We present ground motion prediction equations (GMPEs) for computing natural log means and standard deviations of vertical-component intensity measures (IMs) for shallow crustal earthquakes in active tectonic regions. The equations were derived from a global database with M 3.0–7.9 events. The functions are similar to those for our horizontal GMPEs. We derive equations for the primary M- and distance-dependence of peak acceleration, peak velocity, and 5%-damped pseudo-spectral accelerations at oscillator periods between 0.01–10 s. We observe pronounced M-dependent geometric spreading and region-dependent anelastic attenuation for high-frequency IMs. We do not observe significant region-dependence in site amplification. Aleatory uncertainty is found to decrease with increasing magnitude; within-event variability is independent of distance. Compared to our horizontal-component GMPEs, attenuation rates are broadly comparable (somewhat slower geometric spreading, faster apparent anelastic attenuation), VS30-scaling is reduced, nonlinear site response is much weaker, within-event variability is comparable, and between-event variability is greater.
","language":"English","publisher":"Earthquake Engineering Research Institute","doi":"10.1193/072114EQS116M","usgsCitation":"Stewart, J.P., Boore, D.M., Seyhan, E., and Atkinson, G.M., 2016, NGA-West2 equations for predicting vertical-component PGA, PGV, and 5%-damped PSA from shallow crustal earthquakes: Earthquake Spectra, v. 32, no. 2, p. 1005-1031, https://doi.org/10.1193/072114EQS116M.","productDescription":"27 p.","startPage":"1005","endPage":"1031","ipdsId":"IP-061692","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":338265,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-01","publicationStatus":"PW","scienceBaseUri":"58d63038e4b05ec7991310eb","contributors":{"authors":[{"text":"Stewart, Jonathan P.","contributorId":100110,"corporation":false,"usgs":false,"family":"Stewart","given":"Jonathan","email":"","middleInitial":"P.","affiliations":[{"id":7081,"text":"University of California - Los Angeles","active":true,"usgs":false}],"preferred":false,"id":685959,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boore, David M. boore@usgs.gov","contributorId":2509,"corporation":false,"usgs":true,"family":"Boore","given":"David","email":"boore@usgs.gov","middleInitial":"M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":685958,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Seyhan, Emel","contributorId":51193,"corporation":false,"usgs":false,"family":"Seyhan","given":"Emel","email":"","affiliations":[{"id":7081,"text":"University of California - Los Angeles","active":true,"usgs":false}],"preferred":false,"id":685960,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Atkinson, Gail M.","contributorId":60515,"corporation":false,"usgs":false,"family":"Atkinson","given":"Gail","email":"","middleInitial":"M.","affiliations":[{"id":13255,"text":"University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":685961,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70176210,"text":"70176210 - 2016 - Organic petrology and geochemistry of Eocene Suzak bituminous marl, north-central Afghanistan: Depositional environment and source rock potential","interactions":[],"lastModifiedDate":"2016-09-01T16:21:44","indexId":"70176210","displayToPublicDate":"2016-05-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2682,"text":"Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"Organic petrology and geochemistry of Eocene Suzak bituminous marl, north-central Afghanistan: Depositional environment and source rock potential","docAbstract":"Organic geochemistry and petrology of Eocene Suzak bituminous marl outcrop samples from Madr village in north-central Afghanistan were characterized via an integrated analytical approach to evaluate depositional environment and source rock potential. Multiple proxies suggest the organic-rich (TOC ∼6 wt.%) bituminous marls are ‘immature’ for oil generation (e.g., vitrinite Ro < 0.4%, Tmax < 425 °C, PI ≤ 0.05, C29 ααα S/S + R ≤ 0.12, C29 ββS/ββS+ααR ≤ 0.10, others), yet oil seeps are present at outcrop and live oil and abundant solid bitumen were observed via optical microscopy. Whole rock sulfur content is ∼2.3 wt.% whereas sulfur content is ∼5.0–5.6 wt.% in whole rock extracts with high polar components, consistent with extraction from S-rich Type IIs organic matter which could generate hydrocarbons at low thermal maturity. Low Fe-sulfide mineral abundance and comparison of Pr/Ph ratios between saturate and whole extracts suggest limited Fe concentration resulted in sulfurization of organic matter during early diagenesis. From these observations, we infer that a Type IIs kerogen in ‘immature’ bituminous marl at Madr could be generating high sulfur viscous oil which is seeping from outcrop. However, oil-seep samples were not collected for correlation studies. Aluminum-normalized trace element concentrations indicate enrichment of redox sensitive trace elements Mo, U and V and suggest anoxic-euxinic conditions during sediment deposition. The bulk of organic matter observed via optical microscopy is strongly fluorescent amorphous bituminite grading to lamalginite, possibly representing microbial mat facies. Short chain n-alkanes peak at C14–C16 (n-C17/n-C29 > 1) indicating organic input from marine algae and/or bacterial biomass, and sterane/hopane ratios are low (0.12–0.14). Monoaromatic steroids are dominated by C28clearly indicating a marine setting. High gammacerane index values (∼0.9) are consistent with anoxia stratification and may indicate intermittent saline-hypersaline conditions. Stable C isotope ratios also suggest a marine depositional scenario for the Suzak samples, consistent with the presence of marine foraminifera including abundant planktic globigerinida(?) and rare benthic discocyclina(?) and nummulites(?). Biomarker 2α-methylhopane for photosynthetic cyanobacteria implies shallow photic zone deposition of Madr marls and 3β-methylhopane indicates presence of methanotrophic archaea in the microbial consortium. The data presented herein are consistent with deposition of Suzak bituminous marls in shallow stratified waters of a restricted marine basin associated with the southeastern incipient or proto-Paratethys. Geochemical proxies from Suzak rock extracts (S content, high polar content, C isotopes, normal (αααR) C27–29 steranes, and C29/C30 and C26/C25 hopane ratios) are similar to extant data from Paleogene oils produced to the north in the Afghan-Tajik Basin. This observation may indicate laterally equivalent strata are effective source rocks as suggested by previous workers; however, further work is needed to strengthen oil-source correlations.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2016.02.029","usgsCitation":"Hackley, P.C., and Sanfilipo, J., 2016, Organic petrology and geochemistry of Eocene Suzak bituminous marl, north-central Afghanistan: Depositional environment and source rock potential: Marine and Petroleum Geology, v. 73, p. 572-589, https://doi.org/10.1016/j.marpetgeo.2016.02.029.","productDescription":"18 p.","startPage":"572","endPage":"589","ipdsId":"IP-069387","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":328205,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"73","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57c95130e4b0f2f0cec15bfc","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":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":647807,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sanfilipo, John 0000-0002-8739-5628 jsan@usgs.gov","orcid":"https://orcid.org/0000-0002-8739-5628","contributorId":140236,"corporation":false,"usgs":true,"family":"Sanfilipo","given":"John","email":"jsan@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":647808,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70170937,"text":"70170937 - 2016 - Assessing predation risks for small fish in a large river ecosystem between contrasting habitats and turbidity conditions","interactions":[],"lastModifiedDate":"2016-05-11T14:06:47","indexId":"70170937","displayToPublicDate":"2016-04-30T15:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":737,"text":"American Midland Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Assessing predation risks for small fish in a large river ecosystem between contrasting habitats and turbidity conditions","docAbstract":"This study examined predation risk for juvenile native fish between two riverine shoreline habitats, backwater and debris fan, across three discrete turbidity levels (low, intermediate, high) to understand environmental risks associated with habitat use in a section of the Colorado River in Grand Canyon, AZ. Inferences are particularly important to juvenile native fish, including the federally endangered humpback chub Gila cypha. This species uses a variety of habitats including backwaters which are often considered important rearing areas. Densities of two likely predators, adult rainbow trout Oncorhynchus mykiss and adult humpback chub, were estimated between habitats using binomial mixture models to examine whether higher predator density was associated with patterns of predation risk. Tethering experiments were used to quantify relative predation risk between habitats and turbidity conditions. Under low and intermediate turbidity conditions, debris fan habitat showed higher relative predation risk compared to backwaters. In both habitats the highest predation risk was observed during intermediate turbidity conditions. Density of likely predators did not significantly differ between these habitats. This information can help managers in Grand Canyon weigh flow policy options designed to increase backwater availability or extant turbidity conditions.
","language":"English","publisher":"University of Notre Dame","publisherLocation":"Notre Dame, IN","doi":"10.1674/0003-0031-175.2.206","usgsCitation":"Dodrill, M.J., Yard, M.D., and Pine, W.E., 2016, Assessing predation risks for small fish in a large river ecosystem between contrasting habitats and turbidity conditions: American Midland Naturalist, v. 175, no. 2, p. 206-221, https://doi.org/10.1674/0003-0031-175.2.206.","productDescription":"16 p.","startPage":"206","endPage":"221","numberOfPages":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-044798","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":321128,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.04907226562499,\n 35.545635932499415\n ],\n [\n -114.04907226562499,\n 36.99377838872517\n ],\n [\n -111.2860107421875,\n 36.99377838872517\n ],\n [\n -111.2860107421875,\n 35.545635932499415\n ],\n [\n -114.04907226562499,\n 35.545635932499415\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"175","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"573457abe4b0dae0d5ddd2e4","contributors":{"authors":[{"text":"Dodrill, Michael J. 0000-0002-7038-7170 mdodrill@usgs.gov","orcid":"https://orcid.org/0000-0002-7038-7170","contributorId":5468,"corporation":false,"usgs":true,"family":"Dodrill","given":"Michael","email":"mdodrill@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":629170,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yard, Michael D. 0000-0002-6580-6027 myard@usgs.gov","orcid":"https://orcid.org/0000-0002-6580-6027","contributorId":169281,"corporation":false,"usgs":true,"family":"Yard","given":"Michael","email":"myard@usgs.gov","middleInitial":"D.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":629169,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pine, William E. III","contributorId":139959,"corporation":false,"usgs":false,"family":"Pine","given":"William","suffix":"III","email":"","middleInitial":"E.","affiliations":[{"id":13332,"text":"Uni. of Florida Department of Wildlife Ecology and Conservation","active":true,"usgs":false}],"preferred":false,"id":629171,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70170957,"text":"70170957 - 2016 - Challenges for mapping cyanotoxin patterns from remote sensing of cyanobacteria","interactions":[],"lastModifiedDate":"2018-08-09T12:12:53","indexId":"70170957","displayToPublicDate":"2016-04-30T10:30:00","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":"Challenges for mapping cyanotoxin patterns from remote sensing of cyanobacteria","docAbstract":"Using satellite imagery to quantify the spatial patterns of cyanobacterial toxins has several challenges. These challenges include the need for surrogate pigments – since cyanotoxins cannot be directly detected by remote sensing, the variability in the relationship between the pigments and cyanotoxins – especially microcystins (MC), and the lack of standardization of the various measurement methods. A dual-model strategy can provide an approach to address these challenges. One model uses either chlorophyll-a (Chl-a) or phycocyanin (PC) collected in situ as a surrogate to estimate the MC concentration. The other uses a remote sensing algorithm to estimate the concentration of the surrogate pigment. Where blooms are mixtures of cyanobacteria and eukaryotic algae, PC should be the preferred surrogate to Chl-a. Where cyanobacteria dominate, Chl-a is a better surrogate than PC for remote sensing. Phycocyanin is less sensitive to detection by optical remote sensing, it is less frequently measured, PC laboratory methods are still not standardized, and PC has greater intracellular variability. Either pigment should not be presumed to have a fixed relationship with MC for any water body. The MC-pigment relationship can be valid over weeks, but have considerable intra- and inter-annual variability due to changes in the amount of MC produced relative to cyanobacterial biomass. To detect pigments by satellite, three classes of algorithms (analytic, semi-analytic, and derivative) have been used. Analytical and semi-analytical algorithms are more sensitive but less robust than derivatives because they depend on accurate atmospheric correction; as a result derivatives are more commonly used. Derivatives can estimate Chl-a concentration, and research suggests they can detect and possibly quantify PC. Derivative algorithms, however, need to be standardized in order to evaluate the reproducibility of parameterizations between lakes. A strategy for producing useful estimates of microcystins from cyanobacterial biomass is described, provided cyanotoxin variability is addressed.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.hal.2016.01.005","usgsCitation":"Stumpf, R.P., Davis, T.W., Wynne, T.T., Graham, J., Loftin, K.A., Johengen, T., Gossiaux, D., Palladino, D., and Burtner, A., 2016, Challenges for mapping cyanotoxin patterns from remote sensing of cyanobacteria: Harmful Algae, v. 54, p. 160-173, https://doi.org/10.1016/j.hal.2016.01.005.","productDescription":"14 p.","startPage":"160","endPage":"173","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070534","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":471038,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.hal.2016.01.005","text":"Publisher Index Page"},{"id":321204,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"54","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5736faade4b0dae0d5e03bf4","contributors":{"authors":[{"text":"Stumpf, Rick P","contributorId":169288,"corporation":false,"usgs":false,"family":"Stumpf","given":"Rick","email":"","middleInitial":"P","affiliations":[{"id":6637,"text":"National Oceanic and Atmospheric Administration, Northwest Fisheries Science Center, 2725 Montlake Blvd E, Seattle, WA 98112","active":true,"usgs":false}],"preferred":false,"id":629218,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davis, Timothy W.","contributorId":169289,"corporation":false,"usgs":false,"family":"Davis","given":"Timothy","email":"","middleInitial":"W.","affiliations":[{"id":6637,"text":"National Oceanic and Atmospheric Administration, Northwest Fisheries Science Center, 2725 Montlake Blvd E, Seattle, WA 98112","active":true,"usgs":false}],"preferred":false,"id":629219,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wynne, Timothy T.","contributorId":169290,"corporation":false,"usgs":false,"family":"Wynne","given":"Timothy","email":"","middleInitial":"T.","affiliations":[{"id":6637,"text":"National Oceanic and Atmospheric Administration, Northwest Fisheries Science Center, 2725 Montlake Blvd E, Seattle, WA 98112","active":true,"usgs":false}],"preferred":false,"id":629220,"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":150737,"corporation":false,"usgs":true,"family":"Graham","given":"Jennifer L.","email":"jlgraham@usgs.gov","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":false,"id":629217,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":629221,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johengen, T.H.","contributorId":169291,"corporation":false,"usgs":false,"family":"Johengen","given":"T.H.","affiliations":[{"id":25465,"text":"Cooperative Institute for Limnology and Ecosystem Research","active":true,"usgs":false}],"preferred":false,"id":629222,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gossiaux, D.","contributorId":169292,"corporation":false,"usgs":false,"family":"Gossiaux","given":"D.","affiliations":[{"id":25466,"text":"National Oceanic and Atmostpheric Administration","active":true,"usgs":false}],"preferred":false,"id":629223,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Palladino, D.","contributorId":169293,"corporation":false,"usgs":false,"family":"Palladino","given":"D.","email":"","affiliations":[{"id":25465,"text":"Cooperative Institute for Limnology and Ecosystem Research","active":true,"usgs":false}],"preferred":false,"id":629224,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Burtner, A.","contributorId":169294,"corporation":false,"usgs":false,"family":"Burtner","given":"A.","email":"","affiliations":[{"id":25465,"text":"Cooperative Institute for Limnology and Ecosystem Research","active":true,"usgs":false}],"preferred":false,"id":629225,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70169062,"text":"sim3351 - 2016 - Geologic map of the Valdez D-1 and D-2 quadrangles (Mount Wrangell Volcano), Alaska","interactions":[],"lastModifiedDate":"2018-06-20T19:49:59","indexId":"sim3351","displayToPublicDate":"2016-04-29T15:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3351","title":"Geologic map of the Valdez D-1 and D-2 quadrangles (Mount Wrangell Volcano), Alaska","docAbstract":"Mount Wrangell (elev. 4,317 m) is the youngest and only active volcano in the Oligocene to Holocene-aged Wrangell volcanic field that extends from beyond the Alaska-Yukon border northwest through the Wrangell Mountains to the Copper River Basin. The volcano is a very large (900 km3) broad shield containing an ice-filled, nonexplosive, collapse caldera measuring 3.2 by 5.6 kilometers. Three known craters, the West, North, and East occur along the north and west margins of the caldera; the caldera is open to the southeast. The volcano is best exposed on its southwest flank (this map area) where a number of deep glaciated canyons cut through hundreds of meters of shield lava flows creating routes for younger, valley-filling lava flows. The shield extends north into the Gulkana A-1 quadrangle, northeast into the Nabesna A-6 quadrangle, and east into the McCarthy quadrangle where it is almost entirely covered by ice. The present extent of the Mount Wrangell shield showing the entire caldera and locations of the three summit craters is depicted in figure 1.
\nMount Wrangell was built rapidly beginning about 650 ka by the outpourings of hundreds of voluminous lava flows from a vent, or vents, apparently in the present summit area. By 200 ka to 300 ka, activity waned and only an occasional lava flow coursed down the glacially carved valleys radiating from the summit or flowed over the upper summit area above the heads of the glacial valleys. The youngest dated valley-fill lava flow is approximately 25,000 years old; one or two undated flows may be younger.
\nIn historical times there have been several reports of lava flows issuing from the summit area. The most reliable and convincing of these were two independent observations from Copper Center, Alaska on September 3, 1899 that described great earth movements (the 1899 Yakutat Bay earthquake) followed by an eruption at Mount Wrangell’s summit, consisting of vigorous ash emission and flowing lava on the volcano’s northwest flank. This eruptive activity apparently continued for several years after the earthquake, as a photo taken around 1901–02 shows a large part of Mount Wrangell’s summit blanketed by ash. During this study, no evidence of young lava flows in the region were found, although it is very possible that a small-volume flow could be entirely hidden by snow and ice in the 100 years since the event. However, abundant juvenile andesitic pumice was found on the upper Chetaslina Glacier, strongly supporting a very young pyroclastic eruption.
\nIn addition to the 1899–1902 eruptions there have been accounts of strong ash-producing activity on at least four different occasions: 1912, July 3, 1921, April 6, 1930, and February 20, 1982. Of these, the 1921 activity was the most spectacular, and possibly erupted from the northeast side of the summit caldera.
\nPresent activity is limited to fumaroles in North and West Crater at the summit, at the summit ridge near East Crater, and at two localities at an elevation of 3,657 m on the southwest flank. The summit fumaroles frequently give rise to visible steam plumes, and occasionally sporadic explosive phreatic activity in North and West Crater will put a thin dusting of ash on the summit ice.
\nThis study was directed toward Mount Wrangell volcano and the older Wrangell volcanic field rocks that underlie the volcano. These older lavas include the Chetaslina lavas (867 ka–1,650 ka) and a basaltic andesite–dacite center (1,590 ka–1,640 ka) whose source areas are not well defined. Older Paleozoic and Mesozoic sedimentary, igneous, and metamorphic rocks of the Wrangellia terrane underlie the entire Wrangell volcanic field.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3351","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Richter, D.H., McGimsey, R.G., Labay, K.A., Lanphere, M.A., Moore, R.B., Nye, C.J., Rosenkrans, D.S., and Winkler, G.R., 2016, Geologic map of the Valdez D-1 and D-2 quadrangles (Mount Wrangell Volcano), Alaska: U.S. Geological Survey Scientific Investigations Map 3351, 20 p., scale 1:63,360, https://dx.doi.org/10.3133/sim3351.","productDescription":"Pamphlet: iii, 20 p.; Sheet: 45.54 x 28.53 inches; Metadata: FAQ, html, txt, xml; Read Me; Databases","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-061459","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":318874,"rank":5,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3351/sim3351_readme.pdf","text":"Read Me","size":"22 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3351 Read Me"},{"id":318866,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3351/coverthb.jpg"},{"id":318873,"rank":4,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3351/sim3351_databases.zip","text":"Databases","size":"5.2 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3351 Databases"},{"id":318867,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3351/sim3351_sheet1.pdf","text":"Sheet 1","size":"49.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3351 Sheet 1"},{"id":318868,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3351/sim3351_pamphlet.pdf","text":"Pamphlet","size":"880 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3351 Pamphlet"},{"id":318869,"rank":7,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3351/sim3351_meta.html","text":"Metadata (html)","size":"58 KB","linkFileType":{"id":5,"text":"html"},"description":"SIM 3351 Metadata (html)"},{"id":318870,"rank":8,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3351/sim3351_meta.txt","text":"Metadata (txt)","size":"41 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3351 Metadata (txt)"},{"id":318871,"rank":9,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3351/sim3351_meta.xml","text":"Metadata (xml)","size":"38 KB","description":"SIM 3351 Metadata (xml)"},{"id":318872,"rank":6,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3351/sim3351_meta.faq.html","text":"Metadata FAQ","size":"33 KB","linkFileType":{"id":5,"text":"html"},"description":"SIM 3351 Metadata FAQ"}],"country":"United States","state":"Alaska","otherGeospatial":"Mount Wrangell Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -144.75,\n 62\n ],\n [\n -144.75,\n 61.75\n ],\n [\n -144,\n 61.75\n ],\n [\n -144,\n 62\n ],\n [\n -144.75,\n 62\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Staff, Alaska Science Center
U.S. Geological Survey
4210 University Dr.
Anchorage, AK 99508
Alaska Science Center
Alaska Mineral Resources
Streams and estuaries with urban watersheds commonly exhibit increased streamflow and decreased base flow; diminished stream-channel stability; excessive amounts of contaminants such as pesticides, metals, industrial and municipal waste, and combustion products; and alterations to biotic community structure. Collectively, these detrimental effects have been termed the “urban-stream syndrome.” Water-resource managers seek to lessen the effects on receiving water bodies of new urban development and remediate the effects in areas of existing urbanization. Similarly, the scientific community has produced extensive research on these topics, with researchers from the U.S. Geological Survey (USGS) leading many studies of urban streams and the processes responsible for the urban-stream syndrome. Increasingly, USGS studies are evaluating the effects of management and restoration activities to better understand how urban waters respond to the implementation of management practices. The USGS has expertise in collecting and interpreting data for many physical, chemical, and ecological processes in urban waters and, thus, provides holistic assessments to inform managers of urban water resources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163024","collaboration":"Northeast Region Urban Landscape Capabilities Team","usgsCitation":"U.S. Geological Survey, 2016, Contaminants in urban waters—Science capabilities of the U.S. Geological Survey: U.S. Geological Survey Fact Sheet 2016–3024, 2 p., https://dx.doi.org/10.3133/fs20163024.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-074176","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":320432,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3024/coverthb.jpg"},{"id":320433,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3024/fs20163024.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016-3024"},{"id":320434,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163023","text":"Fact Sheet 2016-3023","description":"FS 2016-3024"},{"id":320435,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163025","text":"Fact Sheet 2016-3025","description":"FS 2016-3024"},{"id":320436,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163026","text":"Fact Sheet 2016-3026","description":"FS 2016-3024"}],"contact":"U.S. Geological Survey
Northeast Region Urban Landscapes Capability Team
Email: GS-NE_ULCT@usgs.gov
Urban development creates multiple stressors that can degrade stream ecosystems by changing stream hydrology, water quality, and physical habitat. Contaminants, habitat destruction, and increasing streamflow variability resulting from urban development have been associated with the disruption of biological communities, particularly the loss of sensitive aquatic biota. Understanding how algal, invertebrate, and fish communities respond to these physical and chemical stressors can provide important clues as to how streams should be managed to protect stream ecosystems as a watershed becomes increasingly urbanized. The U.S. Geological Survey continues to lead monitoring efforts and scientific studies on the effects of urban development on stream ecosystems in metropolitan areas across the United States.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163026","collaboration":"Northeast Region Urban Landscape Capabilities Team","usgsCitation":"U.S. Geological Survey, 2016, Urban development and stream ecosystem health—Science capabilities of the U.S. Geological Survey: U.S. Geological Survey Fact Sheet 2016–3026, 2 p., https://dx.doi.org/10.3133/fs20163026.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-074179","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":320444,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3026/fs20163026.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016-3026"},{"id":320445,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163023","text":"Fact Sheet 2016-3023"},{"id":320443,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3026/coverthb.jpg"},{"id":320446,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163024","text":"Fact Sheet 2016-3024"},{"id":320447,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163025","text":"Fact Sheet 2016-3025"}],"contact":"U.S. Geological Survey
Northeast Region Urban Landscapes Capability Team
Email: GS-NE_ULCT@usgs.gov
Managing the urban-water cycle has increasingly become a challenge for water-resources planners and regulators faced with the problem of providing clean drinking water to urban residents. Sanitary and combined sanitary and storm sewer networks convey wastewater to centralized treatment plants. Impervious surfaces, which include roads, parking lots, and buildings, increase stormwater runoff and the efficiency by which runoff is conveyed to nearby stream channels; therefore, impervious surfaces increase the risk of urban flooding and alteration of natural ecosystems. These challenges will increase with the expansion of urban centers and the probable effects of climate change on precipitation patterns. Understanding the urban-water cycle is critical to effectively manage water resources and to protect people, infrastructure, and urban-stream ecosystems. As a leader in water-supply, wastewater, and stormwater assessments, the U.S. Geological Survey has the expertise and resources needed to monitor, model, and interpret data related to the urban-water cycle and thereby enable water-resources managers to make informed decisions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163025","collaboration":"Northeast Region Urban Landscape Capabilities Team","usgsCitation":"U.S. Geological Survey, 2016, Urban infrastructure and water management—Science capabilities of the U.S. Geological Survey: U.S. Geological Survey Fact Sheet 2016–3025, 2 p., https://dx.doi.org/10.3133/fs20163025.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-074177","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":320439,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3025/fs20163025.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016-3025"},{"id":320438,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3025/coverthb.jpg"},{"id":320440,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163023","text":"Fact Sheet 2016-3023"},{"id":320441,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163024","text":"Fact Sheet 2016-3024"},{"id":320442,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163026","text":"Fact Sheet 2016-3026"}],"contact":"U.S. Geological Survey
Northeast Region Urban Landscapes Capability Team
Email: GS-NE_ULCT@usgs.gov
Urbanization affects streamflow characteristics, coastal flooding, and groundwater recharge. Increasing impervious areas, streamflow diversions, and groundwater pumpage are some of the ways that the natural water cycle is affected by urbanization. Assessment of the relations among these factors and changes in land use helps water-resource managers with issues such as stormwater management and vulnerability to flood and drought. Scientists with the U.S. Geological Survey (USGS) have the expertise to monitor and model urban hydrologic systems. Streamflow and groundwater data are available in national databases, and analyses of these data, including identification of long-term streamflow trends and the efficacy of management practices, are published in USGS reports.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163023","collaboration":"Northeast Region Urban Landscape Capabilities Team ","usgsCitation":"U.S. Geological Survey, 2016, Urban hydrology—Science capabilities of the U.S. Geological Survey: U.S. Geological Survey Fact Sheet 2016–3023, 2 p., https://dx.doi.org/10.3133/fs20163023.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-074174","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":320426,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163025","text":"Fact Sheet 2016-3025","description":"FS 2016-3023"},{"id":320425,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163024","text":"Fact Sheet 2016-3024","description":"FS 2016-3023"},{"id":320423,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3023/coverthb.jpg"},{"id":320427,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163026","text":"Fact Sheet 2016-3026","description":"FS 2016-3023"},{"id":320424,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3023/fs20163023.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016-3023"}],"contact":"U.S. Geological Survey
Northeast Region Urban Landscapes Capability Team
Email: GS-NE_ULCT@usgs.gov
Evidence suggests that lakes are important sites for atmospheric CO2 exchange and so play a substantial role in the global carbon budget. Previous research has 2 weaknesses: (1) most data have been collected only during the open-water or summer seasons, and (2) data are concentrated principally on natural lakes in northern latitudes. Here, we report on the full annual cycle of atmospheric CO2 exchanges of 15 oligotrophic to eutrophic reservoirs in the Glacial Till Plains of the United States. With one exception, these reservoirs showed an overall loss of CO2 during the year, with most values within the lower range reported for temperate lakes. There was a strong cross-system seasonal pattern: an average of 70% of total annual CO2 efflux occurred by the end of spring mixis; some 20% of annual flux was reabsorbed during summer stratification; and the remaining 50% of efflux was lost during autumnal mixing. Net annual flux was negatively correlated with depth and positively correlated with both water residence time and DOC, with the smallest annual CO2 efflux measured in shallow fertile impoundments. Strong correlations yield relationships allowing regional up-scaling of CO2 evasion. Understanding lacustrine CO2 uptake and evasion requires seasonal analyses across the full range of lake trophic states and morphometric attributes.
","language":"English","publisher":"International Society of Limnology","doi":"10.5268/IW-6.2.982","usgsCitation":"Jones, J., Obrecht, D.V., Graham, J., Balmer, M.B., Filstrup, C.T., and Downing, J.A., 2016, Seasonal patterns in carbon dioxide in 15 mid-continent (USA) reservoirs: Inland Waters, v. 2, no. 6, p. 265-272, https://doi.org/10.5268/IW-6.2.982.","productDescription":"8 p.","startPage":"265","endPage":"272","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-074423","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":471040,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5268/iw-6.2.982","text":"Publisher Index Page"},{"id":320803,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","county":"Adair County, Chariton County, Harrison County, Linn County, Mercer County, Nodaway 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2008","interactions":[],"lastModifiedDate":"2016-04-28T13:28:53","indexId":"ds991","displayToPublicDate":"2016-04-28T13:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"991","title":"Baseline coastal oblique aerial photographs collected from Calcasieu Lake, Louisiana, to Brownsville, Texas, September 9-10, 2008","docAbstract":"The U.S. Geological Survey (USGS), as part of the National Assessment of Coastal Change Hazards project, conducts baseline and storm-response photography missions to document and understand the changes in vulnerability of the Nation's coasts to extreme storms (Morgan, 2009). On September 9-10, 2008, the USGS conducted an oblique aerial photographic survey from Calcasieu Lake, Louisiana, to Brownsville, Texas, aboard a Cessna C-210 (aircraft) at an altitude of 500 feet (ft) and approximately 1,000 ft offshore. This mission was flown to collect baseline data for assessing incremental changes of the beach and nearshore area, and the data can be used in the assessment of future coastal change.
The photographs provided in this report are Joint Photographic Experts Group (JPEG) images. ExifTool was used to add the following to the header of each photo: time of collection, Global Positioning System (GPS) latitude, GPS longitude, keywords, credit, artist (photographer), caption, copyright, and contact information. The photograph locations are an estimate of the position of the aircraft at the time the photograph was taken and do not indicate the location of any feature in the images (see the Navigation Data page). These photographs document the state of the barrier islands and other coastal features at the time of the survey. Pages containing thumbnail images of the photographs, referred to as contact sheets, were created in 5-minute segments of flight time. These segments can be found on the Photos and Maps page. Photographs can be opened directly with any JPEG-compatible image viewer by clicking on a thumbnail on the contact sheet.
In addition to the photographs, a Google Earth Keyhole Markup Language (KML) file is provided and can be used to view the images by clicking on the marker and then clicking on either the thumbnail or the link above the thumbnail. The KML file was created using the photographic navigation files. The KML file can be found in the kml folder.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds991","usgsCitation":"Morgan, K.L.M., and Westphal, K.A., 2016, Baseline coastal oblique aerial photographs collected from Calcasieu Lake, Louisiana, to Brownsville, Texas, September 9-10, 2008: U.S. Geological Survey Data Series 991, https://dx.doi.org/10.3133/ds991.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2008-09-09","ipdsId":"IP-072328","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":320621,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":320527,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0991"}],"country":"United States","state":"Louisiana, Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.657470703125,\n 25.849336891707605\n ],\n [\n -97.657470703125,\n 30.221101852485987\n ],\n [\n -92.63671875,\n 30.221101852485987\n ],\n [\n -92.63671875,\n 25.849336891707605\n ],\n [\n -97.657470703125,\n 25.849336891707605\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
(727) 502–8000
http://coastal.er.usgs.gov
The U.S. Geological Survey (USGS), as part of the National Assessment of Coastal Change Hazards project, conducts baseline and storm-response photography missions to document and understand the changes in vulnerability of the Nation's coasts to extreme storms (Morgan, 2009). On September 14-15, 2008, the USGS conducted an oblique aerial photographic survey along the Alabama, Mississippi, and Louisiana barrier islands and the north Texas coast, aboard a Beechcraft Super King Air 200 (aircraft) at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was flown to collect post-Hurricane Ike data for assessing incremental changes in the beach and nearshore area since the last survey, flown on September 9-10, 2008, and the data can be used in the assessment of future coastal change.
The photographs provided in this report are Joint Photographic Experts Group (JPEG) images. ExifTool was used to add the following to the header of each photo: time of collection, Global Positioning System (GPS) latitude, GPS longitude, keywords, credit, artist (photographer), caption, copyright, and contact information. The photograph locations are an estimate of the position of the aircraft at the time the photograph was taken and do not indicate the location of any feature in the images (see the Navigation Data page). These photographs document the state of the barrier islands and other coastal features at the time of the survey. Pages containing thumbnail images of the photographs, referred to as contact sheets, were created in 5-minute segments of flight time. These segments can be found on the Photos and Maps page. Photographs can be opened directly with any JPEG-compatible image viewer by clicking on a thumbnail on the contact sheet.
In addition to the photographs, a Google Earth Keyhole Markup Language (KML) file is provided and can be used to view the images by clicking on the marker and then clicking on either the thumbnail or the link above the thumbnail. The KML file was created using the photographic navigation files. The KML file can be found in the kml folder.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds990","usgsCitation":"Morgan, K.L.M., Krohn, M.D., and Guy, K.K., 2016, Post-Hurricane Ike coastal oblique aerial photographs collected along the Alabama, Mississippi, and Louisiana barrier islands and the north Texas coast, September 14-15, 2008: U.S. Geological Survey Data Series 990, https://dx.doi.org/10.3133/ds990.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-070992","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":320622,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":320553,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0990/index.html"}],"country":"United States","state":"Alabama, Louisiana, Mississippi, Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.82421875,\n 29.075375179558346\n ],\n [\n -89.82421875,\n 30.637912028341123\n ],\n [\n -87.857666015625,\n 30.637912028341123\n ],\n [\n -87.857666015625,\n 29.075375179558346\n ],\n [\n -89.82421875,\n 29.075375179558346\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.417236328125,\n 28.83504997263515\n ],\n [\n -91.417236328125,\n 30.51494904517773\n ],\n [\n -89.835205078125,\n 30.51494904517773\n ],\n [\n -89.835205078125,\n 28.83504997263515\n ],\n [\n -91.417236328125,\n 28.83504997263515\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.284423828125,\n 28.9023972285585\n ],\n [\n -95.284423828125,\n 30.268556249047727\n ],\n [\n -92.955322265625,\n 30.268556249047727\n ],\n [\n -92.955322265625,\n 28.9023972285585\n ],\n [\n -95.284423828125,\n 28.9023972285585\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
600 4th Street South
St. Petersburg, FL 33701
(727) 502–8000
http://coastal.er.usgs.gov
Lake and river ice seasonality (dates of ice freeze and breakup) responds sensitively to climatic change and variability. We analyzed climate-related changes using direct human observations of ice freeze dates (1443–2014) for Lake Suwa, Japan, and of ice breakup dates (1693–2013) for Torne River, Finland. We found a rich array of changes in ice seasonality of two inland waters from geographically distant regions: namely a shift towards later ice formation for Suwa and earlier spring melt for Torne, increasing frequencies of years with warm extremes, changing inter-annual variability, waning of dominant inter-decadal quasi-periodic dynamics, and stronger correlations of ice seasonality with atmospheric CO2 concentration and air temperature after the start of the Industrial Revolution. Although local factors, including human population growth, land use change, and water management influence Suwa and Torne, the general patterns of ice seasonality are similar for both systems, suggesting that global processes including climate change and variability are driving the long-term changes in ice seasonality.
","language":"English","publisher":"Nature","doi":"10.1038/srep25061","usgsCitation":"Sharma, S., Magnuson, J., Batt, R., Winslow, L., Korhonen, J., and Aono, Y., 2016, Direct observations of ice seasonality reveal changes in climate over the past 320–570 years: Scientific Reports, v. 6, e25061: 11 p., https://doi.org/10.1038/srep25061.","productDescription":"e25061: 11 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065827","costCenters":[],"links":[{"id":471041,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/srep25061","text":"Publisher Index Page"},{"id":320636,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Finland, Japan","otherGeospatial":"Torne River, Lake 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pollinators, bees are cornerstones for terrestrial ecosystem stability and key components in agricultural productivity. All animals, including bees, are associated with a diverse community of microbes, commonly referred to as the microbiome. The bee microbiome is likely to be a crucial factor affecting host health. However, with the exception of a few pathogens, the impacts of most members of the bee microbiome on host health are poorly understood. Further, the evolutionary and ecological forces that shape and change the microbiome are unclear. Here, we discuss recent progress in our understanding of the bee microbiome, and we present challenges associated with its investigation. We conclude that global coordination of research efforts is needed to fully understand the complex and highly dynamic nature of the interplay between the bee microbiome, its host, and the environment. High-throughput sequencing technologies are ideal for exploring complex biological systems, including host-microbe interactions. To maximize their value and to improve assessment of the factors affecting bee health, sequence data should be archived, curated, and analyzed in ways that promote the synthesis of different studies. To this end, the BeeBiome consortium aims to develop an online database which would provide reference sequences, archive metadata, and host analytical resources. The goal would be to support applied and fundamental research on bees and their associated microbes and to provide a collaborative framework for sharing primary data from different research programs, thus furthering our understanding of the bee microbiome and its impact on pollinator health.
","language":"English","publisher":"American Society for Microbiology","doi":"10.1128/mBio.02164-15","usgsCitation":"Engel, P., Kwong, W.K., McFrederick, Q., Anderson, K.E., Barribeau, S.M., Chandler, J., Cornman, R.S., Dainat, J., de Miranda, J.R., Doublet, V., Emery, O., Evans, J.D., Farinelli, L., Flenniken, M., Granberg, F., Grasis, J.A., Gauthier, L., Hayer, J., Koch, H., Kocher, S., Martinson, V.G., Moran, N., Munoz-Torres, M., Newton, I., Paxton, R.J., Powell, E., Sadd, B.M., Schmid-Hempel, P., Schmid-Hempel, R., Song, J., Schwarz, R.S., vanEngelsdorp, D., and Dainat, B., 2016, The bee microbiome: Impact on bee health and model for evolution and ecology of host-microbe interactions: mBio, https://doi.org/10.1128/mBio.02164-15.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071278","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":471042,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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Mercury (Hg) monitoring programs are valuable for generating data that can be compiled for spatially broad syntheses to identify emergent ecosystem properties that influence fish Hg bioaccumulation. Fish total Hg (THg) concentrations were evaluated across the Western United States (US) and Canada, a region defined by extreme gradients in habitat structure and water management. A database was compiled with THg concentrations in 96,310 fish that comprised 206 species from 4262 locations, and used to evaluate the spatial distribution of fish THg across the region and effects of species, foraging guilds, habitats, and ecoregions. Areas of elevated THg exposure were identified by developing a relativized estimate of fish mercury concentrations at a watershed scale that accounted for the variability associated with fish species, fish size, and site effects. THg concentrations in fish muscle ranged between 0.001 and 28.4 (μg/g wet weight (ww)) with a geometric mean of 0.17. Overall, 30% of individual fish samples and 17% of means by location exceeded the 0.30 μg/g ww US EPA fish tissue criterion. Fish THg concentrations differed among habitat types, with riverine habitats consistently higher than lacustrine habitats. Importantly, fish THg concentrations were not correlated with sediment THg concentrations at a watershed scale, but were weakly correlated with sediment MeHg concentrations, suggesting that factors influencing MeHg production may be more important than inorganic Hg loading for determining fish MeHg exposure. There was large heterogeneity in fish THg concentrations across the landscape; THg concentrations were generally higher in semi-arid and arid regions such as the Great Basin and Desert Southwest, than in temperate forests. Results suggest that fish mercury exposure is widespread throughout Western US and Canada, and that species, habitat type, and region play an important role in influencing ecological risk of mercury in aquatic ecosystems.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.03.229","usgsCitation":"Eagles-Smith, C.A., Ackerman, J., Willacker, J.J., Tate, M., Lutz, M.A., Fleck, J., Stewart, A.R., Wiener, J.G., Evers, D.C., Lepak, J.M., Davis, J., and Pritz, C.F., 2016, Spatial and temporal patterns of mercury concentrations in freshwater fish across the Western United States and Canada: Science of the Total Environment, v. 568, p. 1171-1184, https://doi.org/10.1016/j.scitotenv.2016.03.229.","productDescription":"14 p.","startPage":"1171","endPage":"1184","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070592","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":482076,"rank":4,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.03.229","text":"Publisher Index Page"},{"id":320593,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":354415,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ja/70170374/70170374_appendix.pdf","text":"USGS open-access version of article appendix","size":"1.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-access journal article appendix"},{"id":354414,"rank":2,"type":{"id":42,"text":"Open Access USGS Document"},"url":"https://pubs.usgs.gov/ja/70170374/70170374.pdf","text":"USGS open-access version of article","size":"1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-access journal article"}],"volume":"568","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5721d4a4e4b0b13d3912914b","chorus":{"doi":"10.1016/j.scitotenv.2016.03.229","url":"http://dx.doi.org/10.1016/j.scitotenv.2016.03.229","publisher":"Elsevier BV","authors":"Eagles-Smith Collin A., Ackerman Joshua T., Willacker James J., Tate Michael T., Lutz Michelle A., Fleck Jacob A., Stewart A. 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Robin 0000-0003-2918-546X arstewar@usgs.gov","orcid":"https://orcid.org/0000-0003-2918-546X","contributorId":1482,"corporation":false,"usgs":true,"family":"Stewart","given":"A.","email":"arstewar@usgs.gov","middleInitial":"Robin","affiliations":[{"id":40553,"text":"WMA - Office of the Chief Operating Officer","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":627021,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wiener, James G.","contributorId":93853,"corporation":false,"usgs":false,"family":"Wiener","given":"James","email":"","middleInitial":"G.","affiliations":[{"id":17913,"text":"River Studies Center, University of Wisconsin-La Crosse","active":true,"usgs":false}],"preferred":false,"id":627022,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Evers, David C.","contributorId":96160,"corporation":false,"usgs":false,"family":"Evers","given":"David","email":"","middleInitial":"C.","affiliations":[{"id":6928,"text":"BioDiversity Research Institute, Gorham, ME 04038","active":true,"usgs":false}],"preferred":false,"id":627023,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lepak, Jesse M.","contributorId":168695,"corporation":false,"usgs":false,"family":"Lepak","given":"Jesse","email":"","middleInitial":"M.","affiliations":[{"id":13449,"text":"Colorado Division of Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":627024,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Davis, Jay A.","contributorId":168696,"corporation":false,"usgs":false,"family":"Davis","given":"Jay A.","affiliations":[{"id":12703,"text":"San Francisco Estuary Institute","active":true,"usgs":false}],"preferred":false,"id":627025,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Pritz, Colleen Flanagan","contributorId":67422,"corporation":false,"usgs":true,"family":"Pritz","given":"Colleen","email":"","middleInitial":"Flanagan","affiliations":[],"preferred":false,"id":627026,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70171336,"text":"70171336 - 2016 - Carbon dioxide as a tool to deter the movement of invasive bigheaded carps","interactions":[],"lastModifiedDate":"2017-08-15T12:34:37","indexId":"70171336","displayToPublicDate":"2016-04-27T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Carbon dioxide as a tool to deter the movement of invasive bigheaded carps","docAbstract":"Nonnative bigheaded carps are established in the Mississippi River and there is substantial concern about their potential entry into the interconnected Laurentian Great Lakes. While electrical barriers currently exist as a preventative measure, there is need for additional control mechanisms to promote barrier security through redundancy. We tested the effectiveness of infused carbon dioxide gas (CO2) as a tool to influence the movement and behavior invasive bigheaded carps, namely Bighead Carp Hypophthalmichthys nobilis and Silver Carp H. molitrix, as well as native Bigmouth Buffalo Ictiobus cyprinellus, Channel Catfish Ictalurus punctatus, Paddlefish Polyodon spathula, and Yellow Perch Perca flavescens in an experimental pond. Individuals were monitored with acoustic telemetry before, during, and after CO2 addition to the pond. We noted distinct changes in fish behavior following CO2 addition. Each species except Paddlefish maintained farther distances from the CO2 infusion manifold relative to controls. Both bigheaded carp species had slower persistence velocities (persistence of a movement in a given direction) following CO2 infusion and Bighead Carp used a smaller area of the pond immediately after CO2 addition. Pond pH progressively decreased up to 1.5 units following CO2 infusion. This work provides evidence that could inform future research to enhance existing control measures used to deter high-risk invasive fishes, such as bigheaded carps.
","language":"English","publisher":"American Fisheries Society","publisherLocation":"Bethesda, MD","doi":"10.1080/00028487.2016.1143397","usgsCitation":"Donaldson, M.R., Amberg, J., Adhikari, S., Cupp, A.R., Jensen, N., Romine, J.G., Wright, A., Gaikowski, M., and Cory D. Suski, 2016, Carbon dioxide as a tool to deter the movement of invasive bigheaded carps: Transactions of the American Fisheries Society, v. 145, no. 3, p. 657-670, https://doi.org/10.1080/00028487.2016.1143397.","productDescription":"14 p.","startPage":"657","endPage":"670","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061434","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":471044,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":321883,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"145","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-27","publicationStatus":"PW","scienceBaseUri":"574eb5b7e4b0ee97d51a8399","contributors":{"authors":[{"text":"Donaldson, Michael R.","contributorId":169664,"corporation":false,"usgs":false,"family":"Donaldson","given":"Michael","email":"","middleInitial":"R.","affiliations":[{"id":25569,"text":"Department of Natural Resources and Environmental Sciences, University of Illinois","active":true,"usgs":false}],"preferred":false,"id":630617,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Amberg, Jon 0000-0002-8351-4861 jamberg@usgs.gov","orcid":"https://orcid.org/0000-0002-8351-4861","contributorId":149785,"corporation":false,"usgs":true,"family":"Amberg","given":"Jon","email":"jamberg@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":630616,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adhikari, Shivani","contributorId":169665,"corporation":false,"usgs":false,"family":"Adhikari","given":"Shivani","email":"","affiliations":[{"id":25569,"text":"Department of Natural Resources and Environmental Sciences, University of Illinois","active":true,"usgs":false}],"preferred":false,"id":630618,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cupp, Aaron R. 0000-0001-5995-2100 acupp@usgs.gov","orcid":"https://orcid.org/0000-0001-5995-2100","contributorId":5162,"corporation":false,"usgs":true,"family":"Cupp","given":"Aaron","email":"acupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":630619,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jensen, Nathan njensen@usgs.gov","contributorId":146353,"corporation":false,"usgs":true,"family":"Jensen","given":"Nathan","email":"njensen@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":630620,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Romine, Jason G. 0000-0002-6938-1185 jromine@usgs.gov","orcid":"https://orcid.org/0000-0002-6938-1185","contributorId":2823,"corporation":false,"usgs":true,"family":"Romine","given":"Jason","email":"jromine@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":630621,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wright, Adam","contributorId":169666,"corporation":false,"usgs":false,"family":"Wright","given":"Adam","email":"","affiliations":[{"id":25569,"text":"Department of Natural Resources and Environmental Sciences, University of Illinois","active":true,"usgs":false}],"preferred":false,"id":630622,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gaikowski, Mark P. 0000-0002-6507-9341 mgaikowski@usgs.gov","orcid":"https://orcid.org/0000-0002-6507-9341","contributorId":149357,"corporation":false,"usgs":true,"family":"Gaikowski","given":"Mark P.","email":"mgaikowski@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":630623,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cory D. Suski","contributorId":169667,"corporation":false,"usgs":false,"family":"Cory D. Suski","affiliations":[{"id":25569,"text":"Department of Natural Resources and Environmental Sciences, University of Illinois","active":true,"usgs":false}],"preferred":false,"id":630624,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70170558,"text":"70170558 - 2016 - Magnetotelluric investigation of the Vestfold Hills and Rauer Group, East Antarctica","interactions":[],"lastModifiedDate":"2019-12-14T06:33:33","indexId":"70170558","displayToPublicDate":"2016-04-27T10:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Magnetotelluric investigation of the Vestfold Hills and Rauer Group, East Antarctica","docAbstract":"The Vestfold Hills and Rauer Group in East Antarctica have contrasting Archean to Neoproterozoic geological histories and are believed to be juxtaposed along a suture zone that now lies beneath the Sørsdal Glacier. Exact location and age of this suture zone are unknown, as is its relationship to regional deformation associated with the amalgamation of East Gondwana. To image the suture zone, magnetotelluric (MT) data were collected in Prydz Bay, East Antarctica, mainly along a profile crossing the Sørsdal Glacier and regions inland of the Vestfold Hills and Rauer Group islands. Time-frequency analysis of the MT time series yielded three important observations: (1) Wind speeds in excess of ∼8 m/s reduce coherence between electric and magnetic fields due to charged wind-blown particles of ice and snow. (2) Estimation of the MT transfer function is best between 1000 and 1400 UT when ionospheric Hall currents enhance the magnetic source field. (3) Nonplanar source field effects were minimal but detectable and removed from estimation of the MT transfer function. Inversions of MT data in 2-D and 3-D produce similar resistivity models, where structures in the preferred 3-D resistivity model correlate strongly with regional magnetic data. The electrically conductive Rauer Group is separated from the less conductive Vestfold Hills by a resistive zone under the Sørsdal Glacier, which is interpreted to be caused by oxidation during suturing. Though a suture zone has been imaged, no time constrains on suturing can be made from the MT data.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015JB012677","usgsCitation":"Peacock, J.R., and Selway, K., 2016, Magnetotelluric investigation of the Vestfold Hills and Rauer Group, East Antarctica: Journal of Geophysical Research B: Solid Earth, v. 121, no. 4, p. 2258-2273, https://doi.org/10.1002/2015JB012677.","productDescription":"16 p.","startPage":"2258","endPage":"2273","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071990","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":471045,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jb012677","text":"Publisher Index Page"},{"id":320586,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"121","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-26","publicationStatus":"PW","scienceBaseUri":"5721d4a4e4b0b13d39129147","contributors":{"authors":[{"text":"Peacock, Jared R. 0000-0002-0439-0224 jpeacock@usgs.gov","orcid":"https://orcid.org/0000-0002-0439-0224","contributorId":4996,"corporation":false,"usgs":true,"family":"Peacock","given":"Jared","email":"jpeacock@usgs.gov","middleInitial":"R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":627647,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Selway, Katherine","contributorId":168903,"corporation":false,"usgs":false,"family":"Selway","given":"Katherine","email":"","affiliations":[{"id":13368,"text":"University of Adelaide, Australia","active":true,"usgs":false}],"preferred":false,"id":627648,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70170560,"text":"70170560 - 2016 - Fluctuating water depths affect American alligator (Alligator mississippiensis) body condition in the Everglades, Florida, USA","interactions":[],"lastModifiedDate":"2016-07-11T15:40:41","indexId":"70170560","displayToPublicDate":"2016-04-27T10:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Fluctuating water depths affect American alligator (Alligator mississippiensis) body condition in the Everglades, Florida, USA","docAbstract":"Successful restoration of wetland ecosystems requires knowledge of wetland hydrologic patterns and an understanding of how those patterns affect wetland plant and animal populations.Within the Everglades, Florida, USA restoration, an applied science strategy including conceptual ecological models linking drivers to indicators is being used to organize current scientific understanding to support restoration efforts. A key driver of the ecosystem affecting the distribution and abundance of organisms is the timing, distribution, and volume of water flows that result in water depth patterns across the landscape. American alligators (Alligator mississippiensis) are one of the ecological indicators being used to assess Everglades restoration because they are a keystone species and integrate biological impacts of hydrological operations through all life stages. Alligator body condition (the relative fatness of an animal) is one of the metrics being used and targets have been set to allow us to track progress. We examined trends in alligator body condition using Fulton’s K over a 15 year period (2000–2014) at seven different wetland areas within the Everglades ecosystem, assessed patterns and trends relative to restoration targets, and related those trends to hydrologic variables. We developed a series of 17 a priori hypotheses that we tested with an information theoretic approach to identify which hydrologic factors affect alligator body condition. Alligator body condition was highest throughout the Everglades during the early 2000s and is approximately 5–10% lower now (2014). Values have varied by year, area, and hydrology. Body condition was positively correlated with range in water depth and fall water depth. Our top model was the “Current” model and included variables that describe current year hydrology (spring depth, fall depth, hydroperiod, range, interaction of range and fall depth, interaction of range and hydroperiod). Across all models, interaction between range and fall water depth was the most important variable (relative weight of 1.0) followed by spring and fall water depths (0.99), range (0.96), hydroperiod (0.95) and interaction between range and hydroperiod (0.95). Our work provides additional evidence that restoring a greater range in annual water depths is important for improvement of alligator body condition and ecosystem function. This information can be incorporated into both planning and operations to assist in reaching Everglades restoration goals.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2016.03.003","usgsCitation":"Brandt, L., Beauchamp, J.S., Jeffery, B.M., Cherkiss, M.S., and Mazzotti, F., 2016, Fluctuating water depths affect American alligator (Alligator mississippiensis) body condition in the Everglades, Florida, USA: Ecological Indicators, v. 67, p. 441-450, https://doi.org/10.1016/j.ecolind.2016.03.003.","productDescription":"10 p.","startPage":"441","endPage":"450","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069792","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471046,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2016.03.003","text":"Publisher Index Page"},{"id":320585,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.4473876953125,\n 26.676913083105454\n ],\n [\n -80.36773681640625,\n 26.684275490019488\n ],\n [\n -80.23590087890624,\n 26.571333057252076\n ],\n [\n -80.23590087890624,\n 26.382027976025352\n ],\n [\n -80.29083251953124,\n 26.347575438494673\n ],\n [\n -80.29632568359375,\n 26.185018250078308\n ],\n [\n -80.35400390625,\n 26.118452068488097\n ],\n [\n -80.44189453125,\n 26.145576207592274\n ],\n [\n -80.43365478515625,\n 25.962983554822678\n ],\n [\n -80.48858642578125,\n 25.760319754713887\n ],\n [\n -80.57373046875,\n 25.46559428893416\n ],\n [\n -80.93353271484375,\n 25.40854689267053\n ],\n [\n -81.10382080078125,\n 25.631621577258493\n ],\n [\n -80.8428955078125,\n 25.767740402713383\n ],\n [\n -80.83740234375,\n 26.165298896316042\n ],\n [\n -80.82366943359375,\n 26.330345320410842\n ],\n [\n -80.54901123046875,\n 26.406630642556795\n ],\n [\n -80.452880859375,\n 26.458279167084125\n ],\n [\n -80.4473876953125,\n 26.676913083105454\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"67","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5721d4a3e4b0b13d39129145","contributors":{"authors":[{"text":"Brandt, Laura A.","contributorId":18608,"corporation":false,"usgs":false,"family":"Brandt","given":"Laura A.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":627656,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beauchamp, Jeffrey S.","contributorId":138880,"corporation":false,"usgs":false,"family":"Beauchamp","given":"Jeffrey","email":"","middleInitial":"S.","affiliations":[{"id":12559,"text":"University of Florida, FLEC","active":true,"usgs":false}],"preferred":false,"id":627657,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jeffery, Brian M.","contributorId":138879,"corporation":false,"usgs":false,"family":"Jeffery","given":"Brian","email":"","middleInitial":"M.","affiliations":[{"id":12558,"text":"University of Florida, Gainesville","active":true,"usgs":false}],"preferred":false,"id":627658,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cherkiss, Michael S. 0000-0002-7802-6791 mcherkiss@usgs.gov","orcid":"https://orcid.org/0000-0002-7802-6791","contributorId":4571,"corporation":false,"usgs":true,"family":"Cherkiss","given":"Michael","email":"mcherkiss@usgs.gov","middleInitial":"S.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":627655,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mazzotti, Frank J.","contributorId":12358,"corporation":false,"usgs":false,"family":"Mazzotti","given":"Frank J.","affiliations":[{"id":12604,"text":"Department of Wildlife Ecology and Conservation, Fort Lauderdale Research and Education Center, 3205 College Avenue, University of Florida, Davie, FL 33314, USA","active":true,"usgs":false}],"preferred":false,"id":627659,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70170564,"text":"70170564 - 2016 - Will changes in phenology track climate change? A study of growth initiation timing in coast Douglas-fir","interactions":[],"lastModifiedDate":"2016-10-21T13:41:54","indexId":"70170564","displayToPublicDate":"2016-04-27T10:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Will changes in phenology track climate change? A study of growth initiation timing in coast Douglas-fir","docAbstract":"Under climate change, the reduction of frost risk, onset of warm temperatures and depletion of soil moisture are all likely to occur earlier in the year in many temperate regions. The resilience of tree species will depend on their ability to track these changes in climate with shifts in phenology that lead to earlier growth initiation in the spring. Exposure to warm temperatures (“forcing”) typically triggers growth initiation, but many trees also require exposure to cool temperatures (“chilling”) while dormant to readily initiate growth in the spring. If warming increases forcing and decreases chilling, climate change could maintain, advance or delay growth initiation phenology relative to the onset of favorable conditions. We modeled the timing of height- and diameter-growth initiation in coast Douglas-fir (an ecologically and economically vital tree in western North America) to determine whether changes in phenology are likely to track changes in climate using data from field-based and controlled-environment studies, which included conditions warmer than those currently experienced in the tree's range. For high latitude and elevation portions of the tree's range, our models predicted that warming will lead to earlier growth initiation and allow trees to track changes in the onset of the warm but still moist conditions that favor growth, generally without substantially greater exposure to frost. In contrast, towards lower latitude and elevation range limits, the models predicted that warming will lead to delayed growth initiation relative to changes in climate due to reduced chilling, with trees failing to capture favorable conditions in the earlier parts of the spring. This maladaptive response to climate change was more prevalent for diameter-growth initiation than height-growth initiation. The decoupling of growth initiation with the onset of favorable climatic conditions could reduce the resilience of coast Douglas-fir to climate change at the warm edges of its distribution.
","language":"English","publisher":"Blackwell Science","doi":"10.1111/gcb.13328","usgsCitation":"Ford, K.R., Harrington, C.A., Bansal, S., Gould, P.J., and St. Clair, B., 2016, Will changes in phenology track climate change? A study of growth initiation timing in coast Douglas-fir: Global Change Biology, v. 22, no. 11, p. 3712-3723, https://doi.org/10.1111/gcb.13328.","productDescription":"12 p.","startPage":"3712","endPage":"3723","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070150","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":320583,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.26660156249999,\n 49.03786794532644\n ],\n [\n -117.46582031249999,\n 49.06666839558117\n ],\n [\n -117.6416015625,\n 48.516604348867475\n ],\n [\n -117.99316406249999,\n 47.368594345213374\n ],\n [\n -118.125,\n 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PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-19","publicationStatus":"PW","scienceBaseUri":"5721d4a4e4b0b13d3912914d","contributors":{"authors":[{"text":"Ford, Kevin R.","contributorId":168906,"corporation":false,"usgs":false,"family":"Ford","given":"Kevin","email":"","middleInitial":"R.","affiliations":[{"id":25384,"text":"USDA, Forest Service, Pacific Northwest Research Station","active":true,"usgs":false}],"preferred":false,"id":627673,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harrington, Constance A.","contributorId":168907,"corporation":false,"usgs":false,"family":"Harrington","given":"Constance","email":"","middleInitial":"A.","affiliations":[{"id":25384,"text":"USDA, Forest Service, Pacific Northwest Research Station","active":true,"usgs":false}],"preferred":false,"id":627674,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bansal, Sheel 0000-0003-1233-1707 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Corvallis","active":true,"usgs":false}],"preferred":false,"id":627676,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70171475,"text":"70171475 - 2016 - Longitudinal evaluation of leukocyte transcripts in killer whales (Orcinus Orca)","interactions":[],"lastModifiedDate":"2016-06-01T15:27:21","indexId":"70171475","displayToPublicDate":"2016-04-27T01:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3682,"text":"Veterinary Immunology and Immunopathology","active":true,"publicationSubtype":{"id":10}},"title":"Longitudinal evaluation of leukocyte transcripts in killer whales (Orcinus Orca)","docAbstract":"Early identification of illness and/or presence of environmental and/or social stressors in free-ranging and domestic cetaceans is a priority for marine mammal health care professionals. Incorporation of leukocyte gene transcript analysis into the diagnostic tool kit has the potential to augment classical diagnostics based upon ease of sample storage and shipment, inducible nature and well-defined roles of transcription and associated downstream actions. Development of biomarkers that could serve to identify “insults” and potentially differentiate disease etiology would be of great diagnostic value. To this end, a modest number of peripheral blood leukocyte gene transcripts were selected for application to a domestic killer whale population with a focus on broad representation of inducible immunologically relevant genes. Normalized leukocyte transcript values, longitudinally acquired from 232 blood samples derived from 26 clinically healthy whales, were not visibly influenced temporally nor by sex or the specific Park in which they resided. Stability in leukocyte transcript number during periods of health enhances their potential use in diagnostics through identification of outliers. Transcript levels of two cytokine genes, IL-4 and IL-17, were highly variable within the group as compared to the other transcripts. IL-4 transcripts were typically absent. Analysis of transcript levels on the other genes of interest, on an individual animal basis, identified more outliers than were visible when analyzed in the context of the entire population. The majority of outliers (9 samples) were low, though elevated transcripts were identified for IL-17 from 2 animals and one each for Cox-2 and IL-10. The low number of outliers was not unexpected as sample selection was intentionally directed towards animals that were clinically healthy at the time of collection. Outliers may reflect animals experiencing subclinical disease that is transient and self-limiting. The immunologic knowledge derived from longitudinal immunologic studies in killer whales, as was the target of the present study, has the potential to improve diagnostics and health related decision making for this and other domestic and free-ranging cetacean species.
","language":"English","publisher":"Science Direct","doi":"10.1016/j.vetimm.2016.04.011","usgsCitation":"Sitt, T., Bowen, L., Lee, C., Blanchard, M., McBain, J., Dold, C., and Stott, J.L., 2016, Longitudinal evaluation of leukocyte transcripts in killer whales (Orcinus Orca): Veterinary Immunology and Immunopathology, v. 175, p. 7-15, https://doi.org/10.1016/j.vetimm.2016.04.011.","productDescription":"8 p.","startPage":"7","endPage":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-076179","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":322042,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"175","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57500769e4b0ee97d51bb677","contributors":{"authors":[{"text":"Sitt, Tatjana","contributorId":169842,"corporation":false,"usgs":false,"family":"Sitt","given":"Tatjana","email":"","affiliations":[{"id":25601,"text":"Dep't Animal and Vet Sciences, UVM, Burlington, VT","active":true,"usgs":false}],"preferred":false,"id":631232,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bowen, Lizabeth 0000-0001-9115-4336 lbowen@usgs.gov","orcid":"https://orcid.org/0000-0001-9115-4336","contributorId":4539,"corporation":false,"usgs":true,"family":"Bowen","given":"Lizabeth","email":"lbowen@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":631231,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lee, Chia-Shan","contributorId":169843,"corporation":false,"usgs":false,"family":"Lee","given":"Chia-Shan","email":"","affiliations":[{"id":25602,"text":"Dep't Pathology, Vet School, UC Davis, CA","active":true,"usgs":false}],"preferred":false,"id":631233,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blanchard, Myra","contributorId":169844,"corporation":false,"usgs":false,"family":"Blanchard","given":"Myra","email":"","affiliations":[{"id":25603,"text":"Dep't of Pathology, Vet School, UC Davis, CA","active":true,"usgs":false}],"preferred":false,"id":631234,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McBain, James","contributorId":169845,"corporation":false,"usgs":false,"family":"McBain","given":"James","email":"","affiliations":[{"id":25604,"text":"Vet consultant, San Diego, CA","active":true,"usgs":false}],"preferred":false,"id":631235,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dold, Christopher","contributorId":169846,"corporation":false,"usgs":false,"family":"Dold","given":"Christopher","email":"","affiliations":[{"id":25605,"text":"Corp. VP, Vet Services, SeaWorld Parks & Entertainment, Orlando, FL","active":true,"usgs":false}],"preferred":false,"id":631236,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stott, Jeffrey L.","contributorId":82146,"corporation":false,"usgs":true,"family":"Stott","given":"Jeffrey","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":631237,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70173602,"text":"70173602 - 2016 - Interactions between hatch dates, growth rates, and mortality of Age-0 native Rainbow Smelt and nonnative Alewife in Lake Champlain","interactions":[],"lastModifiedDate":"2016-06-07T16:35:26","indexId":"70173602","displayToPublicDate":"2016-04-27T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Interactions between hatch dates, growth rates, and mortality of Age-0 native Rainbow Smelt and nonnative Alewife in Lake Champlain","docAbstract":"Timing of hatch in fish populations can be critical for first-year survival and, therefore, year-class strength and subsequent species interactions. We compared hatch timing, growth rates, and subsequent mortality of age-0 Rainbow Smelt Osmerus mordax and Alewife Alosa pseudoharengus, two common open-water fish species of northern North America. In our study site, Lake Champlain, Rainbow Smelt hatched (beginning May 26) almost a month earlier than Alewives (June 20). Abundance in the sampling area was highest in July for age-0 Rainbow Smelt and August for age-0 Alewives. Late-hatching individuals of both species grew faster than those hatching earlier (0.6 mm/d versus 0.4 for Rainbow Smelt; 0.7 mm/d versus 0.6 for Alewives). Mean mortality rate during the first 45 d of life was 3.4%/d for age-0 Rainbow Smelt and was 5.5%/d for age-0 Alewives. Alewife mortality rates did not differ with hatch timing but daily mortality rates of Rainbow Smelt were highest for early-hatching fish. Cannibalism is probably the primary mortality source for age-0 Rainbow Smelt in this lake. Therefore, hatching earlier may not be advantageous because the overlap of adult and age-0 Rainbow Smelt is highest earlier in the season. However, Alewives, first documented in Lake Champlain in 2003, may increase the mortality of age-0 Rainbow Smelt in the summer, which should favor selection for earlier hatching.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00028487.2016.1143401","usgsCitation":"Parrish, D.L., Simonin, P.W., Rudstam, L.G., Pientka, B., and Sullivan, P., 2016, Interactions between hatch dates, growth rates, and mortality of Age-0 native Rainbow Smelt and nonnative Alewife in Lake Champlain: Transactions of the American Fisheries Society, v. 145, no. 3, p. 649-656, https://doi.org/10.1080/00028487.2016.1143401.","productDescription":"8 p.","startPage":"649","endPage":"656","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064234","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323231,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Vermont","otherGeospatial":"Lake Champlain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.223876953125,\n 44.450447876762844\n ],\n [\n -73.29666137695312,\n 44.44064372873941\n ],\n [\n -73.32206726074219,\n 44.383747221908365\n ],\n [\n -73.22250366210938,\n 44.37540429036203\n ],\n [\n -73.2183837890625,\n 44.440153478144595\n ],\n [\n -73.223876953125,\n 44.450447876762844\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"145","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-27","publicationStatus":"PW","scienceBaseUri":"5757f037e4b04f417c24daad","contributors":{"authors":[{"text":"Parrish, Donna L. 0000-0001-9693-6329 dparrish@usgs.gov","orcid":"https://orcid.org/0000-0001-9693-6329","contributorId":138661,"corporation":false,"usgs":true,"family":"Parrish","given":"Donna","email":"dparrish@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":637391,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Simonin, Paul W.","contributorId":171499,"corporation":false,"usgs":false,"family":"Simonin","given":"Paul","email":"","middleInitial":"W.","affiliations":[{"id":18160,"text":"Rubenstein School of Environment and Natural Resources, University of Vermont","active":true,"usgs":false}],"preferred":false,"id":637763,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rudstam, Lars G.","contributorId":56609,"corporation":false,"usgs":false,"family":"Rudstam","given":"Lars","email":"","middleInitial":"G.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":637764,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pientka, Bernard","contributorId":171500,"corporation":false,"usgs":false,"family":"Pientka","given":"Bernard","email":"","affiliations":[],"preferred":false,"id":637765,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sullivan, Patrick J.","contributorId":97813,"corporation":false,"usgs":true,"family":"Sullivan","given":"Patrick J.","affiliations":[],"preferred":false,"id":637766,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70171114,"text":"70171114 - 2016 - Wave attenuation in the shallows of San Francisco Bay","interactions":[],"lastModifiedDate":"2016-06-16T11:23:54","indexId":"70171114","displayToPublicDate":"2016-04-26T14:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1262,"text":"Coastal Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Wave attenuation in the shallows of San Francisco Bay","docAbstract":"Waves propagating over broad, gently-sloped shallows decrease in height due to frictional dissipation at the bed. We quantified wave-height evolution across 7 km of mudflat in San Pablo Bay (northern San Francisco Bay), an environment where tidal mixing prevents the formation of fluid mud. Wave height was measured along a cross shore transect (elevation range−2mto+0.45mMLLW) in winter 2011 and summer 2012. Wave height decreased more than 50% across the transect. The exponential decay coefficient λ was inversely related to depth squared (λ=6×10−4h−2). The physical roughness length scale kb, estimated from near-bed turbulence measurements, was 3.5×10−3 m in winter and 1.1×10−2 m in summer. Estimated wave friction factor fw determined from wave-height data suggests that bottom friction dominates dissipation at high Rew but not at low Rew. Predictions of near-shore wave height based on offshore wave height and a rough formulation for fw were quite accurate, with errors about half as great as those based on the smooth formulation for fw. Researchers often assume that the wave boundary layer is smooth for settings with fine-grained sediments. At this site, use of a smooth fw results in an underestimate of wave shear stress by a factor of 2 for typical waves and as much as 5 for more energetic waves. It also inadequately captures the effectiveness of the mudflats in protecting the shoreline through wave attenuation.
","language":"English","publisher":"World Scientific Pub.","doi":"10.1016/j.coastaleng.2016.03.008","usgsCitation":"Lacy, J.R., and MacVean, L.J., 2016, Wave attenuation in the shallows of San Francisco Bay: Coastal Engineering, v. 114, p. 159-168, https://doi.org/10.1016/j.coastaleng.2016.03.008.","productDescription":"10 p.","startPage":"159","endPage":"168","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069928","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":321455,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay, San Pablo Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.56622314453124,\n 37.81032643553478\n ],\n [\n -122.56622314453124,\n 39\n ],\n [\n -122.22015380859374,\n 39\n ],\n [\n -122.22015380859374,\n 37.81032643553478\n ],\n [\n -122.56622314453124,\n 37.81032643553478\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"114","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57403560e4b07e28b65e9732","contributors":{"authors":[{"text":"Lacy, Jessica R. 0000-0002-2797-6172 jlacy@usgs.gov","orcid":"https://orcid.org/0000-0002-2797-6172","contributorId":3158,"corporation":false,"usgs":true,"family":"Lacy","given":"Jessica","email":"jlacy@usgs.gov","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":629943,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"MacVean, Lissa J. lmacvean@usgs.gov","contributorId":4698,"corporation":false,"usgs":true,"family":"MacVean","given":"Lissa","email":"lmacvean@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":629944,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70171018,"text":"70171018 - 2016 - Numerical experiments to explain multiscale hydrological responses to mountain pine beetle tree mortality in a headwater watershed","interactions":[],"lastModifiedDate":"2016-05-19T10:54:17","indexId":"70171018","displayToPublicDate":"2016-04-26T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Numerical experiments to explain multiscale hydrological responses to mountain pine beetle tree mortality in a headwater watershed","docAbstract":"The effects of mountain pine beetle (MPB)-induced tree mortality on a headwater hydrologic system were investigated using an integrated physical modeling framework with a high-resolution computational grid. Simulations of MPB-affected and unaffected conditions, each with identical atmospheric forcing for a normal water year, were compared at multiple scales to evaluate the effects of scale on MPB-affected hydrologic systems. Individual locations within the larger model were shown to maintain hillslope-scale processes affecting snowpack dynamics, total evapotranspiration, and soil moisture that are comparable to several field-based studies and previous modeling work. Hillslope-scale analyses also highlight the influence of compensating changes in evapotranspiration and snow processes. Reduced transpiration in the Grey Phase of MPB-induced tree mortality was offset by increased late-summer evaporation, while overall snowpack dynamics were more dependent on elevation effects than MPB-induced tree mortality. At the watershed scale, unaffected areas obscured the magnitude of MPB effects. Annual water yield from the watershed increased during Grey Phase simulations by 11 percent; a difference that would be difficult to diagnose with long-term gage observations that are complicated by inter-annual climate variability. The effects on hydrology observed and simulated at the hillslope scale can be further damped at the watershed scale, which spans more life zones and a broader range of landscape properties. These scaling effects may change under extreme conditions, e.g., increased total MPB-affected area or a water year with above average snowpack.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Richmond, VA","doi":"10.1002/2015WR018300","usgsCitation":"Penn, C.A., Bearup, L.A., Maxwell, R.M., and Clow, D.W., 2016, Numerical experiments to explain multiscale hydrological responses to mountain pine beetle tree mortality in a headwater watershed: Water Resources Research, v. 52, no. 4, p. 3143-3161, https://doi.org/10.1002/2015WR018300.","productDescription":"19 p.","startPage":"3143","endPage":"3161","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070327","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":471047,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015wr018300","text":"Publisher Index Page"},{"id":321299,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-26","publicationStatus":"PW","scienceBaseUri":"573ee3d2e4b04a3a6a24ad3d","contributors":{"authors":[{"text":"Penn, Colin A. 0000-0002-5195-2744 cpenn@usgs.gov","orcid":"https://orcid.org/0000-0002-5195-2744","contributorId":5336,"corporation":false,"usgs":true,"family":"Penn","given":"Colin","email":"cpenn@usgs.gov","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629555,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bearup, Lindsay A.","contributorId":139257,"corporation":false,"usgs":false,"family":"Bearup","given":"Lindsay","email":"","middleInitial":"A.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":629556,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maxwell, Reed M.","contributorId":95373,"corporation":false,"usgs":true,"family":"Maxwell","given":"Reed","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":629557,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clow, David W. 0000-0001-6183-4824 dwclow@usgs.gov","orcid":"https://orcid.org/0000-0001-6183-4824","contributorId":1671,"corporation":false,"usgs":true,"family":"Clow","given":"David","email":"dwclow@usgs.gov","middleInitial":"W.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629558,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70170331,"text":"fs20163027 - 2016 - U.S. Geological Survey response to flooding in Texas, May–June 2015","interactions":[],"lastModifiedDate":"2016-04-26T11:33:30","indexId":"fs20163027","displayToPublicDate":"2016-04-26T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-3027","title":"U.S. Geological Survey response to flooding in Texas, May–June 2015","docAbstract":"As a Federal science agency within the Department of the Interior, the U.S. Geological Survey (USGS) collects and disseminates streamflow stage and discharge information along with other types of water information as a major part of its Water mission area. Data collected at USGS streamflow-gaging stations (hereinafter referred to as “streamgages”) are used for a variety of purposes including flood warning, engineering design, management of water resources, and scientific research.
During flood events, the need for timely, accurate, and complete streamflow data is underscored because these data are relied on by local, State, and Federal emergency management personnel for flood response purposes. For example, the National Weather Service uses the data from USGS streamgages to develop flood forecasts for specific locations on a river. Tasks that the USGS performs in response to floods include monitoring the operation of gages and responding to any interruptions in data collection, calibrating and verifying stage-discharge ratings, and documenting extreme events including peak stage and peak discharge.
Frequent, severe storms during May and June 2015 caused widespread flooding in Texas. By various measures, the storms that caused the flooding were extreme and persistent. May 2015 was the wettest month on record for Texas, with a statewide average precipitation of 9.06 inches. In comparison, the long-term statewide average monthly precipitation is 3.37 inches, with the previous record average monthly precipitation reported as 6.66 inches during June 2004. The Office of the Texas State Climatologist compiled monthly precipitation amounts for 19 selected cities throughout Texas and for 1 city in Louisiana; the total monthly precipitation amounts exceeded the monthly normal precipitation for 18 of the 19 selected cities in Texas, with 5 of these cities exceeding their previous record for the month of May.
The onset of abundant precipitation in May 2015 resulted in the National Weather Service flood stage being exceeded at USGS streamgages on numerous rivers. The widespread and prolonged nature of the flooding was unusual; most flood events in Texas are localized, typically affecting only one or two river basins and generally lasting only a few days. With the exception of the Rio Grande, flooding was widespread in all of the major rivers in Texas during May–June 2015.
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\"}}]}","contact":"Director, Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4733
Stable isotope delta values (δ18O and δ2H) of precipitation can vary with elevation, and quantification of the precipitation elevation gradient can be used to predict recharge elevation within a watershed. Precipitation samples were analyzed for stable isotope delta values between 2003 and 2014 from the Verde River watershed of north-central Arizona. Results indicate a significant decrease in summer isotopic values overtime at 3,100-, 4,100-, 6,100-, 7,100-, and 8,100-feet elevation. The updated local meteoric water line for the area is δ2H = 7.11 δ18O + 3.40. Equations to predict stable isotopic values based on elevation were updated from previous publications in Blasch and others (2006), Blasch and Bryson (2007), and Bryson and others (2007). New equations were separated for samples from the Camp Verde to Flagstaff transect and the Prescott to Chino Valley transect. For the Camp Verde to Flagstaff transect, the new equations for winter precipitation are δ18O = -0.0004z − 8.87 and δ2H = -0.0029z − 59.8 (where z represents elevation in feet) and the summer precipitation equations were not statistically significant. For the Prescott to Chino Valley transect, the new equations for summer precipitation are δ18O = -0.0005z − 3.22 and δ2H = -0.0022z − 27.9; the winter precipitation equations were not statistically significant and, notably, stable isotope values were similar across all elevations. Interpretation of elevation of recharge contributing to surface and groundwaters in the Verde River watershed using the updated equations for the Camp Verde to Flagstaff transect will give lower elevation values compared with interpretations presented in the previous studies. For waters in the Prescott and Chino Valley area, more information is needed to understand local controls on stable isotope values related to elevation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161053","collaboration":"Prepared in cooperation with Yavapai County Water Advisory Committee and Arizona Department of Water Resources","usgsCitation":"Beisner, K.R., Paretti, N.V., and Tucci, R.S., 2016, Analysis of stable isotope ratios (δ18O and δ2H) in precipitation of the Verde River watershed, Arizona, 2003 through 2014: U.S. Geological Survey Open-File Report 2016–1053, 11 p., https://dx.doi.org/10.3133/ofr20161053.","productDescription":"Report: iv, 9 p.; Stable Isotope Data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-070405","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":320392,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1053/ofr20161053.pdf","text":"Report","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1053"},{"id":320393,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1053/ofr20161053_appendix_tables.xlsx","text":"Stable Isotope Data","size":"31.1 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1053"},{"id":320391,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1053/coverthbr.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Verde River Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.6,\n 34.4\n ],\n [\n -112.6,\n 35.3\n ],\n [\n -111.3,\n 35.3\n ],\n [\n -111.3,\n 34.4\n ],\n [\n -112.6,\n 34.4\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Arizona Water Science Center
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http://az.water.usgs.gov/