Marked uncertainties persist regarding the climatic evolution of the Mediterranean region during the Holocene. For instance, whether moisture availability gradually decreased, remained relatively constant, or increased during the last 7000 years remains a matter of debate. To assess Holocene limnology, hydrology and moisture dynamics, the coastal lakes Lago Preola and Gorgo Basso, located in southwestern Sicily, were investigated through several stratigraphic analyses of ostracodes, including multivariate analyses of assemblages, transfer functions of salinity, and biochemical analyses of valves (Sr/Ca, δ18O and δ13C). During the early Holocene, the Gorgo Basso and Lago Preola ostracode records are similar. After an initial period of moderate salinity (1690–6100 mg/l from ca. 10,000–8190 cal yr BP), syndepositional or diagenetic dissolution of ostracode valves suggests that salinity declined to <250 mg/L from ca. 8190 to 7000 cal yr BP at both sites. After ca. 6250 cal yr BP, the ostracode records are strikingly different. Lago Preola became much more saline, with paleosalinity values that ranged from 2270 to about 24,420 mg/L. We suggest that Lago Preola's change from a freshwater to mesosaline lake at about 6250 cal yr BP was related to sea level rise and resulting intrusion of seawater-influenced groundwater. In contrast, Gorgo Basso remained a freshwater lake. The salinity of Gorgo Basso declined somewhat after 6250 cal yr BP, in comparison to the early Holocene, ranging from about 550 to 1680 mg/L. Cypria ophtalmica, a species capable of rapid swimming and flourishing in waters with low dissolved oxygen levels, became dominant at approximately the time when Greek civilization took root in Sicily (2600 cal yr BP), and it completely dominates the record during Roman occupation (roughly 2100 to 1700 cal yr BP). These freshwater conditions at Gorgo Basso suggest high effective moisture when evergreen olive-oak forests collapsed in response to increased Greco-Roman land use and fire. Ostracode valve geochemistry (Sr/Ca, δ18O) suggests significant changes in early vs. late Holocene hydrochemistry, either as changes in salinity or in the seasonality of precipitation. Harmonizing the autecological and geochemical data from Gorgo Basso suggests the latter was more likely, with relatively more late Holocene precipitation falling during the spring, summer, and fall, than winter compared to the early Holocene. Our ostracode-inferred paleosalinity data indicate that moisture availability did not decline during the late Holocene in the central Mediterranean region. Instead, moisture availability was lowest during the early Holocene, and most abundant during the late Holocene.
","language":"English","publisher":"Pergamon Press","doi":"10.1016/j.quascirev.2016.08.013","usgsCitation":"Curry, B., Henne, P., Mezquita-Joanes, F., Marrone, F., Pieri, V., La Mantia, T., Calo, C., and Tinner, W., 2016, Holocene paleoclimate inferred from salinity histories of adjacent lakes in southwestern Sicily (Italy): Quaternary Science Reviews, v. 150, p. 67-83, https://doi.org/10.1016/j.quascirev.2016.08.013.","productDescription":"17 p.","startPage":"67","endPage":"83","ipdsId":"IP-070996","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":328313,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Italy","state":"Trapani Province","otherGeospatial":"Riserva Naturale Integrale Lago Preola e Gorghi Tondi, Sicily","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 12.6,\n 37.6\n ],\n [\n 12.6,\n 37.64\n ],\n [\n 12.66,\n 37.64\n ],\n [\n 12.66,\n 37.6\n ],\n [\n 12.6,\n 37.6\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"150","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57d13a3de4b0571647cf8ddc","contributors":{"authors":[{"text":"Curry, B Brandon","contributorId":174032,"corporation":false,"usgs":false,"family":"Curry","given":"B Brandon","affiliations":[{"id":27342,"text":"Illinois State Geological Survey, Prairie Research Institute, University of Illinois at Urbana-Champaign, IL, USA","active":true,"usgs":false}],"preferred":false,"id":647000,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Henne, Paul D. 0000-0003-1211-5545 phenne@usgs.gov","orcid":"https://orcid.org/0000-0003-1211-5545","contributorId":169166,"corporation":false,"usgs":true,"family":"Henne","given":"Paul D.","email":"phenne@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":646999,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mezquita-Joanes, Francesc","contributorId":174033,"corporation":false,"usgs":false,"family":"Mezquita-Joanes","given":"Francesc","email":"","affiliations":[{"id":27343,"text":"Department of Microbiology and Ecology/ICBiBE, University of Valencia, Spain","active":true,"usgs":false}],"preferred":false,"id":647001,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marrone, Federico","contributorId":174034,"corporation":false,"usgs":false,"family":"Marrone","given":"Federico","email":"","affiliations":[{"id":27344,"text":"Universita' degli Studi di Palermo, Sicily, Italy","active":true,"usgs":false}],"preferred":false,"id":647002,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pieri, Valentina","contributorId":174035,"corporation":false,"usgs":false,"family":"Pieri","given":"Valentina","email":"","affiliations":[{"id":27345,"text":"Royal Belgian Institure of Natural Sciences, Brussels, Belgium","active":true,"usgs":false}],"preferred":false,"id":647005,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"La Mantia, Tommaso","contributorId":169175,"corporation":false,"usgs":false,"family":"La Mantia","given":"Tommaso","email":"","affiliations":[{"id":25431,"text":"University of Palermo","active":true,"usgs":false}],"preferred":false,"id":647003,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Calo, Camilla","contributorId":174036,"corporation":false,"usgs":false,"family":"Calo","given":"Camilla","email":"","affiliations":[{"id":27346,"text":"Institute of Plant Sciences & Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland","active":true,"usgs":false}],"preferred":false,"id":647006,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Tinner, Willy 0000-0001-7352-0144","orcid":"https://orcid.org/0000-0001-7352-0144","contributorId":169167,"corporation":false,"usgs":false,"family":"Tinner","given":"Willy","email":"","affiliations":[{"id":25430,"text":"University of Bern","active":true,"usgs":false}],"preferred":false,"id":647004,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70178585,"text":"70178585 - 2016 - A python framework for environmental model uncertainty analysis","interactions":[],"lastModifiedDate":"2016-11-30T11:44:14","indexId":"70178585","displayToPublicDate":"2016-09-03T00:00:00","publicationYear":"2016","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":"A python framework for environmental model uncertainty analysis","docAbstract":"We have developed pyEMU, a python framework for Environmental Modeling Uncertainty analyses, open-source tool that is non-intrusive, easy-to-use, computationally efficient, and scalable to highly-parameterized inverse problems. The framework implements several types of linear (first-order, second-moment (FOSM)) and non-linear uncertainty analyses. The FOSM-based analyses can also be completed prior to parameter estimation to help inform important modeling decisions, such as parameterization and objective function formulation. Complete workflows for several types of FOSM-based and non-linear analyses are documented in example notebooks implemented using Jupyter that are available in the online pyEMU repository. Example workflows include basic parameter and forecast analyses, data worth analyses, and error-variance analyses, as well as usage of parameter ensemble generation and management capabilities. These workflows document the necessary steps and provides insights into the results, with the goal of educating users not only in how to apply pyEMU, but also in the underlying theory of applied uncertainty quantification.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2016.08.017","usgsCitation":"White, J.T., Fienen, M., and Doherty, J.E., 2016, A python framework for environmental model uncertainty analysis: Environmental Modelling and Software, v. 85, p. 217-228, https://doi.org/10.1016/j.envsoft.2016.08.017.","productDescription":"12 p.","startPage":"217","endPage":"228","ipdsId":"IP-077464","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":331312,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"85","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"583ff34ee4b04fc80e437264","contributors":{"authors":[{"text":"White, Jeremy T. 0000-0002-4950-1469 jwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-4950-1469","contributorId":167708,"corporation":false,"usgs":true,"family":"White","given":"Jeremy","email":"jwhite@usgs.gov","middleInitial":"T.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":654466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fienen, Michael N. 0000-0002-7756-4651 mnfienen@usgs.gov","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":177065,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","email":"mnfienen@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":654467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Doherty, John E.","contributorId":8817,"corporation":false,"usgs":false,"family":"Doherty","given":"John","email":"","middleInitial":"E.","affiliations":[{"id":7046,"text":"Watermark Numerical Computing","active":true,"usgs":false}],"preferred":false,"id":654468,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70176247,"text":"70176247 - 2016 - Sex differences in contaminant concentrations of fish: a synthesis","interactions":[],"lastModifiedDate":"2018-08-08T10:18:06","indexId":"70176247","displayToPublicDate":"2016-09-03T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5200,"text":"Biology of Sex Differences","active":true,"publicationSubtype":{"id":10}},"title":"Sex differences in contaminant concentrations of fish: a synthesis","docAbstract":"Comparison of whole-fish polychlorinated biphenyl (PCB) and total mercury (Hg) concentrations in mature males with those in mature females may provide insights into sex differences in behavior, metabolism, and other physiological processes. In eight species of fish, we observed that males exceeded females in whole-fish PCB concentration by 17 to 43%. Based on results from hypothesis testing, we concluded that these sex differences were most likely primarily driven by a higher rate of energy expenditure, stemming from higher resting metabolic rate (or standard metabolic rate (SMR)) and higher swimming activity, in males compared with females. A higher rate of energy expenditure led to a higher rate of food consumption, which, in turn, resulted in a higher rate of PCB accumulation. For two fish species, the growth dilution effect also made a substantial contribution to the sex difference in PCB concentrations, although the higher energy expenditure rate for males was still the primary driver. Hg concentration data were available for five of the eight species. For four of these five species, the ratio of PCB concentration in males to PCB concentration in females was substantially greater than the ratio of Hg concentration in males to Hg concentration in females. In sea lamprey (Petromyzon marinus), a very primitive fish, the two ratios were nearly identical. The most plausible explanation for this pattern was that certain androgens, such as testosterone and 11-ketotestosterone, enhanced Hg-elimination rate in males. In contrast, long-term elimination of PCBs is negligible for both sexes. According to this explanation, males ingest Hg at a higher rate than females, but also eliminate Hg at a higher rate than females, in fish species other than sea lamprey. Male sea lamprey do not possess either of the above-specified androgens. These apparent sex differences in SMRs, activities, and Hg-elimination rates in teleost fishes may also apply, to some degree, to higher vertebrates including humans. Our synthesis findings will be useful in: (1) developing sex-specific bioenergetics models for fish, (2) developing sex-specific risk assessment models for exposure of humans and wildlife to contaminants, and (3) refining Hg mass balance models for fish and higher vertebrates.","language":"English","publisher":"BioMed Central","doi":"10.1186/s13293-016-0090-x","usgsCitation":"Madenjian, C.P., Rediske, R.R., Krabbenhoft, D.P., Stapanian, M.A., Chernyak, S.M., and O'Keefe, J., 2016, Sex differences in contaminant concentrations of fish: a synthesis: Biology of Sex Differences, v. 7, p. 1-16, https://doi.org/10.1186/s13293-016-0090-x.","productDescription":"Article 42; 16 p.","startPage":"1","endPage":"16","ipdsId":"IP-076759","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":470590,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s13293-016-0090-x","text":"Publisher Index Page"},{"id":328230,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-02","publicationStatus":"PW","scienceBaseUri":"57cbe61be4b0f2f0cec372ad","contributors":{"authors":[{"text":"Madenjian, Charles P. 0000-0002-0326-164X cmadenjian@usgs.gov","orcid":"https://orcid.org/0000-0002-0326-164X","contributorId":2200,"corporation":false,"usgs":true,"family":"Madenjian","given":"Charles","email":"cmadenjian@usgs.gov","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":648066,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rediske, Richard R.","contributorId":79053,"corporation":false,"usgs":true,"family":"Rediske","given":"Richard","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":648067,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":648068,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stapanian, Martin A. 0000-0001-8173-4273 mstapanian@usgs.gov","orcid":"https://orcid.org/0000-0001-8173-4273","contributorId":3425,"corporation":false,"usgs":true,"family":"Stapanian","given":"Martin","email":"mstapanian@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":648069,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chernyak, Sergei M.","contributorId":98668,"corporation":false,"usgs":true,"family":"Chernyak","given":"Sergei","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":648070,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O'Keefe, James P.","contributorId":99499,"corporation":false,"usgs":true,"family":"O'Keefe","given":"James P.","affiliations":[],"preferred":false,"id":648071,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70174994,"text":"sir20165107 - 2016 - Flood-inundation maps for the Green River in Colrain, Leyden, and Greenfield, Massachusetts, from U.S. Geological Survey streamgage 01170100 Green River near Colrain to the confluence with the Deerfield River","interactions":[],"lastModifiedDate":"2016-12-05T09:45:08","indexId":"sir20165107","displayToPublicDate":"2016-09-02T11:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5107","title":"Flood-inundation maps for the Green River in Colrain, Leyden, and Greenfield, Massachusetts, from U.S. Geological Survey streamgage 01170100 Green River near Colrain to the confluence with the Deerfield River","docAbstract":"The U.S. Geological Survey developed flood elevations in cooperation with the Federal Emergency Management Agency for a 14.3-mile reach of the Green River in Colrain, Leyden, and Greenfield, Massachusetts, to assist landowners and emergency management workers to prepare for and recover from floods. The river reach extends from the U.S. Geological Survey Green River near Colrain, MA (01170100) streamgage downstream to the confluence with the Deerfield River. A series of seven digital flood inundation maps were developed for the upper 4.4 miles of the river reach downstream from the stream. Flood discharges corresponding to the 50-, 10-, 1-, and 0.2-percent annual exceedance probabilities were computed for the reach from updated flood-frequency analyses. These peak flows and the flood flows associated with the stages of 10.2, 12.4, and 14.4 feet (ft) at the Green River streamgage were routed through a one-dimensional step-backwater hydraulic model to obtain the corresponding peak water-surface elevations and to place the Tropical Storm Irene flood of August 28, 2011 (stage 13.97 ft), into historical context. The hydraulic model was calibrated by using the current (2015) stage-discharge relation at the U.S. Geological Survey Green River near Colrain, MA (01170100) streamgage and from documented high-water marks from the Tropical Storm Irene flood, which had a flow higher than a 0.2-percent annual exceedance probability flood discharge.
The hydraulic model was used to compute water-surface profiles for flood stages referenced to the streamgage and ranging from the 50-percent annual exceedance probability (bankfull flow) at 7.6 ft (439.8 ft above the North American Vertical Datum of 1988 [NAVD 88]) to 14.4 ft (446.7 ft NAVD 88), which exceeds the maximum recorded water level of 13.97 ft (Tropical Storm Irene) at the streamgage. The mapped stages of 7.6 to 14.4 ft were selected to match the stages for bankfull; the 50-, 10-, 1-, and 0.2-percent annual exceedance probabilities; incremental stages of 10.2 and 12.4 ft; and the maximum stage of the stage-discharge rating curve. The simulated water-surface profiles were combined with a geographic information system digital elevation model derived from light detection and ranging (lidar) data having a 0.5-ft vertical accuracy to create a set of flood-inundation maps.
The availability of the flood-inundation maps, combined with information regarding near real-time stage from U.S. Geological Survey Green River near Colrain, MA (01170100) streamgage, can provide emergency management personnel and residents with information that is critical for flood response activities, such as evacuations and road closures, and postflood recovery efforts. The flood-inundation maps are nonregulatory but provide Federal, State, and local agencies and the public with estimates of the potential extent of flooding during selected peak-flow events.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165107","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Flynn, R.H., Bent, G.C., and Lombard, P.J., 2016, Flood-inundation maps for the Green River in Colrain, Leyden, and Greenfield, Massachusetts, from U.S. Geological Survey streamgage 01170100 Green River near Colrain to the confluence with the Deerfield River (ver. 1.1, November 2016): U.S. Geological Survey Scientific Investigations Report 2016–5107, 18 p., appendixes, https://doi.org/10.3133/sir20165107.","productDescription":"Report: vi, 18 p.; Appendix 2; Application Site; Metadata; Spatial Data","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-062774","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":331081,"rank":8,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2016/5107/versionHist.txt","size":"1 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2016-5107"},{"id":331083,"rank":7,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2016/5107/sir20165107_flood-inundation_gis.zip","text":"Flood Inundation GIS","size":"4.59 MB"},{"id":327919,"rank":6,"type":{"id":4,"text":"Application Site"},"url":"https://wimcloud.usgs.gov/apps/FIM/FloodInundationMapper.html","text":"Flood Inundation Mapper ","linkFileType":{"id":5,"text":"html"},"description":"SIR 2016-5107"},{"id":327920,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2016/5107/sir20165107_appendix2_metadata.xml ","text":"Appendix 2 - ","size":"13.6 KB xml","description":"SIR 2016-5107","linkHelpText":"metadata"},{"id":327917,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5107/sir20165107.pdf","text":"Report","size":"1.21 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5107"},{"id":327918,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5107/sir20165107_appendix2_gis.zip","text":"Appendix 2 - ","size":"160 KB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2016-5107 - Spatial Data","linkHelpText":"GIS"},{"id":327916,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5107/coverthb2.jpg"},{"id":331082,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2016/5107/sir20165107_flood-inundation_metadata.xml","text":"Flood Inundation GIS ","size":"26 KB xml","linkHelpText":"metadata"}],"country":"United States","state":"Massachusetts","city":"Colrain, Greenfield, Leyden","otherGeospatial":"Green River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.55,\n 42.55\n ],\n [\n -72.55,\n 42.72\n ],\n [\n -72.7,\n 42.72\n ],\n [\n -72.7,\n 42.55\n ],\n [\n -72.55,\n 42.55\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally posted September 2, 2016; Version 1.1: November 23, 2016","contact":"Director, New England Water Science Center
U.S. Geological Survey
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Northborough, MA 01532
Or visit our Web site at:
http://newengland.water.usgs.gov
A Presidential disaster was declared in northwestern Massachusetts, following flooding from tropical storm Irene on August 28, 2011. During the storm, 3 to 10 inches of rain fell on soils that were susceptible to flash flooding because of wet antecedent conditions. The gage height at one U.S. Geological Survey streamgage rose nearly 20 feet in less than 4 hours because of the combination of saturated soils and intense rainfall. On August 28, 2011, in the Deerfield and Hoosic River Basins in northwestern Massachusetts, new peaks of record were set at six of eight U.S. Geological Survey long-term streamgages with 46 to 100 years of record. Additionally, high-water marks were surveyed and indirect measurements of peak discharge were calculated at two discontinued streamgages in the Deerfield and Hoosic River Basins with 24 and 61 years of record, respectively. This data resulted in new historic peaks of record at the two discontinued streamgages from tropical storm Irene.
\nPeak flows that resulted from tropical storm Irene (August 28, 2011) were determined at the U.S. Geological Survey streamgages by using stage-discharge rating curves and indirect computation methods. For six streamgages, indirect computation methods were used to compute the peak flows. Peak flows from tropical storm Irene had annual exceedance probabilities (AEPs) that ranged from 5.4 percent to less than 0.2 percent at 10 streamgages in northwestern Massachusetts.
\nDischarges calculated for select AEPs as a part of this study were compared with discharges published for the same AEPs in the effective Federal Emergency Management Agency flood insurance studies (FISs) for communities in the study area. Discharges estimated for the 10-, 2-, 1-, and 0.2-percent AEPs at two streamgages on the main stem of the Deerfield River ranged from about 3 percent lower to 14 percent higher than discharges in the FISs. AEP discharges calculated for two streamgages on tributaries to the Deerfield River were 27 to 89 percent higher than the FISs. For the four streamgages in the Hoosic River Basin, the 10-, 2-, 1-, and 0.2-percent AEP discharges calculated ranged from about 33 percent lower to 5 percent higher than the FISs.
\nThe simulated 1-percent AEP discharge water-surface elevations (nonregulatory) from recent (2015–16) hydraulic models for river reaches in the study area, which include the Deerfield, Green, and North Rivers in the Deerfield River Basin and the Hoosic River in the Hoosic River Basin, were compared with water-surface profiles in the FISs. The water-surface elevation comparisons were generally done downstream and upstream from bridges, dams, and major tributaries. The simulated 1-percent AEP discharge water-surface elevations of the recent hydraulic studies averaged 2.2, 2.3, 0.3, and 0.7 ft higher than water-surface elevations in the FISs for the Deerfield, Green, North, and Hoosic Rivers, respectively. The differences in water-surface elevations between the recent (2015–16) hydraulic studies and the FISs likely are because of (1) improved land elevation data from light detection and ranging (lidar) data collected in 2012, (2) detailed surveying of hydraulic structures and cross sections throughout the river reaches in 2012–13 (reflecting structure and cross section changes during the last 30–35 years), (3) updated hydrology analyses (30–35 water years of additional peak flow data at streamgages), and (4) high-water marks from the 2011 tropical storm Irene flood being used for model calibration.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165027","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Bent, G.C., Olson, S.A., and Massey, A.J., 2016, Tropical storm Irene flood of August 2011 in northwestern Massachusetts: U.S. Geological Survey Scientific Investigations Report 2016–5027, 28 p., https://dx.doi.org/10.3133/sir20165027.","productDescription":"v, 28 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-067697","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":327911,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5027/coverthb.jpg"},{"id":327912,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5027/sir20165027.pdf","text":"Report","size":"1.21 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5027"}],"country":"United States","state":"Massachusetts","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.61688232421875,\n 42.731378652044185\n ],\n [\n -72.60452270507812,\n 42.718263627309774\n ],\n [\n -72.58804321289061,\n 42.693539313660004\n ],\n [\n -72.55989074707031,\n 42.653656930109726\n ],\n [\n -72.55302429199219,\n 42.64153569439977\n ],\n [\n -72.5592041015625,\n 42.628906895633456\n ],\n [\n -72.55851745605469,\n 42.61122227199062\n ],\n [\n -72.56813049316406,\n 42.603641609996586\n ],\n [\n -72.57637023925781,\n 42.59606002548659\n ],\n [\n -72.58049011230469,\n 42.59454359788448\n ],\n [\n -72.57980346679686,\n 42.58493869951935\n ],\n [\n -72.57568359375,\n 42.578871685346364\n ],\n [\n -72.57431030273438,\n 42.560161341916064\n ],\n [\n -72.58323669433594,\n 42.54296310520116\n ],\n [\n -72.59078979492188,\n 42.52677220056902\n ],\n [\n -72.60246276855469,\n 42.50804623455747\n ],\n [\n -72.62718200683594,\n 42.50500906265383\n ],\n [\n -72.652587890625,\n 42.50956476517422\n ],\n [\n -72.6800537109375,\n 42.51766297209017\n ],\n [\n -72.69515991210938,\n 42.52879629320373\n ],\n [\n -72.70683288574219,\n 42.51766297209017\n ],\n [\n -72.71781921386719,\n 42.50754004948742\n ],\n [\n -72.74116516113281,\n 42.49387150323448\n ],\n [\n -72.78923034667969,\n 42.47817430242153\n ],\n [\n -72.80845642089844,\n 42.46753847696729\n ],\n [\n -72.82699584960938,\n 42.50500906265383\n ],\n [\n -72.84347534179688,\n 42.52069952914966\n ],\n [\n -72.85308837890624,\n 42.53638605645048\n ],\n [\n -72.89840698242188,\n 42.55055114674488\n ],\n [\n -72.90252685546875,\n 42.54448078729858\n ],\n [\n -72.90390014648438,\n 42.53739795519656\n ],\n [\n -72.94166564941406,\n 42.53638605645048\n ],\n [\n -72.94647216796874,\n 42.525760129656845\n ],\n [\n -72.96363830566406,\n 42.51968735985934\n ],\n [\n -72.97531127929688,\n 42.53588010092859\n ],\n [\n -72.9876708984375,\n 42.54852775918642\n ],\n [\n -73.00277709960938,\n 42.55560932868032\n ],\n [\n -73.01239013671875,\n 42.562184352321886\n ],\n [\n -73.02200317382812,\n 42.57027573801005\n ],\n [\n -73.02818298339844,\n 42.58645536081647\n ],\n [\n -73.04054260253906,\n 42.601619944327965\n ],\n [\n -73.04672241210938,\n 42.605157816197334\n ],\n [\n -73.06938171386719,\n 42.58696090638245\n ],\n [\n -73.06800842285156,\n 42.5798828953732\n ],\n [\n -73.06869506835938,\n 42.560161341916064\n ],\n [\n -73.05770874023438,\n 42.54144538620976\n ],\n [\n -73.05770874023438,\n 42.53486817758702\n ],\n [\n -73.07212829589844,\n 42.52677220056902\n ],\n [\n -73.10508728027344,\n 42.51158941527828\n ],\n [\n -73.11126708984375,\n 42.49690921618136\n ],\n [\n -73.14628601074219,\n 42.50500906265383\n ],\n [\n -73.15864562988281,\n 42.49944053092116\n ],\n [\n -73.16963195800781,\n 42.489820989777066\n ],\n [\n -73.18954467773438,\n 42.48830197960227\n ],\n [\n -73.21563720703125,\n 42.49032731830467\n ],\n [\n -73.22181701660156,\n 42.50905859240087\n ],\n [\n -73.22181701660156,\n 42.52829027619378\n ],\n [\n -73.21769714355469,\n 42.54448078729858\n ],\n [\n -73.21151733398436,\n 42.553586105099654\n ],\n [\n -73.20533752441406,\n 42.56370156708076\n ],\n [\n -73.19366455078125,\n 42.587971985214814\n ],\n [\n -73.201904296875,\n 42.58594981115061\n ],\n [\n -73.23211669921875,\n 42.58493869951935\n ],\n [\n -73.24928283691406,\n 42.5995982130586\n ],\n [\n -73.25889587402344,\n 42.5995982130586\n ],\n [\n -73.26301574707031,\n 42.58746644784856\n ],\n [\n -73.32069396972655,\n 42.59252163701558\n ],\n [\n -73.26507568359375,\n 42.74600367786244\n ],\n [\n -72.61688232421875,\n 42.731378652044185\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Or visit our Web site at:
http://newengland.water.usgs.gov
Habitat selection is an active behavioral process that may vary across spatial and temporal scales. Animals choose an area of primary utilization (i.e., home range) then make decisions focused on resource needs within patches. Dominance may affect the spatial distribution of conspecifics and concomitant habitat selection. Size-dependent social dominance hierarchies have been documented in captive alligators, but evidence is lacking from wild populations. We studied habitat selection for adult male American alligators (Alligator mississippiensis; n = 17) on the Pearl River in central Mississippi, USA, to test whether habitat selection was scale-dependent and individual resource selectivity was a function of conspecific body size. We used K-select analysis to quantify selection at the home range scale and patches within the home range to determine selection congruency and important habitat variables. In addition, we used linear models to determine if body size was related to selection patterns and strengths. Our results indicated habitat selection of adult male alligators was a scale-dependent process. Alligators demonstrated greater overall selection for habitat variables at the patch level and less at the home range level, suggesting resources may not be limited when selecting a home range for animals in our study area. Further, diurnal habitat selection patterns may depend on thermoregulatory needs. There was no relationship between resource selection or home range size and body size, suggesting size-dependent dominance hierarchies may not have influenced alligator resource selection or space use in our sample. Though apparent habitat suitability and low alligator density did not manifest in an observed dominance hierarchy, we hypothesize that a change in either could increase intraspecific interactions, facilitating a dominance hierarchy. Due to the broad and diverse ecological roles of alligators, understanding the factors that influence their social dominance and space use can provide great insight into their functional role in the ecosystem.
","language":"English","publisher":"PLOS One","doi":"10.1371/journal.pone.0161814","usgsCitation":"Strickland, B.A., Vilella, F., and Belant, J.L., 2016, Scale-dependent habitat selection and size-based dominance in adult male American alligators: PLoS ONE, p. 1-16, https://doi.org/10.1371/journal.pone.0161814.","productDescription":"e0161814; 16 p.","startPage":"1","endPage":"16","ipdsId":"IP-070818","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":470592,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0161814","text":"Publisher Index Page"},{"id":331825,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Mississippi","otherGeospatial":"Pearl River, Ross Barnett Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.96566772460936,\n 32.48601763026006\n ],\n [\n -89.96566772460936,\n 32.601783214045184\n ],\n [\n -89.77203369140625,\n 32.601783214045184\n ],\n [\n -89.77203369140625,\n 32.48601763026006\n ],\n [\n -89.96566772460936,\n 32.48601763026006\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-02","publicationStatus":"PW","scienceBaseUri":"584bd0dde4b077fc20250e08","contributors":{"authors":[{"text":"Strickland, Bradley A.","contributorId":177343,"corporation":false,"usgs":false,"family":"Strickland","given":"Bradley","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":655399,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vilella, Francisco 0000-0003-1552-9989 fvilella@usgs.gov","orcid":"https://orcid.org/0000-0003-1552-9989","contributorId":171363,"corporation":false,"usgs":true,"family":"Vilella","given":"Francisco","email":"fvilella@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":655386,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belant, Jerrold L.","contributorId":108394,"corporation":false,"usgs":false,"family":"Belant","given":"Jerrold","email":"","middleInitial":"L.","affiliations":[{"id":35599,"text":"Carnivore Ecology Laboratory, Mississippi State University, Mississippi State, MS","active":true,"usgs":false}],"preferred":false,"id":655400,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70176199,"text":"70176199 - 2016 - Characterizing potentially induced earthquake rate changes in the Brawley Seismic Zone, southern California","interactions":[],"lastModifiedDate":"2016-09-28T16:06:53","indexId":"70176199","displayToPublicDate":"2016-09-01T17:30:00","publicationYear":"2016","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":"Characterizing potentially induced earthquake rate changes in the Brawley Seismic Zone, southern California","docAbstract":"The Brawley seismic zone (BSZ), in the Salton trough of southern California, has a history of earthquake swarms and geothermal energy exploitation. Some earthquake rate changes may have been induced by fluid extraction and injection activity at local geothermal fields, particularly at the North Brawley Geothermal Field (NBGF) and at the Salton Sea Geothermal Field (SSGF). We explore this issue by examining earthquake rate changes and interevent distance distributions in these fields. In Oklahoma and Arkansas, where considerable wastewater injection occurs, increases in background seismicity rate and aftershock productivity and decreases in interevent distance were indicative of fluid‐injection‐induced seismicity. Here, we test if similar changes occur that may be associated with fluid injection and extraction in geothermal areas. We use stochastic epidemic‐type aftershock sequence models to detect changes in the underlying seismogenic processes, shown by statistically significant changes in the model parameters. The most robust model changes in the SSGF roughly occur when large changes in net fluid production occur, but a similar correlation is not seen in the NBGF. Also, although both background seismicity rate and aftershock productivity increased for fluid‐injection‐induced earthquake rate changes in Oklahoma and Arkansas, the background rate increases significantly in the BSZ only, roughly corresponding with net fluid production rate increases. Moreover, in both fields the interevent spacing does not change significantly during active energy projects. This suggests that, although geothermal field activities in a tectonically active region may not significantly change the physics of earthquake interactions, earthquake rates may still be driven by fluid injection or extraction rates, particularly in the SSGF.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120150053","usgsCitation":"Llenos, A.L., and Michael, A.J., 2016, Characterizing potentially induced earthquake rate changes in the Brawley Seismic Zone, southern California: Bulletin of the Seismological Society of America, v. 106, no. 5, p. 2045-2062, https://doi.org/10.1785/0120150053.","productDescription":"18 p.","startPage":"2045","endPage":"2062","ipdsId":"IP-063493","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":328209,"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 \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.8,\n 32.8\n ],\n [\n -115.8,\n 33.3\n ],\n [\n -115.4,\n 33.3\n ],\n [\n -115.4,\n 32.8\n ],\n [\n -115.8,\n 32.8\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"106","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-23","publicationStatus":"PW","scienceBaseUri":"57c9431ce4b0f2f0cec1355f","contributors":{"authors":[{"text":"Llenos, Andrea L. 0000-0002-4088-6737 allenos@usgs.gov","orcid":"https://orcid.org/0000-0002-4088-6737","contributorId":4455,"corporation":false,"usgs":true,"family":"Llenos","given":"Andrea","email":"allenos@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":647757,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Michael, Andrew J. 0000-0002-2403-5019 michael@usgs.gov","orcid":"https://orcid.org/0000-0002-2403-5019","contributorId":1280,"corporation":false,"usgs":true,"family":"Michael","given":"Andrew","email":"michael@usgs.gov","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":647758,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70176208,"text":"70176208 - 2016 - Organic petrology and geochemistry of mudrocks from the lacustrine Lucaogou Formation, Santanghu Basin, northwest China: Application to lake basin evolution","interactions":[],"lastModifiedDate":"2016-12-01T12:55:40","indexId":"70176208","displayToPublicDate":"2016-09-01T17:20:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2033,"text":"International Journal of Coal Geology","active":true,"publicationSubtype":{"id":10}},"title":"Organic petrology and geochemistry of mudrocks from the lacustrine Lucaogou Formation, Santanghu Basin, northwest China: Application to lake basin evolution","docAbstract":"Exploration for tight oil in the frontier Santanghu Basin of northwest China has resulted in recent commercial discoveries sourced from the lacustrine Upper Permian Lucaogou Formation, already considered a “world class source rock” in the Junggar Basin to the west. Here we apply an integrated analytical program to carbonate-dominated mudrocks from the Lucaogou Formation in Santanghu Basin to document the nature of organic matter (OM) in the context of an evolving lake system. The organic-rich samples (TOC 2.8–11.4 wt%; n = 10) were widely spaced from an ~ 200 m cored section, interpreted from textural and mineralogical evidence to document transition from a lower under-filled to an overlying balanced-filled lake. Organic matter is dominated by moderate to strongly fluorescent amorphous material with Type I geochemical signature (HI values 510–755; n = 10) occurring in a continuum from lamellar stringers, 10–20 μm thick, some ≥ 1 mm in length (possible microbial mat; preserved only in lower under-filled section) to finely-disseminated amorphous groundmass intimately intermixed with mineral matrix. Biomarkers for methanotrophs and photosynthetic cyanobacteria indicate a complex microbial consortium. A unicellular prasinophyte green alga(?), similar to Tasmanites in marine rocks, is present as discrete flattened discs 50–100 μm in diameter. Type III OM including vitrinite (some fluorescent) and inertinite also is abundant. Solid bitumen, indicating local kerogen conversion, fills voids and occurs throughout the cored section. Vitrinite reflectance values are 0.47–0.58%, consistent with strong OM fluorescence but may be “suppressed”. Other proxies, e.g., biomarker parameters, indicate the Lucaogou Formation is in the early oil window at this location. On average, slightly more amorphous OM and telalginite are present in the lower section, consistent with a shallow, stratified, saline environment with low sediment dilution. More inertinite is present in the upper section, indicating greater terrestrial influx and consistent with higher quartz and plagioclase content (dominantly authigenic chalcedony and albite). Laminated mudstones in the upper section indicate anoxia prevented bioturbation from benthic grazing, also indicating stratified water column conditions. A decrease upsection in authigenic dolomite with reciprocal increase of ankerite/siderite is consistent with decreasing salinity, as is an overall decrease in gammacerane index values. These observations suggest evolution from a shallow, stratified evaporative (saline) setting to a deeper, stratified freshwater basin with higher water input during Lucaogou deposition. The evolution from an under-filled to balance-filled lake in Santanghu Basin is similar to Lucaogou deposition in Junggar Basin, suggesting similar tectonic and climatic controls. Paleoclimate interpretations from other researchers in this area suggested an evolution from semi-arid to humid conditions during the Roadian; we interpret that the evolution from an under-filled to balanced-filled lake seen in our data is in response to climate change, and may represent increased groundwater delivery to the Santanghu Basin.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2016.05.011","usgsCitation":"Hackley, P.C., Fishman, N., Wu, T., and Baugher, G., 2016, Organic petrology and geochemistry of mudrocks from the lacustrine Lucaogou Formation, Santanghu Basin, northwest China: Application to lake basin evolution: International Journal of Coal Geology, v. 168, no. 1, p. 20-34, https://doi.org/10.1016/j.coal.2016.05.011.","productDescription":"15 p.","startPage":"20","endPage":"34","ipdsId":"IP-075908","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":488525,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.coal.2016.05.011","text":"Publisher Index Page"},{"id":328207,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"168","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57c94321e4b0f2f0cec135a1","chorus":{"doi":"10.1016/j.coal.2016.05.011","url":"http://dx.doi.org/10.1016/j.coal.2016.05.011","publisher":"Elsevier BV","authors":"Hackley Paul C., Fishman Neil, Wu Tao, Baugher Gregory","journalName":"International Journal of Coal Geology","publicationDate":"11/2016"},"contributors":{"authors":[{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":647801,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fishman, Neil","contributorId":145906,"corporation":false,"usgs":false,"family":"Fishman","given":"Neil","affiliations":[{"id":16290,"text":"Hess Corporation, Houston, Texas, USA","active":true,"usgs":false}],"preferred":false,"id":647802,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wu, Tao","contributorId":174230,"corporation":false,"usgs":false,"family":"Wu","given":"Tao","email":"","affiliations":[{"id":16290,"text":"Hess Corporation, Houston, Texas, USA","active":true,"usgs":false}],"preferred":false,"id":647803,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baugher, Gregory","contributorId":174231,"corporation":false,"usgs":false,"family":"Baugher","given":"Gregory","email":"","affiliations":[],"preferred":false,"id":647804,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70199854,"text":"70199854 - 2016 - Maxent modeling for predicting potential distribution of goitered gazelle in central Iran: the effect of extent and grain size on performance of the model","interactions":[],"lastModifiedDate":"2018-10-02T10:05:19","indexId":"70199854","displayToPublicDate":"2016-09-01T15:38:26","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5759,"text":"Turkish Journal of Zoology","active":true,"publicationSubtype":{"id":10}},"title":"Maxent modeling for predicting potential distribution of goitered gazelle in central Iran: the effect of extent and grain size on performance of the model","docAbstract":"The spatial scale of environmental layers is an important factor to consider in developing an understanding of ecological processes. This study employed Maxent modeling to investigate the geographic distribution of goitered gazelle, Gazella subgutturosa (Güldenstädt, 1780), in central Iran using uncorrelated variables at a spatial resolution of 250 m. We used spatial downscaling to downscale WorldClim data to 250-m resolution. We evaluated the sensitivity of the model to different grain and extent sizes from 250 m to 3 km. We compared the performance of the model at different scales using suitability indexes (AUC) and predicted habitat areas. Two models performed with AUC values higher than random (AUCun = 0.957, AUCpu = 0.953). The distribution of potential habitats at 250- m grid size was strongly influenced by bioclimatic data, vegetation type and density, and elevation. There were few spatial divergences between uncorrelated and pruned models. The mean AUC across eight different spatial scales ranged from 0.936 to 0.959. There was a significant negative correlation between grain size and AUC (R2 = 0.57). An increase in grain size increased the predicted habitat area. The extent size and AUC showed a positive correlation (R2 = 0.18). Predicted suitability habitat also decreased as extent size increased (R2 = 0.49). Spatial congruence AUC fluctuated within a small range and the maximum difference occurred between models of 1 × 1 and 2.5 × 2.5 km. These results showed that an increase in extent size is more accurate than an increase in grain size, and the maximum accuracy for predicting distribution of goitered gazelle in Iran was obtained if the grain size and extent size were 750 m.
","language":"English","publisher":"Tubitak","doi":"10.3906/zoo-1505-38","usgsCitation":"Khosravi, R., Hemami, M., Malekian, M., Flint, A.L., and Flint, L.E., 2016, Maxent modeling for predicting potential distribution of goitered gazelle in central Iran: the effect of extent and grain size on performance of the model: Turkish Journal of Zoology, v. 40, p. 574-585, https://doi.org/10.3906/zoo-1505-38.","productDescription":"12 p.","startPage":"574","endPage":"585","ipdsId":"IP-070743","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":470594,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.3906/zoo-1505-38","text":"External Repository"},{"id":357988,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Iran","volume":"40","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc032a7e4b0fc368eb53a6b","contributors":{"authors":[{"text":"Khosravi, Rasoul","contributorId":208380,"corporation":false,"usgs":false,"family":"Khosravi","given":"Rasoul","email":"","affiliations":[{"id":37792,"text":"Isfahan University of Technology, Iran","active":true,"usgs":false}],"preferred":false,"id":746911,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hemami, Mahmoud-Reza","contributorId":208381,"corporation":false,"usgs":false,"family":"Hemami","given":"Mahmoud-Reza","email":"","affiliations":[{"id":37792,"text":"Isfahan University of Technology, Iran","active":true,"usgs":false}],"preferred":false,"id":746912,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Malekian, Mansoureh","contributorId":208382,"corporation":false,"usgs":false,"family":"Malekian","given":"Mansoureh","email":"","affiliations":[{"id":37792,"text":"Isfahan University of Technology, Iran","active":true,"usgs":false}],"preferred":false,"id":746913,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":746914,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":746910,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70173934,"text":"70173934 - 2016 - Persistent slip rate discrepancies in the eastern California (USA) shear zone","interactions":[],"lastModifiedDate":"2018-08-07T13:52:11","indexId":"70173934","displayToPublicDate":"2016-09-01T13:52:03","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Persistent slip rate discrepancies in the eastern California (USA) shear zone","docAbstract":"Understanding fault slip rates in the eastern California shear zone (ECSZ) using GPS geodesy is complicated by potentially overlapping strain signals due to many sub-parallel strike-slip faults and by inconsistencies with geologic slip rates. The role of fault system geometry in describing ECSZ deformation may be investigated with total variation regularization, which algorithmically determines a best-fitting geometry from an initial model with numerous faults, constrained by a western United States GPS velocity field. The initial dense model (1) enables construction of the first geodetically constrained block model to include all ECSZ faults with geologic slip rates, allowing direct geologic-geodetic slip rate comparisons, and (2) permits fault system geometries with many active faults that are analogous to distributed interseismic deformation. Beginning with 58 ECSZ blocks, a model containing 10 ECSZ blocks is most consistent with geologic slip rates, reproducing five of 11 within their reported uncertainties. The model fits GPS observations with a mean residual velocity of 1.5 mm/yr. Persistent geologic-geodetic slip rate discrepancies occur on the Calico and Garlock faults, on which we estimate slip rates of 7.6 mm/yr and <2 mm/yr, respectively, indicating that inconsistencies between geology and geodesy may be concentrated on or near these faults and are not due to pervasive distributed deformation in the region. Discrepancies may in part be due to postseismic relaxation following the A.D. 1992 Mw 7.3 Landers and 1999 Mw 7.1 Hector Mine earthquakes. Otherwise, resolving geologic-geodetic discrepancies would require as much as 11.4 mm/yr of off-fault deformation within <10 km of the main ECSZ faults, with ∼5 mm/yr concentrated near the Calico fault.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/G37967.1","usgsCitation":"Evans, E., Thatcher, W.R., Pollitz, F., and Murray, J.R., 2016, Persistent slip rate discrepancies in the eastern California (USA) shear zone: Geology, v. 44, no. 9, p. 691-694, https://doi.org/10.1130/G37967.1.","productDescription":"4 p.","startPage":"691","endPage":"694","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071254","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":356289,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","volume":"44","issue":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-01","publicationStatus":"PW","scienceBaseUri":"5b6fc890e4b0f5d57878ec38","contributors":{"authors":[{"text":"Evans, Eileen 0000-0002-7290-5269 eevans@usgs.gov","orcid":"https://orcid.org/0000-0002-7290-5269","contributorId":167021,"corporation":false,"usgs":true,"family":"Evans","given":"Eileen","email":"eevans@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":639547,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thatcher, Wayne R. 0000-0001-6324-545X thatcher@usgs.gov","orcid":"https://orcid.org/0000-0001-6324-545X","contributorId":2599,"corporation":false,"usgs":true,"family":"Thatcher","given":"Wayne","email":"thatcher@usgs.gov","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":639548,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pollitz, Frederick 0000-0002-4060-2706 fpollitz@usgs.gov","orcid":"https://orcid.org/0000-0002-4060-2706","contributorId":139578,"corporation":false,"usgs":true,"family":"Pollitz","given":"Frederick","email":"fpollitz@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":639549,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Murray, Jessica R. 0000-0002-6144-1681 jrmurray@usgs.gov","orcid":"https://orcid.org/0000-0002-6144-1681","contributorId":2759,"corporation":false,"usgs":true,"family":"Murray","given":"Jessica","email":"jrmurray@usgs.gov","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":639550,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70176197,"text":"70176197 - 2016 - Global biodiversity monitoring: from data sources to essential biodiversity variables","interactions":[],"lastModifiedDate":"2017-08-16T17:34:04","indexId":"70176197","displayToPublicDate":"2016-09-01T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Global biodiversity monitoring: from data sources to essential biodiversity variables","docAbstract":"Essential Biodiversity Variables (EBVs) consolidate information from varied biodiversity observation sources. Here we demonstrate the links between data sources, EBVs and indicators and discuss how different sources of biodiversity observations can be harnessed to inform EBVs. We classify sources of primary observations into four types: extensive and intensive monitoring schemes, ecological field studies and satellite remote sensing. We characterize their geographic, taxonomic and temporal coverage. Ecological field studies and intensive monitoring schemes inform a wide range of EBVs, but the former tend to deliver short-term data, while the geographic coverage of the latter is limited. In contrast, extensive monitoring schemes mostly inform the population abundance EBV, but deliver long-term data across an extensive network of sites. Satellite remote sensing is particularly suited to providing information on ecosystem function and structure EBVs. Biases behind data sources may affect the representativeness of global biodiversity datasets. To improve them, researchers must assess data sources and then develop strategies to compensate for identified gaps. We draw on the population abundance dataset informing the Living Planet Index (LPI) to illustrate the effects of data sources on EBV representativeness. We find that long-term monitoring schemes informing the LPI are still scarce outside of Europe and North America and that ecological field studies play a key role in covering that gap. Achieving representative EBV datasets will depend both on the ability to integrate available data, through data harmonization and modeling efforts, and on the establishment of new monitoring programs to address critical data gaps.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2016.07.014","usgsCitation":"Proenca, V., Martin, L.J., Pereira, H.M., Fernandez, M., McRae, L., Belnap, J., Böhm, M., Brummitt, N., Garcia-Moreno, J., Gregory, R., Honrado, J.P., Jurgens, N., Opige, M., Schmeller, D.S., Tiago, P., and van Sway, C.A., 2016, Global biodiversity monitoring: from data sources to essential biodiversity variables: Biological Conservation, v. 213, no. B, p. 256-263, https://doi.org/10.1016/j.biocon.2016.07.014.","productDescription":"8 p.","startPage":"256","endPage":"263","ipdsId":"IP-066053","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":470595,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2016.07.014","text":"Publisher Index Page"},{"id":328158,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"213","issue":"B","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57c94320e4b0f2f0cec13592","contributors":{"authors":[{"text":"Proenca, Vania","contributorId":174213,"corporation":false,"usgs":false,"family":"Proenca","given":"Vania","email":"","affiliations":[{"id":27383,"text":"MARETEC, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa,","active":true,"usgs":false}],"preferred":false,"id":647734,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Laura J.","contributorId":147654,"corporation":false,"usgs":false,"family":"Martin","given":"Laura","email":"","middleInitial":"J.","affiliations":[{"id":16883,"text":"Department of Natural Resources, Cornell University, Ithaca, NY, 14853, USA","active":true,"usgs":false}],"preferred":false,"id":647735,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pereira, Henrique M.","contributorId":147659,"corporation":false,"usgs":false,"family":"Pereira","given":"Henrique","email":"","middleInitial":"M.","affiliations":[{"id":16888,"text":"(1) German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, 04103 Leipzig, Germany; (2) Institute of Biology, Martin Luther University Halle Wittenberg, Am Kirchtor 1, 06108 Halle (Saale), Germany","active":true,"usgs":false}],"preferred":false,"id":647736,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fernandez, Miguel","contributorId":174214,"corporation":false,"usgs":false,"family":"Fernandez","given":"Miguel","email":"","affiliations":[{"id":27384,"text":"German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, Leipzig, Germany","active":true,"usgs":false}],"preferred":false,"id":647737,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McRae, Louise","contributorId":41703,"corporation":false,"usgs":true,"family":"McRae","given":"Louise","email":"","affiliations":[],"preferred":false,"id":647738,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":647733,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Böhm, Monika","contributorId":11095,"corporation":false,"usgs":true,"family":"Böhm","given":"Monika","affiliations":[],"preferred":false,"id":647739,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brummitt, Neil","contributorId":147648,"corporation":false,"usgs":false,"family":"Brummitt","given":"Neil","email":"","affiliations":[{"id":16878,"text":"Department of Life Sciences, The Natural History Museum, Cromwell Road, South Kensington, London SW7 5BD, UK","active":true,"usgs":false}],"preferred":false,"id":647740,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Garcia-Moreno, Jaime","contributorId":174215,"corporation":false,"usgs":false,"family":"Garcia-Moreno","given":"Jaime","affiliations":[{"id":27385,"text":"ESiLi consulting. Het Haam 16, 6846 KW Arnhem, The Netherlands","active":true,"usgs":false}],"preferred":false,"id":647741,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Gregory, Richard D.","contributorId":96161,"corporation":false,"usgs":true,"family":"Gregory","given":"Richard D.","affiliations":[],"preferred":false,"id":647742,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Honrado, Joao P","contributorId":174216,"corporation":false,"usgs":false,"family":"Honrado","given":"Joao","email":"","middleInitial":"P","affiliations":[{"id":27386,"text":"CIBIO / InBIO - Rede de Investigação em Biodiversidade e Biologia Evolutiva & Faculdade de Ciencias, Universidade do Porto, Vairao, Portugal","active":true,"usgs":false}],"preferred":false,"id":647743,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Jurgens, Norbert","contributorId":174217,"corporation":false,"usgs":false,"family":"Jurgens","given":"Norbert","email":"","affiliations":[{"id":27387,"text":"Biodiversity, Evolution and Ecology (BEE), Biocenter Klein Flottbek, University of Hamburg, Hamburg, Germany","active":true,"usgs":false}],"preferred":false,"id":647744,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Opige, Michael","contributorId":174218,"corporation":false,"usgs":false,"family":"Opige","given":"Michael","email":"","affiliations":[{"id":27388,"text":"NatureUganda, The East Africa Natural History Society, P. O. Box 27034, Katalima Crescent, Naguru,Kampala, Uganda","active":true,"usgs":false}],"preferred":false,"id":647745,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Schmeller, Dirk S.","contributorId":147645,"corporation":false,"usgs":false,"family":"Schmeller","given":"Dirk","email":"","middleInitial":"S.","affiliations":[{"id":16875,"text":"(1)Dept of Conservation Biology, Helmholtz Centre for Environmental Research – UFZ, Permoserstrasse 15, 04318 Leipzig, Germany;","active":true,"usgs":false}],"preferred":false,"id":647747,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Tiago, Patricia","contributorId":174220,"corporation":false,"usgs":false,"family":"Tiago","given":"Patricia","email":"","affiliations":[{"id":27390,"text":"Centre for Ecology, Evolution and Environmental Changes (CE3C), Faculdade de Ciências, Universidade de Lisboa, Lisbon, Portugal","active":true,"usgs":false}],"preferred":false,"id":647748,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"van Sway, Chris A","contributorId":174221,"corporation":false,"usgs":false,"family":"van Sway","given":"Chris","email":"","middleInitial":"A","affiliations":[{"id":27391,"text":"Dutch Butterfly Conservation, P.O. Box 506, 6700 AMWageningen, Netherlands","active":true,"usgs":false}],"preferred":false,"id":647749,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70176196,"text":"70176196 - 2016 - Duration of fuels reduction following prescribed fire in coniferous forests of U.S. national parks in California and the Colorado Plateau","interactions":[],"lastModifiedDate":"2016-09-01T09:41:08","indexId":"70176196","displayToPublicDate":"2016-09-01T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Duration of fuels reduction following prescribed fire in coniferous forests of U.S. national parks in California and the Colorado Plateau","docAbstract":"Prescribed fire is a widely used forest management tool, yet the long-term effectiveness of prescribed fire in reducing fuels and fire hazards in many vegetation types is not well documented. We assessed the magnitude and duration of reductions in surface fuels and modeled fire hazards in coniferous forests across nine U.S. national parks in California and the Colorado Plateau. We used observations from a prescribed fire effects monitoring program that feature standard forest and surface fuels inventories conducted pre-fire, immediately following an initial (first-entry) prescribed fire and at varying intervals up to >20 years post-fire. A subset of these plots was subjected to prescribed fire again (second-entry) with continued monitoring. Prescribed fire effects were highly variable among plots, but we found on average first-entry fires resulted in a significant post-fire reduction in surface fuels, with litter and duff fuels not returning to pre-fire levels over the length of our observations. Fine and coarse woody fuels often took a decade or longer to return to pre-fire levels. For second-entry fires we found continued fuels reductions, without strong evidence of fuel loads returning to levels observed immediately prior to second-entry fire. Following both first- and second-entry fire there were increases in estimated canopy base heights, along with reductions in estimated canopy bulk density and modeled flame lengths. We did not find evidence of return to pre-fire conditions during our observation intervals for these measures of fire hazard. Our results show that prescribed fire can be a valuable tool to reduce fire hazards and, depending on forest conditions and the measurement used, reductions in fire hazard can last for decades. Second-entry prescribed fire appeared to reinforce the reduction in fuels and fire hazard from first-entry fires.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2016.07.028","usgsCitation":"van Mantgem, P.J., Lalemand, L., Keifer, M., and Kane, J., 2016, Duration of fuels reduction following prescribed fire in coniferous forests of U.S. national parks in California and the Colorado Plateau: Forest Ecology and Management, v. 379, p. 265-272, https://doi.org/10.1016/j.foreco.2016.07.028.","productDescription":"8 p.","startPage":"265","endPage":"272","ipdsId":"IP-075251","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":328155,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"379","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57c9431de4b0f2f0cec13571","contributors":{"authors":[{"text":"van Mantgem, Phillip J. 0000-0002-3068-9422 pvanmantgem@usgs.gov","orcid":"https://orcid.org/0000-0002-3068-9422","contributorId":2838,"corporation":false,"usgs":true,"family":"van Mantgem","given":"Phillip","email":"pvanmantgem@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":647729,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lalemand, Laura 0000-0001-8025-5975 llalemand@usgs.gov","orcid":"https://orcid.org/0000-0001-8025-5975","contributorId":174212,"corporation":false,"usgs":true,"family":"Lalemand","given":"Laura","email":"llalemand@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":647730,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keifer, MaryBeth","contributorId":21841,"corporation":false,"usgs":true,"family":"Keifer","given":"MaryBeth","affiliations":[],"preferred":false,"id":647731,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kane, Jeffrey M.","contributorId":35169,"corporation":false,"usgs":true,"family":"Kane","given":"Jeffrey M.","affiliations":[],"preferred":false,"id":647732,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70209673,"text":"70209673 - 2016 - Highly conductive horizons in the Mesoproterozoic Belt-Purcell Basin: Sulfidic early basin strata as key markers of Cordilleran shortening and Eocene extension","interactions":[],"lastModifiedDate":"2020-04-21T14:45:32.418007","indexId":"70209673","displayToPublicDate":"2016-09-01T09:45:09","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Highly conductive horizons in the Mesoproterozoic Belt-Purcell Basin: Sulfidic early basin strata as key markers of Cordilleran shortening and Eocene extension","docAbstract":"We investigated the crustal structure of the central Mesoproterozoic Belt Basin in northwestern Montana and northern Idaho using a crustal resistivity section derived from a transect of new short- and long-period magnetotelluric (MT) stations. Two- and three-dimensional resistivity models were generated from these data in combination with data collected previously along three parallel short-period MT profiles and from EarthScope MT stations. The models were interpreted together with coincident deep seismic-reflection data collected during the Consortium for Continental Reflection Profiling (COCORP) program. The upper-crustal portion of the resistivity model correlates well with the mapped surface geology and reveals a three-layer resistivity stratigraphy, best expressed beneath the axis of the Libby syncline. Prominent features in the resistivity models are thick conductive horizons that serve as markers in reconstructing the disrupted basin stratigraphy. The uppermost unit (up to 5 km thick), consisting of all of the Belt Supergroup above the Prichard Formation, is highly resistive (1000–10,000 Ω·m) and has relatively low seismic layer velocities. The intermediate unit (up to 7 km thick) consists of the exposed Prichard Formation and 3+ km of stratigraphy below the deepest stratigraphic exposures of the unit. The intermediate unit has low to moderate resistivity (30–200 Ω·m), relatively high seismic velocities, and high seismic reflectivity, with the latter two characteristics resulting from an abundance of thick syndepositional mafic sills. The lowest unit (5–10 km thick) is nowhere exposed but underlies the intermediate unit and has very high conductivity (4–8 Ω·m) and intermediate seismic velocities. This 17–22-km-thick three-layer stratigraphy is repeated below the Libby syncline, with a base at ~37 km depth. Seismic layer velocities indicate high mantle-like velocities below 37 km beneath the Libby syncline. The continuous high-conductivity layer in the lower repeated section is apparently displaced ~26 km to the east above a low-angle normal fault inferred to be the downdip continuation of the Eocene, east-dipping Purcell Trench detachment fault. Reversal of that and other Eocene displacements reveals a >50-km-thick crustal section at late Paleocene time. Further reversal of apparent thrust displacements of the three-layer stratigraphy along the Lewis, Pinkham, Libby, and Moyie thrusts allows construction of a restored cross section prior to the onset of Cordilleran thrusting in the Jurassic. A total of ~220 km of Jurassic–Paleocene shortening along these faults is indicated. The enhanced conductivity within the lowest (unexposed) Belt stratigraphic unit is primarily attributed to one or more horizons of laminated metallic sulfides; graphite, though not described within the Belt Supergroup, may also contribute to the enhanced conductivity of the lowest stratigraphic unit. A narrow conductive horizon observed within the Prichard Formation in the eastern part of the transect correlates with the stratigraphic position of the world-class Sullivan sedimentary exhalative massive sulfide deposit in southern British Columbia, and it may represent a distal sulfide blanket deposit broadly dispersed across the Belt Basin. By analogy, the thick conductive sub–Prichard Formation unit may represent repeated sulfide depositional events within the early rift history of the basin, potentially driven by hydrothermal fluids released during basaltic underplating of attenuated continental crust.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Belt basin: Window to Mesoproterozoic Earth","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2016.2522(12)","collaboration":"","usgsCitation":"Bedrosian, P.A., and Box, S.E., 2016, Highly conductive horizons in the Mesoproterozoic Belt-Purcell Basin: Sulfidic early basin strata as key markers of Cordilleran shortening and Eocene extension, chap. of Belt basin: Window to Mesoproterozoic Earth, v. 522, p. 305-339, https://doi.org/10.1130/2016.2522(12).","productDescription":"36 p.","startPage":"305","endPage":"339","ipdsId":"IP-058401","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":470598,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/2016.2522(12)","text":"Publisher Index Page"},{"id":374153,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alberta, British Columbia, Idaho, Montana, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.14672851562499,\n 45.034714778688624\n ],\n [\n -110.775146484375,\n 45.034714778688624\n ],\n [\n -110.775146484375,\n 50.15578588538455\n ],\n [\n -119.14672851562499,\n 50.15578588538455\n ],\n [\n -119.14672851562499,\n 45.034714778688624\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"522","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":787470,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Box, Stephen E. 0000-0002-5268-8375 sbox@usgs.gov","orcid":"https://orcid.org/0000-0002-5268-8375","contributorId":1843,"corporation":false,"usgs":true,"family":"Box","given":"Stephen","email":"sbox@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":787471,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70195835,"text":"70195835 - 2016 - Estimating microcystin levels at recreational sites in western Lake Erie and Ohio","interactions":[],"lastModifiedDate":"2018-03-07T10:40:01","indexId":"70195835","displayToPublicDate":"2016-09-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1878,"text":"Harmful Algae","active":true,"publicationSubtype":{"id":10}},"title":"Estimating microcystin levels at recreational sites in western Lake Erie and Ohio","docAbstract":"Cyanobacterial harmful algal blooms (cyanoHABs) and associated toxins, such as microcystin, are a major global water-quality issue. Water-resource managers need tools to quickly predict when and where toxin-producing cyanoHABs will occur. This could be done by using site-specific models that estimate the potential for elevated toxin concentrations that cause public health concerns. With this study, samples were collected at three Ohio lakes to identify environmental and water-quality factors to develop linear-regression models to estimate microcystin levels. Measures of the algal community (phycocyanin, cyanobacterial biovolume, and cyanobacterial gene concentrations) and pH were most strongly correlated with microcystin concentrations. Cyanobacterial genes were quantified for general cyanobacteria, general Microcystis and Dolichospermum, and for microcystin synthetase (mcyE) for Microcystis, Dolichospermum, and Planktothrix. For phycocyanin, the relations were different between sites and were different between hand-held measurements on-site and nearby continuous monitor measurements for the same site. Continuous measurements of parameters such as phycocyanin, pH, and temperature over multiple days showed the highest correlations to microcystin concentrations. The development of models with high R2values (0.81–0.90), sensitivities (92%), and specificities (100%) for estimating microcystin concentrations above or below the Ohio Recreational Public Health Advisory level of 6 μg L−1 was demonstrated for one site; these statistics may change as more data are collected in subsequent years. This study showed that models could be developed for estimates of exceeding a microcystin threshold concentration at a recreational freshwater lake site, with potential to expand their use to provide relevant public health information to water resource managers and the public for both recreational and drinking waters.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.hal.2016.07.003","usgsCitation":"Francy, D.S., Brady, A.M., Ecker, C.D., Graham, J.L., Stelzer, E.A., Struffolino, P., and Loftin, K.A., 2016, Estimating microcystin levels at recreational sites in western Lake Erie and Ohio: Harmful Algae, v. 58, p. 23-34, https://doi.org/10.1016/j.hal.2016.07.003.","productDescription":"12 p.","startPage":"23","endPage":"34","ipdsId":"IP-068433","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":352264,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","otherGeospatial":"Lake Erie","volume":"58","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee98be4b0da30c1bfc568","contributors":{"authors":[{"text":"Francy, Donna S. 0000-0001-9229-3557 dsfrancy@usgs.gov","orcid":"https://orcid.org/0000-0001-9229-3557","contributorId":1853,"corporation":false,"usgs":true,"family":"Francy","given":"Donna","email":"dsfrancy@usgs.gov","middleInitial":"S.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":730225,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brady, Amie M.G. 0000-0002-7414-0992 amgbrady@usgs.gov","orcid":"https://orcid.org/0000-0002-7414-0992","contributorId":2544,"corporation":false,"usgs":true,"family":"Brady","given":"Amie","email":"amgbrady@usgs.gov","middleInitial":"M.G.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":730222,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ecker, Christopher D. 0000-0003-0353-5855 cdecker@usgs.gov","orcid":"https://orcid.org/0000-0003-0353-5855","contributorId":149530,"corporation":false,"usgs":true,"family":"Ecker","given":"Christopher","email":"cdecker@usgs.gov","middleInitial":"D.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":false,"id":730221,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Graham, Jennifer L. 0000-0002-6420-9335 jlgraham@usgs.gov","orcid":"https://orcid.org/0000-0002-6420-9335","contributorId":1769,"corporation":false,"usgs":true,"family":"Graham","given":"Jennifer","email":"jlgraham@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":730220,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stelzer, Erin A. 0000-0001-7645-7603 eastelzer@usgs.gov","orcid":"https://orcid.org/0000-0001-7645-7603","contributorId":1933,"corporation":false,"usgs":true,"family":"Stelzer","given":"Erin","email":"eastelzer@usgs.gov","middleInitial":"A.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":730224,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Struffolino, Pamela","contributorId":202922,"corporation":false,"usgs":false,"family":"Struffolino","given":"Pamela","affiliations":[{"id":12455,"text":"University of Toledo","active":true,"usgs":false}],"preferred":false,"id":730219,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Loftin, Keith A. 0000-0001-5291-876X kloftin@usgs.gov","orcid":"https://orcid.org/0000-0001-5291-876X","contributorId":868,"corporation":false,"usgs":true,"family":"Loftin","given":"Keith","email":"kloftin@usgs.gov","middleInitial":"A.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":730223,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70185032,"text":"70185032 - 2016 - Iron oxide minerals in dust-source sediments from the Bodélé Depression, Chad: Implications for radiative properties and Fe bioavailability of dust plumes from the Sahara","interactions":[],"lastModifiedDate":"2017-03-14T12:15:24","indexId":"70185032","displayToPublicDate":"2016-09-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":666,"text":"Aeolian Research","active":true,"publicationSubtype":{"id":10}},"title":"Iron oxide minerals in dust-source sediments from the Bodélé Depression, Chad: Implications for radiative properties and Fe bioavailability of dust plumes from the Sahara","docAbstract":"Atmospheric mineral dust can influence climate and biogeochemical cycles. An important component of mineral dust is ferric oxide minerals (hematite and goethite) which have been shown to influence strongly the optical properties of dust plumes and thus affect the radiative forcing of global dust. Here we report on the iron mineralogy of dust-source samples from the Bodélé Depression (Chad, north-central Africa), which is estimated to be Earth’s most prolific dust producer and may be a key contributor to the global radiative budget of the atmosphere as well as to long-range nutrient transport to the Amazon Basin. By using a combination of magnetic property measurements, Mössbauer spectroscopy, reflectance spectroscopy, chemical analysis, and scanning electron microscopy, we document the abundance and relative amounts of goethite, hematite, and magnetite in dust-source samples from the Bodélé Depression. The partition between hematite and goethite is important to know to improve models for the radiative effects of ferric oxide minerals in mineral dust aerosols. The combination of methods shows (1) the dominance of goethite over hematite in the source sediments, (2) the abundance and occurrences of their nanosize components, and (3) the ubiquity of magnetite, albeit in small amounts. Dominant goethite and subordinate hematite together compose about 2% of yellow-reddish dust-source sediments from the Bodélé Depression and contribute strongly to diminution of reflectance in bulk samples. These observations imply that dust plumes from the Bodélé Depression that are derived from goethite-dominated sediments strongly absorb solar radiation. The presence of ubiquitous magnetite (0.002–0.57 wt%) is also noteworthy for its potentially higher solubility relative to ferric oxide and for its small sizes, including PM < 0.1 μm. For all examined samples, the average iron apportionment is estimated at about 33% in ferric oxide minerals, 1.4% in magnetite, and 65% in ferric silicates. Structural iron in clay minerals may account for much of the iron in the ferric silicates. We estimate that the mean ferric oxides flux exported from the Bodélé Depression is 0.9 Tg/yr with greater than 50% exported as ferric oxide nanoparticles (<0.1 μm). The high surface-to-volume ratios of ferric oxide nanoparticles once entrained into dust plumes may facilitate increased atmospheric chemical and physical processing and affect iron solubility and bioavailability to marine and terrestrial ecosystems.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.aeolia.2016.07.001","usgsCitation":"Moskowitz, B.M., Reynolds, R.L., Goldstein, H.L., Beroquo, T., Kokaly, R.F., and Bristow, C.S., 2016, Iron oxide minerals in dust-source sediments from the Bodélé Depression, Chad: Implications for radiative properties and Fe bioavailability of dust plumes from the Sahara: Aeolian Research, v. 22, p. 93-106, https://doi.org/10.1016/j.aeolia.2016.07.001.","productDescription":"14 p.","startPage":"93","endPage":"106","ipdsId":"IP-071700","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":462095,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.aeolia.2016.07.001","text":"Publisher Index Page"},{"id":337498,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58c90126e4b0849ce97abcdb","contributors":{"authors":[{"text":"Moskowitz, Bruce M.","contributorId":189164,"corporation":false,"usgs":false,"family":"Moskowitz","given":"Bruce","email":"","middleInitial":"M.","affiliations":[{"id":17684,"text":"University of Minnesota, Minneapolis, MN","active":true,"usgs":false}],"preferred":false,"id":684016,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reynolds, Richard L. 0000-0002-4572-2942 rreynolds@usgs.gov","orcid":"https://orcid.org/0000-0002-4572-2942","contributorId":147880,"corporation":false,"usgs":true,"family":"Reynolds","given":"Richard","email":"rreynolds@usgs.gov","middleInitial":"L.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":271,"text":"Federal Center","active":false,"usgs":true}],"preferred":true,"id":684017,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goldstein, Harland L. 0000-0002-6092-8818 hgoldstein@usgs.gov","orcid":"https://orcid.org/0000-0002-6092-8818","contributorId":147881,"corporation":false,"usgs":true,"family":"Goldstein","given":"Harland","email":"hgoldstein@usgs.gov","middleInitial":"L.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":684015,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beroquo, Thelma","contributorId":189165,"corporation":false,"usgs":false,"family":"Beroquo","given":"Thelma","email":"","affiliations":[],"preferred":false,"id":684018,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kokaly, Raymond F. 0000-0003-0276-7101 raymond@usgs.gov","orcid":"https://orcid.org/0000-0003-0276-7101","contributorId":150717,"corporation":false,"usgs":true,"family":"Kokaly","given":"Raymond","email":"raymond@usgs.gov","middleInitial":"F.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":684019,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bristow, Charlie S","contributorId":189166,"corporation":false,"usgs":false,"family":"Bristow","given":"Charlie","email":"","middleInitial":"S","affiliations":[],"preferred":false,"id":684020,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70176518,"text":"70176518 - 2016 - Balanced sediment fluxes in southern California’s Mediterranean-climate zone salt marshes","interactions":[],"lastModifiedDate":"2017-07-19T15:38:12","indexId":"70176518","displayToPublicDate":"2016-09-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Balanced sediment fluxes in southern California’s Mediterranean-climate zone salt marshes","docAbstract":"Salt marsh elevation and geomorphic stability depends on mineral sedimentation. Many Mediterranean-climate salt marshes along southern California, USA coast import sediment during El Niño storm events, but sediment fluxes and mechanisms during dry weather are potentially important for marsh stability. We calculated tidal creek sediment fluxes within a highly modified, sediment-starved, 1.5-km2 salt marsh (Seal Beach) and a less modified 1-km2marsh (Mugu) with fluvial sediment supply. We measured salt marsh plain suspended sediment concentration and vertical accretion using single stage samplers and marker horizons. At Seal Beach, a 2014 storm yielded 39 and 28 g/s mean sediment fluxes and imported 12,000 and 8800 kg in a western and eastern channel. Western channel storm imports offset 8700 kg exported during 2 months of dry weather, while eastern channel storm imports augmented 9200 kg imported during dry weather. During the storm at Mugu, suspended sediment concentrations on the marsh plain increased by a factor of four; accretion was 1–2 mm near creek levees. An exceptionally high tide sequence yielded 4.4 g/s mean sediment flux, importing 1700 kg: 20 % of Mugu’s dry weather fluxes. Overall, low sediment fluxes were observed, suggesting that these salt marshes are geomorphically stable during dry weather conditions. Results suggest storms and high lunar tides may play large roles, importing sediment and maintaining dry weather sediment flux balances for southern California salt marshes. However, under future climate change and sea level rise scenarios, results suggest that balanced sediment fluxes lead to marsh elevational instability based on estimated mineral sediment deficits.
In 2013, the U.S. Geological Survey, in cooperation with the Minnesota Pollution Control Agency, completed a geomorphic assessment of 51 Duluth-area stream sites in 20 basins to describe and document the stream geomorphic changes associated with the June 2012 flood. Heavy rainfall caused flood peaks with annual exceedance probabilities of less than 0.002 (flood recurrence interval of greater than 500 years) on large and small streams in and surrounding the Duluth area. A geomorphic segment-scale classification previously developed in 2003–4 by the U.S. Geological Survey for Duluth-area streams was used as a framework to characterize the observed flood-related responses along a longitudinal continuum from headwaters to rivermouths at Lake Superior related to drainage network position, slope, geologic setting, and valley type. Field assessments in 2013 followed and expanded on techniques used in 2003–4 at intensive and rapid sites. A third level of assessment was added in 2013 to increase the amount of quantitative data at a subset of 2003–4 rapid sites. Characteristics of channel morphology, channel bed substrate, exposed bars and soft sediment deposition, large wood, pools, and bank erosion were measured; and repeat photographs were taken. Additional measurements in 2013 included identification of Rosgen Level II stream types. The comparative analyses of field data collected in 2003–4 and again in 2013 indicated notable geomorphic changes, some of them expected and others not. As expected, in headwaters with gently sloping wetland segments, geomorphic changes were negligible (little measured or observed change). Downstream, middle main stems generally had bank and bluff erosion and bar formation as expected. Steep bedrock sites along middle and lower main stems had localized bank and bluff erosion in short sections with intermittent bedrock. Lower main stem and alluvial sites had bank erosion, widening, gravel bar deposition, and aggradation. Bar formation and accumulation of gravel was more widespread than expected among all main stems, especially for sites upstream and downstream from channel constrictions from road crossings, or even steep sites with localized, more gently sloping sections. Decreases in large wood and pools also were observed throughout the longitudinal continuum of main-stem sites, with immediate implications for fish and benthic invertebrate aquatic habitat. Whether or not the geomorphic conditions will return to their preflood condition depends on the location along the longitudinal continuum. The amount of large wood and pools may return after more moderate floods, whereas bars with coarse material may remain in place, locally altering flow direction and causing continued bank erosion. Results from this study can be used by local managers in postflood reconstruction efforts and provide baseline information for continued monitoring of geomorphic responses to the June 2012 flood.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165104","collaboration":"Prepared in cooperation with the Minnesota Pollution Control Agency","usgsCitation":"Fitzpatrick, F.A., Ellison, C.A., Czuba, C.R., Young, B.M., McCool, M.M., and Groten, J.T., 2016, Geomorphic responses of Duluth-area streams to the June 2012 flood, Minnesota: U.S. Geological Survey Scientific Investigations Report 2016–5104, 53 p. with appendixes, https://dx.doi.org/10.3133/sir20165104.","productDescription":"Report: vi, 53 p.; Appendixes: 1–4","numberOfPages":"64","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-065922","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":328169,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5104/sir20165104_appendix4.xlsx","text":"Appendix 4","size":"990 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016–5104 Appendix 4"},{"id":328168,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5104/sir20165104_appendix3.zip","text":"Appendix 3","size":"2.36 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2016–5104 Appendix 3"},{"id":328167,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5104/sir20165104_appendix2.pdf","text":"Appendix 2","size":"83 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5104 Appendix 2"},{"id":328166,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5104/sir20165104_appendix1.xlsx","text":"Appendix 1","size":"30.3 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016–5104 Appendix 1"},{"id":328164,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5104/coverthb.jpg"},{"id":328165,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5104/sir20165104.pdf","text":"Report","size":"5.94 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5104"}],"country":"United States","state":"Minnesota","city":"Duluth","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.92741394042969,\n 46.87849898215226\n ],\n [\n -92.01805114746094,\n 46.924007100770275\n ],\n [\n -92.0328140258789,\n 46.981891954654735\n ],\n [\n -92.07744598388672,\n 47.003202171774475\n ],\n [\n -92.13890075683594,\n 46.96666516842388\n ],\n [\n -92.14302062988281,\n 46.90806019832023\n ],\n [\n -92.19657897949219,\n 46.81039934792954\n ],\n [\n -92.20756530761719,\n 46.785956378641224\n ],\n [\n -92.35382080078125,\n 46.69301892051677\n ],\n [\n -92.31021881103516,\n 46.66758028334327\n ],\n [\n -92.24292755126953,\n 46.65438516352555\n ],\n [\n -92.20378875732422,\n 46.65532777888051\n ],\n [\n -92.20172882080078,\n 46.703614817813545\n ],\n [\n -92.1866226196289,\n 46.71915170604123\n ],\n [\n -92.1488571166992,\n 46.71891633201399\n ],\n [\n -92.13924407958984,\n 46.739390031317825\n ],\n [\n -92.02869415283203,\n 46.822616668804926\n ],\n [\n -91.92741394042969,\n 46.87849898215226\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Minnesota Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, MN 55112
Although the round goby (Neogobius melanostomus) has become established throughout the Laurentian Great Lakes, information is scarce on spatial variation in round goby growth between and within lakes. Based on a sample of 754 specimens captured in 2014, age, growth, and mortality of round gobies at four locations in Lake Huron were assessed via otolith analysis. Total length (TL) of round gobies ranged from 44 to 111 mm for Saginaw Bay, from 45 to 115 mm for Rockport, from 50 to 123 mm for Hammond Bay, and from 51 to 118 mm for Thunder Bay. Estimated ages of round gobies ranged from 2 to 5 years for Saginaw Bay, from 2 to 6 years for Rockport, and from 2 to 7 years for Hammond Bay and Thunder Bay. Sex-specific, body–otolith relationships were used to back-calculate total lengths at age, which were then fitted to von Bertalanffy growth models. For each sex, round goby growth showed significant spatial variation among the four locations within Lake Huron. At all four locations in Lake Huron, males grew significantly faster than females and attained a larger asymptotic length than females. Annual mortality rate estimates were high (62 to 85%), based on catch-curve analysis, suggesting that round gobies may be under predatory control in Lake Huron.
","language":"English","publisher":"International Association for Great Lakes Research","doi":"10.1016/j.jglr.2016.08.010","usgsCitation":"Duan, Y.J., Madenjian, C.P., Xie, C., Diana, J., O’Brien, T.P., Zhao, Y.M., He, J.X., Farha, S., and Huo, B., 2016, Age and growth of round gobies in Lake Huron: Implications for food web dynamics: Journal of Great Lakes Research, v. 42, no. 6, p. 1443-1451, https://doi.org/10.1016/j.jglr.2016.08.010.","productDescription":"9 p.","startPage":"1443","endPage":"1451","ipdsId":"IP-072233","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":462097,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2016.08.010","text":"Publisher Index Page"},{"id":328810,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Lake Huron","geographicExtents":"{\n 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0000-0002-0326-164X cmadenjian@usgs.gov","orcid":"https://orcid.org/0000-0002-0326-164X","contributorId":2200,"corporation":false,"usgs":true,"family":"Madenjian","given":"Charles","email":"cmadenjian@usgs.gov","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":649193,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Xie, Cong X.","contributorId":138597,"corporation":false,"usgs":false,"family":"Xie","given":"Cong X.","affiliations":[{"id":12457,"text":"Huazhong Agricultural University, College of Fisheries","active":true,"usgs":false}],"preferred":false,"id":649194,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Diana, James S.","contributorId":52137,"corporation":false,"usgs":true,"family":"Diana","given":"James S.","affiliations":[],"preferred":false,"id":649195,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"O’Brien, Timothy P. 0000-0003-4502-5204 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X.","contributorId":53254,"corporation":false,"usgs":true,"family":"He","given":"Ji","email":"","middleInitial":"X.","affiliations":[],"preferred":false,"id":649198,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Farha, Steve A. 0000-0001-9953-6996 sfarha@usgs.gov","orcid":"https://orcid.org/0000-0001-9953-6996","contributorId":5170,"corporation":false,"usgs":true,"family":"Farha","given":"Steve A.","email":"sfarha@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":649199,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Huo, Bin","contributorId":127463,"corporation":false,"usgs":false,"family":"Huo","given":"Bin","email":"","affiliations":[{"id":6955,"text":"College of Fisheries, Huazhong Agricultural University","active":true,"usgs":false}],"preferred":false,"id":649200,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70178867,"text":"70178867 - 2016 - Factors affecting wetland connectivity for wintering semipalmated sandpipers (Calidris pusilla) in the Caribbean","interactions":[],"lastModifiedDate":"2016-12-09T15:52:13","indexId":"70178867","displayToPublicDate":"2016-09-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3731,"text":"Waterbirds","onlineIssn":"19385390","printIssn":"15244695","active":true,"publicationSubtype":{"id":10}},"title":"Factors affecting wetland connectivity for wintering semipalmated sandpipers (Calidris pusilla) in the Caribbean","docAbstract":"Wetland connectivity provides migratory shorebirds varying options to meet energy requirements to survive and complete their annual cycle. Multiple factors mediate movement and residency of spatially segregated wetlands. Information on these factors is lacking in the tropics, yet such information is invaluable for conservation design. The influence of seven biotic and abiotic factors on local movement and residency rates of Semipalmated Sandpipers (Calidris pusilla) among three major wetlands in southwestern Puerto Rico in 2013–2014 was assessed using multi-state models. The model with highest support (AICc wi= 0.78) indicated that weekly residency rates increased seasonally, and were positively influenced by bird abundance and the interaction of prey density and rainfall. Movement rates were negatively influenced by inter-wetland distance, which varied annually, ranging from 0.01 ± 0.004 to 0.33 ± 0.08. Age class (adult, juvenile), extent of shoreline habitat (km), and body condition (estimated percent fat) did not influence residency rates (95% CIs overlapped Betas). Our findings indicated that coastal wetlands in southwestern Puerto Rico were connected, pointing at the joint value of salt flats and mangroves for overwintering Semipalmated Sandpipers. Connectivity between different types of wetlands likely widens resource diversity, which is essential for coping with unpredictable environments. Additional work is needed to generalize our understanding of inter-wetland dynamics and their potential benefits to inform shorebird conservation strategies in the Caribbean.
","language":"English","publisher":"The Waterbird Society","doi":"10.1675/063.039.0304","usgsCitation":"Parks, M.A., Collazo, J., and Ramos Alvarez, K.R., 2016, Factors affecting wetland connectivity for wintering semipalmated sandpipers (Calidris pusilla) in the Caribbean: Waterbirds, v. 39, no. 3, p. 250-259, https://doi.org/10.1675/063.039.0304.","productDescription":"10 p.","startPage":"250","endPage":"259","ipdsId":"IP-070138","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":331827,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.21641540527344,\n 17.928109247721633\n ],\n [\n -67.21641540527344,\n 18.061659495798455\n ],\n [\n -67.05162048339844,\n 18.061659495798455\n ],\n [\n -67.05162048339844,\n 17.928109247721633\n ],\n [\n -67.21641540527344,\n 17.928109247721633\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"39","issue":"3","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"584bd0dee4b077fc20250e0a","contributors":{"authors":[{"text":"Parks, Morgan A.","contributorId":177347,"corporation":false,"usgs":false,"family":"Parks","given":"Morgan","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":655404,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collazo, Jaime A. 0000-0002-1816-7744 jaime_collazo@usgs.gov","orcid":"https://orcid.org/0000-0002-1816-7744","contributorId":173448,"corporation":false,"usgs":true,"family":"Collazo","given":"Jaime A.","email":"jaime_collazo@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":655384,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramos Alvarez, Katsi R.","contributorId":177348,"corporation":false,"usgs":false,"family":"Ramos Alvarez","given":"Katsi","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":655405,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70184981,"text":"70184981 - 2016 - The water content of recurring slope lineae on Mars","interactions":[],"lastModifiedDate":"2017-03-14T15:35:52","indexId":"70184981","displayToPublicDate":"2016-09-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"The water content of recurring slope lineae on Mars","docAbstract":"Observations of recurring slope lineae (RSL) from the High-Resolution Imaging Science Experiment have been interpreted as present-day, seasonally variable liquid water flows; however, orbital spectroscopy has not confirmed the presence of liquid H2O, only hydrated salts. Thermal Emission Imaging System (THEMIS) temperature data and a numerical heat transfer model definitively constrain the amount of water associated with RSL. Surface temperature differences between RSL-bearing and dry RSL-free terrains are consistent with no water associated with RSL and, based on measurement uncertainties, limit the water content of RSL to at most 0.5–3 wt %. In addition, distinct high thermal inertia regolith signatures expected with crust-forming evaporitic salt deposits from cyclical briny water flows are not observed, indicating low water salinity (if any) and/or low enough volumes to prevent their formation. Alternatively, observed salts may be preexisting in soils at low abundances (i.e., near or below detection limits) and largely immobile. These RSL-rich surfaces experience ~100 K diurnal temperature oscillations, possible freeze/thaw cycles and/or complete evaporation on time scales that challenge their habitability potential. The unique surface temperature measurements provided by THEMIS are consistent with a dry RSL hypothesis or at least significantly limit the water content of Martian RSL.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2016GL070179","usgsCitation":"Edwards, C.S., and Piqueux, S., 2016, The water content of recurring slope lineae on Mars: Geophysical Research Letters, v. 43, no. 17, p. 8912-8919, https://doi.org/10.1002/2016GL070179.","productDescription":"8 p.","startPage":"8912","endPage":"8919","ipdsId":"IP-062637","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":500022,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/cf107a42de8c405cbe062d62efb1f576","text":"External Repository"},{"id":337537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"17","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-14","publicationStatus":"PW","scienceBaseUri":"58c90126e4b0849ce97abcdd","contributors":{"authors":[{"text":"Edwards, Christopher S. cedwards@usgs.gov","contributorId":147153,"corporation":false,"usgs":true,"family":"Edwards","given":"Christopher","email":"cedwards@usgs.gov","middleInitial":"S.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":false,"id":683815,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Piqueux, Sylvain","contributorId":56986,"corporation":false,"usgs":false,"family":"Piqueux","given":"Sylvain","email":"","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":683816,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70176346,"text":"70176346 - 2016 - Resource management and operations in central North Dakota: Climate change scenario planning workshop summary November 12-13, 2015, Bismarck, ND","interactions":[],"lastModifiedDate":"2017-12-19T09:43:22","indexId":"70176346","displayToPublicDate":"2016-09-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":53,"text":"Natural Resource Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"NPS/NRSS/NRR--2016/1262","title":"Resource management and operations in central North Dakota: Climate change scenario planning workshop summary November 12-13, 2015, Bismarck, ND","docAbstract":"The Scaling Climate Change Adaptation in the Northern Great Plains through Regional Climate Summaries and Local Qualitative-Quantitative Scenario Planning Workshops project synthesizes climate data into 3-5 distinct but plausible climate summaries for the northern Great Plains region; crafts quantitative summaries of these climate futures for two focal areas; and applies these local summaries by developing climate-resource-management scenarios through participatory workshops and, where possible, simulation models. The two focal areas are central North Dakota and southwest South Dakota (Figure 1). The primary objective of this project is to help resource managers and scientists in a focal area use scenario planning to make management and planning decisions based on assessments of critical future uncertainties.
This report summarizes project work for public and tribal lands in the central North Dakota focal area, with an emphasis on Knife River Indian Villages National Historic Site. The report explains
scenario planning as an adaptation tool in general, then describes how it was applied to the central North Dakota focal area in three phases. Priority resource management and climate uncertainties were identified in the orientation phase. Local climate summaries for relevant, divergent, and challenging climate scenarios were developed in the second phase. In the final phase, a two-day scenario planning workshop held November 12-13, 2015 in Bismarck, ND, featured scenario development and implications, testing management decisions, and methods for operationalizing scenario planning outcomes.
The Scaling Climate Change Adaptation in the Northern Great Plains through Regional Climate Summaries and Local Qualitative-Quantitative Scenario Planning Workshops project synthesizes climate data into 3-5 distinct but plausible climate summaries for the northern Great Plains region; crafts quantitative summaries of these climate futures for two focal areas; and applies these local summaries by developing climate-resource-management scenarios through participatory workshops and, where possible, simulation models. The two focal areas are central North Dakota and southwest South Dakota (Figure 1). The primary objective of this project is to help resource managers and scientists in a focal area use scenario planning to make management and planning decisions based on assessments of critical future uncertainties.
This report summarizes project work for public and tribal lands in the southwest South Dakota grasslands focal area, with an emphasis on Badlands National Park and Buffalo Gap National Grassland. The report explains scenario planning as an adaptation tool in general, then describes how it was applied to the focal area in three phases. Priority resource management and climate uncertainties were identified in the orientation phase. Local climate summaries for relevant, divergent, and challenging climate scenarios were developed in the second phase. In the final phase, a two-day scenario planning workshop held January 20-21, 2016 in Rapid City, South Dakota, featured scenario development and implications, testing management decisions, and methods for operationalizing scenario planning outcomes.
","language":"English","publisher":"National Park Service","publisherLocation":"Fort Collins, Colorado","usgsCitation":"Fisichelli, N.A., Schuurman, G.W., Symstad, A.J., Ray, A., Miller, B., Cross, M., and Rowland, E., 2016, Resource management and operations in southwest South Dakota: Climate change scenario planning workshop summary January 20-21, 2016, Rapid City, SD: Natural Resource Report NPS/NRSS/NRR—2016/1289, ix, 61 p.","productDescription":"ix, 61 p.","numberOfPages":"76","ipdsId":"IP-075140","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":328475,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":328423,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/DataStore/Reference/Profile/2233058"}],"publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57d3dd3ce4b0571647d19ac3","contributors":{"authors":[{"text":"Fisichelli, Nicholas A.","contributorId":174508,"corporation":false,"usgs":false,"family":"Fisichelli","given":"Nicholas","email":"","middleInitial":"A.","affiliations":[{"id":27461,"text":"NPS, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":648451,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schuurman, Gregor W. 0000-0002-9304-7742","orcid":"https://orcid.org/0000-0002-9304-7742","contributorId":147698,"corporation":false,"usgs":false,"family":"Schuurman","given":"Gregor","email":"","middleInitial":"W.","affiliations":[{"id":16909,"text":"U.S. National Park Service, Natural Resource Stewardship and Science, Fort Collins, CO, 80525, USA","active":true,"usgs":false}],"preferred":false,"id":648452,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Symstad, Amy J. 0000-0003-4231-2873 asymstad@usgs.gov","orcid":"https://orcid.org/0000-0003-4231-2873","contributorId":147543,"corporation":false,"usgs":true,"family":"Symstad","given":"Amy","email":"asymstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":648450,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ray, Andrea","contributorId":71869,"corporation":false,"usgs":true,"family":"Ray","given":"Andrea","affiliations":[],"preferred":false,"id":648453,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miller, Brian","contributorId":100753,"corporation":false,"usgs":true,"family":"Miller","given":"Brian","affiliations":[],"preferred":false,"id":648454,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cross, Molly","contributorId":73455,"corporation":false,"usgs":true,"family":"Cross","given":"Molly","affiliations":[],"preferred":false,"id":648455,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rowland, Erika","contributorId":146177,"corporation":false,"usgs":false,"family":"Rowland","given":"Erika","email":"","affiliations":[{"id":6624,"text":"University of Arizona, Laboratory of Tree-Ring Research","active":true,"usgs":false}],"preferred":false,"id":648456,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70176428,"text":"70176428 - 2016 - Delta smelt habitat in the San Francisco Estuary: A reply to Manly, Fullerton, Hendrix, and Burnham’s “Comments on Feyrer et al. Modeling the effects of future outflow on the abiotic habitat of an imperiled estuarine fish\"","interactions":[],"lastModifiedDate":"2016-09-13T12:39:46","indexId":"70176428","displayToPublicDate":"2016-09-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Delta smelt habitat in the San Francisco Estuary: A reply to Manly, Fullerton, Hendrix, and Burnham’s “Comments on Feyrer et al. Modeling the effects of future outflow on the abiotic habitat of an imperiled estuarine fish\"","docAbstract":"Manly et al. (2015) commented on the approach we (Feyrer et al. 2011) used to calculate an index of the abiotic habitat of delta smelt Hypomesus transpacificus. The delta smelt is an annual fish species endemic to the San Francisco Estuary (SFE) in California, USA. Conserving the delta smelt population while providing reliability to California’s water supply with water diverted from the SFE ecosystem is a major management and policy issue. Feyrer et al. (2011) evaluated historic and projected future abiotic habitat conditions for delta smelt. Manly et al. (2015) specifically commented regarding the following: (1) use of an independent abundance estimate, (2) spatial bias in the habitat index, and (3) application of the habitat index to future climate change projections. Here, we provide our reply to these three topics. While we agree that some of the concepts raised by Manly et al. (2015) have the potential to improve habitat assessments and their application to climate change scenarios as knowledge is gained, we note that the Feyrer et al. (2011) delta smelt habitat index is essentially identical to one reconstructed using Manly et al.’s (2015) preferred approach (their model 8), as shown here in Fig. 1.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-015-9987-6","usgsCitation":"Feyrer, F.V., Newman, K.B., Nobriga, M., and Sommer, T., 2016, Delta smelt habitat in the San Francisco Estuary: A reply to Manly, Fullerton, Hendrix, and Burnham’s “Comments on Feyrer et al. Modeling the effects of future outflow on the abiotic habitat of an imperiled estuarine fish\": Estuaries and Coasts, v. 39, no. 1, p. 287-289, https://doi.org/10.1007/s12237-015-9987-6.","productDescription":"3 p.","startPage":"287","endPage":"289","ipdsId":"IP-065000","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":328605,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2015-05-15","publicationStatus":"PW","scienceBaseUri":"57d92332e4b090824ffa1a44","contributors":{"authors":[{"text":"Feyrer, Frederick V. 0000-0003-1253-2349 ffeyrer@usgs.gov","orcid":"https://orcid.org/0000-0003-1253-2349","contributorId":5901,"corporation":false,"usgs":true,"family":"Feyrer","given":"Frederick","email":"ffeyrer@usgs.gov","middleInitial":"V.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":648726,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Newman, Ken B.","contributorId":51139,"corporation":false,"usgs":true,"family":"Newman","given":"Ken","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":648727,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nobriga, Matthew","contributorId":139247,"corporation":false,"usgs":false,"family":"Nobriga","given":"Matthew","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":648728,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sommer, Ted","contributorId":105242,"corporation":false,"usgs":true,"family":"Sommer","given":"Ted","email":"","affiliations":[],"preferred":false,"id":648729,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70182823,"text":"70182823 - 2016 - Forward modeling of gravity data using geostatistically generated subsurface density variations","interactions":[],"lastModifiedDate":"2017-03-01T10:56:24","indexId":"70182823","displayToPublicDate":"2016-09-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1808,"text":"Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Forward modeling of gravity data using geostatistically generated subsurface density variations","docAbstract":"Using geostatistical models of density variations in the subsurface, constrained by geologic data, forward models of gravity anomalies can be generated by discretizing the subsurface and calculating the cumulative effect of each cell (pixel). The results of such stochastically generated forward gravity anomalies can be compared with the observed gravity anomalies to find density models that match the observed data. These models have an advantage over forward gravity anomalies generated using polygonal bodies of homogeneous density because generating numerous realizations explores a larger region of the solution space. The stochastic modeling can be thought of as dividing the forward model into two components: that due to the shape of each geologic unit and that due to the heterogeneous distribution of density within each geologic unit. The modeling demonstrates that the internally heterogeneous distribution of density within each geologic unit can contribute significantly to the resulting calculated forward gravity anomaly. Furthermore, the stochastic models match observed statistical properties of geologic units, the solution space is more broadly explored by producing a suite of successful models, and the likelihood of a particular conceptual geologic model can be compared. The Vaca Fault near Travis Air Force Base, California, can be successfully modeled as a normal or strike-slip fault, with the normal fault model being slightly more probable. It can also be modeled as a reverse fault, although this structural geologic configuration is highly unlikely given the realizations we explored.
Knowledge of the local state of stress is critical in appraising intraplate seismic hazard. Inverting earthquake moment tensors, we demonstrate that principal stress directions in the New Madrid seismic zone (NMSZ) differ significantly from those in the surrounding region. Faults in the NMSZ that are incompatible with slip in the regional stress field are favorably oriented relative to local stress. We jointly analyze seismic velocity, gravity, and topography to develop a 3-D crustal and upper mantle density model, revealing uniquely dense lower crust beneath the NMSZ. Finite element simulations then estimate the stress tensor due to gravitational body forces, which sums with regional stress. The anomalous lower crust both elevates gravity-derived stress at seismogenic depths in the NMSZ and rotates it to interfere more constructively with far-field stress, producing a regionally maximal deviatoric stress coincident with the highest concentration of modern seismicity. Moreover, predicted principal stress directions mirror variations (observed independently in moment tensors) at the NMSZ and across the region.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2016GL070175","usgsCitation":"Levandowski, W.B., Boyd, O.S., and Ramirez-Guzman, L., 2016, Dense lower crust elevates long-term earthquake rates in the New Madrid seismic zone: Geophysical Research Letters, v. 43, no. 16, p. 8499-8510, https://doi.org/10.1002/2016GL070175.","productDescription":"12 p.","startPage":"8499","endPage":"8510","numberOfPages":"12","ipdsId":"IP-077991","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":470613,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gl070175","text":"Publisher Index Page"},{"id":329638,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Missouri, Tennessee","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.703125,\n 35.137879119634185\n ],\n [\n -90.703125,\n 36.99377838872517\n ],\n [\n -88.714599609375,\n 36.99377838872517\n ],\n [\n -88.714599609375,\n 35.137879119634185\n ],\n [\n -90.703125,\n 35.137879119634185\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","issue":"16","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-30","publicationStatus":"PW","scienceBaseUri":"5805e34ee4b0824b2d1c24c0","contributors":{"authors":[{"text":"Levandowski, William Brower 0000-0003-4903-5012 wlevandowski@usgs.gov","orcid":"https://orcid.org/0000-0003-4903-5012","contributorId":5729,"corporation":false,"usgs":true,"family":"Levandowski","given":"William","email":"wlevandowski@usgs.gov","middleInitial":"Brower","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":651141,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boyd, Oliver S. 0000-0001-9457-0407 olboyd@usgs.gov","orcid":"https://orcid.org/0000-0001-9457-0407","contributorId":140739,"corporation":false,"usgs":true,"family":"Boyd","given":"Oliver","email":"olboyd@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":651142,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramirez-Guzman, Leonardo","contributorId":175444,"corporation":false,"usgs":false,"family":"Ramirez-Guzman","given":"Leonardo","email":"","affiliations":[],"preferred":false,"id":651143,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}