation":false,"usgs":true,"family":"Stapanian","given":"Martin","email":"mstapanian@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":481062,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kocovsky, Patrick M.","contributorId":89381,"corporation":false,"usgs":true,"family":"Kocovsky","given":"Patrick M.","affiliations":[],"preferred":false,"id":481063,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70198337,"text":"70198337 - 2013 - Variability and trends in irrigated and non-irrigated croplands in the central U.S","interactions":[],"lastModifiedDate":"2018-12-07T14:36:21","indexId":"70198337","displayToPublicDate":"2013-10-01T14:52:11","publicationYear":"2013","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Variability and trends in irrigated and non-irrigated croplands in the central U.S","docAbstract":"<p><span>Over 23 million hectares (233 thousand km</span><sup>2</sup><span>) of U.S. croplands are irrigated and there was an overall net expansion of 522 thousand hectares nationally from 2002 to 2007. Most of this expansion occurred across the High Plains Aquifer (HPA) in the central Great Plains. Until recently, there has been a lack of geospatially-detailed irrigation data that are consistent, timely, geographically extensive, and periodic to support studies linking agricultural land use change to crop yields, aquifer water use, and other factors. We employed a modeling approach implemented at two time intervals (2002 and 2007) to map irrigated agriculture across the conterminous U.S. at a sub-county spatial detail (250 m</span><sup>2</sup><span>&nbsp;spatial resolution). The model integrated U.S. Department of Agriculture (USDA) county statistics, satellite imagery, and a national land cover map. The geospatial model output, called the Moderate Resolution Imaging Spectroradiometer (MODIS) Irrigated Agriculture Dataset for the United States (MIrAD-US), was then used to depict detailed spatial patterns of irrigation change across the HPA from 2002 to 2007. Spatial changes in irrigation may result in shifts in local and regional climate, groundwater depletion, and higher crop yields and farm income. A closer investigation of irrigated corn across the HPA from 2000 to 2012 revealed even more variability through time, underscoring the need for more frequent periodic mapping of irrigated agriculture.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Information for sustainable agriculture, International Conference on Agro-Geoinformatics, 2nd, Fairfax, Va., 12–16 August 2013, Proceedings","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Second International Conference on Agro-Geoinformatics","conferenceDate":"August 12-16, 2013","conferenceLocation":"Fairfax, VA","language":"English","publisher":"Institute of Electrical and Electronics Engineers (IEEE)","publisherLocation":"Piscataway, NJ","doi":"10.1109/Argo-Geoinformatics.2013.6621888","isbn":"978-1-4799-0868-4","usgsCitation":"Brown, J.F., and Pervez, M., 2013, Variability and trends in irrigated and non-irrigated croplands in the central U.S, <i>in</i> Information for sustainable agriculture, International Conference on Agro-Geoinformatics, 2nd, Fairfax, Va., 12–16 August 2013, Proceedings, Fairfax, VA, August 12-16, 2013, p. 102-105, https://doi.org/10.1109/Argo-Geoinformatics.2013.6621888.","productDescription":"4 p.","startPage":"102","endPage":"105","ipdsId":"IP-049069","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":359681,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bfd1472e4b0815414ca390c","contributors":{"authors":[{"text":"Brown, Jesslyn F. 0000-0002-9976-1998 jfbrown@usgs.gov","orcid":"https://orcid.org/0000-0002-9976-1998","contributorId":176609,"corporation":false,"usgs":true,"family":"Brown","given":"Jesslyn","email":"jfbrown@usgs.gov","middleInitial":"F.","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":741130,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pervez, Md Shahriar 0000-0003-3417-1871 shahriar.pervez.ctr@usgs.gov","orcid":"https://orcid.org/0000-0003-3417-1871","contributorId":74230,"corporation":false,"usgs":true,"family":"Pervez","given":"Md Shahriar","email":"shahriar.pervez.ctr@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":false,"id":741131,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70074270,"text":"70074270 - 2013 - Statistical mapping of zones of focused groundwater/surface-water exchange using fiber-optic distributed temperature sensing","interactions":[],"lastModifiedDate":"2014-01-28T14:47:30","indexId":"70074270","displayToPublicDate":"2013-10-01T14:41:15","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Statistical mapping of zones of focused groundwater/surface-water exchange using fiber-optic distributed temperature sensing","docAbstract":"Fiber-optic distributed temperature sensing (FO-DTS) increasingly is used to map zones of focused groundwater/surface-water exchange (GWSWE). Previous studies of GWSWE using FO-DTS involved identification of zones of focused GWSWE based on arbitrary cutoffs of FO-DTS time-series statistics (e.g., variance, cross-correlation between temperature and stage, or spectral power). New approaches are needed to extract more quantitative information from large, complex FO-DTS data sets while concurrently providing an assessment of uncertainty associated with mapping zones of focused GSWSE. Toward this end, we present a strategy combining discriminant analysis (DA) and spectral analysis (SA). We demonstrate the approach using field experimental data from a reach of the Columbia River adjacent to the Hanford 300 Area site. Results of the combined SA/DA approach are shown to be superior to previous results from qualitative interpretation of FO-DTS spectra alone.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Water Resources Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/wrcr.20458","usgsCitation":"Mwakanyamale, K., Day-Lewis, F.D., and Slater, L.D., 2013, Statistical mapping of zones of focused groundwater/surface-water exchange using fiber-optic distributed temperature sensing: Water Resources Research, v. 49, no. 10, p. 6979-6984, https://doi.org/10.1002/wrcr.20458.","productDescription":"6 p.","startPage":"6979","endPage":"6984","numberOfPages":"6","ipdsId":"IP-050678","costCenters":[{"id":496,"text":"Office of Groundwater-Branch of Geophysics","active":false,"usgs":true}],"links":[{"id":473493,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wrcr.20458","text":"Publisher Index Page"},{"id":281623,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281622,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/wrcr.20458"}],"country":"United States","state":"Washington","city":"Richland","otherGeospatial":"Columbia River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119.400445,46.198408 ], [ -119.400445,46.370576 ], [ -119.211582,46.370576 ], [ -119.211582,46.198408 ], [ -119.400445,46.198408 ] ] ] } } ] }","volume":"49","issue":"10","noUsgsAuthors":false,"publicationDate":"2013-10-25","publicationStatus":"PW","scienceBaseUri":"53cd7401e4b0b29085109465","contributors":{"authors":[{"text":"Mwakanyamale, Kisa","contributorId":75847,"corporation":false,"usgs":true,"family":"Mwakanyamale","given":"Kisa","email":"","affiliations":[],"preferred":false,"id":489469,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Day-Lewis, Frederick D. 0000-0003-3526-886X daylewis@usgs.gov","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":1672,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","email":"daylewis@usgs.gov","middleInitial":"D.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":489468,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Slater, Lee D.","contributorId":95792,"corporation":false,"usgs":true,"family":"Slater","given":"Lee","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":489470,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70103862,"text":"70103862 - 2013 - Seasonal circulation over the Catalan inner-shelf (northwest Mediterranean Sea)","interactions":[],"lastModifiedDate":"2014-05-08T13:34:17","indexId":"70103862","displayToPublicDate":"2013-10-01T13:28:14","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2315,"text":"Journal of Geophysical Research C: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal circulation over the Catalan inner-shelf (northwest Mediterranean Sea)","docAbstract":"This study characterizes the seasonal cycle of the Catalan inner-shelf circulation using observations and complementary numerical results. The relation between seasonal circulation and forcing mechanisms is explored through the depth-averaged momentum balance, for the period between May 2010 and April 2011, when velocity observations were partially available. The monthly-mean along-shelf flow is mainly controlled by the along-shelf pressure gradient and by surface and bottom stresses. During summer, fall, and winter, the along-shelf momentum balance is dominated by the barotropic pressure gradient and local winds. During spring, both wind stress and pressure gradient act in the same direction and are compensated by bottom stress. In the cross-shelf direction the dominant forces are in geostrophic balance, consistent with dynamic altimetry data.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research C: Oceans","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Geophysical Union","doi":"10.1002/jgrc.20403","usgsCitation":"Grifoll, M., Aretxabaleta, A., Pelegri, J.L., Espino, M., Warner, J., and Sanchez-Arcilla, A., 2013, Seasonal circulation over the Catalan inner-shelf (northwest Mediterranean Sea): Journal of Geophysical Research C: Oceans, v. 118, no. 10, p. 5844-5857, https://doi.org/10.1002/jgrc.20403.","productDescription":"14 p.","startPage":"5844","endPage":"5857","numberOfPages":"14","ipdsId":"IP-051806","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":473497,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jgrc.20403","text":"Publisher Index Page"},{"id":286997,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286994,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jgrc.20403"}],"otherGeospatial":"Catalan Sea;Mediterranean Sea","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -10.0,35.0 ], [ -10.0,50.0 ], [ 9.0,50.0 ], [ 9.0,35.0 ], [ -10.0,35.0 ] ] ] } } ] }","volume":"118","issue":"10","noUsgsAuthors":false,"publicationDate":"2013-10-25","publicationStatus":"PW","scienceBaseUri":"536ca77ae4b060efff280dcf","contributors":{"authors":[{"text":"Grifoll, Manel","contributorId":41310,"corporation":false,"usgs":true,"family":"Grifoll","given":"Manel","affiliations":[],"preferred":false,"id":493508,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aretxabaleta, Alfredo L.","contributorId":41311,"corporation":false,"usgs":true,"family":"Aretxabaleta","given":"Alfredo L.","affiliations":[],"preferred":false,"id":493509,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pelegri, Josep L.","contributorId":44462,"corporation":false,"usgs":true,"family":"Pelegri","given":"Josep","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":493510,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Espino, Manuel","contributorId":88240,"corporation":false,"usgs":true,"family":"Espino","given":"Manuel","affiliations":[],"preferred":false,"id":493512,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":493507,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sanchez-Arcilla, Agustin","contributorId":68223,"corporation":false,"usgs":true,"family":"Sanchez-Arcilla","given":"Agustin","email":"","affiliations":[],"preferred":false,"id":493511,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70048208,"text":"70048208 - 2013 - Alternative ways of using field-based estimates to calibrate ecosystem models and their implications for carbon cycle studies","interactions":[],"lastModifiedDate":"2014-01-08T13:10:33","indexId":"70048208","displayToPublicDate":"2013-10-01T13:05:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Alternative ways of using field-based estimates to calibrate ecosystem models and their implications for carbon cycle studies","docAbstract":"Model-data fusion is a process in which field observations are used to constrain model parameters. How observations are used to constrain parameters has a direct impact on the carbon cycle dynamics simulated by ecosystem models. In this study, we present an evaluation of several options for the use of observations in modeling regional carbon dynamics and explore the implications of those options. We calibrated the Terrestrial Ecosystem Model on a hierarchy of three vegetation classification levels for the Alaskan boreal forest: species level, plant-functional-type level (PFT level), and biome level, and we examined the differences in simulated carbon dynamics. Species-specific field-based estimates were directly used to parameterize the model for species-level simulations, while weighted averages based on species percent cover were used to generate estimates for PFT- and biome-level model parameterization. We found that calibrated key ecosystem process parameters differed substantially among species and overlapped for species that are categorized into different PFTs. Our analysis of parameter sets suggests that the PFT-level parameterizations primarily reflected the dominant species and that functional information of some species were lost from the PFT-level parameterizations. The biome-level parameterization was primarily representative of the needleleaf PFT and lost information on broadleaf species or PFT function. Our results indicate that PFT-level simulations may be potentially representative of the performance of species-level simulations while biome-level simulations may result in biased estimates. Improved theoretical and empirical justifications for grouping species into PFTs or biomes are needed to adequately represent the dynamics of ecosystem functioning and structure.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research: Biogeosciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/jgrg.20080","usgsCitation":"He, Y., Zhuang, Q., McGuire, D., Liu, Y., and Chen, M., 2013, Alternative ways of using field-based estimates to calibrate ecosystem models and their implications for carbon cycle studies: Journal of Geophysical Research: Biogeosciences, v. 118, no. 3, p. 983-993, https://doi.org/10.1002/jgrg.20080.","productDescription":"11 p.","startPage":"983","endPage":"993","ipdsId":"IP-042199","costCenters":[{"id":108,"text":"Alaska Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":473498,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jgrg.20080","text":"Publisher Index Page"},{"id":280733,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280730,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jgrg.20080"}],"country":"United States","state":"Alaska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 172.45,51.21 ], [ 172.45,71.39 ], [ -129.99,71.39 ], [ -129.99,51.21 ], [ 172.45,51.21 ] ] ] } } ] }","volume":"118","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd4c35e4b0b290850f0d6a","contributors":{"authors":[{"text":"He, Yujie","contributorId":32444,"corporation":false,"usgs":true,"family":"He","given":"Yujie","affiliations":[],"preferred":false,"id":483999,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhuang, Qianlai","contributorId":101975,"corporation":false,"usgs":true,"family":"Zhuang","given":"Qianlai","affiliations":[],"preferred":false,"id":484002,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGuire, David","contributorId":37243,"corporation":false,"usgs":true,"family":"McGuire","given":"David","affiliations":[],"preferred":false,"id":484000,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Liu, Yaling","contributorId":103172,"corporation":false,"usgs":true,"family":"Liu","given":"Yaling","affiliations":[],"preferred":false,"id":484003,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chen, Min","contributorId":56140,"corporation":false,"usgs":true,"family":"Chen","given":"Min","email":"","affiliations":[],"preferred":false,"id":484001,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70045061,"text":"70045061 - 2013 - Vs30 and spectral response from collocated shallow, active- and passive-source Vs data at 27 sites in Puerto Rico","interactions":[],"lastModifiedDate":"2014-01-15T13:08:48","indexId":"70045061","displayToPublicDate":"2013-10-01T12:55:06","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Vs30 and spectral response from collocated shallow, active- and passive-source Vs data at 27 sites in Puerto Rico","docAbstract":"Shear‐wave velocity (V<sub>S</sub>) and time‐averaged shear‐wave velocity to 30 m depth (V<sub>S30</sub>) are the key parameters used in seismic site response modeling and earthquake engineering design. Where V<sub>S</sub> data are limited, available data are often used to develop and refine map‐based proxy models of V<sub>S30</sub> for predicting ground‐motion intensities. In this paper, we present shallow V<sub>S</sub> data from 27 sites in Puerto Rico. These data were acquired using a multimethod acquisition approach consisting of noninvasive, collocated, active‐source body‐wave (refraction/reflection), active‐source surface wave at nine sites, and passive‐source surface‐wave refraction microtremor (ReMi) techniques. V<sub>S</sub>‐versus‐depth models are constructed and used to calculate spectral response plots for each site. Factors affecting method reliability are analyzed with respect to site‐specific differences in bedrock V<sub>S</sub> and spectral response. At many but not all sites, body‐ and surface‐wave methods generally determine similar depths to bedrock, and it is the difference in bedrock V<sub>S</sub> that influences site amplification. The predicted resonant frequencies for the majority of the sites are observed to be within a relatively narrow bandwidth of 1–3.5 Hz. For a first‐order comparison of peak frequency position, predictive spectral response plots from eight sites are plotted along with seismograph instrument spectra derived from the time series of the 16 May 2010 Puerto Rico earthquake. We show how a multimethod acquisition approach using collocated arrays compliments and corroborates V<sub>S</sub> results, thus adding confidence that reliable site characterization information has been obtained.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Bulletin of the Seismological Society of America","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120120349","usgsCitation":"Odum, J.K., Stephenson, W.J., Williams, R., and von Hillebrandt-Andrade, C., 2013, Vs30 and spectral response from collocated shallow, active- and passive-source Vs data at 27 sites in Puerto Rico: Bulletin of the Seismological Society of America, v. 103, no. 5, p. 2709-2728, https://doi.org/10.1785/0120120349.","productDescription":"20 p.","startPage":"2709","endPage":"2728","numberOfPages":"20","ipdsId":"IP-044448","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":281099,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281097,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1785/0120120349"}],"country":"Puerto Rico","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -74.0,14.0 ], [ -74.0,22.0 ], [ -60.0,22.0 ], [ -60.0,14.0 ], [ -74.0,14.0 ] ] ] } } ] }","volume":"103","issue":"5","noUsgsAuthors":false,"publicationDate":"2013-09-30","publicationStatus":"PW","scienceBaseUri":"53cd7b3de4b0b2908510e01f","contributors":{"authors":[{"text":"Odum, Jack K. 0000-0002-3162-0355","orcid":"https://orcid.org/0000-0002-3162-0355","contributorId":97900,"corporation":false,"usgs":true,"family":"Odum","given":"Jack","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":476710,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stephenson, William J. 0000-0001-8699-0786 wstephens@usgs.gov","orcid":"https://orcid.org/0000-0001-8699-0786","contributorId":695,"corporation":false,"usgs":true,"family":"Stephenson","given":"William","email":"wstephens@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":476708,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Williams, Robert A. rawilliams@usgs.gov","contributorId":1357,"corporation":false,"usgs":true,"family":"Williams","given":"Robert A.","email":"rawilliams@usgs.gov","affiliations":[{"id":301,"text":"Geologic Hazards Team","active":false,"usgs":true}],"preferred":false,"id":476709,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"von Hillebrandt-Andrade, Christa","contributorId":106593,"corporation":false,"usgs":true,"family":"von Hillebrandt-Andrade","given":"Christa","affiliations":[],"preferred":false,"id":476711,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70057609,"text":"70057609 - 2013 - Temporal, spatial, and body size effects on growth rates of loggerhead sea turtles (<i>Caretta caretta</i>) in the Northwest Atlantic","interactions":[],"lastModifiedDate":"2013-11-26T13:02:23","indexId":"70057609","displayToPublicDate":"2013-10-01T12:49:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2660,"text":"Marine Biology","active":true,"publicationSubtype":{"id":10}},"title":"Temporal, spatial, and body size effects on growth rates of loggerhead sea turtles (<i>Caretta caretta</i>) in the Northwest Atlantic","docAbstract":"In response to a call from the US National Research Council for research programs to combine their data to improve sea turtle population assessments, we analyzed somatic growth data for Northwest Atlantic (NWA) loggerhead sea turtles (Caretta caretta) from 10 research programs. We assessed growth dynamics over wide ranges of geography (9–33°N latitude), time (1978–2012), and body size (35.4–103.3 cm carapace length). Generalized additive models revealed significant spatial and temporal variation in growth rates and a significant decline in growth rates with increasing body size. Growth was more rapid in waters south of the USA (<24°N) than in USA waters. Growth dynamics in southern waters in the NWA need more study because sample size was small. Within USA waters, the significant spatial effect in growth rates of immature loggerheads did not exhibit a consistent latitudinal trend. Growth rates declined significantly from 1997 through 2007 and then leveled off or increased. During this same interval, annual nest counts in Florida declined by 43 % (Witherington et al. in Ecol Appl 19:30–54, 2009) before rebounding. Whether these simultaneous declines reflect responses in productivity to a common environmental change should be explored to determine whether somatic growth rates can help interpret population trends based on annual counts of nests or nesting females. Because of the significant spatial and temporal variation in growth rates, population models of NWA loggerheads should avoid employing growth data from restricted spatial or temporal coverage to calculate demographic metrics such as age at sexual maturity.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Marine Biology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s00227-013-2264-y","usgsCitation":"Bjorndal, K.A., Schroeder, B.A., Foley, A., Witherington, B.E., Bresette, M., Clark, D., Herren, R.M., Arendt, M.D., Schmid, J., Meylan, A.B., Meylan, P.A., Provancha, J., Hart, K.M., Lamont, M.M., Carthy, R.R., and Bolten, A.B., 2013, Temporal, spatial, and body size effects on growth rates of loggerhead sea turtles (<i>Caretta caretta</i>) in the Northwest Atlantic: Marine Biology, v. 160, no. 10, p. 2711-2721, https://doi.org/10.1007/s00227-013-2264-y.","productDescription":"11 p.","startPage":"2711","endPage":"2721","numberOfPages":"11","temporalStart":"1978-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-044468","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":279838,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":279837,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s00227-013-2264-y"}],"country":"United States","otherGeospatial":"Northwest Atlantic","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -81.6,9.0 ], [ -81.6,33.0 ], [ -51.9,33.0 ], [ -51.9,9.0 ], [ -81.6,9.0 ] ] ] } } ] }","volume":"160","issue":"10","noUsgsAuthors":false,"publicationDate":"2013-06-07","publicationStatus":"PW","scienceBaseUri":"5295d12be4b0becc369c8c9c","contributors":{"authors":[{"text":"Bjorndal, Karen A.","contributorId":96997,"corporation":false,"usgs":false,"family":"Bjorndal","given":"Karen","email":"","middleInitial":"A.","affiliations":[{"id":12567,"text":"Archie Carr Center for Sea Turtle Research, Department of Biology, University of Florida","active":true,"usgs":false}],"preferred":false,"id":486854,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schroeder, Barbara A.","contributorId":87853,"corporation":false,"usgs":true,"family":"Schroeder","given":"Barbara","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":486852,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Foley, Allen M.","contributorId":80178,"corporation":false,"usgs":true,"family":"Foley","given":"Allen M.","affiliations":[],"preferred":false,"id":486850,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Witherington, Blair E.","contributorId":60117,"corporation":false,"usgs":true,"family":"Witherington","given":"Blair","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":486847,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bresette, Michael","contributorId":61335,"corporation":false,"usgs":true,"family":"Bresette","given":"Michael","email":"","affiliations":[],"preferred":false,"id":486848,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Clark, David","contributorId":95383,"corporation":false,"usgs":true,"family":"Clark","given":"David","affiliations":[],"preferred":false,"id":486853,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Herren, Richard M.","contributorId":46409,"corporation":false,"usgs":true,"family":"Herren","given":"Richard","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":486845,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Arendt, Michael D.","contributorId":105639,"corporation":false,"usgs":true,"family":"Arendt","given":"Michael","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":486855,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schmid, Jeffrey R.","contributorId":79794,"corporation":false,"usgs":true,"family":"Schmid","given":"Jeffrey R.","affiliations":[],"preferred":false,"id":486849,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Meylan, Anne B.","contributorId":36045,"corporation":false,"usgs":true,"family":"Meylan","given":"Anne","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":486844,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Meylan, Peter A.","contributorId":82609,"corporation":false,"usgs":true,"family":"Meylan","given":"Peter","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":486851,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Provancha, Jane A.","contributorId":56551,"corporation":false,"usgs":true,"family":"Provancha","given":"Jane A.","affiliations":[],"preferred":false,"id":486846,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Hart, Kristen M. 0000-0002-5257-7974 kristen_hart@usgs.gov","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":1966,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","email":"kristen_hart@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":486840,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Lamont, Margaret M. 0000-0001-7520-6669 mlamont@usgs.gov","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":4525,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","email":"mlamont@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":486842,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Carthy, Raymond R. 0000-0001-8978-5083 rayc@usgs.gov","orcid":"https://orcid.org/0000-0001-8978-5083","contributorId":3685,"corporation":false,"usgs":true,"family":"Carthy","given":"Raymond","email":"rayc@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":486841,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Bolten, Alan B.","contributorId":20247,"corporation":false,"usgs":false,"family":"Bolten","given":"Alan","email":"","middleInitial":"B.","affiliations":[{"id":12567,"text":"Archie Carr Center for Sea Turtle Research, Department of Biology, University of Florida","active":true,"usgs":false}],"preferred":false,"id":486843,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}}
,{"id":70147937,"text":"70147937 - 2013 - Links between climate change, water-table depth, and water chemistry in a mineralized mountain watershed","interactions":[],"lastModifiedDate":"2015-05-11T10:45:24","indexId":"70147937","displayToPublicDate":"2013-10-01T11:45:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Links between climate change, water-table depth, and water chemistry in a mineralized mountain watershed","docAbstract":"<p>Recent studies suggest that climate change is causing rising solute concentrations in mountain lakes and streams. These changes may be more pronounced in mineralized watersheds due to the sensitivity of sulfide weathering to changes in subsurface oxygen transport. Specific causal mechanisms linking climate change and accelerated weathering rates have been proposed, but in general remain entirely hypothetical. For mineralized watersheds, a favored hypothesis is that falling water tables caused by declining recharge rates allow an increasing volume of sulfide-bearing rock to become exposed to air, thus oxygen. Here, we test the hypothesis that falling water tables are the primary cause of an increase in metals and SO4 (100-400%) observed since 1980 in the Upper Snake River (USR), Colorado. The USR drains an alpine watershed geologically and climatologically representative of many others in mineralized areas of the western U.S. Hydrologic and chemical data collected from 2005 to 2011 in a deep monitoring well (WP1) at the top of the USR watershed are utilized. During this period, both water table depths and groundwater SO4 concentrations have generally increased in the well. A numerical model was constructed using TOUGHREACT that simulates pyrite oxidation near WP1, including groundwater flow and oxygen transport in both saturated and unsaturated zones. The modeling suggests that a falling water table could produce an increase in metals and SO4 of a magnitude similar to that observed in the USR (up to 300%). Future water table declines may produce limited increases in sulfide weathering high in the watershed because of the water table dropping below the depth of oxygen penetration, but may continue to enhance sulfide weathering lower in the watershed where water tables are shallower. Advective air (oxygen) transport in the unsaturated zone caused by seasonally variable recharge and associated water table fluctuations was found to have little influence on pyrite oxidation rates near WP1. However, this mechanism could be important in the case of a shallow dynamic water table and more abundant/reactive sulfides in the shallow subsurface. Data from WP1 and numerical modeling results are thus consistent with the falling water table hypothesis, and illustrate fundamental processes linking climate and sulfide weathering in mineralized watersheds.</p>","language":"English","publisher":"International Association of Geochemistry and Cosmochemistry","publisherLocation":"New York, NY","doi":"10.1016/j.apgeochem.2013.07.002","usgsCitation":"Manning, A.H., Verplanck, P.L., Caine, J.S., and Todd, A.S., 2013, Links between climate change, water-table depth, and water chemistry in a mineralized mountain watershed: Applied Geochemistry, v. 37, p. 64-78, https://doi.org/10.1016/j.apgeochem.2013.07.002.","productDescription":"15 p.","startPage":"64","endPage":"78","numberOfPages":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-044072","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":300277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5551d2b6e4b0a92fa7e93bf2","contributors":{"authors":[{"text":"Manning, Andrew H. 0000-0002-6404-1237 amanning@usgs.gov","orcid":"https://orcid.org/0000-0002-6404-1237","contributorId":1305,"corporation":false,"usgs":true,"family":"Manning","given":"Andrew","email":"amanning@usgs.gov","middleInitial":"H.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":546436,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Verplanck, Philip L. 0000-0002-3653-6419 plv@usgs.gov","orcid":"https://orcid.org/0000-0002-3653-6419","contributorId":728,"corporation":false,"usgs":true,"family":"Verplanck","given":"Philip","email":"plv@usgs.gov","middleInitial":"L.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":546437,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Caine, Jonathan S. 0000-0002-7269-6989 jscaine@usgs.gov","orcid":"https://orcid.org/0000-0002-7269-6989","contributorId":1272,"corporation":false,"usgs":true,"family":"Caine","given":"Jonathan","email":"jscaine@usgs.gov","middleInitial":"S.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":546438,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Todd, Andrew S. atodd@usgs.gov","contributorId":1022,"corporation":false,"usgs":true,"family":"Todd","given":"Andrew","email":"atodd@usgs.gov","middleInitial":"S.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":546439,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70074336,"text":"70074336 - 2013 - Multivariate analysis of ATR-FTIR spectra for assessment of oil shale organic geochemical properties","interactions":[],"lastModifiedDate":"2014-01-29T11:29:18","indexId":"70074336","displayToPublicDate":"2013-10-01T11:27:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2958,"text":"Organic Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Multivariate analysis of ATR-FTIR spectra for assessment of oil shale organic geochemical properties","docAbstract":"In this study, attenuated total reflectance (ATR) Fourier transform infrared spectroscopy (FTIR) was coupled with partial least squares regression (PLSR) analysis to relate spectral data to parameters from total organic carbon (TOC) analysis and programmed pyrolysis to assess the feasibility of developing predictive models to estimate important organic geochemical parameters. The advantage of ATR-FTIR over traditional analytical methods is that source rocks can be analyzed in the laboratory or field in seconds, facilitating more rapid and thorough screening than would be possible using other tools. ATR-FTIR spectra, TOC concentrations and Rock–Eval parameters were measured for a set of oil shales from deposits around the world and several pyrolyzed oil shale samples. PLSR models were developed to predict the measured geochemical parameters from infrared spectra. Application of the resulting models to a set of test spectra excluded from the training set generated accurate predictions of TOC and most Rock–Eval parameters. The critical region of the infrared spectrum for assessing S1, S2, Hydrogen Index and TOC consisted of aliphatic organic moieties (2800–3000 cm<sup>−1</sup>) and the models generated a better correlation with measured values of TOC and S2 than did integrated aliphatic peak areas. The results suggest that combining ATR-FTIR with PLSR is a reliable approach for estimating useful geochemical parameters of oil shales that is faster and requires less sample preparation than current screening methods.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Organic Geochemistry","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.orggeochem.2013.07.007","usgsCitation":"Washburn, K.E., and Birdwell, J.E., 2013, Multivariate analysis of ATR-FTIR spectra for assessment of oil shale organic geochemical properties: Organic Geochemistry, v. 63, p. 1-7, https://doi.org/10.1016/j.orggeochem.2013.07.007.","productDescription":"7 p.","startPage":"1","endPage":"7","numberOfPages":"7","ipdsId":"IP-045241","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":281649,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281639,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.orggeochem.2013.07.007"}],"volume":"63","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd686ee4b0b2908510209f","contributors":{"authors":[{"text":"Washburn, Kathryn E.","contributorId":76644,"corporation":false,"usgs":false,"family":"Washburn","given":"Kathryn","email":"","middleInitial":"E.","affiliations":[{"id":7152,"text":"Weatherford International","active":true,"usgs":false}],"preferred":false,"id":489513,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":489512,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70039923,"text":"70039923 - 2013 - Retrospective analysis of bottlenose dolphin foraging: a legacy of anthropogenic ecosystem disturbance","interactions":[],"lastModifiedDate":"2014-01-08T11:23:20","indexId":"70039923","displayToPublicDate":"2013-10-01T11:18:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2671,"text":"Marine Mammal Science","active":true,"publicationSubtype":{"id":10}},"title":"Retrospective analysis of bottlenose dolphin foraging: a legacy of anthropogenic ecosystem disturbance","docAbstract":"We used stable isotope analysis to investigate the foraging ecology of coastal bottlenose dolphins (Tursiops truncatus) in relation to a series of anthropogenic disturbances. We first demonstrated that stable isotopes are a faithful indicator of habitat use by comparing muscle isotope values to behavioral foraging data from the same individuals. δ<sup>13</sup>C values increased, while δ<sup>34</sup>S and δ<sup>15</sup>N values decreased with the percentage of feeding observations in seagrass habitat. We then utilized stable isotope values of muscle to assess temporal variation in foraging habitat from 1991 to 2010 and collagen from tooth crown tips to assess the time period 1944 to 2007. From 1991 to 2010, δ<sup>13</sup>C values of muscle decreased while δ<sup>34</sup>S values increased indicating reduced utilization of seagrass habitat. From 1944 to 1989 δ<sup>13</sup>C values of the crown tip declined significantly, likely due to a reduction in the coverage of seagrass habitat and δ<sup>15</sup>N values significantly increased, a trend we attribute to nutrient loading from a rapidly increasing human population. Our results demonstrate the utility of using marine mammal foraging habits to retrospectively assess the extent to which anthropogenic disturbance impacts coastal food webs.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Marine Mammal Science","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/j.1748-7692.2012.00618.x","usgsCitation":"Rossman, S., Barros, N., Ostrom, P., Stricker, C.A., Hohn, A.A., Gandhi, H., and Wells, R.S., 2013, Retrospective analysis of bottlenose dolphin foraging: a legacy of anthropogenic ecosystem disturbance: Marine Mammal Science, v. 29, no. 4, p. 705-718, https://doi.org/10.1111/j.1748-7692.2012.00618.x.","productDescription":"14 p.","startPage":"705","endPage":"718","numberOfPages":"14","ipdsId":"IP-040745","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":280714,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280712,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1748-7692.2012.00618.x"}],"country":"United States","state":"Florida","otherGeospatial":"Sarasota Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -82.716235,27.280335 ], [ -82.716235,27.483156 ], [ -82.522979,27.483156 ], [ -82.522979,27.280335 ], [ -82.716235,27.280335 ] ] ] } } ] }","volume":"29","issue":"4","noUsgsAuthors":false,"publicationDate":"2012-10-24","publicationStatus":"PW","scienceBaseUri":"53cd70e0e4b0b2908510752b","contributors":{"authors":[{"text":"Rossman, Sam","contributorId":8759,"corporation":false,"usgs":false,"family":"Rossman","given":"Sam","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":467205,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barros, Nélio B.","contributorId":89053,"corporation":false,"usgs":true,"family":"Barros","given":"Nélio B.","affiliations":[],"preferred":false,"id":467210,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ostrom, Peggy H.","contributorId":55736,"corporation":false,"usgs":false,"family":"Ostrom","given":"Peggy H.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":467208,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stricker, Craig A. 0000-0002-5031-9437 cstricker@usgs.gov","orcid":"https://orcid.org/0000-0002-5031-9437","contributorId":1097,"corporation":false,"usgs":true,"family":"Stricker","given":"Craig","email":"cstricker@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":467204,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hohn, Aleta A.","contributorId":32819,"corporation":false,"usgs":true,"family":"Hohn","given":"Aleta","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":467207,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gandhi, Hasand","contributorId":31300,"corporation":false,"usgs":false,"family":"Gandhi","given":"Hasand","affiliations":[],"preferred":false,"id":467206,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wells, Randall S.","contributorId":81773,"corporation":false,"usgs":true,"family":"Wells","given":"Randall","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":467209,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70044590,"text":"70044590 - 2013 - Social-ecological predictors of global invasions and extinctions","interactions":[],"lastModifiedDate":"2013-11-14T11:18:53","indexId":"70044590","displayToPublicDate":"2013-10-01T11:13:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1468,"text":"Ecology and Society","active":true,"publicationSubtype":{"id":10}},"title":"Social-ecological predictors of global invasions and extinctions","docAbstract":"Most assessments of resilience have been focused on local conditions. Studies focused on the relationship between humanity and environmental degradation are rare, and are rarely comprehensive. We investigated multiple social-ecological factors for 100 countries around the globe in relation to the percentage of invasions and extinctions within each country. These 100 countries contain approximately 87% of the world’s population, produce 43% of the world’s per capita gross domestic product (GDP), and take up 74% of the earth’s total land area. We used an information theoretic approach to determine which models were most supported by our data, utilizing an a priori set of plausible models that included a combination of 15 social-ecological variables, each social-ecological factor by itself, and selected social-ecological factors grouped into three broad classes. These variables were per capita GDP, export-import ratio, tourism, undernourishment, energy efficiency, agricultural intensity, rainfall, water stress, wilderness protection, total biodiversity, life expectancy, adult literacy, pesticide regulation, political stability, and female participation in government. Our results indicate that as total biodiversity and total land area increase, the percentage of endangered birds also increases. As the independent variables (agricultural intensity, rainfall, water stress, and total biodiversity) in the ecological class model increase, the percentage of endangered mammals in a country increases. The percentage of invasive birds and mammals in a country increases as per capita GDP increases. As life expectancy increases, the percentage of invasive and endangered birds and mammals increases. Although our analysis does not determine mechanisms, the patterns observed in this study provide insight into the dynamics of a complex, global, social-ecological system.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecology and Society","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Ecological Society of America","doi":"10.5751/ES-05550-180315","usgsCitation":"Lotz, A., and Allen, C.R., 2013, Social-ecological predictors of global invasions and extinctions: Ecology and Society, v. 18, no. 3, 15 p., https://doi.org/10.5751/ES-05550-180315.","productDescription":"15 p.","numberOfPages":"15","ipdsId":"IP-041216","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":473503,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/es-05550-180315","text":"Publisher Index Page"},{"id":279074,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":279073,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.5751/ES-05550-180315"}],"volume":"18","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"528607a4e4b00926c21865b7","contributors":{"authors":[{"text":"Lotz, Aaron","contributorId":105211,"corporation":false,"usgs":true,"family":"Lotz","given":"Aaron","email":"","affiliations":[],"preferred":false,"id":475927,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":475926,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70046836,"text":"70046836 - 2013 - A multilocus evaluation of ermine (<i>Mustela erminea</i>) across the Holarctic, testing hypotheses of Pleistocene diversification in response to climate change","interactions":[],"lastModifiedDate":"2018-08-20T18:10:59","indexId":"70046836","displayToPublicDate":"2013-10-01T11:13:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2193,"text":"Journal of Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"A multilocus evaluation of ermine (<i>Mustela erminea</i>) across the Holarctic, testing hypotheses of Pleistocene diversification in response to climate change","docAbstract":"Aim: \nWe examined data for ermine (Mustela erminea) to test two sets of diversification hypotheses concerning the number and location of late Pleistocene refugia, the timing and mode of diversification, and the evolutionary influence of insularization.\n\nLocation: \nTemperate and sub-Arctic Northern Hemisphere.\n\nMethods: \nWe used up to two mitochondrial and four nuclear loci from 237 specimens for statistical phylogeographical and demographic analyses. Coalescent species-tree estimation used a Bayesian approach for clade divergence based on external mutation rate calibrations. Approximate Bayesian methods were used to assess population size, timing of divergence and gene flow.\n\nResults: \nLimited structure coupled with evidence of population growth across broad regions, including previously ice-covered areas, indicated expansion from multiple centres of differentiation, but high endemism along the North Pacific coast (NPC). A bifurcating model of diversification with recent growth spanning three glacial cycles best explained the empirical data.\n\nMain conclusions: \nA newly identified clade in North America indicated a fourth refugial area for ermine. The shallow coalescence of all extant ermine reflects a recent history of diversification overlying a deeper fossil record. Post-glacial colonization has led to potential contact zones for multiple lineages in north-western North America. A model of diversification of ermine accompanied by recent gene flow was marginally less well supported than a model of divergence of major clades in response to the most recent glacial cycles.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Biogeography","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/jbi.12221","usgsCitation":"Dawson, N., Hope, A.G., Talbot, S.L., and Cook, J.A., 2013, A multilocus evaluation of ermine (<i>Mustela erminea</i>) across the Holarctic, testing hypotheses of Pleistocene diversification in response to climate change: Journal of Biogeography, v. 41, no. 3, p. 464-475, https://doi.org/10.1111/jbi.12221.","productDescription":"12 p.","startPage":"464","endPage":"475","ipdsId":"IP-048873","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":473502,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jbi.12221","text":"Publisher Index Page"},{"id":280864,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280862,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/jbi.12221"}],"volume":"41","issue":"3","noUsgsAuthors":false,"publicationDate":"2013-10-31","publicationStatus":"PW","scienceBaseUri":"53cd4a20e4b0b290850ef950","contributors":{"authors":[{"text":"Dawson, Natalie G.","contributorId":27781,"corporation":false,"usgs":true,"family":"Dawson","given":"Natalie G.","affiliations":[],"preferred":false,"id":480422,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hope, Andrew G. 0000-0003-3814-2891 ahope@usgs.gov","orcid":"https://orcid.org/0000-0003-3814-2891","contributorId":4309,"corporation":false,"usgs":true,"family":"Hope","given":"Andrew","email":"ahope@usgs.gov","middleInitial":"G.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":480423,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Talbot, Sandra L. 0000-0002-3312-7214 stalbot@usgs.gov","orcid":"https://orcid.org/0000-0002-3312-7214","contributorId":140512,"corporation":false,"usgs":true,"family":"Talbot","given":"Sandra","email":"stalbot@usgs.gov","middleInitial":"L.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":480420,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cook, Joseph A.","contributorId":8323,"corporation":false,"usgs":false,"family":"Cook","given":"Joseph","email":"","middleInitial":"A.","affiliations":[{"id":7000,"text":"Department of Biology, University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":480421,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70047293,"text":"70047293 - 2013 - Evaluation of potential gas clogging associated with managed aquifer recharge from a spreading basin, southwestern Utah, U.S.A.","interactions":[],"lastModifiedDate":"2017-01-03T15:04:27","indexId":"70047293","displayToPublicDate":"2013-10-01T11:04:00","publicationYear":"2013","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Evaluation of potential gas clogging associated with managed aquifer recharge from a spreading basin, southwestern Utah, U.S.A.","docAbstract":"<p>Sand Hollow Reservoir in southwestern Utah, USA, is operated for both surface-water storage and managed aquifer recharge via infiltration from surface basin spreading to the underlying Navajo Sandstone. The total volume of estimated recharge from 2002 through 2011 was 131 Mm<sup>3</sup>., resulting in groundwater levels rising as much as 40 m. Hydraulic and hydrochemical data from the reservoir and various monitoring wells in Sand Hollow were used to evaluate the timing and location or reservoir recharge moving through the aquifer, along either potential clogging from trapped gases in pore throats, siltation, or algal mats. Several hyrdochemical tracers indicated this recharge had arrived at four monitoring wells located within about 300 m of the reservoir by 2012. At these wells, peak total dissolved-gas pressures exceeded two atmospheres (&gt;1,500 mm mercury) and dissolved oxygen approached three times atmospherically equilibrated concentrations (&gt;25 mg/L). these field parameters indicate that large amounts of gas trapped in pore spaces beneath the water table have dissolved. Lesser but notable increases in these dissolved-gas parameters (without increases in other indicators such as chloride-to-bromide ratios) at monitoring wells farther away (&gt;300 m) indicate moderate amounts of in-situ sir entrapment and dissolution caused by the rise in regional groundwater levels. This is confirmed by hydrochemical difference between these sites and wells closer to the reservoir where recharge had already arrived. As the reservoir was being filled by 2002, managed aquifer recharge rates were initially very high (1.5 x 10<sup>-4</sup> cm/s) with the vadose zone becoming saturated beneath and surrounding the reservoir. These rates declined to less than 3.5 x 10<sup>-6</sup> cm/s during 2008. The 2002-08 decrease was likely associated with a declining regional hydraulic gradient and clogging. Increasing recharge rates during mid-2009 through 2010 may have been partly caused by dissolution of air bubbles initially entrapped in the aquifer matrix. Theoretical gas dissolution rates, coupled with field evidence of a decline iin total dissolved-gas pressure and dissolved oxygen from nearby monitoring wells, support the timing of this gas dissipation.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Clogging issues associated with managed aquifer recharge methods","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"IAH Commission on Managing Aquifer Recharge","publisherLocation":"Australia","isbn":"9780646908526","usgsCitation":"Heilweil, V.M., and Marston, T., 2013, Evaluation of potential gas clogging associated with managed aquifer recharge from a spreading basin, southwestern Utah, U.S.A., chap. <i>of</i> Clogging issues associated with managed aquifer recharge methods, p. 84-94.","productDescription":"11 p.","startPage":"84","endPage":"94","numberOfPages":"11","ipdsId":"IP-046038","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":278967,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278966,"type":{"id":15,"text":"Index Page"},"url":"https://recharge.iah.org/recharge/clogging.htm"}],"country":"United States","state":"Utah","otherGeospatial":"Sand Hollow Reservoir","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -113.39374,37.101658 ], [ -113.39374,37.127394 ], [ -113.35936,37.127394 ], [ -113.35936,37.101658 ], [ -113.39374,37.101658 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"527e586ae4b02d2057dd95db","contributors":{"authors":[{"text":"Heilweil, Victor M. heilweil@usgs.gov","contributorId":837,"corporation":false,"usgs":true,"family":"Heilweil","given":"Victor","email":"heilweil@usgs.gov","middleInitial":"M.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":481651,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marston, Thomas","contributorId":61734,"corporation":false,"usgs":true,"family":"Marston","given":"Thomas","affiliations":[],"preferred":false,"id":481652,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70047957,"text":"70047957 - 2013 - An international network of magnetic observatories","interactions":[],"lastModifiedDate":"2014-01-17T10:28:45","indexId":"70047957","displayToPublicDate":"2013-10-01T10:19:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1578,"text":"Eos, Transactions, American Geophysical Union","onlineIssn":"2324-9250","printIssn":"0096-394","active":true,"publicationSubtype":{"id":10}},"title":"An international network of magnetic observatories","docAbstract":"Since its formation in the late 1980s, the International Real-Time Magnetic Observatory Network (INTERMAGNET), a voluntary consortium of geophysical institutes from around the world, has promoted the operation of magnetic observatories according to modern standards [eg. Rasson, 2007]. INTERMAGNET institutes have cooperatively developed infrastructure for data exchange and management ads well as methods for data processing and checking. INTERMAGNET institute have also helped to expand global geomagnetic monitoring capacity, most notably by assisting magnetic observatory institutes in economically developing countries by working directly with local geophysicists. Today the INTERMAGNET consortium encompasses 57 institutes from 40 countries supporting 120 observatories (see Figures 1a and 1b). INTERMAGNET data record a wide variety of time series signals related to a host of different physical processes in the Earth's interiors and in the Earth's surrounding space environment [e.g., Love, 2008]. Observatory data have always had a diverse user community, and to meet evolving demand, INTERMAGNET has recently coordinated the introduction of several new data services.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Eos, Transactions American Geophysical Union","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Geophysical Union","doi":"10.1002/2013EO420001","usgsCitation":"Love, J.J., and Chulliat, A., 2013, An international network of magnetic observatories: Eos, Transactions, American Geophysical Union, v. 94, no. 42, p. 373-374, https://doi.org/10.1002/2013EO420001.","productDescription":"2 p.","startPage":"373","endPage":"374","numberOfPages":"2","ipdsId":"IP-050889","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":473508,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/2013eo420001","text":"External Repository"},{"id":281234,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281233,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/2013EO420001"}],"volume":"94","issue":"42","noUsgsAuthors":false,"publicationDate":"2013-10-15","publicationStatus":"PW","scienceBaseUri":"53cd4c9ae4b0b290850f114c","contributors":{"authors":[{"text":"Love, Jeffrey J. 0000-0002-3324-0348 jlove@usgs.gov","orcid":"https://orcid.org/0000-0002-3324-0348","contributorId":760,"corporation":false,"usgs":true,"family":"Love","given":"Jeffrey","email":"jlove@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":483400,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chulliat, A.","contributorId":108393,"corporation":false,"usgs":true,"family":"Chulliat","given":"A.","affiliations":[],"preferred":false,"id":483401,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70101100,"text":"70101100 - 2013 - Spatial variability of  \"Did You Feel It?\" intensity data:  insights into sampling biases in historical earthquake intensity distributions","interactions":[],"lastModifiedDate":"2014-04-10T10:20:47","indexId":"70101100","displayToPublicDate":"2013-10-01T10:17:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Spatial variability of  \"Did You Feel It?\" intensity data:  insights into sampling biases in historical earthquake intensity distributions","docAbstract":"Recent parallel development of improved quantitative methods to analyze intensity distributions for historical earthquakes and of web‐based systems for collecting intensity data for modern earthquakes provides an opportunity to reconsider not only important individual historical earthquakes but also the overall characterization of intensity distributions for historical events. The focus of this study is a comparison between intensity distributions of historical earthquakes with those from modern earthquakes for which intensities have been determined by the U.S. Geological Survey “Did You Feel It?” (DYFI) website (see Data and Resources). As an example of a historical earthquake, I focus initially on the 1843 Marked Tree, Arkansas, event. Its magnitude has been previously estimated as 6.0–6.2. I first reevaluate the macroseismic effects of this earthquake, assigning intensities using a traditional approach, and estimate a preferred magnitude of 5.4. Modified Mercalli intensity (MMI) values for the Marked Tree earthquake are higher, on average, than those from the 2011 <i>>Mw</i> 5.8 Mineral, Virginia, earthquake for distances ≤500  km but comparable or lower on average at larger distances, with a smaller overall felt extent. Intensity distributions for other moderate historical earthquakes reveal similar discrepancies; the discrepancy is also even more pronounced using earlier published intensities for the 1843 earthquake. I discuss several hypotheses to explain the discrepancies, including the possibility that intensity values associated with historical earthquakes are commonly inflated due to reporting/sampling biases. A detailed consideration of the DYFI intensity distribution for the Mineral earthquake illustrates how reporting and sampling biases can account for historical earthquake intensity biases as high as two intensity units and for the qualitative difference in intensity distance decays for modern versus historical events. Thus, intensity maps for historical earthquakes tend to imply more widespread damage patterns than are revealed by intensity distributions of modern earthquakes of comparable magnitude. However, intensity accounts of historical earthquakes often include fragmentary accounts suggesting long‐period shaking effects that will likely not be captured fully in historical intensity distributions.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Bulletin of the Seismological Society of America","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"BSSA","doi":"10.1785/0120120285","usgsCitation":"Hough, S.E., 2013, Spatial variability of  \"Did You Feel It?\" intensity data:  insights into sampling biases in historical earthquake intensity distributions: Bulletin of the Seismological Society of America, v. 103, no. 5, p. 2767-2781, https://doi.org/10.1785/0120120285.","productDescription":"15 p.","startPage":"2767","endPage":"2781","ipdsId":"IP-044980","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":286158,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286157,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1785/0120120285"}],"volume":"103","issue":"5","noUsgsAuthors":false,"publicationDate":"2013-09-30","publicationStatus":"PW","scienceBaseUri":"53559566e4b0120853e8c201","contributors":{"authors":[{"text":"Hough, Susan E. 0000-0002-5980-2986 hough@usgs.gov","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":587,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"hough@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":492597,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70074640,"text":"70074640 - 2013 - Monitoring of livestock grazing effects on Bureau of Land Management land","interactions":[{"subject":{"id":70005589,"text":"ofr20111263 - 2011 - Range-wide assessment of livestock grazing across the sagebrush biome","indexId":"ofr20111263","publicationYear":"2011","noYear":false,"title":"Range-wide assessment of livestock grazing across the sagebrush biome"},"predicate":"SUPERSEDED_BY","object":{"id":70074640,"text":"70074640 - 2013 - Monitoring of livestock grazing effects on Bureau of Land Management land","indexId":"70074640","publicationYear":"2013","noYear":false,"title":"Monitoring of livestock grazing effects on Bureau of Land Management land"},"id":1}],"lastModifiedDate":"2017-12-27T15:02:13","indexId":"70074640","displayToPublicDate":"2013-10-01T09:54:49","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3407,"text":"Society for Range Management","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring of livestock grazing effects on Bureau of Land Management land","docAbstract":"Public land management agencies, such as the Bureau of Land Management (BLM), are charged with managing rangelands throughout the western United States for multiple uses, such as livestock grazing and conservation of sensitive species and their habitats. Monitoring of condition and trends of these rangelands, particularly with respect to effects of livestock grazing, provides critical information for effective management of these multiuse landscapes. We therefore investigated the availability of livestock grazing-related quantitative monitoring data and qualitative region-specific Land Health Standards (LHS) data across BLM grazing allotments in the western United States. We then queried university and federal rangeland science experts about how best to prioritize rangeland monitoring activities. We found that the most commonly available monitoring data were permittee-reported livestock numbers and season-of-use data (71% of allotments) followed by repeat photo points (58%), estimates of forage utilization (52%), and, finally, quantitative vegetation measurements (37%). Of the 57% of allotments in which LHS had been evaluated as of 2007, the BLM indicated 15% had failed to meet LHS due to livestock grazing. A full complement of all types of monitoring data, however, existed for only 27% of those 15%. Our data inspections, as well as conversations with rangeland experts, indicated a need for greater emphasis on collection of grazing-related monitoring data, particularly ground cover. Prioritization of where monitoring activities should be focused, along with creation of regional monitoring teams, may help improve monitoring. Overall, increased emphasis on monitoring of BLM rangelands will require commitment at multiple institutional levels.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Society for Range Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Society for Range Management","doi":"10.2111/REM-D-12-00178.1","usgsCitation":"Veblen, K.E., Pyke, D.A., Aldridge, C.L., Casazza, M.L., Assal, T.J., and Farinha, M.A., 2013, Monitoring of livestock grazing effects on Bureau of Land Management land: Society for Range Management, v. 67, no. 1, p. 68-77, https://doi.org/10.2111/REM-D-12-00178.1.","productDescription":"10 p.","startPage":"68","endPage":"77","ipdsId":"IP-051639","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":281797,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281762,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2111/REM-D-12-00178.1"}],"country":"United States","volume":"67","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd6822e4b0b29085101d62","contributors":{"authors":[{"text":"Veblen, Kari E.","contributorId":76872,"corporation":false,"usgs":false,"family":"Veblen","given":"Kari","email":"","middleInitial":"E.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":489642,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pyke, David A. 0000-0002-4578-8335 david_a_pyke@usgs.gov","orcid":"https://orcid.org/0000-0002-4578-8335","contributorId":3118,"corporation":false,"usgs":true,"family":"Pyke","given":"David","email":"david_a_pyke@usgs.gov","middleInitial":"A.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":489639,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":489641,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":489637,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Assal, Timothy J. 0000-0001-6342-2954 assalt@usgs.gov","orcid":"https://orcid.org/0000-0001-6342-2954","contributorId":2203,"corporation":false,"usgs":true,"family":"Assal","given":"Timothy","email":"assalt@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":489638,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Farinha, Melissa A.","contributorId":7791,"corporation":false,"usgs":true,"family":"Farinha","given":"Melissa","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":489640,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
]}