{"pageNumber":"558","pageRowStart":"13925","pageSize":"25","recordCount":46679,"records":[{"id":70048570,"text":"sir20135170 - 2013 - Revised shallow and deep water-level and storage-volume changes in the <i>Equus</i> Beds Aquifer near Wichita, Kansas, predevelopment to 1993","interactions":[],"lastModifiedDate":"2013-11-14T18:06:19","indexId":"sir20135170","displayToPublicDate":"2013-10-24T09:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5170","title":"Revised shallow and deep water-level and storage-volume changes in the <i>Equus</i> Beds Aquifer near Wichita, Kansas, predevelopment to 1993","docAbstract":"Beginning in the 1940s, the Wichita well field was developed in the <i>Equus</i> Beds aquifer in southwestern Harvey County and northwestern Sedgwick County to supply water to the city of Wichita. The decline of water levels in the aquifer was noted soon after the development of the Wichita well field began. Development of irrigation wells began in the 1960s. City and agricultural withdrawals led to substantial water-level declines. Water-level declines enhanced movement of brines from past oil and gas activities near Burrton, Kansas and enhanced movement of natural saline water from the Arkansas River into the well field area. Large chloride concentrations may limit use or require the treatment of water from the well field for irrigation or public supply. In 1993, the city of Wichita adopted the Integrated Local Water Supply Program (ILWSP) to ensure an adequate water supply for the city through 2050 and as part of its effort to effectively manage the part of the <i>Equus</i> Beds aquifer it uses. ILWSP uses several strategies to do this including the <i>Equus</i> Beds Aquifer Storage and Recovery (ASR) project. The purpose of the ASR project is to store water in the aquifer for later recovery and to help protect the aquifer from encroachment of a known oilfield brine plume near Burrton and saline water from the Arkansas River.\n\nAs part of Wichita’s ASR permits, Wichita is prohibited from artificially recharging water into the aquifer in a Basin Storage area (BSA) grid cell if water levels in that cell are above the January 1940 water levels or are less than 10 feet below land surface. The map previously used for this purpose did not provide an accurate representation of the shallow water table. The revised predevelopment water-level altitude map of the shallow part of the aquifer is presented in this report.\n\nThe city of Wichita’s ASR permits specify that the January 1993 water-level altitudes will be used as a lower baseline for regulating the withdrawal of artificial rechage credits from the <i>Equus</i> Beds aquifer by the city of Wichita. The 1993 water levels correspond to the lowest recorded levels and largest storage declines since 1940. Revised and new water-level maps of shallow and deep layers were developed to better represent the general condition of the aquifer. Only static water levels were used to better represent the general condition of the aquifer and comply with Wichita’s ASR permits. To ensure adequate data density, the January 1993 period was expanded to October 1992 through February 1993. Static 1993 water levels from the deep aquifer layer of the <i>Equus</i> Beds aquifer possibly could be used as the lower baseline for regulatory purposes.\n\nPreviously, maps of water-level changes used to estimate the storage-volume changes included a combination of static (unaffected by pumping or nearby pumping) and stressed (affected by pumping or nearby pumping) water levels from wells. Some of these wells were open to the shallow aquifer layer and some were open to the deep aquifer layer of the <i>Equus</i> Beds aquifer. In this report, only static water levels in the shallow aquifer layer were used to determine storage-volume changes.\n\nThe effects on average water-level and storage-volume change from the use of mixed, stressed water levels and a specific yield of 0.20 were compared to the use of static water levels in the shallow aquifer and a specific yield of 0.15. This comparison indicates that the change in specific yield causes storage-volume changes to decrease about 25 percent, whereas the use of static water levels in the shallow aquifer layer causes an increase of less than 4 percent. Use of a specific yield of 0.15 will result in substantial decreases in the amount of storage-volume change compared to those reported previously that were calculated using a specific yield of 0.20. Based on these revised water-level maps and computations, the overall decline and change in storage from predevelopment to 1993 represented a loss in storage of about 6 percent (-202,000 acre-feet) of the overall storage volume within the newly defined study area.","language":"English","publisher":"U.S Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135170","usgsCitation":"Hansen, C.V., Lanning-Rush, J., and Ziegler, A., 2013, Revised shallow and deep water-level and storage-volume changes in the <i>Equus</i> Beds Aquifer near Wichita, Kansas, predevelopment to 1993: U.S. Geological Survey Scientific Investigations Report 2013-5170, v.; 18 p., https://doi.org/10.3133/sir20135170.","productDescription":"v.; 18 p.","numberOfPages":"23","onlineOnly":"Y","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":278347,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135170.gif"},{"id":278346,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5170/"},{"id":278345,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5170/pdf/sir2013_5170.pdf"}],"country":"United States","state":"Kansas","city":"Wichita","otherGeospatial":"Equus Beds Aquifer","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -97.68355,37.73379 ], [ -97.68355,38.181032 ], [ -97.396098,38.181032 ], [ -97.396098,37.73379 ], [ -97.68355,37.73379 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"526a3365e4b0c0d229f9bde0","contributors":{"authors":[{"text":"Hansen, Cristi V. chansen@usgs.gov","contributorId":435,"corporation":false,"usgs":true,"family":"Hansen","given":"Cristi","email":"chansen@usgs.gov","middleInitial":"V.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":485108,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lanning-Rush, Jennifer L. jlanning@usgs.gov","contributorId":5809,"corporation":false,"usgs":true,"family":"Lanning-Rush","given":"Jennifer L.","email":"jlanning@usgs.gov","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":485109,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ziegler, Andrew C. aziegler@usgs.gov","contributorId":433,"corporation":false,"usgs":true,"family":"Ziegler","given":"Andrew C.","email":"aziegler@usgs.gov","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":485107,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70048530,"text":"70048530 - 2013 - Influence of monsoon-related riparian phenology on yellow-billed cuckoo habitat selection in Arizona","interactions":[],"lastModifiedDate":"2017-11-25T13:36:41","indexId":"70048530","displayToPublicDate":"2013-10-22T15:19:00","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":"Influence of monsoon-related riparian phenology on yellow-billed cuckoo habitat selection in Arizona","docAbstract":"Aim: The western yellow-billed cuckoo (Coccyzus americanus occidentalis), a Neotropical migrant bird, is facing steep population declines in its western breeding grounds owing primarily to loss of native habitat. The favoured  esting habitat for the cuckoo in the south-western United States is low-elevation riparian forests and woodlands. Our aim was to explore relationships between vegetation phenology patterns captured by satellite phenometrics and the distribution of the yellow-billed cuckoo, and to use this information to map cuckoo habitat. Location: Arizona, USA. Methods: Land surface phenometrics were derived from satellite Advanced Very High-Resolution Radiometer (AVHRR), bi-weekly time-composite,  ormalized difference vegetation index (NDVI) data for 1998 and 1999 at a resolution of 1 km. Fourier harmonics were used to analyse the waveform of the annual NDVI profile in each pixel. To create the models, we coupled 1998 satellite phenometrics with 1998 field survey data of cuckoo presence or absence and with point data that sampled riparian and cottonwood–willow vegetation types. Our models were verified and refined using field and  satellite data collected in 1999.  Results: The models reveal that cuckoos prefer areas that experience peak greenness 29 days later, are 36% more dynamic and slightly (< 1%) more  productive than their average cottonwood–willow habitat. The results support a scenario in which cuckoos migrate northwards, following the greening of riparian  corridors and surrounding landscapes in response to monsoon precipitation, but then select a nesting site based on optimizing the near-term foraging potential of the neighbourhood. Main conclusions: The identification of preferred phenotypes within recognized habitat can be used to refine future habitat models, inform habitat response to climate change, and suggest adaptation strategies. For example, models of phenotype preferences can guide management actions by identifying and prioritizing for conservation those landscapes that reliably exhibit highly preferred phenometrics on a consistent basis.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Biogeography","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/jbi.12167","usgsCitation":"Wallace, C., Villarreal, M.L., and van Riper, C., 2013, Influence of monsoon-related riparian phenology on yellow-billed cuckoo habitat selection in Arizona: Journal of Biogeography, v. 40, no. 11, p. 2094-2107, https://doi.org/10.1111/jbi.12167.","productDescription":"14 p.","startPage":"2094","endPage":"2107","numberOfPages":"14","ipdsId":"IP-013518","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":473475,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jbi.12167","text":"Publisher Index Page"},{"id":278336,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278334,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/jbi.12167"}],"country":"United States","state":"Arizona","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114.8184,31.3322 ], [ -114.8184,37.0043 ], [ -109.0452,37.0043 ], [ -109.0452,31.3322 ], [ -114.8184,31.3322 ] ] ] } } ] }","volume":"40","issue":"11","noUsgsAuthors":false,"publicationDate":"2013-07-19","publicationStatus":"PW","scienceBaseUri":"52679067e4b0c24c90856d8a","contributors":{"authors":[{"text":"Wallace, Cynthia S.A. cwallace@usgs.gov","contributorId":3335,"corporation":false,"usgs":true,"family":"Wallace","given":"Cynthia S.A.","email":"cwallace@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":484978,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":1424,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":484977,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Riper, Charles III 0000-0003-1084-5843 charles_van_riper@usgs.gov","orcid":"https://orcid.org/0000-0003-1084-5843","contributorId":169488,"corporation":false,"usgs":true,"family":"van Riper","given":"Charles","suffix":"III","email":"charles_van_riper@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":484976,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70048533,"text":"70048533 - 2013 - Influence of management and precipitation on carbon fluxes in greatplains grasslands","interactions":[],"lastModifiedDate":"2013-10-30T10:47:20","indexId":"70048533","displayToPublicDate":"2013-10-22T14:57:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Influence of management and precipitation on carbon fluxes in greatplains grasslands","docAbstract":"Suitable management and sufficient precipitation on grasslands can provide carbon sinks. The net carbon accumulation of a site from the atmosphere, modeled as the Net Ecosystem Productivity (NEP), is a useful means to gauge carbon balance. Previous research has developed methods to integrate flux tower data with satellite biophysical datasets to estimate NEP across large regions. A related method uses the Ecosystem Performance Anomaly (EPA) as a satellite-derived indicator of disturbance intensity (e.g., livestock stocking rate, fire, and insect damage). To better understand the interactions among management, climate, and carbon dynamics, we evaluated the relationship between EPA and NEP data at the 250 m scale for grasslands in the Central Great Plains, USA (ranging from semi-arid to mesic). We also used weekly estimates of NEP to evaluate the phenology of carbon dynamics, classified by EPA (i.e., by level of disturbance impact). Results show that the cumulative carbon balance over these grasslands from 2000 to 2008 was a weak net sink of 13.7 g C m<sup>−2</sup> yr<sup>−1</sup>. Overall, NEP increased with precipitation (R<sup>2</sup> = 0.39, P < 0.05) from west to east. Disturbance influenced NEP phenology; however, climate and biophysical conditions were usually more important. The NEP response to disturbance varies by ecoregion, and more generally by grassland type, where the shortgrass prairie NEP is most sensitive to disturbance, the mixed-grass prairie displays a moderate response, and tallgrass prairie is the least impacted by disturbance (as measured by EPA). Sustainable management practices in the tallgrass and mixed-grass prairie may potentially induce a period of average net carbon sink until a new equilibrium soil organic carbon is achieved. In the shortgrass prairie, management should be considered sustainable if carbon stocks are simply maintained. The consideration of site carbon balance adds to the already difficult task of managing grasslands appropriately to site conditions. Results clarify the seasonal and interannual dynamics of NEP, specifically the influence of disturbance and moisture availability.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecological Indicators","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Ecological Indicators","doi":"10.1016/j.ecolind.2013.06.028","usgsCitation":"Rigge, M.B., Wylie, B.K., Zhang, L., and Boyte, S.P., 2013, Influence of management and precipitation on carbon fluxes in greatplains grasslands: Ecological Indicators, v. 34, p. 590-599, https://doi.org/10.1016/j.ecolind.2013.06.028.","productDescription":"10 p.","startPage":"590","endPage":"599","ipdsId":"IP-042112","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":278332,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278333,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.ecolind.2013.06.028"}],"volume":"34","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52679067e4b0c24c90856d87","contributors":{"authors":[{"text":"Rigge, Matthew B. 0000-0003-4471-8009 mrigge@usgs.gov","orcid":"https://orcid.org/0000-0003-4471-8009","contributorId":751,"corporation":false,"usgs":true,"family":"Rigge","given":"Matthew","email":"mrigge@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":484983,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","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":484982,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhang, Li","contributorId":98139,"corporation":false,"usgs":true,"family":"Zhang","given":"Li","affiliations":[],"preferred":false,"id":484985,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boyte, Stephen P. 0000-0002-5462-3225 sboyte@usgs.gov","orcid":"https://orcid.org/0000-0002-5462-3225","contributorId":3463,"corporation":false,"usgs":true,"family":"Boyte","given":"Stephen","email":"sboyte@usgs.gov","middleInitial":"P.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":484984,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70048546,"text":"70048546 - 2013 - Estimating riparian and agricultural evapotranspiration by reference crop evapotranspiration and MODIS Enhanced Vegetation Index","interactions":[],"lastModifiedDate":"2025-12-11T21:30:40.075464","indexId":"70048546","displayToPublicDate":"2013-10-22T14:51:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Estimating riparian and agricultural evapotranspiration by reference crop evapotranspiration and MODIS Enhanced Vegetation Index","docAbstract":"Dryland river basins frequently support both irrigated agriculture and riparian vegetation and remote sensing methods are needed to monitor water use by both crops and natural vegetation in irrigation districts. We developed an algorithm for estimating actual evapotranspiration (ET<sub>a</sub>) based on the Enhanced Vegetation Index (EVI) from the Moderate Resolution Imaging Spectrometer (MODIS) sensor on the EOS-1 Terra satellite and locally-derived measurements of reference crop ET (ET<sub>o</sub>). The algorithm was calibrated with five years of ETa data from three eddy covariance flux towers set in riparian plant associations on the upper San Pedro River, Arizona, supplemented with ETa data for alfalfa and cotton from the literature. The algorithm was based on an equation of the form ET<sub>a</sub> = ET<sub>o</sub> [a(1 − e<sup>−bEVI</sup>) − c], where the term (1 − e<sup>−bEVI</sup>) is derived from the Beer-Lambert Law to express light absorption by a canopy, with EVI replacing leaf area index as an estimate of the density of light-absorbing units. The resulting algorithm capably predicted ET<sub>a</sub> across riparian plants and crops (r<sup>2</sup> = 0.73). It was then tested against water balance data for five irrigation districts and flux tower data for two riparian zones for which season-long or multi-year ET<sub>a</sub> data were available. Predictions were within 10% of measured results in each case, with a non-significant (P = 0.89) difference between mean measured and modeled ET<sub>a</sub> of 5.4% over all validation sites. Validation and calibration data sets were combined to present a final predictive equation for application across crops and riparian plant associations for monitoring individual irrigation districts or for conducting global water use assessments of mixed agricultural and riparian biomes.","language":"English","publisher":"MDPI","doi":"10.3390/rs5083849","usgsCitation":"Nagler, P.L., Glenn, E.P., Nguyen, U., Scott, R., and Doody, T., 2013, Estimating riparian and agricultural evapotranspiration by reference crop evapotranspiration and MODIS Enhanced Vegetation Index: Remote Sensing, v. 5, no. 8, p. 3849-3871, https://doi.org/10.3390/rs5083849.","productDescription":"23 p.","startPage":"3849","endPage":"3871","ipdsId":"IP-045908","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":473476,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs5083849","text":"Publisher Index Page"},{"id":278313,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"8","noUsgsAuthors":false,"publicationDate":"2013-08-05","publicationStatus":"PW","scienceBaseUri":"52679064e4b0c24c90856d7b","contributors":{"authors":[{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":485028,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Glenn, Edward P.","contributorId":19289,"corporation":false,"usgs":true,"family":"Glenn","given":"Edward","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":485030,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nguyen, Uyen","contributorId":71863,"corporation":false,"usgs":false,"family":"Nguyen","given":"Uyen","email":"","affiliations":[{"id":13060,"text":"Department of Soil, Water and Environmental Science, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":485032,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Scott, Russell","contributorId":11931,"corporation":false,"usgs":true,"family":"Scott","given":"Russell","affiliations":[],"preferred":false,"id":485029,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Doody, Tania","contributorId":23836,"corporation":false,"usgs":true,"family":"Doody","given":"Tania","email":"","affiliations":[],"preferred":false,"id":485031,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70048550,"text":"70048550 - 2013 - InSAR Evidence for an active shallow thrust fault beneath the city of Spokane Washington, USA","interactions":[],"lastModifiedDate":"2013-10-30T10:48:26","indexId":"70048550","displayToPublicDate":"2013-10-22T14:40:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"InSAR Evidence for an active shallow thrust fault beneath the city of Spokane Washington, USA","docAbstract":"In 2001, a nearly five month long sequence of shallow, mostly small magnitude earthquakes occurred beneath the city of Spokane, a city with a population of about 200,000, in the state of Washington. During most of the sequence, the earthquakes were not well located because seismic instrumentation was sparse. Despite poor-quality locations, the earthquake hypocenters were likely very shallow, because residents near the city center both heard and felt many of the earthquakes. The combination of poor earthquake locations and a lack of known surface faults with recent movement make assessing the seismic hazards related to the earthquake swarm difficult. However, the potential for destruction from a shallow moderate-sized earthquake is high, for example Christchurch New Zealand in 2011, so assessing the hazard potential of a seismic structure involved in the Spokane earthquake sequence is important. Using interferometric synthetic aperture radar (InSAR) data from the European Space Agency ERS2 and ENVISAT satellites and the Canadian Space Agency RADARSAT-1, satellite we are able to show that slip on a shallow previously unknown thrust fault, which we name the Spokane Fault, is the source of the earthquake sequence. The part of the Spokane Fault that slipped during the 2001 earthquake sequence underlies the north part of the city, and slip on the fault was concentrated between ~0.3 and 2 km depth. Projecting the buried fault plane to the surface gives a possible surface trace for the Spokane Fault that strikes northeast from the city center into north Spokane.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research B: Solid Earth","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/jgrb.50118","usgsCitation":"Wicks, C., Weaver, C.S., Bodin, P., and Sherrod, B.L., 2013, InSAR Evidence for an active shallow thrust fault beneath the city of Spokane Washington, USA: Journal of Geophysical Research B: Solid Earth, v. 118, no. 3, p. 1268-1276, https://doi.org/10.1002/jgrb.50118.","productDescription":"9 p.","startPage":"1268","endPage":"1276","ipdsId":"IP-038809","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":278330,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278307,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jgrb.50118"}],"country":"United States","state":"Washington","city":"Spokane","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117.584713,47.49886 ], [ -117.584713,47.81886 ], [ -117.264713,47.81886 ], [ -117.264713,47.49886 ], [ -117.584713,47.49886 ] ] ] } } ] }","volume":"118","issue":"3","noUsgsAuthors":false,"publicationDate":"2013-03-27","publicationStatus":"PW","scienceBaseUri":"52679066e4b0c24c90856d84","contributors":{"authors":[{"text":"Wicks, Charles W. Jr. cwicks@usgs.gov","contributorId":3476,"corporation":false,"usgs":true,"family":"Wicks","given":"Charles W.","suffix":"Jr.","email":"cwicks@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":485045,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weaver, Craig S. craig@usgs.gov","contributorId":2690,"corporation":false,"usgs":true,"family":"Weaver","given":"Craig","email":"craig@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":485043,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bodin, Paul","contributorId":104142,"corporation":false,"usgs":true,"family":"Bodin","given":"Paul","affiliations":[],"preferred":false,"id":485046,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sherrod, Brian L. 0000-0002-4492-8631 bsherrod@usgs.gov","orcid":"https://orcid.org/0000-0002-4492-8631","contributorId":2834,"corporation":false,"usgs":true,"family":"Sherrod","given":"Brian","email":"bsherrod@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":485044,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70048551,"text":"70048551 - 2013 - Low copper and high manganese levels in prion protein plaques","interactions":[],"lastModifiedDate":"2018-01-04T15:23:44","indexId":"70048551","displayToPublicDate":"2013-10-22T10:16:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3700,"text":"Viruses","active":true,"publicationSubtype":{"id":10}},"title":"Low copper and high manganese levels in prion protein plaques","docAbstract":"<p>Accumulation of aggregates rich in an abnormally folded form of the prion protein characterize the neurodegeneration caused by transmissible spongiform encephalopathies (TSEs). The molecular triggers of plaque formation and neurodegeneration remain unknown, but analyses of TSE-infected brain homogenates and preparations enriched for abnormal prion protein suggest that reduced levels of copper and increased levels of manganese are associated with disease. The objectives of this study were to: (1) assess copper and manganese levels in healthy and TSE-infected Syrian hamster brain homogenates; (2) determine if the distribution of these metals can be mapped in TSE-infected brain tissue using X-ray photoelectron emission microscopy (X-PEEM) with synchrotron radiation; and (3) use X-PEEM to assess the relative amounts of copper and manganese in prion plaques in situ. In agreement with studies of other TSEs and species, we found reduced brain levels of copper and increased levels of manganese associated with disease in our hamster model. We also found that the in situ levels of these metals in brainstem were sufficient to image by X-PEEM. Using immunolabeled prion plaques in directly adjacent tissue sections to identify regions to image by X-PEEM, we found a statistically significant relationship of copper-manganese dysregulation in prion plaques: copper was depleted whereas manganese was enriched. These data provide evidence for prion plaques altering local transition metal distribution in the TSE-infected central nervous system.</p>","language":"English","publisher":"Multidisciplinary Digital Publishing Institute","doi":"10.3390/v5020654","usgsCitation":"Johnson, C.J., Gilbert, P., Abrecth, M., Baldwin, K.L., Russell, R.E., Pedersen, J.A., and McKenzie, D., 2013, Low copper and high manganese levels in prion protein plaques: Viruses, v. 5, no. 2, p. 654-662, https://doi.org/10.3390/v5020654.","productDescription":"9 p.","startPage":"654","endPage":"662","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-043607","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":473479,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/v5020654","text":"Publisher Index Page"},{"id":278315,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278314,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3390/v5020654"}],"volume":"5","issue":"2","noUsgsAuthors":false,"publicationDate":"2013-02-11","publicationStatus":"PW","scienceBaseUri":"52679068e4b0c24c90856d90","contributors":{"authors":[{"text":"Johnson, Christopher J. cjjohnson@usgs.gov","contributorId":3491,"corporation":false,"usgs":true,"family":"Johnson","given":"Christopher","email":"cjjohnson@usgs.gov","middleInitial":"J.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":485047,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gilbert, P.U.P.A.","contributorId":80172,"corporation":false,"usgs":true,"family":"Gilbert","given":"P.U.P.A.","email":"","affiliations":[],"preferred":false,"id":485051,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Abrecth, Mike","contributorId":53281,"corporation":false,"usgs":true,"family":"Abrecth","given":"Mike","email":"","affiliations":[],"preferred":false,"id":485050,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baldwin, Katherine L.","contributorId":44821,"corporation":false,"usgs":true,"family":"Baldwin","given":"Katherine","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":485049,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Russell, Robin E. 0000-0001-8726-7303 rerussell@usgs.gov","orcid":"https://orcid.org/0000-0001-8726-7303","contributorId":3998,"corporation":false,"usgs":true,"family":"Russell","given":"Robin","email":"rerussell@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":485048,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pedersen, Joel A.","contributorId":85079,"corporation":false,"usgs":true,"family":"Pedersen","given":"Joel","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":485053,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McKenzie, Debbie","contributorId":82211,"corporation":false,"usgs":true,"family":"McKenzie","given":"Debbie","affiliations":[],"preferred":false,"id":485052,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70048553,"text":"ofr20131221 - 2013 - Chuckwalla Valley multiple-well monitoring site, Chuckwalla Valley, Riverside County","interactions":[],"lastModifiedDate":"2013-11-14T17:54:58","indexId":"ofr20131221","displayToPublicDate":"2013-10-22T08:52:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1221","title":"Chuckwalla Valley multiple-well monitoring site, Chuckwalla Valley, Riverside County","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the Bureau of Land Management, is evaluating the geohydrology and water availability of the Chuckwalla Valley, California. As part of this evaluation, the USGS installed the Chuckwalla Valley multiple-well monitoring site (CWV1) in the southeastern portion of the Chuckwalla Basin. Data collected at this site provide information about the geology, hydrology, geophysics, and geochemistry of the local aquifer system, thus enhancing the understanding of the geohydrologic framework of the Chuckwalla Valley. This report presents construction information for the CWV1 multiple-well monitoring site and initial geohydrologic data collected from the site.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131221","collaboration":"Prepared in cooperation with U.S. Bureau of Land Management, California Desert District","usgsCitation":"Everett, R., 2013, Chuckwalla Valley multiple-well monitoring site, Chuckwalla Valley, Riverside County: U.S. Geological Survey Open-File Report 2013-1221, 6 p., https://doi.org/10.3133/ofr20131221.","productDescription":"6 p.","numberOfPages":"6","additionalOnlineFiles":"N","ipdsId":"IP-041881","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":278310,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131221.jpg"},{"id":278308,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1221/"},{"id":278309,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1221/pdf/ofr2013-1221.pdf"}],"projection":"Albers","datum":"North American Datum of 1983","country":"United States","state":"California","otherGeospatial":"Chuckwalla Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -115.9982,33.1941 ], [ -115.9982,34.0801 ], [ -114.4349,34.0801 ], [ -114.4349,33.1941 ], [ -115.9982,33.1941 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52679052e4b0c24c90856d72","contributors":{"authors":[{"text":"Everett, Rhett R. 0000-0001-7983-6270 reverett@usgs.gov","orcid":"https://orcid.org/0000-0001-7983-6270","contributorId":843,"corporation":false,"usgs":true,"family":"Everett","given":"Rhett R.","email":"reverett@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":false,"id":485062,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70156369,"text":"70156369 - 2013 - A computational- And storage-cloud for integration of biodiversity collections","interactions":[],"lastModifiedDate":"2015-08-20T12:18:01","indexId":"70156369","displayToPublicDate":"2013-10-22T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"A computational- And storage-cloud for integration of biodiversity collections","docAbstract":"<p><span>A core mission of the Integrated Digitized Biocollections (iDigBio) project is the building and deployment of a cloud computing environment customized to support the digitization workflow and integration of data from all U.S. nonfederal biocollections. iDigBio chose to use cloud computing technologies to deliver a cyberinfrastructure that is flexible, agile, resilient, and scalable to meet the needs of the biodiversity community. In this context, this paper describes the integration of open source cloud middleware, applications, and third party services using standard formats, protocols, and services. In addition, this paper demonstrates the value of the digitized information from collections in a broader scenario involving multiple disciplines.</span></p>","largerWorkType":{"id":24,"text":"Conference Paper"},"largerWorkTitle":"Proceedings - IEEE 9th International Conference on e-Science, e-Science 2013","conferenceTitle":"Proceedings - IEEE 9th International Conference on e-Science, e-Science 2013","conferenceDate":"22-25 Oct. 2013","conferenceLocation":"Beijing","language":"English","publisher":"eScience","doi":"10.1109/eScience.2013.48","usgsCitation":"Matsunaga, A., Thompson, A., Figueiredo, R.J., Germain-Aubrey, C., Collins, M., Beeman, R., Macfadden, B., Riccardi, G., Soltis, P., Page, L.M., and Fortes, J., 2013, A computational- And storage-cloud for integration of biodiversity collections, <i>in</i> Proceedings - IEEE 9th International Conference on e-Science, e-Science 2013, Beijing, 22-25 Oct. 2013, p. 78-87, https://doi.org/10.1109/eScience.2013.48.","startPage":"78","endPage":"87","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":307011,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f22ee4b0bc0bec0a021e","contributors":{"authors":[{"text":"Matsunaga, A.","contributorId":146762,"corporation":false,"usgs":false,"family":"Matsunaga","given":"A.","email":"","affiliations":[],"preferred":false,"id":568913,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, A.","contributorId":146763,"corporation":false,"usgs":false,"family":"Thompson","given":"A.","affiliations":[],"preferred":false,"id":568914,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Figueiredo, R. J.","contributorId":146764,"corporation":false,"usgs":false,"family":"Figueiredo","given":"R.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":568915,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Germain-Aubrey, C.C","contributorId":146765,"corporation":false,"usgs":false,"family":"Germain-Aubrey","given":"C.C","email":"","affiliations":[],"preferred":false,"id":568916,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Collins, M.","contributorId":49224,"corporation":false,"usgs":true,"family":"Collins","given":"M.","email":"","affiliations":[],"preferred":false,"id":568917,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Beeman, R.S","contributorId":146766,"corporation":false,"usgs":false,"family":"Beeman","given":"R.S","email":"","affiliations":[],"preferred":false,"id":568918,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Macfadden, B.J.","contributorId":13383,"corporation":false,"usgs":true,"family":"Macfadden","given":"B.J.","affiliations":[],"preferred":false,"id":568919,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Riccardi, G.","contributorId":146767,"corporation":false,"usgs":false,"family":"Riccardi","given":"G.","email":"","affiliations":[],"preferred":false,"id":568920,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Soltis, P.S","contributorId":146768,"corporation":false,"usgs":false,"family":"Soltis","given":"P.S","email":"","affiliations":[],"preferred":false,"id":568921,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Page, L. M.","contributorId":146769,"corporation":false,"usgs":false,"family":"Page","given":"L.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":568922,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Fortes, J.A.B","contributorId":146770,"corporation":false,"usgs":false,"family":"Fortes","given":"J.A.B","email":"","affiliations":[],"preferred":false,"id":568923,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70048516,"text":"70048516 - 2013 - Comparison of a karst groundwater model with and without discrete conduit flow","interactions":[],"lastModifiedDate":"2017-10-12T20:18:58","indexId":"70048516","displayToPublicDate":"2013-10-18T16:03:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of a karst groundwater model with and without discrete conduit flow","docAbstract":"Karst aquifers exhibit a dual flow system characterized by interacting conduit and matrix domains. This study evaluated the coupled continuum pipe-flow framework for modeling karst groundwater flow in the Madison aquifer of western South Dakota (USA). Coupled conduit and matrix flow was simulated within a regional finite-difference model over a 10-year transient period. An existing equivalent porous medium (EPM) model was modified to include major conduit networks whose locations were constrained by dye-tracing data and environmental tracer analysis. Model calibration data included measured hydraulic heads at observation wells and estimates of discharge at four karst springs. Relative to the EPM model, the match to observation well hydraulic heads was substantially improved with the addition of conduits. The inclusion of conduit flow allowed for a simpler hydraulic conductivity distribution in the matrix continuum. Two of the high-conductivity zones in the EPM model, which were required to indirectly simulate the effects of conduits, were eliminated from the new model. This work demonstrates the utility of the coupled continuum pipe-flow method and illustrates how karst aquifer model parameterization is dependent on the physical processes that are simulated.","language":"English","publisher":"Springer","doi":"10.1007/s10040-013-1036-6","usgsCitation":"Saller, S.P., Ronayne, M.J., and Long, A.J., 2013, Comparison of a karst groundwater model with and without discrete conduit flow: Hydrogeology Journal, v. 21, no. 7, p. 1555-1566, https://doi.org/10.1007/s10040-013-1036-6.","productDescription":"12 p.","startPage":"1555","endPage":"1566","ipdsId":"IP-042678","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":278287,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Dakota","otherGeospatial":"Madison Aquifer","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -104.06,42.48 ], [ -104.06,45.95 ], [ -101.86,45.95 ], [ -101.86,42.48 ], [ -104.06,42.48 ] ] ] } } ] }","volume":"21","issue":"7","noUsgsAuthors":false,"publicationDate":"2013-09-06","publicationStatus":"PW","scienceBaseUri":"52624a53e4b079a99629a0d3","contributors":{"authors":[{"text":"Saller, Stephen P.","contributorId":60118,"corporation":false,"usgs":true,"family":"Saller","given":"Stephen","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":484911,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ronayne, Michael J.","contributorId":101556,"corporation":false,"usgs":true,"family":"Ronayne","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":484912,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Long, Andrew J. 0000-0001-7385-8081 ajlong@usgs.gov","orcid":"https://orcid.org/0000-0001-7385-8081","contributorId":989,"corporation":false,"usgs":true,"family":"Long","given":"Andrew","email":"ajlong@usgs.gov","middleInitial":"J.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":484910,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70048537,"text":"fs20133097 - 2013 - The 3D Elevation Program: summary for Texas","interactions":[],"lastModifiedDate":"2016-08-17T16:03:57","indexId":"fs20133097","displayToPublicDate":"2013-10-18T15:06:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-3097","title":"The 3D Elevation Program: summary for Texas","docAbstract":"<p><span>Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of 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":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","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":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":554,"text":"Science and Decisions Center","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":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western 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":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","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 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