The seasonal activity pattern of immature Ixodes scapularis Say (Acari: Ixodidae) varies geographically in the United States, which may affect the efficiency of transmission cycles of pathogens transmitted by this species. To study the factors that determine seasonality, a multiyear study at seven sites across the geographic range of I. scapularis systematically collected questing ticks by flagging/dragging, and feeding ticks by capture of their hosts. The observed phenology patterns were consistent with previous studies reporting geographic variation in seasonal tick activity. Predictions of seasonal activity for each site were obtained from an I. scapularis simulation model calibrated using contemporaneous weather data. A range of scenarios for life-cycle processes—including different regimes of temperature-independent behavioral and developmental diapause, variations in temperature–development rate relationships, and temperature-dependent tick activity—were used in model formulations. These formulations produced a range of simulations of seasonal activity for each site and were compared against the field observed tick data using negative binomial regression models. Best fit scenarios were chosen for each site on the basis of Akaike’s information criterion and regression model parameters. This analysis suggests that temperature-independent diapause mechanisms explain some key observed variations in I. scapularis seasonality, and are responsible in part for geographic variations in I. scapularis seasonality in the United States. However, diapause appears to operate in idiosyncratic ways in different regions of the United States, so further studies on populations in different regions will be needed to enable predictive modeling of climatic and climate change effects on I. scapularis seasonal activity and pathogen transmission.
","language":"English","publisher":"Entomological Society of America","doi":"10.1093/jme/tjy104","usgsCitation":"Ogden, N.H., Pang, G., Ginsberg, H., Hickling, G., Burke, R.L., Beati, L., and Tsao, J.I., 2018, Evidence for geographic variation in life-cycle processes affecting phenology of the Lyme disease vector Ixodes scapularis (Acari: Ixodidae) in the United States: Journal of Medical Entomology, v. 55, no. 6, p. 1386-1401, https://doi.org/10.1093/jme/tjy104.","productDescription":"16 p.","startPage":"1386","endPage":"1401","ipdsId":"IP-095991","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":468286,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jme/tjy104","text":"Publisher Index Page"},{"id":358827,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"55","issue":"6","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-07","publicationStatus":"PW","scienceBaseUri":"5c10a915e4b034bf6a7e4f67","contributors":{"authors":[{"text":"Ogden, Nicholas H.","contributorId":147667,"corporation":false,"usgs":false,"family":"Ogden","given":"Nicholas","email":"","middleInitial":"H.","affiliations":[{"id":16890,"text":"Public Health Agency of Canada","active":true,"usgs":false}],"preferred":false,"id":749791,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pang, Genevieve","contributorId":71087,"corporation":false,"usgs":true,"family":"Pang","given":"Genevieve","affiliations":[],"preferred":false,"id":749795,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ginsberg, Howard S. 0000-0002-4933-2466 hginsberg@usgs.gov","orcid":"https://orcid.org/0000-0002-4933-2466","contributorId":147665,"corporation":false,"usgs":true,"family":"Ginsberg","given":"Howard S.","email":"hginsberg@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":749790,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hickling, Graham J.","contributorId":88639,"corporation":false,"usgs":true,"family":"Hickling","given":"Graham J.","affiliations":[],"preferred":false,"id":749792,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Burke, Russell L.","contributorId":127374,"corporation":false,"usgs":false,"family":"Burke","given":"Russell","email":"","middleInitial":"L.","affiliations":[{"id":6921,"text":"Hofstra University","active":true,"usgs":false}],"preferred":false,"id":749793,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Beati, Lorenza","contributorId":148019,"corporation":false,"usgs":false,"family":"Beati","given":"Lorenza","email":"","affiliations":[{"id":16976,"text":"Georgia Southern University","active":true,"usgs":false}],"preferred":false,"id":749794,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tsao, Jean I.","contributorId":140905,"corporation":false,"usgs":false,"family":"Tsao","given":"Jean","email":"","middleInitial":"I.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":749796,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70200605,"text":"70200605 - 2018 - Establishing chronologies for alluvial-fan sequences with analysis of high-resolution topographic data: San Luis Valley, Colorado, USA","interactions":[],"lastModifiedDate":"2018-11-14T08:48:06","indexId":"70200605","displayToPublicDate":"2018-10-25T12:11:27","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Establishing chronologies for alluvial-fan sequences with analysis of high-resolution topographic data: San Luis Valley, Colorado, USA","docAbstract":"On active alluvial fans, debris-flow deposits and frequent avulsions produce a rough topographic surface. As is the case in many initially rough landforms produced by catastrophic processes, the topography of alluvial fans is progressively smoothed, producing textural differences useful in establishing relative age criteria for fans. Here, we outline an approach for defining a quantitative, numerical chronology for the surfaces of alluvial fans from topographic analysis, although the method is generalizable to any arbitrary landform. Our chronology relies on predictions for the evolution of topography by purely diffusive modification. Specifically, by comparing the surface roughness of active and abandoned alluvial-fan surfaces measured from spectral transformations of topography, we can directly estimate a fan’s “morphologic age,” which is the product of the duration and efficiency of diffusive modification by surface processes. We tested the method on a suite of alluvial fans in the San Luis Valley, Colorado, USA, and evaluated the results against field observations and available geochronologic data. Estimated morphologic ages obey stratigraphic constraints and imply reasonable efficiencies of sediment transport. We highlight the fact that the oldest fan surfaces observed here, constrained to be older than 100 ka by U-series dating of pedogenic carbonates, have morphologic ages near the method’s saturation point. In addition, many fans have morphologies that are not entirely consistent with a purely diffusive modification from the initial fan morphology recorded on active fan surfaces, likely as a result of postdepositional modification by sediment transport driven by wind and overland flow. However, we remain optimistic that morphologic dating can provide useful insights into the history of alluvial-fan activity, in particular, because our method provides a means for both computing a morphologic age and assessing the validity of the assumptions required for that computation from analysis of topography alone.
","language":"English","publisher":"Geologic Society of America","doi":"10.1130/GES01680.1","usgsCitation":"Johnstone, S., Hudson, A.M., Nicovich, S., Ruleman, C.A., Sare, R.M., and Thompson, R., 2018, Establishing chronologies for alluvial-fan sequences with analysis of high-resolution topographic data: San Luis Valley, Colorado, USA: Geosphere, v. 14, no. 6, p. 1-18, https://doi.org/10.1130/GES01680.1.","productDescription":"18 p.","startPage":"1","endPage":"18","ipdsId":"IP-095218","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":468287,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges01680.1","text":"Publisher Index Page"},{"id":437711,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Q2BP9P","text":"USGS data release","linkHelpText":"U and Th isotope data for "Establishing chronologies for alluvial-fan sequences with analysis of high-resolution topographic data: San Luis Valley, Colorado, USA""},{"id":358813,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Luis Valley","volume":"14","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-24","publicationStatus":"PW","scienceBaseUri":"5bed4272e4b0b3fc5cf91c84","contributors":{"authors":[{"text":"Johnstone, Samuel 0000-0002-3945-2499","orcid":"https://orcid.org/0000-0002-3945-2499","contributorId":207545,"corporation":false,"usgs":true,"family":"Johnstone","given":"Samuel","email":"","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":749711,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hudson, Adam M. 0000-0002-3387-9838 ahudson@usgs.gov","orcid":"https://orcid.org/0000-0002-3387-9838","contributorId":195419,"corporation":false,"usgs":true,"family":"Hudson","given":"Adam","email":"ahudson@usgs.gov","middleInitial":"M.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":749712,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nicovich, Sylvia","contributorId":210054,"corporation":false,"usgs":false,"family":"Nicovich","given":"Sylvia","affiliations":[{"id":38060,"text":"Department of Earth Sciences, Montana State University, Bozeman, MT","active":true,"usgs":false}],"preferred":false,"id":749713,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ruleman, Chester A. 0000-0002-1503-4591 cruleman@usgs.gov","orcid":"https://orcid.org/0000-0002-1503-4591","contributorId":1264,"corporation":false,"usgs":true,"family":"Ruleman","given":"Chester","email":"cruleman@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":749714,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sare, Robert M.","contributorId":210055,"corporation":false,"usgs":false,"family":"Sare","given":"Robert","email":"","middleInitial":"M.","affiliations":[{"id":38061,"text":"Department of Geological Sciences, Stanford University, Stanford, CA","active":true,"usgs":false}],"preferred":false,"id":749715,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thompson, Ren A. 0000-0002-3044-3043","orcid":"https://orcid.org/0000-0002-3044-3043","contributorId":207982,"corporation":false,"usgs":true,"family":"Thompson","given":"Ren A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":749716,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70200586,"text":"70200586 - 2018 - Molecular systematics of sturgeon nucleocytoplasmic large DNA viruses","interactions":[],"lastModifiedDate":"2018-10-25T11:29:11","indexId":"70200586","displayToPublicDate":"2018-10-25T11:29:07","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2779,"text":"Molecular Phylogenetics and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Molecular systematics of sturgeon nucleocytoplasmic large DNA viruses","docAbstract":"Namao virus (NV) is a sturgeon nucleocytoplasmic large DNA virus (sNCLDV) that can cause a lethal disease of the integumentary system in lake sturgeon Acipenser fulvescens. As a group, the sNCLDV have not been assigned to any currently recognized taxonomic family of viruses. In this study, a data set of NV DNA sequences was generated and assembled as two non-overlapping contigs of 306,448 bp and then used to conduct a comprehensive systematics analysis using Bayesian inference of phylogeny for NV, other sNCLDV and representative members of six families of the NCLDV superfamily. The phylogeny of NV was reconstructed using protein homologues encoded by nine nucleocytoplasmic virus orthologous genes (NCVOGs): NCVOG0022 – mcp, NCVOG0038 – DNA polymerase B elongation subunit, NCVOG0076 – VV A18-type helicase, NCVOG0249 – VV A32-type ATPase, NCVOG0262 – AL2 VLTF3-like transcription factor, NCVOG0271 – RNA polymerase II subunit II, NCVOG0274 – RNA polymerase II subunit I, NCVOG0276 – ribonucleotide reductase small subunit and NCVOG1117 – mRNA capping enzyme. The accuracy of our phylogenetic method was evaluated using a combination of Bayesian statistical analysis and congruence analysis. Stable tree topologies were obtained with data sets differing in target molecule(s), sequence length and taxa. Congruent topologies were obtained in phylogenies constructed using individual protein data sets. The major capsid protein phylogeny inferred that ten representative sNCLDV form a monophyletic group comprised of four lineages within a polyphyletic Mimi-Phycodnaviridae group of taxa. Overall, the analyses revealed that Namao virus is a member of the Mimiviridae family with strong and consistent support for a clade containing NV and CroV as sister taxa.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ympev.2018.07.019","usgsCitation":"Clouthier, S., Anderson, E., Kurath, G., and Breyta, R., 2018, Molecular systematics of sturgeon nucleocytoplasmic large DNA viruses: Molecular Phylogenetics and Evolution, v. 128, p. 26-37, https://doi.org/10.1016/j.ympev.2018.07.019.","productDescription":"12 p.","startPage":"26","endPage":"37","ipdsId":"IP-095370","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":358800,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"128","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10a916e4b034bf6a7e4f76","contributors":{"authors":[{"text":"Clouthier, Sharon","contributorId":210029,"corporation":false,"usgs":false,"family":"Clouthier","given":"Sharon","affiliations":[{"id":38053,"text":"Fisheries & Oceans Canada, Freshwater Institute, 501 University Crescent, Winnipeg, Manitoba R3T 2N6, Canada","active":true,"usgs":false}],"preferred":false,"id":749647,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Eric","contributorId":168940,"corporation":false,"usgs":false,"family":"Anderson","given":"Eric","affiliations":[],"preferred":false,"id":749648,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kurath, Gael 0000-0003-3294-560X gkurath@usgs.gov","orcid":"https://orcid.org/0000-0003-3294-560X","contributorId":2629,"corporation":false,"usgs":true,"family":"Kurath","given":"Gael","email":"gkurath@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":749649,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Breyta, Rachel","contributorId":150355,"corporation":false,"usgs":false,"family":"Breyta","given":"Rachel","affiliations":[],"preferred":false,"id":749650,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70223286,"text":"70223286 - 2018 - Evaluating inter-rater reliability and statistical power of vegetation measures assessing deer impact","interactions":[],"lastModifiedDate":"2021-08-20T14:43:09.267987","indexId":"70223286","displayToPublicDate":"2018-10-25T09:36:25","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1689,"text":"Forests","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating inter-rater reliability and statistical power of vegetation measures assessing deer impact","docAbstract":"Long-term vegetation monitoring projects are often used to evaluate how plant communities change through time in response to some external influence. Here, we evaluate the efficacy of vegetation monitoring to consistently detect changes in white-tailed deer browsing effects. Specifically, we compared inter-rater reliability (Cohen’s κ and Lin’s concordance correlation coefficient) between two identically trained field crews for several plant metrics used by Pennsylvania state agencies to monitor deer browsing impact. Additionally, we conducted a power analysis to determine the effect of sampling scale (1/2500th or 1/750th ha plots) on the ability to detect changes in tree seedling stem counts over time. Inter-rater reliability across sampling crews was substantial for most metrics based on direct measurements, while the observational based Deer Impact Index (DII) had only moderate inter-rater reliability. The smaller, 1/2500th ha sampling scale resulted in higher statistical power to detect changes in tree seedling stem counts due to reduced observer error. Overall, this study indicates that extensive training on plant identification, project protocols, and consistent data collection methods can result in reliable vegetation metrics useful for tracking understory responses to white-tailed deer browsing. Smaller sampling scales and objective plant measures (i.e., seedling counts, species richness) improve inter-rater reliability over subjective measures of deer impact (i.e., DII). However, considering objective plant measures when making a subjective assessment regarding deer browsing effects may also improve DII inter-rater reliability.
","language":"English","publisher":"MDPI","doi":"10.3390/f9110669","usgsCitation":"Begley-Miller, D.R., Diefenbach, D.R., McDill, M.E., Rosenberry, C., and Just, E.H., 2018, Evaluating inter-rater reliability and statistical power of vegetation measures assessing deer impact: Forests, v. 9, no. 11, 669, 17 p., https://doi.org/10.3390/f9110669.","productDescription":"669, 17 p.","ipdsId":"IP-101441","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468290,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/f9110669","text":"Publisher Index Page"},{"id":388235,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Bald Eagle State Forest, Rothrock State Forest, Susquehannock State Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.14437866210938,\n 41.49006348843993\n ],\n [\n -77.47833251953125,\n 41.49006348843993\n ],\n [\n -77.47833251953125,\n 41.840920397579936\n ],\n [\n -78.14437866210938,\n 41.840920397579936\n ],\n [\n -78.14437866210938,\n 41.49006348843993\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.25698852539062,\n 40.447992135544304\n ],\n [\n -76.93862915039062,\n 40.447992135544304\n ],\n [\n -76.93862915039062,\n 41.10212132036491\n ],\n [\n -78.25698852539062,\n 41.10212132036491\n ],\n [\n -78.25698852539062,\n 40.447992135544304\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"11","noUsgsAuthors":false,"publicationDate":"2018-10-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Begley-Miller, Danielle R.","contributorId":264498,"corporation":false,"usgs":false,"family":"Begley-Miller","given":"Danielle","email":"","middleInitial":"R.","affiliations":[{"id":54482,"text":"Teatown Lake Reservation","active":true,"usgs":false}],"preferred":false,"id":821615,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diefenbach, Duane R. 0000-0001-5111-1147 drd11@usgs.gov","orcid":"https://orcid.org/0000-0001-5111-1147","contributorId":5235,"corporation":false,"usgs":true,"family":"Diefenbach","given":"Duane","email":"drd11@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":821614,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McDill, Marc E.","contributorId":264499,"corporation":false,"usgs":false,"family":"McDill","given":"Marc","email":"","middleInitial":"E.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":821616,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rosenberry, Christopher S.","contributorId":264500,"corporation":false,"usgs":false,"family":"Rosenberry","given":"Christopher S.","affiliations":[{"id":12891,"text":"Pennsylvania Game Commission","active":true,"usgs":false}],"preferred":false,"id":821617,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Just, Emily H.","contributorId":264501,"corporation":false,"usgs":false,"family":"Just","given":"Emily","email":"","middleInitial":"H.","affiliations":[{"id":37212,"text":"Pennsylvania Department of Conservation and Natural Resources","active":true,"usgs":false}],"preferred":false,"id":821618,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70200520,"text":"ofr20181172 - 2018 - Preliminary peak stage and streamflow data for selected U.S. Geological Survey streamgaging stations in North and South Carolina for flooding following Hurricane Florence, September 2018","interactions":[],"lastModifiedDate":"2018-10-25T14:53:44","indexId":"ofr20181172","displayToPublicDate":"2018-10-24T16:00:00","publicationYear":"2018","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":"2018-1172","title":"Preliminary peak stage and streamflow data for selected U.S. Geological Survey streamgaging stations in North and South Carolina for flooding following Hurricane Florence, September 2018","docAbstract":"Hurricane Florence made landfall as a Category 1 hurricane at Wrightsville Beach, North Carolina, shortly after dawn on September 14, 2018. Once over land, the forward motion of the hurricane slowed to about 2 to 3 miles per hour. Over the next several days, the hurricane delivered historic amounts of rainfall across North and South Carolina, causing substantial flooding in many communities across both States. For the Hurricane Florence event, a new record rainfall total of 35.93 inches was set in Elizabethtown, N.C. Many other locations throughout North Carolina set new records for rainfall, exceeding the previous State record for rainfall from a tropical system of 24.06 inches, which was set over a 4-day period in Southport, N.C., during Hurricane Floyd in 1999. In South Carolina, the highest reported total rainfall of 23.63 inches was in Loris, S.C., which was the highest total rainfall in South Carolina from a tropical cyclone, replacing the previous total of 17.45 inches associated with Tropical Storm Beryl in 1994. During the October 2015 flood in South Carolina, a 4-day total rainfall of 26.88 inches was recorded in Mount Pleasant; however, because that total rainfall was a combination of a tropical storm system and another front that was centered over the State, it is not considered the largest rainfall event from a tropical storm.
Peak streamflow and stage data at 84 U.S. Geological Survey streamflow gaging stations (referred to hereafter as streamgages) in North and South Carolina with at least 10 years of systematic record and for which the flooding following Hurricane Florence resulted in a peak in the top 5 for the period of record are included in this report. New peak streamflows of record were recorded at 18 sites in North Carolina and 10 sites in South Carolina. Another 49 streamgages recorded peak streamflows in the top 5 for their record (45 in North Carolina and 4 in South Carolina). Peak streamflow data following Hurricane Florence were not available for three additional streamgages prior to the publication of this report. Of those three streamgages, two recorded a new peak stage of record and one recorded the second highest peak stage of record. An additional four stage-only streamgages having at least 10 years of systematic record also had new peak stages (also referred to as gage height) of record. For 11 of the 28 streamgages for which the September 2018 peak streamflow was the peak of record, the October 2016 peak following Hurricane Matthew was the second largest peak, and for another four streamgages the September 1999 peak following Hurricane Floyd was the second largest peak.
For the 28 streamgages for which a new peak streamflow of record was recorded, a flood-frequency analysis was done using available systematic record through September 2017 and the peak streamflow from the Hurricane Florence event. Of the 28 streamgages analyzed, the estimated annual exceedance probability for the Hurricane Florence peak streamflow at 9 of the streamgages was less than 0.2 percent, which in terms of recurrence intervals is greater than a 500-year flood event. At three streamgages, the estimated annual exceedance probability was equal to 0.2 percent, and at six streamgages, it was between 0.2 and 1 percent (between a 500- and 100-year recurrence interval, respectively). For the remaining 10 streamgages, the estimated annual exceedance probability was between 1.5 and 7.1 percent, which in terms of recurrence intervals is approximately a 67- to 14-year event, respectively.
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Carolina\",\"nation\":\"USA \"}}]}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
The Mars Global Digital Dune Database (MGD3) is an online repository that has catalogued dune fields larger than 1 km2 located between latitudes 90° N. and 90° S. The work presented here expands upon previous MGD3 open-file reports, with a new emphasis upon characterizing dune fields through composition, stability, and thermal inertia. Included in this latest addition is a detailed compositional analysis and the associated observational data from Mars Global Surveyor (MGS) Thermal Emission Spectrometer (TES) for dune fields 300 km2 or larger; a near-global dune stability assessment; Mars Odyssey (MO1) Thermal Emission Imaging System (THEMIS) apparent thermal inertia values; and vertical near-surface thermophysical heterogeneities determined by fitting a two-layer thermal model to observed temperatures. These additional datasets are divided into two workbooks: equatorial and south polar regions. A detailed description for the layout of these workbooks can be found in the corresponding metadata document. The continuing goal of the MGD3 is to provide a reliable and multifaceted repository of data for Mars’ dunes, with the intention that such data be easily accessible and useful to future research.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181164","usgsCitation":"Gullikson, A.L., Hayward, R.K., Titus, T.N., Charles, H., Fenton, L.K., Hoover, R., and Putzig, N.E., 2018, Mars global digital dune database (MGD3)—Composition, stability, and thermal inertia: U.S. Geological Survey Open-File Report 2018–1164, 17 p., https://doi.org/10.3133/ofr20181164.","productDescription":"Report: vi, 17 p.; Appendix 1; Dune Database","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-097409","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":358707,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1164/coverthb.jpg"},{"id":358708,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1164/ofr20181164.pdf","text":"Report","size":"2.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1164"},{"id":358709,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1164/ofr20181164_appendix.pdf","text":"Appendix 1","size":"603 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1164 Appendix","linkHelpText":"Graphs pertaining to the spectral glitch"},{"id":358710,"rank":4,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2018/1164/ofr20181164_dunedatabase.zip","text":"Dune Database","size":"3 MB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2018-1164 Database","linkHelpText":"Equatorial and South Polar Dune Databases and metadata"},{"id":358712,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20101170","text":"Open-File Report 2010–1170 —","linkHelpText":"Mars Global Digital Dune Database: MC–1"},{"id":358711,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20071158","text":"Open-File Report 2007–1158 —","linkHelpText":"Mars Global Digital Dune Database: MC2–MC29"},{"id":358713,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20121259","text":"Open-File Report 2012–1259 —","linkHelpText":"Mars Global Digital Dune Database: MC–30"}],"contact":"Contact Astrogeology Research Program staff
Astrogeology Science Center
U.S. Geological Survey
2255 N. Gemini Dr.
Flagstaff, AZ 86001
The potential effect of cemetery leachate on groundwater quality in the United States has rarely been studied. Nutrients and other constituents associated with decomposition and burial processes (such as embalming) have the potential to reach shallow groundwater and could affect nearby drinking-water sources. The objective of this preliminary investigation was to evaluate the potential effect of cemetery leachate on shallow groundwater quality near Mt. Hope Cemetery in Ingham County, Lansing, Michigan, which is within the Well-head Protection Area for the City of Lansing. The constituents measured in this study include nutrients, trace metals, formaldehyde, fecal indicator bacteria, bacterial pathogen genes, contaminants of emerging concern (including pharmaceuticals, personal care products, and wastewater indicator compounds), and age-dating compounds. Three monitoring wells were installed 7 to 12 feet below land surface downgradient from the cemetery and sampled quarterly for 1 year. A fourth well (Fenner) was sampled to determine groundwater conditions outside the potential effects of cemetery leachate; samples from this well were collected near the water table.
Nitrogen and phosphorus compounds were present at higher concentrations in two of the three monitoring wells (wells C1 and C3) than in the Fenner well. Formaldehyde and pharmaceuticals were not detected in any of the wells; however, several trace metals, including arsenic, manganese, and aluminum, were present in high concentrations, with arsenic concentrations typically exceeding the U.S. Environmental Protection Agency (EPA) drinking-water standard. Several wastewater indicator compounds, including atrazine, phenol, p-cresol, camphor, and skatole, were detected in the monitoring wells. Microbial data indicate the presence of staphylococci, enterococci, and Escherichia coli (E. coli), with the highest concentrations being measured in the same two monitoring wells that exhibited elevated concentrations of nutrients in the groundwater (wells C1 and C3). Several bacterial pathogen genes were detected, including several Enterococcus species (spp.)—vanB (vancomycin-resistant enterococci), shiga-toxin-producing E. coli genes (including eaeA [attachment virulence trait] and stx1 [moderate toxin]), and the E. coli 16s ribosomal RNA (rDNA) gene ( E. coli species marker). These results were similar to results of studies conducted in Canada, Australia, and the United Kingdom, in which concentrations of bacteria, metals, and nutrients were elevated in groundwater near cemeteries.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185120","collaboration":"Prepared in cooperation with the Lansing Board of Water and Light and the Lansing Wellhead Protection Team","usgsCitation":"Brennan, A.K., Givens, C.E., Prokopec, J.G., and Hoard, C.J., 2018, Preliminary investigation of groundwater quality near a Michigan cemetery, 2016–17: U.S. Geological Survey Scientific Investigations Report 2018–5120, 23 p., https://doi.org/10.3133/sir20185120.","productDescription":"vi, 23 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-096238","costCenters":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":358631,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5120/sir20185120.pdf","text":"Report","size":"17.8 MB","description":"SIR 2018-5120"},{"id":358630,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5120/coverthb.jpg"}],"country":"United States","state":"Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.52966690063477,\n 42.70460970722399\n ],\n [\n -84.51863765716553,\n 42.70460970722399\n ],\n [\n -84.51863765716553,\n 42.711862740860546\n ],\n [\n -84.52966690063477,\n 42.711862740860546\n ],\n [\n -84.52966690063477,\n 42.70460970722399\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Upper Midwest Water Science Center
U.S. Geological Survey
6520 Mercantile Way, Suite 5
Lansing, MI 48911
Characterization of the subsurface thermal regime is critical for understanding many facets of the petroleum system, from thermal maturation of organic-rich source rocks to thermal preservation and non-degradation of hydrocarbon accumulations. On a broad scale, paleo-heatflow has been mapped for the North American continent (Blackwell and Richards, 2004) as well as the contiguous United States (Blackwell et al., 2011). However, in situ reservoir temperature is a fundamental property (Cooper and Jones, 1959) that is difficult to accurately measure in the subsurface (Deming, 1989). Previous work has described the thermal regime of the offshore U.S. Gulf of Mexico Basin (Waples et al., 2004; Forrest et al., 2005; Nagihara and Jones, 2005; Husson et al., 2008); however, due to the lack of an applicable bottomhole temperature (BHT) correction method, virgin rock temperatures of the onshore portion of the basin remains largely uncharacterized in a regional or subregional context.
The abundance of BHT measurements offers a useful way to characterize the subsurface thermal environment, provided that they are corrected to reflect the reservoir temperature. This study develops BHT correction methods that are specifically calibrated for the onshore U.S. Gulf of Mexico Basin. These BHT corrections are empirically derived and are based on a newly compiled database of temperatures obtained from BHT wireline measurements and, to a lesser extent, from drill stem test (DST) data. The results of this investigation provide a unified BHT correction methodology for the onshore U.S. Gulf of Mexico Basin as well as provide 12 distinct BHT correction equations for each of the 12 physiographic provinces within the onshore Gulf Coast region. This study also characterizes the geothermal gradient regime across the onshore U.S. Gulf Coast, which ranges from 1.89ºF/100 ft in Sabine Uplift area to 1.39ºF/100 ft in the Southern Louisiana Salt Basin.
","language":"English","publisher":"Gulf Coast Association of Geological Societies","usgsCitation":"Burke, L.A., Pearson, O.N., Kinney, S.A., and Pitman, J.K., 2018, Methodology for correcting bottomhole temperatures acquired from wireline logging measurements in the onshore U.S. Gulf of Mexico Basin to characterize the thermal regime of total petroleum systems: GCAGS Journal, v. 7, p. 93-106.","productDescription":"14 p.","startPage":"93","endPage":"106","ipdsId":"IP-088716","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":358667,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":358638,"type":{"id":15,"text":"Index Page"},"url":"https://www.gcags.org/Journal/GCAGS.Journal.Vol.7.html"}],"country":"United States","otherGeospatial":"Gulf of Mexico Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -101.00830078125,\n 25.720735134412106\n ],\n [\n -87.978515625,\n 25.720735134412106\n ],\n [\n -87.978515625,\n 33.284619968887675\n ],\n [\n -101.00830078125,\n 33.284619968887675\n ],\n [\n -101.00830078125,\n 25.720735134412106\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10a917e4b034bf6a7e4f8c","contributors":{"authors":[{"text":"Burke, Lauri A. 0000-0002-2035-8048 lburke@usgs.gov","orcid":"https://orcid.org/0000-0002-2035-8048","contributorId":3859,"corporation":false,"usgs":true,"family":"Burke","given":"Lauri","email":"lburke@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":749389,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pearson, Ofori N. 0000-0002-9550-1128 opearson@usgs.gov","orcid":"https://orcid.org/0000-0002-9550-1128","contributorId":1680,"corporation":false,"usgs":true,"family":"Pearson","given":"Ofori","email":"opearson@usgs.gov","middleInitial":"N.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":749390,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kinney, Scott A. 0000-0001-5008-5813 skinney@usgs.gov","orcid":"https://orcid.org/0000-0001-5008-5813","contributorId":1395,"corporation":false,"usgs":true,"family":"Kinney","given":"Scott","email":"skinney@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":749391,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pitman, Janet K. 0000-0002-0441-779X jpitman@usgs.gov","orcid":"https://orcid.org/0000-0002-0441-779X","contributorId":767,"corporation":false,"usgs":true,"family":"Pitman","given":"Janet","email":"jpitman@usgs.gov","middleInitial":"K.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":749392,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70200726,"text":"70200726 - 2018 - Integrating encounter theory with decision analysis to evaluate collision risk and determine optimal protection zones for wildlife","interactions":[],"lastModifiedDate":"2019-05-29T09:35:51","indexId":"70200726","displayToPublicDate":"2018-10-23T09:59:35","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Integrating encounter theory with decision analysis to evaluate collision risk and determine optimal protection zones for wildlife","docAbstract":"1.Better understanding human‐wildlife interactions and their links with management can help improve the design of wildlife protection zones. One example is the problem of wildlife collisions with vehicles or human‐built structures (e.g. power lines, wind farms). In fact, collisions between marine wildlife and watercraft are among the major threats faced by several endangered species of marine mammals. Natural resource managers are therefore interested in finding cost‐effective solutions to mitigate these threats.
2.We combined abundance estimators with encounter rate theory to estimate relative lethal collision risk of the Florida manatee (Trichechus manatus latirostris) from watercraft. We first modeled seasonal abundance of watercraft and manatees using a Bayesian analysis of aerial survey count data. We then modeled relative lethal collision risk in space and across seasons. Finally, we applied decision analysis and Linear Integer Programming to determine the optimal design of speed zones in terms of relative risk to manatees and costs to waterway users. We used a Pareto efficient frontier approach to evaluate the performance of alternative zones, which included additional practical considerations (e.g. spatial aggregation of speed zones) in relation to the optimal zone configurations.
3.Under the various relationships for probability of death given strike speed that we considered, the current speed zones reduced the relative lethal collision risk by an average of 51.5% to 70% compared to the scenario in which all speed regulations were removed (i.e. the no‐protection scenario). We identified optimal zones and near‐optimal zones with additional management considerations that improved upon the current zones in terms of cost or relative risk.
4.Policy Implications: Our analytical framework combines encounter rate theory and decision analysis to quantify the effectiveness of speed zones protecting manatees while accounting for uncertainty. Our approach can be used to optimize the design of protection zones intended to reduce conflicts between human waterborne activity and marine mammals. This framework could be extended to address many other problems of human‐wildlife interactions, such as the optimal placement of wind farms to minimize collisions with wildlife or the optimal allocation of ranger effort to mitigate poaching threats.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2664.13290","usgsCitation":"Udell, B., Martin, J., Fletcher, R., Bonneau, M., Edwards, H.H., Gowan, T., Hardy, S.K., Gurarie, E., Calleson, C., and Deutsch, C., 2018, Integrating encounter theory with decision analysis to evaluate collision risk and determine optimal protection zones for wildlife: Journal of Applied Ecology, v. 56, no. 5, p. 1050-1062, https://doi.org/10.1111/1365-2664.13290.","productDescription":"13 p.","startPage":"1050","endPage":"1062","ipdsId":"IP-084422","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":460829,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.13290","text":"Publisher Index Page"},{"id":358933,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"56","issue":"5","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-20","publicationStatus":"PW","scienceBaseUri":"5bee93e4e4b08f163c24a1b9","contributors":{"authors":[{"text":"Udell, B.J.","contributorId":210251,"corporation":false,"usgs":false,"family":"Udell","given":"B.J.","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":750250,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Julien 0000-0002-7375-129X julienmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-7375-129X","contributorId":5785,"corporation":false,"usgs":true,"family":"Martin","given":"Julien","email":"julienmartin@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":750249,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fletcher, R.J.","contributorId":210252,"corporation":false,"usgs":false,"family":"Fletcher","given":"R.J.","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":750251,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bonneau, Mathieu","contributorId":150041,"corporation":false,"usgs":false,"family":"Bonneau","given":"Mathieu","email":"","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":750252,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Edwards, Holly H.","contributorId":66419,"corporation":false,"usgs":true,"family":"Edwards","given":"Holly","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":751323,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gowan, T.","contributorId":210253,"corporation":false,"usgs":false,"family":"Gowan","given":"T.","email":"","affiliations":[{"id":35758,"text":"FWC","active":true,"usgs":false}],"preferred":false,"id":750254,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hardy, Stacie K.","contributorId":210254,"corporation":false,"usgs":false,"family":"Hardy","given":"Stacie","email":"","middleInitial":"K.","affiliations":[{"id":35758,"text":"FWC","active":true,"usgs":false}],"preferred":false,"id":750255,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gurarie, E.","contributorId":210255,"corporation":false,"usgs":false,"family":"Gurarie","given":"E.","affiliations":[{"id":38092,"text":"UMD","active":true,"usgs":false}],"preferred":false,"id":750256,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Calleson, C.S.","contributorId":210257,"corporation":false,"usgs":false,"family":"Calleson","given":"C.S.","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":750258,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Deutsch, C.J.","contributorId":210256,"corporation":false,"usgs":false,"family":"Deutsch","given":"C.J.","email":"","affiliations":[{"id":35758,"text":"FWC","active":true,"usgs":false}],"preferred":false,"id":750257,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70200492,"text":"70200492 - 2018 - Detecting snow depth change in avalanche path starting zones using uninhabited aerial systems and structure from motion photogrammetry","interactions":[],"lastModifiedDate":"2018-10-23T15:17:46","indexId":"70200492","displayToPublicDate":"2018-10-22T15:17:31","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Detecting snow depth change in avalanche path starting zones using uninhabited aerial systems and structure from motion photogrammetry","docAbstract":"Understanding snow depth distribution and change is useful for avalanche forecasting and mitigation, runoff forecasting, and infrastructure planning. Advances in remote sensing are improving the ability to collect snow depth measurements. The development of structure from motion (SfM), a photogrammetry technique, combined with the use of uninhabited aerial systems (UASs) allows for high resolution mapping of snow depth over complex terrain. The primary objective of this study was to determine the feasibility and efficacy of SfM to examine snow depth distribution and variability in complex terrain such as avalanche path starting zones at multiple times during the season. We used a 3DR Solo quadcopter UAS equipped with a Ricoh GR II camera at 90 m above ground level to acquire images of one avalanche starting zone in northwest Montana, USA. We also placed 4 to 13 ground control points (GCPs) around the area of interest to avoid traveling in steep, avalanche terrain. Ground control measurements resulted in 5 to10 cm horizontal accuracy and 5 to 15 cm vertical accuracy for 90 to 95 % of the collected points (a minimum of 100 points collected at each GCP). In-situ measurements of snow depth difference between sampling days ranged from 20 to 60 cm. We processed the images to create point clouds and digital surface models (DSMs). The resolution of the resultant DSMs was approximately 5 cm. Preliminary DSM and point cloud differencing efforts suggest relative change detection of snow depth at 5 to 15 cm resolution. The use of these relatively low cost and easily accessible methods of snow depth data collection will enhance accuracy of snow depth change estimates in starting zones and can be used to inform avalanche forecasting and mitigation efforts.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the International Snow Science Workshop","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"International Snow Science Workshop","conferenceLocation":"Innsbruck, Austria","language":"English","usgsCitation":"Peitzsch, E.H., Fagre, D.B., Hendrikx, J., and Birkeland, K.W., 2018, Detecting snow depth change in avalanche path starting zones using uninhabited aerial systems and structure from motion photogrammetry, in Proceedings of the International Snow Science Workshop, Innsbruck, Austria, p. 408-412.","productDescription":"5 p.","startPage":"408","endPage":"412","ipdsId":"IP-100777","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":358692,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":358592,"type":{"id":11,"text":"Document"},"url":"https://arc.lib.montana.edu/snow-science/objects/ISSW2018_P04.16.pdf"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10a919e4b034bf6a7e4f9f","contributors":{"authors":[{"text":"Peitzsch, Erich H. 0000-0001-7624-0455 epeitzsch@usgs.gov","orcid":"https://orcid.org/0000-0001-7624-0455","contributorId":3786,"corporation":false,"usgs":true,"family":"Peitzsch","given":"Erich","email":"epeitzsch@usgs.gov","middleInitial":"H.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":749149,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fagre, Daniel B. 0000-0001-8552-9461 dan_fagre@usgs.gov","orcid":"https://orcid.org/0000-0001-8552-9461","contributorId":2036,"corporation":false,"usgs":true,"family":"Fagre","given":"Daniel","email":"dan_fagre@usgs.gov","middleInitial":"B.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":749150,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hendrikx, Jordy","contributorId":166967,"corporation":false,"usgs":false,"family":"Hendrikx","given":"Jordy","affiliations":[{"id":13628,"text":"Department of Earth Sciences, P.O. Box 173480, Montana State University, Bozeman, MT, USA. 59717.","active":true,"usgs":false}],"preferred":false,"id":749151,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Birkeland, Karl W.","contributorId":209943,"corporation":false,"usgs":false,"family":"Birkeland","given":"Karl","email":"","middleInitial":"W.","affiliations":[{"id":38033,"text":"U.S.D.A. Forest Service National Avalanche Center, Bozeman, Montana, USA","active":true,"usgs":false}],"preferred":false,"id":749152,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70199078,"text":"ofr20181144 - 2018 - Emigration and transportation stress of juvenile Chinook salmon relative to their reintroduction upriver of Shasta Dam, California, 2017–18","interactions":[],"lastModifiedDate":"2018-10-23T15:08:27","indexId":"ofr20181144","displayToPublicDate":"2018-10-22T14:14:12","publicationYear":"2018","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":"2018-1144","title":"Emigration and transportation stress of juvenile Chinook salmon relative to their reintroduction upriver of Shasta Dam, California, 2017–18","docAbstract":"The Bureau of Reclamation supports the Shasta Dam Fish Passage Evaluation (SDFPE; Yip, 2015) program, and in 2016 set out to determine the feasibility of reintroducing winter-run and spring-run Chinook salmon (Oncorhynchus tshawytscha) and steelhead (O. mykiss) to tributaries upstream of Shasta Dam. Ideally, reintroduction strategy includes trapping naturally produced downstream-migrating juvenile fish at the head of Lake Shasta (upstream of Shasta Dam), or near the mouth of the tributaries where they flow into the lake. However, evaluations of a juvenile collection system in one of the target tributaries (McCloud River) was delayed because of concerns about the fish source to be used as surrogate for winter-run Chinook salmon and the location and impact of the trap-and-haul operations.
In 2017, the U.S. Geological Survey (USGS) was contracted to evaluate the reintroduction of winter-run salmon into tributaries upstream of Shasta Dam, and the McCloud River, having the most suitable spawning and rearing habitat for salmon adjacent to Shasta Reservoir (Lake) was the chosen study area. The first stage of the project was to assess the feasibility using a head-of-reservoir fish trap to collect juvenile salmon, but these efforts were delayed, so efforts were used to assess how juvenile Chinook salmon would distribute within the McCloud River and Shasta Reservoir and help determine the feasibility of collecting fish at Shasta Dam. Importantly, NOAA fisheries was also conducting an acoustic telemetry project through the Sacramento River, and they provided the additional acoustic detection data on our tagged fish to San Francisco Bay. These data were collected beyond original study goals, but added a large contribution to the findings and inferences from this study.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181144","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Adams, N.S., Liedtke, T.L., Plumb, J.M., Hansen, A.C., Evans, S.D., and Weiland., L.K., 2018, Emigration and transportation stress of juvenile Chinook salmon relative to their reintroduction upriver of Shasta Dam, California, 2017–18: U.S. Geological Survey Open-File Report 2018-1144, 60 p., https://doi.org/10.3133/ofr20181144.","productDescription":"vi, 60 p.","onlineOnly":"Y","ipdsId":"IP-098563","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":358642,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1144/ofr20181144.pdf","text":"Report","size":"8.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1144"},{"id":358641,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1144/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Shasta Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.684326171875,\n 37.6968609874419\n ],\n [\n -121.3604736328125,\n 37.6968609874419\n ],\n [\n -121.3604736328125,\n 41.017210578228436\n ],\n [\n -122.684326171875,\n 41.017210578228436\n ],\n [\n -122.684326171875,\n 37.6968609874419\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
Data collected from April 2014 through September 2016 were used to assess geomorphic characteristics and geomorphic changes over time in a selected reach of Tenmile Creek, a small rural watershed near Clarksburg, Maryland. Longitudinal profiles of the channel bed, water surface, and bank features were developed from field surveys. Changes in cross-section geometry between field surveys were documented. Grain-size distributions for the channel bed were developed from pebble counts. Continuous-record streamflow and precipitation data were also collected in the Tenmile Creek watershed and used to supplement the geomorphic analyses.
The Rosgen system of stream classification was used to classify the stream channel according to morphological measurements of slope, entrenchment ratio, width-to-depth ratio, sinuosity, and median particle diameter of the channel materials. Boundary shear stress near the U.S. Geological Survey (USGS) streamflow-gaging station was assessed by using hydraulic variables computed from the cross-section surveys and slope measurements derived from crest-stage gages and temporary data loggers installed along the study reach.
Analysis of the longitudinal profiles indicated relatively small changes in the percentage and distribution of riffles, pools, and runs in the study reach between April 2014 and March 2015. More noticeable changes were observed during surveys conducted in March 2016 and September 2016. The channel-bed slope showed a net reduction over time from 0.0072 to 0.0040 feet per foot (ft/ft). The low-flow water-surface slope also showed a net reduction over time from 0.0065 to 0.0045 ft/ft. Net aggradation in the lower section of the study reach combined with net degradation in the upper section of the study reach contributed to the net reduction in channel-bed and water-surface slope. The large storm and resulting flood on July 30, 2016 was a major factor in observed changes in the longitudinal profiles between the March 2016 and September 2016 surveys.
Comparison of data from the cross-sectional surveys indicated vertical changes in all cross sections, with more extreme changes observed between surveys in the lower section of the study reach due in part to alternating periods of net storage and transport of sand. Lateral erosion was not a major factor in the study reach, with the exception of cross section Dd, where considerable lateral erosion was documented during the study period. The flood that resulted from the large storm on July 30, 2016 was a major factor in some of the vertical changes observed in the channel bed of the study reach cross sections.
Particle-size analyses of the channel bed from pebble counts indicated median particle diameters ranging from 15.5 millimeters (mm) to 23.1 mm, which is characterized as medium to coarse gravel. Sand percentages ranging from 3.4 percent to 16.4 percent of the total counts were observed over time. Net increases in storage of fine sediment in the reach were observed between April 2014 and March 2016, and a considerable reduction in storage was observed between March 2016 and September 2016.
The Tenmile Creek stream channel was classified as a C4 channel, based on morphological descriptions from the Rosgen system of stream classification. The C4 classification describes a single-thread channel with a slight entrenchment ratio; a moderate to high width-to-depth ratio; moderate to high sinuosity; a water-surface slope of less than 2 percent; and a median particle diameter in the gravel range of 2 to 64 mm.
The analysis of boundary shear stress indicated a range of 0.35 to 1.18 pounds per square foot for instantaneous streamflow ranging from 79 to 2,860 cubic feet per second during the study period. The relation between discharge and boundary shear stress for Tenmile Creek was compared to similar relations that were previously developed for Minebank Run, a small, urban watershed in the eastern section of the Piedmont Physiographic Province in Baltimore County, Md. that was physically restored during 2004–05. The comparison indicated a much flatter slope in the relation for Minebank Run in both its unrestored and restored conditions. This difference in the relations indicates that the erosive power in the urban watershed of Minebank Run is much more sensitive to increases in discharge magnitude than in the non-urban watershed of Tenmile Creek.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185098","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency and the Montgomery County Department of Environmental Protection","usgsCitation":"Doheny, E.J., and Baker, S.M., 2018, Geomorphic characteristics of Tenmile Creek, Montgomery County, Maryland, 2014–16: U.S. Geological Survey Scientific Investigations Report 2018–5098, 34 p., https://doi.org/10.3133/sir20185098.","productDescription":"Report: viii, 34 p.; Data release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-090630","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":437714,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7WW7GKQ","text":"USGS data release","linkHelpText":"Datasets from an assessment of geomorphic characteristics of Tenmile Creek, Montgomery County, Maryland, 2014-16"},{"id":358408,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5098/coverthb.jpg"},{"id":358410,"rank":3,"type":{"id":30,"text":"Data Release"},"url":" https://doi.org/10.5066/F7WW7GKQ","text":"USGS data release","description":"USGS data release","linkHelpText":"Datasets from an assessment of geomorphic characteristics of Tenmile Creek, Montgomery County, Maryland, 2014–16"},{"id":358409,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5098/sir20185098.pdf","text":"Report","size":"17.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5098"}],"country":"United States","state":"Maryland","county":"Montgomery County","otherGeospatial":"Tenmile Creek watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.3356,\n 39.2075\n ],\n [\n -77.2786,\n 39.2075\n ],\n [\n -77.2786,\n 39.2492\n ],\n [\n -77.3356,\n 39.2492\n ],\n [\n -77.3356,\n 39.2075\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, MD-DE-DC Water Science Center
U.S. Geological Survey
5522 Research Park Drive
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An earthquake early warning (EEW) system, ShakeAlert, is under development for the West Coast of the United States. This system currently uses the first few seconds of waveforms recorded by seismic instrumentation to rapidly characterize earthquake magnitude, location, and origin time; ShakeAlert recently added a seismic line source algorithm. For large to great earthquakes, magnitudes estimated from the earliest seismic data alone generally saturate. Real‐time Global Navigation Satellite System (GNSS) data can directly measure large displacements, enabling accurate magnitude estimates for
Study Region
This study region encompasses the Transboundary San Pedro and Santa Cruz aquifers which are shared between the states of Sonora (Mexico) and Arizona (US). Special regional considerations include a semi-arid climate, basin-fill aquifers with predominantly montane recharge areas, economic drivers in the mining, trade, and military sectors, groundwater-dependent cities with expanding cones of depression, interbasin groundwater transfers, ground- and surface-water contamination, and protected aquatic and riparian habitats that act as significant migration corridors for hundreds of species, including some that are threatened and endangered.
Study Focus
We focus on lessons learned from the hydrologic assessment of the Transboundary San Pedro and Santa Cruz aquifers. We conducted the work, in two phases: (1) laying the groundwork and (2) implementation. The “laying the groundwork” phase consisted of binational meetings with stakeholders and key actors (agencies and individuals), and the development of an understanding of the physical, institutional, historical, and socio-political context. This led to signing of the binational Transboundary Aquifer Assessment Program (TAAP) agreement in 2009 and detailed the process for cooperation and coordination in the assessment of shared aquifers. The implementation phase began with an agreement to proceed with the study of four “focus” aquifers (Santa Cruz, San Pedro, Mesilla (Conejos-Médanos in Mexico), and Hueco Bolson (Bolsón del Hueco in Mexico)) and development of associated technical teams. Though we do include a brief discussion of the lessons learned from the physical science portion of the study, the results have been described and published elsewhere. The bulk of the paper instead focuses on the findings and lessons learned from the integration of social-science perspectives into a largely physical-science based program, since there is a growing recognition of the need for this type of approach especially in the management and assessment of transboundary aquifers.
New Hydrological Insights for the Region
The Sonora-Arizona effort succeeded because both countries were adequately represented, and because of flexibility of skills and ability of teams comprising both university and government scientists. Teams included social and earth scientists. Including the social sciences was critical to research design and implementation, and to addressing the cultural, institutional, and socio-political contexts of transboundary aquifer assessment. Significant components of the continuing implementation phase include strategic planning, data compilation and analysis, cross-border integration of datasets, geophysical and geochemical surveys, and internal, peer, and stakeholder engagement.
Capture-recapture methods are commonly used to estimate abundance and density of wild animal populations. Although a variety of sophisticated analytical techniques are available to evaluate capture-recapture data, vertebrate monitoring programs often lack the resources (e.g., time, personnel, and/or analytical expertise) to apply these methods. As an alternative, simple population indices, such as counts of unique individuals, may provide sufficient information to detect meaningful changes in population size. In this study we investigated whether a population index, easily generated from mark-recapture data under all conditions, might be used to provide valid ecological information for managers interested in long-term population trends of deer mice (Peromyscus maniculatus) on the California Channel Islands. In practice, determining the efficacy of estimating abundance from mark-recapture data and indices using empirical data (as opposed to simulated data) is difficult given the scarcity of long-term data sets that describe real populations. Using mark-recapture data that span 18 years (n = 122 trapping events, >12,000 marked individuals) for deer mice on 2 of the islands, we compared density estimates obtained from several commonly used mark-recapture models and also compared these estimates to index counts. Populations of island deer mice are extremely dynamic; estimated densities over the data period varied from 0 to >1200 mice/ha. Density estimates from models in program CAPTURE and program DENSITY, as well as from model-averaged Huggins models, were strongly correlated with each other and with the density index. Densities calculated by the models and the index showed similar patterns of population variation and trend over time for all 5 sites. For long-term population monitoring and assessment of population trends in deer mice, our findings suggest that the use of a simple index may provide adequate understanding of ecologically relevant population changes, though data collection methods that allow for more detailed analyses using advanced modeling techniques should be maintained.
","language":"English","publisher":"Monte L. Bean Life Science Museum, Brigham Young University","doi":"10.3398/064.078.0301","usgsCitation":"Schwemm, C.A., Drost, C.A., Orrock, J.L., Coonan, T.J., and Stanley, T.R., 2018, Comparison of estimators for monitoring long-term population trends in deer mice, Peromyscus maniculatus, on the California Channel Islands: Western North American Naturalist, v. 78, no. 3, p. 496-509, https://doi.org/10.3398/064.078.0301.","productDescription":"14 p.","startPage":"496","endPage":"509","ipdsId":"IP-076415","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":358583,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Channel Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.56396484375,\n 34.161818161230386\n ],\n [\n -120.73974609374999,\n 33.95247360616282\n ],\n [\n -120.56396484375,\n 33.669496972795535\n ],\n [\n -119.86083984375,\n 33.4955977448657\n ],\n [\n -119.72900390625001,\n 33.109948297894285\n ],\n [\n -119.124755859375,\n 32.80574473290688\n ],\n [\n -118.41064453125,\n 32.55607364492026\n ],\n [\n -117.92724609375,\n 32.7503226078097\n ],\n [\n -117.92724609375,\n 33.08233672856376\n ],\n [\n -118.2568359375,\n 33.54139466898275\n ],\n [\n -118.93798828125,\n 33.669496972795535\n ],\n [\n -119.20166015625,\n 34.06176136129718\n ],\n [\n -119.81689453125,\n 34.21634468843463\n ],\n [\n -120.56396484375,\n 34.161818161230386\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"78","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10a91be4b034bf6a7e4fc3","contributors":{"authors":[{"text":"Schwemm, Catherin A.","contributorId":209929,"corporation":false,"usgs":false,"family":"Schwemm","given":"Catherin","email":"","middleInitial":"A.","affiliations":[{"id":38029,"text":"Institute for Wildlife Studies, PO Box 1104, Arcata, CA 95518; schwemm@iws.org","active":true,"usgs":false}],"preferred":false,"id":749111,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Drost, Charles A. 0000-0002-4792-7095 charles_drost@usgs.gov","orcid":"https://orcid.org/0000-0002-4792-7095","contributorId":3151,"corporation":false,"usgs":true,"family":"Drost","given":"Charles","email":"charles_drost@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":749109,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Orrock, John L.","contributorId":209931,"corporation":false,"usgs":false,"family":"Orrock","given":"John","email":"","middleInitial":"L.","affiliations":[{"id":38031,"text":"Department of Zoology, University of Wisconsin, Madison, WI 53706; jorrock@wisc.edu","active":true,"usgs":false}],"preferred":false,"id":749113,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coonan, Timothy J.","contributorId":209930,"corporation":false,"usgs":false,"family":"Coonan","given":"Timothy","email":"","middleInitial":"J.","affiliations":[{"id":38030,"text":"National Park Service, Channel Islands National Park, Ventura, CA (retired); timcoonan81@gmail.com","active":true,"usgs":false}],"preferred":false,"id":749112,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stanley, Thomas R. 0000-0002-8393-0005 stanleyt@usgs.gov","orcid":"https://orcid.org/0000-0002-8393-0005","contributorId":209928,"corporation":false,"usgs":true,"family":"Stanley","given":"Thomas","email":"stanleyt@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":749110,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70200456,"text":"70200456 - 2018 - Downscaling of climate model output for Alaskan stakeholders","interactions":[],"lastModifiedDate":"2018-12-05T14:11:06","indexId":"70200456","displayToPublicDate":"2018-10-18T12:51:09","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Downscaling of climate model output for Alaskan stakeholders","docAbstract":"The paper summarizes an end-to-end activity connecting the global climate modeling enterprise with users of climate information in Alaska. The effort included retrieval of the requisite observational datasets and model output, a model evaluation and selection procedure, the actual downscaling by the delta method with its inherent bias-adjustment, and the provision of products to a range of users through visualization software that empowers users to explore the downscaled output and its sensitivities. An additional software tool enables users to examine skill metrics and relative rankings of 21 global models for Alaska and six other domains in the Northern Hemisphere. The downscaled temperatures and precipitation are made available as calendar-month decadal means under three different greenhouse forcing scenarios through 2100 for more than 4000 communities in Alaska and western Canada. The visualization package displays the uncertainties inherent in the multi-model ensemble projections. These uncertainties are often larger than the projected changes.
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0000-0002-5302-8280","orcid":"https://orcid.org/0000-0002-5302-8280","contributorId":205907,"corporation":false,"usgs":true,"family":"Littell","given":"Jeremy","middleInitial":"S.","affiliations":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":748951,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leonawicz, Matthew","contributorId":209849,"corporation":false,"usgs":false,"family":"Leonawicz","given":"Matthew","email":"","affiliations":[{"id":38013,"text":"Scenarios Network for Alaska and Arctic Planning, University of Alaska, Fairbanks, AK","active":true,"usgs":false}],"preferred":false,"id":748954,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lindgren, Michael","contributorId":198682,"corporation":false,"usgs":false,"family":"Lindgren","given":"Michael","affiliations":[],"preferred":false,"id":748955,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kurkowski, Thomas A.","contributorId":209874,"corporation":false,"usgs":false,"family":"Kurkowski","given":"Thomas","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":749002,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bieniek, Peter A.","contributorId":209850,"corporation":false,"usgs":false,"family":"Bieniek","given":"Peter A.","affiliations":[{"id":38014,"text":"Alaska Climate Science Center, University of Alaska, Fairbanks, AK","active":true,"usgs":false}],"preferred":false,"id":748956,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Thoman, Richard","contributorId":187613,"corporation":false,"usgs":false,"family":"Thoman","given":"Richard","affiliations":[],"preferred":false,"id":748957,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gray, Stephen T. 0000-0002-0959-3418 sgray@usgs.gov","orcid":"https://orcid.org/0000-0002-0959-3418","contributorId":209851,"corporation":false,"usgs":true,"family":"Gray","given":"Stephen","email":"sgray@usgs.gov","middleInitial":"T.","affiliations":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":748958,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Rupp, T. Scott","contributorId":195180,"corporation":false,"usgs":false,"family":"Rupp","given":"T.","email":"","middleInitial":"Scott","affiliations":[],"preferred":false,"id":749003,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70228350,"text":"70228350 - 2018 - Low survey response! Can I still use the data?","interactions":[],"lastModifiedDate":"2022-02-09T18:00:00.545721","indexId":"70228350","displayToPublicDate":"2018-10-18T11:55:37","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1909,"text":"Human Dimensions of Wildlife","active":true,"publicationSubtype":{"id":10}},"title":"Low survey response! Can I still use the data?","docAbstract":"Natural resource agencies often use mail surveys to collect stakeholder information. However, a major concern of mail surveys have long been relatively low response rates compared to telephone or face-to-face interviews. Survey research has largely focused on achieving high response rates; however, in some situations even well designed surveys can have low response rates. We present an example of a 3-page (25 questions) survey measuring opinions and attitudes about native fish management in the South Dakota Black Hills region that received a relatively low response rate (21%) using a mailing, postcard, and second mailing of the questionnaire. We compare response rate and data quality of a third mailing of the full questionnaire with a one-page (5 questions) questionnaire measuring key variables to evaluate possible nonresponse bias. Within the total survey error (TSE) paradigm we provide evidence that reliable and useful information was collected by this survey.","language":"English","publisher":"Taylor & Francis","doi":"10.1080/10871209.2018.1523508","usgsCitation":"Gigliotti, L.M., and Fompa, S., 2018, Low survey response! Can I still use the data?: Human Dimensions of Wildlife, v. 24, no. 1, p. 71-79, https://doi.org/10.1080/10871209.2018.1523508.","productDescription":"9 p.","startPage":"71","endPage":"79","ipdsId":"IP-098484","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":395700,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Dakota","otherGeospatial":"Black Hills","volume":"24","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gigliotti, Larry M. 0000-0002-1693-5113 lgigliotti@usgs.gov","orcid":"https://orcid.org/0000-0002-1693-5113","contributorId":3906,"corporation":false,"usgs":true,"family":"Gigliotti","given":"Larry","email":"lgigliotti@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":833906,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fompa, Seth","contributorId":275271,"corporation":false,"usgs":false,"family":"Fompa","given":"Seth","email":"","affiliations":[{"id":5088,"text":"SDSU","active":true,"usgs":false}],"preferred":false,"id":833907,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70200441,"text":"70200441 - 2018 - Paleoseismic results from the Alpine site, Wasatch fault zone: Timing and displacement data for six holocene earthquakes at the Salt Lake City–Provo segment boundary","interactions":[],"lastModifiedDate":"2020-12-21T12:49:27.337213","indexId":"70200441","displayToPublicDate":"2018-10-17T16:57:20","publicationYear":"2018","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":"Paleoseismic results from the Alpine site, Wasatch fault zone: Timing and displacement data for six holocene earthquakes at the Salt Lake City–Provo segment boundary","docAbstract":"To improve the characterization of Holocene earthquakes on the Wasatch fault zone (WFZ), we conducted light detection and ranging (lidar)‐based neotectonic mapping and excavated a paleoseismic trench across an 8‐m‐high fault scarp near Alpine, Utah, located
The satellite‐derived Normalized Difference Vegetation Index (NDVI) is commonly used by researchers and managers to represent ungulate forage conditions in landscapes across the globe, despite limited information about how it compares to empirical measurements of forage quality and quantity. The application of NDVI as a forage metric is particularly appealing for studying migratory caribou (Rangifer tarandus) in remote Arctic ecosystems, where field assessments are logistically and financially prohibitive, and climate‐mediated changes in vegetation have been hypothesized to influence population declines. To determine the utility of NDVI for adequately representing caribou forage conditions, we compared NDVI derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery to empirical measures of caribou forage biomass, nitrogen, digestible nitrogen, and digestible energy within the summer range of the Central Arctic Caribou Herd on the North Slope of Alaska. Specifically, we determined the strength of forage–NDVI relationships at the start of the growing season and across the summer, assessed the efficacy of NDVI variables for modeling spatiotemporal variation in field measurements of different forage components, and used long‐term MODIS data to estimate temporal changes in forage between 2000 and 2016. We found that NDVI values were weakly correlated with caribou forage quality at the start of the growing season and throughout the summer. Although linear models of forage–NDVI relationships performed poorly, NDVI variables (NDVI and the number of days from when NDVI reached its maximum value) were useful for modeling spatiotemporal variation in empirical measurements of forage components across the growing season, but only when we incorporated nonlinear forage–NDVI relationships and other habitat covariates. Phenological advances in the date of peak NDVI were associated with significant changes in forage conditions, particularly nitrogen, which exhibited earlier seasonal declines. Using long‐term MODIS data, predicted values of forage nitrogen declined between 2000 and 2016, driven by exceedingly low values in 2014 and 2015. Given our results, we caution the application of NDVI as a general (linear) proxy of caribou forage conditions across the growing season, and encourage practitioners to use NDVI variables to model spatiotemporal variation in specific forage conditions from empirical field data, accounting for nonlinear forage–NDVI relationships.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2461","usgsCitation":"Johnson, H.E., Gustine, D., Golden, T.S., Adams, L.G., Parrett, L.S., Lenart, E.A., and Barboza, P.S., 2018, NDVI exhibits mixed success in predicting spatiotemporal variation in caribou summer forage quality and quantity: Ecosphere, v. 9, no. 10, p. 1-19, https://doi.org/10.1002/ecs2.2461.","productDescription":"e02461; 19 p.","startPage":"1","endPage":"19","ipdsId":"IP-096032","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":468314,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2461","text":"Publisher Index Page"},{"id":358477,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -150.062255859375,\n 68.50811862333941\n ],\n [\n -147.908935546875,\n 68.50811862333941\n ],\n [\n -147.908935546875,\n 70.53954317685509\n ],\n [\n -150.062255859375,\n 70.53954317685509\n ],\n [\n -150.062255859375,\n 68.50811862333941\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-03","publicationStatus":"PW","scienceBaseUri":"5bed4273e4b0b3fc5cf91c8a","contributors":{"authors":[{"text":"Johnson, Heather E. 0000-0001-5392-7676 hejohnson@usgs.gov","orcid":"https://orcid.org/0000-0001-5392-7676","contributorId":205919,"corporation":false,"usgs":true,"family":"Johnson","given":"Heather","email":"hejohnson@usgs.gov","middleInitial":"E.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":748651,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gustine, David D.","contributorId":209728,"corporation":false,"usgs":false,"family":"Gustine","given":"David D.","affiliations":[{"id":37975,"text":"Grand Teton National Park","active":true,"usgs":false}],"preferred":false,"id":748652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Golden, Trevor S. 0000-0003-4138-9289","orcid":"https://orcid.org/0000-0003-4138-9289","contributorId":209729,"corporation":false,"usgs":true,"family":"Golden","given":"Trevor","email":"","middleInitial":"S.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":748653,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Adams, Layne G. 0000-0001-6212-2856 ladams@usgs.gov","orcid":"https://orcid.org/0000-0001-6212-2856","contributorId":209730,"corporation":false,"usgs":true,"family":"Adams","given":"Layne","email":"ladams@usgs.gov","middleInitial":"G.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":748654,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Parrett, Lincoln S.","contributorId":209731,"corporation":false,"usgs":false,"family":"Parrett","given":"Lincoln","email":"","middleInitial":"S.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":748655,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lenart, Elizabeth A.","contributorId":209732,"corporation":false,"usgs":false,"family":"Lenart","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":748656,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Barboza, Perry S.","contributorId":36454,"corporation":false,"usgs":false,"family":"Barboza","given":"Perry","email":"","middleInitial":"S.","affiliations":[{"id":13117,"text":"Institute of Arctic Biology, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":748657,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70200420,"text":"70200420 - 2018 - Evaluation of biodiversity data portals based on requirement analysis","interactions":[],"lastModifiedDate":"2018-10-17T10:56:55","indexId":"70200420","displayToPublicDate":"2018-10-17T10:56:52","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1457,"text":"Ecological Informatics","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of biodiversity data portals based on requirement analysis","docAbstract":"In recent years, concern about the misuse of natural resources has been increasing. It is essential to know in detail the biodiversity of an ecosystem to understand and analyze the impact of human activities on nature, as well as to promote the economic growth of a country. To achieve these goals, public and private institutions are aggregating and sharing biological data around the world by means of biodiversity data portals. The main purpose of those portals is to provide a set of tools that help users and institutions catalog, analyze, and publish raw data about different species in a manner that is open and freely available to any interested party. Normally the process of choosing the best software solution is not straightforward. This paper proposes a methodology to evaluate a collection of data portals to establish a clear and consistent selection process that analyzes a collection of requirements and research purposes. The proposed approach is based on three strategies: the use of software engineering techniques to identify the desired group of features to be available in the data portal; the application of the Kano Satisfaction Model to score each requirement according to a preset weight of importance; and the use of tree-maps to visualize the requirements based on their implementation priority, to establish a portal deployment road-map. The proposed methodology is broadly applicable to portal analyses for many communities of practice.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoinf.2018.09.008","usgsCitation":"Pizzigatti Correa, P.L., de Moraes Batista, A.F., Lins da Silva, D., Soares Rodrigues, R., Frame, M., Morandini, M., Stanzani, S., and Correa, F., 2018, Evaluation of biodiversity data portals based on requirement analysis: Ecological Informatics, v. 48, p. 215-225, https://doi.org/10.1016/j.ecoinf.2018.09.008.","productDescription":"11 p.","startPage":"215","endPage":"225","ipdsId":"IP-090505","costCenters":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":487865,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://dx.doi.org/10.1016/j.ecoinf.2018.09.008","text":"External Repository"},{"id":358475,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"48","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10a91ce4b034bf6a7e4fdf","contributors":{"authors":[{"text":"Pizzigatti Correa, Pedro Luiz","contributorId":209775,"corporation":false,"usgs":false,"family":"Pizzigatti Correa","given":"Pedro","email":"","middleInitial":"Luiz","affiliations":[],"preferred":false,"id":748797,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"de Moraes Batista, Andre Filipe","contributorId":209776,"corporation":false,"usgs":false,"family":"de Moraes Batista","given":"Andre","email":"","middleInitial":"Filipe","affiliations":[],"preferred":false,"id":748798,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lins da Silva, Daniel","contributorId":209777,"corporation":false,"usgs":false,"family":"Lins da Silva","given":"Daniel","email":"","affiliations":[],"preferred":false,"id":748799,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Soares Rodrigues, Ronaldo","contributorId":209778,"corporation":false,"usgs":false,"family":"Soares Rodrigues","given":"Ronaldo","email":"","affiliations":[],"preferred":false,"id":748800,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Frame, Mike 0000-0001-9995-2172 mike_frame@usgs.gov","orcid":"https://orcid.org/0000-0001-9995-2172","contributorId":4541,"corporation":false,"usgs":true,"family":"Frame","given":"Mike","email":"mike_frame@usgs.gov","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":748753,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Morandini, Marcelo","contributorId":209779,"corporation":false,"usgs":false,"family":"Morandini","given":"Marcelo","email":"","affiliations":[],"preferred":false,"id":748801,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stanzani, Silvio","contributorId":209780,"corporation":false,"usgs":false,"family":"Stanzani","given":"Silvio","email":"","affiliations":[],"preferred":false,"id":748802,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Correa, Fernando","contributorId":209781,"corporation":false,"usgs":false,"family":"Correa","given":"Fernando","email":"","affiliations":[],"preferred":false,"id":748803,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70196511,"text":"ofr20181055 - 2018 - Determination of representative uranium and selenium concentrations from groundwater, 2016, Homestake Mining Company Superfund site, Milan, New Mexico","interactions":[],"lastModifiedDate":"2018-10-17T07:33:40","indexId":"ofr20181055","displayToPublicDate":"2018-10-17T08:30:00","publicationYear":"2018","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":"2018-1055","title":"Determination of representative uranium and selenium concentrations from groundwater, 2016, Homestake Mining Company Superfund site, Milan, New Mexico","docAbstract":"In 2016, the U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency, collected data on isotopes, age dating, and geochemistry including aqueous uranium concentrations of samples from 20 locations in the vicinity of the Homestake Mining Company Superfund site near Milan, New Mexico. The 20 sampled locations include 19 groundwater wells and 1 treatment plant for water used for injection into aquifers. At 6 of the 19 wells, multiple samples were collected by several different sampling methods, including passive, micropurge, and volumetric methods.
Aqueous uranium concentrations were adjusted on the basis of comparisons between three sampling methods (called sample adjustments). These adjustments were specific to passive sample results because they underestimated uranium concentrations compared with results from purge samples (micropurge and volumetric). Sample adjustments were also made on aqueous selenium concentrations from previously published data for passive sampler results following a similar procedure.
Aqueous uranium concentrations in dissolved and total form were adjusted from the original analytical values (called laboratory analytical adjustments) on the basis of a rigorous comparison to several external tests, including reruns and analysis by a different laboratory after accuracy issues were identified in data from the original laboratory. The original laboratory analytical results were found to be two to five times greater than historical concentrations at the same locations, which prompted further evaluation, as described in this report.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181055","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Harte, P.T., Blake, J.M., and Becher, K.D., 2018, Determination of representative uranium and selenium concentrations from groundwater, 2016, Homestake Mining Company Superfund site, Milan, New Mexico: U.S. Geological Survey Open-File Report 2018–1055, 40 p., appendixes, https://doi.org/10.3133/ofr20181055.","productDescription":"Report: vii, 37 p.; Appendix; Data release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-091402","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":355297,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1055/coverthb.jpg"},{"id":355299,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7CR5RJS","text":"USGS data release","description":"USGS data release","linkHelpText":"Data Associated with Uranium Background Concentrations at Homestake Mining Company Superfund Site near Milan, New Mexico, July 2016 through October 2016 "},{"id":358281,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1055/ofr20181055_app2.csv","text":"Appendix 2","size":"12.6 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"Original and adjusted aqueous uranium concentrations"},{"id":355298,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1055/ofr20181055.pdf","text":"Report","size":"6.27 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1055"}],"country":"United States","state":"New Mexico","city":"Milan","otherGeospatial":"Homestake Mining Company Superfund Site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.8917,\n 35.2083\n ],\n [\n -107.8417,\n 35.2083\n ],\n [\n -107.8417,\n 35.275\n ],\n [\n -107.8917,\n 35.275\n ],\n [\n -107.8917,\n 35.2083\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey 331
Commerce Way, Suite 2
Pembroke, NH 03275
Two three-dimensional seismic surveys totaling 3.4 square miles were acquired in southeastern Miami-Dade County during 2015 as part of an ongoing broad regional investigation by the U.S. Geological Survey, in cooperation with the Miami-Dade Water and Sewer Department, that includes mapping and karst characterization of the Floridan aquifer system in southeastern Florida. Twenty columniform seismic-sag structures were identified in the three-dimensional seismic data acquired at the South Miami Heights study area in Miami-Dade County, Florida. The seismic-sag structures are commonly composed of a lower and upper seismic facies, where the lower facies is interpreted to be a high permeability column-shaped volume of intense karstification composed of faults, fractures, and collapsed caves, and the upper facies is interpreted to be a lower permeability column-shaped volume composed of sagging suprastratal reflections having little or no faulting, fracturing, or caves. The seismic-sag structures are columniform karst-collapse structures that formed by cave collapse or stoping (upward void migration caused primarily by the mechanical process of ceiling collapse) or both in carbonate rocks of the early Eocene Oldsmar Formation and in some cases in the lowermost part of the middle Eocene Avon Park Formation. Columniform subsidence and sagging of overburden succeeded karst collapse in the lower part of the structures. At the study area, there may be relatively higher potential for the columniform karst-collapse structures to provide cross-formational fluid migration upward from the Boulder Zone into the lower part of middle confining unit 2 as compared to a lower potential for cross-formational fluid migration from the upper part of middle confining unit 2 upward to the Upper Floridan aquifer.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185117","collaboration":"Prepared in cooperation with the Miami-Dade County Water and Sewer Department","usgsCitation":"Cunningham, K.J., Dixon, J.F., Westcott, R.L., Norgard, S., and Walker, C., 2018, Three-dimensional seismic characterization of karst in the Floridan aquifer system, southeastern Miami-Dade County, Florida: U.S. Geological Survey Scientific Investigations Report 2018–5117, 39 p., https://doi.org/10.3133/sir20185117.","productDescription":"vii, 39 p.","numberOfPages":"52","onlineOnly":"Y","ipdsId":"IP-085156","costCenters":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"links":[{"id":358377,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5117/coverthb.jpg"},{"id":358378,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5117/sir20185117.pdf","text":"Report","size":"30.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5117"}],"country":"United States","state":"Florida","county":"Miami-Dade County","otherGeospatial":"Floridan Aquifer System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.40442943572998,\n 25.562574731286375\n ],\n [\n -80.37142753601074,\n 25.562574731286375\n ],\n [\n -80.37142753601074,\n 25.591607129189303\n ],\n [\n -80.40442943572998,\n 25.591607129189303\n ],\n [\n -80.40442943572998,\n 25.562574731286375\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
We conducted the first systematic inventory of birds in the lowlands (areas ≤100 m above sea level) of the Alaska Peninsula during summers of 2004–2007 to determine their breeding distributions and habitat associations in this remote region. Using a stratified random survey design, we allocated sample plots by elevation and land cover with a preference for wetland cover types used by shorebirds, a group of particular interest to land managers. We surveyed birds during 10-min counts at 792 points across 52, 5 km × 5 km sample plots distributed from south of the Naknek River (58.70°N,157.00°W) to north of Port Moller (56.00°N,160.52°W). We detected 95 bird species including 19 species of shorebirds and 34 species (36% of total) considered at the time to be of conservation concern for the land managers in the region. The most numerous shorebirds on point counts were dunlin Calidris alpina, short-billed dowitcher Limnodromus griseus, and Wilson's snipe Gallinago delicata.We found the breeding-season endemic marbled godwit Limosa fedoa beringiae at 20 plots within a 3,000-km2 area from north of Ugashik Bay to just north of Port Heiden and east to the headwaters of the Dog Salmon and Ugashik rivers. The most abundant passerines on point counts were American tree sparrow Spizelloides arborea, Lapland longspur Calcarius lapponicus, and savannah sparrow Passerculus sandwichensis. Sandhill crane Antigone canadensis, glaucous-winged gull Larus glaucescens, and greater scaup Aythya marila were also relatively abundant. We categorized habitat associations for 30 common species and found that lowland herbaceous vegetation supported wetland-focused species including sandhill crane, marbled godwit, short-billed dowitcher, and dunlin; whereas, dwarf shrub-ericaceous vegetation supported tundra-associated species such as willow ptarmigan Lagopus lagopus, rock sandpiper Calidris ptilocnemis, and American pipit Anthus rubescens. Tall shrub vegetation was important to several species of warblers and sparrows, as well as one species of shorebird (greater yellowlegs Tringa melanoleuca). We found that point counts augmented with incidental observations provided an almost complete inventory of lowland-breeding species on the study area. These data form a baseline to monitor any future changes in bird distribution and abundance on the Alaska Peninsula.
","language":"English","publisher":"U.S. Fish & Wildlife Service","doi":"10.3996/082017-JFWM-070","usgsCitation":"Savage, S.E., Tibbitts, T.L., Sesser, K., and Kaler, R., 2018, Inventory of lowland-breeding birds on the Alaska Peninsula: Journal of Fish and Wildlife Management, v. 9, no. 2, p. 637-658, https://doi.org/10.3996/082017-JFWM-070.","productDescription":"22 p.","startPage":"637","endPage":"658","ipdsId":"IP-090348","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":468316,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/082017-jfwm-070","text":"Publisher Index Page"},{"id":437716,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FR8FLZ","text":"USGS data release","linkHelpText":"Inventory Data of Lowland-Breeding Birds and Associated Vegetation Types on the Alaska Peninsula, 2004-2007"},{"id":358402,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Alaska Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -164,\n 54.5\n ],\n [\n -152,\n 54.5\n ],\n [\n -152,\n 59\n ],\n [\n -164,\n 59\n ],\n [\n -164,\n 54.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-14","publicationStatus":"PW","scienceBaseUri":"5c10a91ce4b034bf6a7e4fe6","contributors":{"authors":[{"text":"Savage, Susan E.","contributorId":140748,"corporation":false,"usgs":false,"family":"Savage","given":"Susan","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":748673,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tibbitts, T. Lee 0000-0002-0290-7592 ltibbitts@usgs.gov","orcid":"https://orcid.org/0000-0002-0290-7592","contributorId":102185,"corporation":false,"usgs":true,"family":"Tibbitts","given":"T.","email":"ltibbitts@usgs.gov","middleInitial":"Lee","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":748672,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sesser, Kristin","contributorId":209737,"corporation":false,"usgs":false,"family":"Sesser","given":"Kristin","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":748674,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kaler, Robb S.A.","contributorId":69066,"corporation":false,"usgs":true,"family":"Kaler","given":"Robb S.A.","affiliations":[],"preferred":false,"id":748675,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70263619,"text":"70263619 - 2018 - Sources of long-range anthropogenic noise in southern California and implications for tectonic tremor detection","interactions":[],"lastModifiedDate":"2025-02-19T16:24:20.775288","indexId":"70263619","displayToPublicDate":"2018-10-16T10:19:47","publicationYear":"2018","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":"Sources of long-range anthropogenic noise in southern California and implications for tectonic tremor detection","docAbstract":"We study anthropogenic noise sources seen on seismic recordings along the central section of the San Jacinto fault near Anza, southern California. The strongest signals are caused by freight trains passing through the Coachella Valley north of Anza. Train‐induced transients are observed at distances of up to 50 km from the railway, with durations of up to 20 min, and spectra that are peaked between 3 and 5 Hz. Additionally, truck traffic through the Coachella Valley generates a sustained hum with a similar spectral signature as the train transients but with lower amplitude. We also find that wind turbine activity in northern Baja California introduces a seasonal modulation of 1– to 5‐Hz energy across the Anza network. We show that the observed train‐generated transients can be used to constrain shallow attenuation structure at Anza. Using the results from this study as well as available borehole data, we further evaluate the performance of approaches that have been used to detect nonvolcanic tremor at Anza. We conclude that signals previously identified as spontaneous tremor (Hutchison and Ghosh, 2017) were probably generated by other nontectonic sources such as trains.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120180130","usgsCitation":"Inbal, A., Cristea-Platon, T., Ampuero, J., Hillers, G., Agnew, D., and Hough, S.E., 2018, Sources of long-range anthropogenic noise in southern California and implications for tectonic tremor detection: Bulletin of the Seismological Society of America, v. 108, no. 6, p. 3511-3527, https://doi.org/10.1785/0120180130.","productDescription":"17 p.","startPage":"3511","endPage":"3527","ipdsId":"IP-101208","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":500031,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10138/307688","text":"External Repository"},{"id":482224,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.875,\n 34\n ],\n [\n -116.875,\n 33.25\n ],\n [\n -116.2,\n 33.25\n ],\n [\n -116.2,\n 34\n ],\n [\n -116.875,\n 34\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"108","issue":"6","noUsgsAuthors":false,"publicationDate":"2018-10-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Inbal, Asaf","contributorId":350975,"corporation":false,"usgs":false,"family":"Inbal","given":"Asaf","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":927588,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cristea-Platon, Tudor","contributorId":350976,"corporation":false,"usgs":false,"family":"Cristea-Platon","given":"Tudor","affiliations":[{"id":47799,"text":"MIT","active":true,"usgs":false}],"preferred":false,"id":927589,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ampuero, Jean-Paul","contributorId":141194,"corporation":false,"usgs":false,"family":"Ampuero","given":"Jean-Paul","email":"","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":927590,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hillers, Gregor","contributorId":236647,"corporation":false,"usgs":false,"family":"Hillers","given":"Gregor","email":"","affiliations":[{"id":47489,"text":"Institute of Seismology, University of Helsinki, Helsinki, Finland","active":true,"usgs":false}],"preferred":false,"id":927591,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Agnew, Duncan 0000-0002-2360-7783","orcid":"https://orcid.org/0000-0002-2360-7783","contributorId":178605,"corporation":false,"usgs":false,"family":"Agnew","given":"Duncan","email":"","affiliations":[],"preferred":false,"id":927592,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hough, Susan E. 0000-0002-5980-2986 hough@usgs.gov","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":587,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"hough@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927593,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70200371,"text":"70200371 - 2018 - Interseismic ground deformation and fault slip rates in the greater San Francisco Bay Area from two decades of space geodetic data","interactions":[],"lastModifiedDate":"2018-10-23T16:40:08","indexId":"70200371","displayToPublicDate":"2018-10-15T15:38:12","publicationYear":"2018","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":"Interseismic ground deformation and fault slip rates in the greater San Francisco Bay Area from two decades of space geodetic data","docAbstract":"The detailed spatial variations of strain accumulation and creep on major faults in the northern San Francisco Bay Area (North Bay), which are important for seismic potential and evaluation of natural hazards, remain poorly understood. Here we combine interferometric synthetic aperture radar data from the ERS‐1/2 and Envisat satellites between 1992 and 2010 with continuous and campaign GPS data to obtain a high spatial and temporal coverage of ground deformation of the North Bay. The SAR data from both ascending and descending orbits are combined to separate horizontal and vertical components of the deformation. We jointly invert the horizontal component of the mean velocities derived from these data to infer the deep strike‐slip rates on major locked faults. We use the estimated deep rates to simulate the long‐wavelength deformation due to interseismic elastic strain accumulation along these locked faults. After removing the long‐wavelength signal from the InSAR horizontal mean velocity field, we estimate fault‐parallel surface creep rates of up to 2 mm/year along the central section of the Rodgers Creek fault and surface creep rates ranging between 2 and 4 mm/year along the Concord fault. No surface creep is geodetically resolved along the West Napa and Green Valley fault zones. We identified characteristically repeating earthquakes on the Rodgers Creek fault, the West Napa fault, the Green Valley fault, and the Concord fault. Nontectonic deformation in the Geysers geothermal field and in Late Cenozoic basins (Rohnert Park and Sonoma basins) are also observed, likely due to hydrological and sediment‐compaction processes, respectively.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018JB016004","usgsCitation":"Xu, W., Wu, S., Materna, K.Z., Nadeau, R., Floyd, M., Funning, G.J., Chaussard, E., Johnson, C.W., Murray, J.R., Ding, X., and Burgmann, R., 2018, Interseismic ground deformation and fault slip rates in the greater San Francisco Bay Area from two decades of space geodetic data: Journal of Geophysical Research B: Solid Earth, v. 123, no. 9, p. 8095-8109, https://doi.org/10.1029/2018JB016004.","productDescription":"15 p.","startPage":"8095","endPage":"8109","ipdsId":"IP-099081","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":468319,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018jb016004","text":"Publisher Index Page"},{"id":358390,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","issue":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-07","publicationStatus":"PW","scienceBaseUri":"5c10a91ee4b034bf6a7e4ff0","contributors":{"editors":[{"text":"Wu, Songbo 0000-0003-2118-0963","orcid":"https://orcid.org/0000-0003-2118-0963","contributorId":209696,"corporation":false,"usgs":false,"family":"Wu","given":"Songbo","email":"","affiliations":[{"id":37969,"text":"Hong Kong Polytechnic University","active":true,"usgs":false}],"preferred":false,"id":748589,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Nadeau, Robert 0000-0003-1255-0643","orcid":"https://orcid.org/0000-0003-1255-0643","contributorId":209698,"corporation":false,"usgs":false,"family":"Nadeau","given":"Robert","email":"","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":748590,"contributorType":{"id":2,"text":"Editors"},"rank":4},{"text":"Ding, Xiaoling","contributorId":149367,"corporation":false,"usgs":false,"family":"Ding","given":"Xiaoling","email":"","affiliations":[{"id":17720,"text":"College of Marine Science USF","active":true,"usgs":false}],"preferred":false,"id":748591,"contributorType":{"id":2,"text":"Editors"},"rank":10}],"authors":[{"text":"Xu, Wenbin 0000-0001-7294-8229","orcid":"https://orcid.org/0000-0001-7294-8229","contributorId":209695,"corporation":false,"usgs":false,"family":"Xu","given":"Wenbin","email":"","affiliations":[{"id":37969,"text":"Hong Kong Polytechnic University","active":true,"usgs":false}],"preferred":false,"id":748640,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wu, Songbo 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Berkeley","active":true,"usgs":false}],"preferred":false,"id":748643,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Floyd, Michael","contributorId":167568,"corporation":false,"usgs":false,"family":"Floyd","given":"Michael","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":748644,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Funning, Gareth J. 0000-0002-8247-0545","orcid":"https://orcid.org/0000-0002-8247-0545","contributorId":172418,"corporation":false,"usgs":false,"family":"Funning","given":"Gareth","email":"","middleInitial":"J.","affiliations":[{"id":6984,"text":"UC Riverside","active":true,"usgs":false}],"preferred":false,"id":748645,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chaussard, Estelle 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