Hurricanes cause substantial loss of life and resources in coastal areas. Unfortunately, historical hurricane records are too short and incomplete to capture hurricane-climate interactions on multi-decadal and longer timescales. Coarse-grained, hurricane-induced deposits preserved in blue holes in the Caribbean can provide records of past hurricane activity extending back thousands of years. Here we present a high resolution record of intense hurricane events over the past 1500 years from a blue hole on South Andros Island on the Great Bahama Bank. This record is corroborated by shorter reconstructions from cores collected at two nearby blue holes. The record contains coarse-grained event deposits attributable to known historical hurricane strikes within age uncertainties. Over the past 1500 years, South Andros shows evidence of four active periods of hurricane activity. None of these active intervals occurred in the past 163 years. We suggest that Intertropical Convergence Zone position modulates hurricane activity on the island based on a correlation with Cariaco Basin titanium concentrations. An anomalous gap in activity on South Andros Island in the early 13th century corresponds to a period of increased volcanism. The patterns of hurricane activity reconstructed from South Andros Island closely match those from the northeastern Gulf of Mexico but are anti-phased with records from New England. We suggest that either changes in local environmental conditions (e.g., SSTs) or a northeastward shift in storm tracks can account for the increased activity in the western North Atlantic when the Gulf of Mexico and southeastern Caribbean are less active.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019PA003665","usgsCitation":"Wallace, E., Donnelly, J.P., van Hengstum, P.J., Winman, C., Sullivan, R., Winkler, T., D'Entremont, N., Toomey, M., and Albury, N.A., 2019, Intense hurricane activity over the past 1500 years at South Andros Island, The Bahamas: Paleoceanography and Paleoclimatology, v. 34, no. 11, p. 1761-1783, https://doi.org/10.1029/2019PA003665.","productDescription":"23 p.","startPage":"1761","endPage":"1783","ipdsId":"IP-112040","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":459468,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019pa003665","text":"Publisher Index Page"},{"id":396016,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"The Bahamas","otherGeospatial":"South Andros Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.81204223632812,\n 23.626281853879018\n ],\n [\n -77.48313903808594,\n 23.626281853879018\n ],\n [\n -77.48313903808594,\n 23.888976847350275\n ],\n [\n -77.81204223632812,\n 23.888976847350275\n ],\n [\n -77.81204223632812,\n 23.626281853879018\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"34","issue":"11","noUsgsAuthors":false,"publicationDate":"2019-11-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Wallace, Elizabeth","contributorId":245340,"corporation":false,"usgs":false,"family":"Wallace","given":"Elizabeth","affiliations":[{"id":49154,"text":"Woods Hole Oceanographic Institution, Woods Hole","active":true,"usgs":false}],"preferred":false,"id":835014,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Donnelly, Jeffrey P.","contributorId":192783,"corporation":false,"usgs":false,"family":"Donnelly","given":"Jeffrey","email":"","middleInitial":"P.","affiliations":[{"id":6706,"text":"Woods Hole Oceanographic Institution,","active":true,"usgs":false}],"preferred":false,"id":835015,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Hengstum, Peter J.","contributorId":199536,"corporation":false,"usgs":false,"family":"van Hengstum","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":835016,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Winman, Charlotte","contributorId":279501,"corporation":false,"usgs":false,"family":"Winman","given":"Charlotte","email":"","affiliations":[{"id":12698,"text":"Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":835017,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sullivan, Richard","contributorId":211625,"corporation":false,"usgs":false,"family":"Sullivan","given":"Richard","email":"","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":835018,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Winkler, Tyler","contributorId":279503,"corporation":false,"usgs":false,"family":"Winkler","given":"Tyler","email":"","affiliations":[{"id":57261,"text":"Texas A&M, Galveston","active":true,"usgs":false}],"preferred":false,"id":835019,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"D'Entremont, Nicole","contributorId":279505,"corporation":false,"usgs":false,"family":"D'Entremont","given":"Nicole","affiliations":[{"id":16633,"text":"WHOI","active":true,"usgs":false}],"preferred":false,"id":835020,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Toomey, Michael 0000-0003-0167-9273 mtoomey@usgs.gov","orcid":"https://orcid.org/0000-0003-0167-9273","contributorId":184097,"corporation":false,"usgs":true,"family":"Toomey","given":"Michael","email":"mtoomey@usgs.gov","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":835021,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Albury, Nancy A.","contributorId":192785,"corporation":false,"usgs":false,"family":"Albury","given":"Nancy","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":835022,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70206507,"text":"70206507 - 2019 - Review of indicators for comparing environmental effects across energy sources","interactions":[],"lastModifiedDate":"2019-11-07T13:58:45","indexId":"70206507","displayToPublicDate":"2019-10-18T13:57:03","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Review of indicators for comparing environmental effects across energy sources","docAbstract":"Robust, quantitative comparisons of environmental effects across energy sources can support development of energy planning strategies that meet growing demand while managing and minimizing undesirable effects on environmental resources. Multicriteria analyses of energy systems often use a suite of indicators to make such comparisons, but those indicators and their units of measure vary among studies. We reviewed 179 papers that described or applied energy indicators to compare environmental effects of different primary energy sources to answer four questions: (1) what environmental indicators have been used in multicriteria energy-source comparisons? (2) across studies, how consistently are these indicators used to quantify effects? (3) to what degree are different effects accounted for across energy sources and locations? and (4) how comprehensive are indicators in terms of assessing known environmental effects? For reviewed studies, we quantified the number of unique indicators and the diversity of indicators used to measure different effects. We also recorded the specific measurement units applied to quantify each indicator, the energy sources evaluated, and the continent where each study was conducted. While we found that many environmental effects of energy development have been analyzed across multiple sources, indicators were frequently measured, interpreted, and applied in ways that are not directly comparable, and some known environmental effects were infrequently assessed. We also found an emphasis on applying indicators to renewable energy sources; assessing current and potential energy sources, both renewable and nonrenewable, would greatly clarify the full suite of tradeoffs among sources and can inform energy development strategies that minimize adverse environmental effects. Overall, our review indicated that making comprehensive comparisons of the effects of energy development across sources may require efforts to standardize how effects are measured, synthesize effects literature into an open-source database, expand the range of environmental effects analyzed, and establish consistent frameworks for comparison.","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/ab402d","usgsCitation":"Dorning, M., Diffendorfer, J., Loss, S.R., and Bagstad, K.J., 2019, Review of indicators for comparing environmental effects across energy sources: Environmental Research Letters, v. 14, no. 10, 103002, 15 p., https://doi.org/10.1088/1748-9326/ab402d.","productDescription":"103002, 15 p.","ipdsId":"IP-103123","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":459469,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/ab402d","text":"Publisher Index Page"},{"id":369053,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-10-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Dorning, Monica 0000-0002-7576-1256 mdorning@usgs.gov","orcid":"https://orcid.org/0000-0002-7576-1256","contributorId":191772,"corporation":false,"usgs":true,"family":"Dorning","given":"Monica","email":"mdorning@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":774835,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":774836,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Loss, Scott R","contributorId":220356,"corporation":false,"usgs":false,"family":"Loss","given":"Scott","email":"","middleInitial":"R","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":774837,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":774838,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70206180,"text":"70206180 - 2019 - Life cycle of the trout cecal nematode, Truttaedacnitis truttae (Nematoda: Cucullanidae): Experimental and field observations","interactions":[],"lastModifiedDate":"2019-10-25T06:22:34","indexId":"70206180","displayToPublicDate":"2019-10-18T13:48:28","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2414,"text":"Journal of Parasitology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Life cycle of the trout cecal nematode, Truttaedacnitis truttae (Nematoda: Cucullanidae): Experimental and field observations","title":"Life cycle of the trout cecal nematode, Truttaedacnitis truttae (Nematoda: Cucullanidae): Experimental and field observations","docAbstract":"Truttaedacnitis truttae is a cucullanid nematode of primarily salmonine fishes. Brown trout (Salmo trutta) in Europe reportedly become parasitized by ingesting lampreys (Lampetra planeri) carrying infective larvae. However, our field and laboratory observations suggested that North American specimens of T. truttae have an alternative life cycle. High abundances and potential impact of T. truttae in rainbow trout, Oncorhynchus mykiss, in the Colorado River drainage in Grand Canyon, where there are no lampreys, prompted a study on the transmission dynamics of this nematode. Eggs of T. truttae, collected from live gravid females, were incubated in the laboratory. Snails, Physa gyrina and Lymnaea sp., were exposed to T. truttae larvae 3–4 wk later. Active larvae of T. truttae were observed penetrating the intestinal wall of exposed snails, and worm larvae were found in the visceral tissues when examined 1 wk after exposure. Larvae in snails showed little growth and development 2 wk later and corresponded to L3 larvae. Infected snails were fed to hatchery-reared juvenile rainbow trout. Developing stages were subsequently found in the mucosal lining and lumen of trout intestines. Adult male and female (gravid) worms were found in the ceca of trout examined 5–6 mo after consuming infected snails. Larvae found in pepsin/trypsin digests and mucosal scrapings from wild, naturally infected, trout corroborate laboratory findings. Screening of Physa sp. and gammarids collected from Colorado River, Grand Canyon, for natural infections with T. truttae using the ITS1 rDNA marker gave positive results. Truttaedacnitis truttae is the second species, after Truttaedacnitis clitellarius of lake sturgeon, capable of using a snail first intermediate/paratenic host and is similar to several other cucullanids in having a histotropic phase of development in the definitive fish host.
","language":"English","publisher":"BioOne","doi":"10.1645/18-22","usgsCitation":"Choudhury, A., and Cole, R.A., 2019, Life cycle of the trout cecal nematode, Truttaedacnitis truttae (Nematoda: Cucullanidae): Experimental and field observations: Journal of Parasitology, v. 105, no. 5, p. 769-782, https://doi.org/10.1645/18-22.","productDescription":"14 p.","startPage":"769","endPage":"782","ipdsId":"IP-092857","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":368560,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River, Lees Ferry Reach","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.57835006713867,\n 36.85668612175977\n ],\n [\n -111.57354354858397,\n 36.86190535174327\n ],\n [\n -111.58607482910156,\n 36.869733528373395\n ],\n [\n -111.62212371826172,\n 36.851878620917546\n ],\n [\n -111.63602828979491,\n 36.82659992957925\n ],\n [\n -111.65782928466797,\n 36.79581459490302\n ],\n [\n -111.66658401489256,\n 36.769829841046075\n ],\n [\n -111.6712188720703,\n 36.75745305234459\n ],\n [\n -111.6598892211914,\n 36.75098882435508\n ],\n [\n -111.63362503051758,\n 36.794439960959835\n ],\n [\n -111.63516998291016,\n 36.80323719192363\n ],\n [\n -111.60152435302734,\n 36.84610922079688\n ],\n [\n -111.57835006713867,\n 36.85668612175977\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"105","issue":"5","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Choudhury, Anindo 0000-0001-7553-4179","orcid":"https://orcid.org/0000-0001-7553-4179","contributorId":220015,"corporation":false,"usgs":false,"family":"Choudhury","given":"Anindo","email":"","affiliations":[{"id":40120,"text":"St. Norbert College, DePere WI","active":true,"usgs":false}],"preferred":false,"id":773786,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cole, Rebecca A. 0000-0003-2923-1622 rcole@usgs.gov","orcid":"https://orcid.org/0000-0003-2923-1622","contributorId":2873,"corporation":false,"usgs":true,"family":"Cole","given":"Rebecca","email":"rcole@usgs.gov","middleInitial":"A.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":773785,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70227713,"text":"70227713 - 2019 - Morphological identification of Bighead Carp, Silver Carp, and Grass Carp eggs using random forests machine learning classification","interactions":[],"lastModifiedDate":"2022-01-27T16:17:18.542828","indexId":"70227713","displayToPublicDate":"2019-10-18T10:08:38","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Morphological identification of Bighead Carp, Silver Carp, and Grass Carp eggs using random forests machine learning classification","docAbstract":"Visual identification of fish eggs is difficult and unreliable due to a lack of information on the morphological egg characteristics of many species. We used random forests machine learning to predict the identity of genetically identified Bighead Carp Hypophthalmichthys nobilis, Grass Carp Ctenopharyngodon idella, and Silver Carp H. molitrix eggs based on egg morphometric and environmental characteristics. Family, genus, and species taxonomic-level random forests models were explored to assess the performance and accuracy of the predictor variables. The egg characteristics of Bighead Carp, Grass Carp, and Silver Carp were similar, and they were difficult to distinguish from one another. When combined into a single invasive carp class, the random forests models were ≥ 97% accurate at identifying invasive carp eggs, with a ≤5% false positive rate. Egg membrane diameter was the most important predictive variable, but the addition of ten other variables resulted in a 98% success rate for identifying invasive carp eggs from 26 other upper Mississippi River basin species. Our results revealed that a combination of morphometric and environmental measurements can be used to identify invasive carp eggs. Similar machine learning approaches could be used to identify the eggs of other fishes. These results will help managers more easily and quickly assess invasive carp reproduction.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10380","usgsCitation":"Camacho, C., Sullivan, C., Weber, M., and Pierce, C., 2019, Morphological identification of Bighead Carp, Silver Carp, and Grass Carp eggs using random forests machine learning classification: North American Journal of Fisheries Management, v. 39, no. 6, p. 1373-1384, https://doi.org/10.1002/nafm.10380.","productDescription":"12 p.","startPage":"1373","endPage":"1384","ipdsId":"IP-080766","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":459471,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://lib.dr.iastate.edu/nrem_pubs/327","text":"External Repository"},{"id":394976,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","otherGeospatial":"Cedar River, Des Moines River, Iowa river, Mississippi River, Skunk River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.5,\n 40.32141999593439\n ],\n [\n -90.120849609375,\n 40.32141999593439\n ],\n [\n -90.120849609375,\n 42\n ],\n [\n -93.5,\n 42\n ],\n [\n -93.5,\n 40.32141999593439\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"39","issue":"6","noUsgsAuthors":false,"publicationDate":"2019-10-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Camacho, Carlos A.","contributorId":272254,"corporation":false,"usgs":false,"family":"Camacho","given":"Carlos A.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":831867,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sullivan, Christopher J.","contributorId":272255,"corporation":false,"usgs":false,"family":"Sullivan","given":"Christopher J.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":831868,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weber, Michael J.","contributorId":272256,"corporation":false,"usgs":false,"family":"Weber","given":"Michael J.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":831869,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pierce, Clay 0000-0001-5088-5431 cpierce@usgs.gov","orcid":"https://orcid.org/0000-0001-5088-5431","contributorId":150492,"corporation":false,"usgs":true,"family":"Pierce","given":"Clay","email":"cpierce@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":831866,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70210789,"text":"70210789 - 2019 - Multi-decade mortality and a novel homolog of hepatitis C virus in bald eagles (Haliaeetus leucocephalus), the national bird of the USA","interactions":[],"lastModifiedDate":"2020-06-25T14:58:18.19717","indexId":"70210789","displayToPublicDate":"2019-10-18T09:41:40","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Multi-decade mortality and a novel homolog of hepatitis C virus in bald eagles (Haliaeetus leucocephalus), the national bird of the USA","docAbstract":"The bald eagle (Haliaeetus leucocephalus) once experienced near-extinction but has since rebounded. For decades, bald eagles near the Wisconsin River, USA, have experienced a lethal syndrome with characteristic clinical and pathological features but unknown etiology. Here, we describe a novel hepacivirus-like virus (Flaviviridae: Hepacivirus) identified during an investigation of Wisconsin River eagle syndrome (WRES). Bald eagle hepacivirus (BeHV) belongs to a divergent clade of avian viruses that share features with members of the genera Hepacivirus and Pegivirus. BeHV infected 31.9% of eagles spanning 4,254 km of the coterminous USA, with negative strand viral RNA demonstrating active replication in liver tissues. Eagles from Wisconsin were approximately 10-fold more likely to be infected than eagles from elsewhere. Eagle mitochondrial DNA sequences were homogeneous and geographically unstructured, likely reflecting a recent population bottleneck, whereas BeHV envelope gene sequences showed strong population genetic substructure and isolation by distance, suggesting localized transmission. Cophylogenetic analyses showed no congruity between eagles and their viruses, supporting horizontal rather than vertical transmission. These results expand our knowledge of the Flaviviridae, reveal a striking pattern of decoupled host/virus coevolution on a continental scale, and highlight knowledge gaps about health and conservation in even the most iconic of wildlife species.","language":"English","publisher":"Nature","doi":"10.1038/s41598-019-50580-8","usgsCitation":"Golberg, T.L., Sibley, S.D., Pinkerton, M., Dunn, C.D., Long, L., White, C.L., and Strom, S., 2019, Multi-decade mortality and a novel homolog of hepatitis C virus in bald eagles (Haliaeetus leucocephalus), the national bird of the USA: Scientific Reports, v. 9, 14953, 12 p., https://doi.org/10.1038/s41598-019-50580-8.","productDescription":"14953, 12 p.","ipdsId":"IP-111425","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":459474,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-019-50580-8","text":"Publisher Index 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Menlo Park, CA 94025
Water-withdrawal, water-use, and water-return information have been collected and compiled for each county in Georgia every 5 years since 1980 using data obtained from various Federal, State, and private agencies, as well as additional online sources. For 2015, water use, water withdrawal, and water returns were estimated for each county, water-planning region, major river basin, and principal aquifer in Georgia. Offstream water use in 2015 is estimated for the categories of domestic, commercial, industrial processing, mining, irrigation (subdivided into crop and golf course irrigation), livestock, aquaculture, and thermoelectric power cooling.
According to the U.S. Census Bureau, approximately 10.2 million people in Georgia needed water resources to meet their personal, commercial, and recreational needs in 2015. Public water suppliers provided water to about 85 percent of the population of Georgia. Estimated total water withdrawals from both surface-water and groundwater sources were about 3,384 million gallons per day (Mgal/d) in 2015, which is a 27-percent reduction from 2010, a 48.1-percent reduction from 2000, and a 49.7-percent reduction from 1980. In 2015, surface-water withdrawals were greatest for thermoelectric power cooling (839.8 Mgal/d), and groundwater withdrawals were greatest for irrigating crops (547.9 Mgal/d). Water needs in northern Georgia are typically met by withdrawing a larger percentage of water from surface-water than groundwater sources; conversely, counties in southern Georgia withdraw more water from groundwater sources. About 1,571 Mgal/d of water were returned to Georgia streams and lakes in 2015, which represents about 46 percent of the total water withdrawn from all sources in 2015.
Water users in the Apalachicola River Basin, in 2015, withdrew the highest percentage of water (35 percent) and returned the highest percentage of water to surface-water bodies (almost 40 percent) compared to other major river basins in Georgia. Withdrawals in the Apalachicola River Basin are primarily extracted by public-supply systems (43 percent) and irrigation (34 percent). The aquifer from which 68 percent of statewide groundwater withdrawals were extracted was the Floridan aquifer system, and the majority of the water was used for irrigation (57 percent).
Historically, statewide water use in Georgia was highest in 1980 (6,735 Mgal/d), decreased to 5,353 Mgal/d in 1990, peaked at 6,531 Mgal/d in 2000, and has been declining since that time. The reduction in water use between 2000 and 2015 came primarily from surface-water withdrawals (90 percent of total reduction) and thermoelectric power cooling use (78 percent of total reduction). Water use for livestock and aquaculture increased between 1985 and 2015, and this increase correlates with the growth of agriculture in Georgia during that period. The driving forces behind the observed water-use changes include (1) shifts in population numbers and locations, (2) five periods of major drought, (3) water conservation efforts and education programs initiated by State and local governments and water utilities, and (4) changing water needs for thermoelectric power cooling, industry, and agricultural activities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191086","collaboration":"Prepared in cooperation with the Georgia Department of Natural Resources, Environmental Protection Division","usgsCitation":"Painter, J.A., 2019, Estimated use of water in Georgia for 2015 and water-use trends, 1985–2015: U.S. Geological Survey Open-File Report 2019–1086, 216 p., https://doi.org/10.3133/ofr20191086.","productDescription":"vi, 216 p.","numberOfPages":"226","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-096369","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":437300,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V2F373","text":"USGS data release","linkHelpText":"Georgia Water Use 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\"}}]}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
1770 Corporate Drive
Suite 500
Norcross, GA 30093
Embedded within the North American Prairie Pothole Region (PPR) are millions of small, depressional wetlands that annually support 50–80% of the continent’s waterfowl production. We recently assembled evidence that demonstrates a change towards a wetter climate that is driving a shift in the state of the region’s wetland ecosystems. This ecological state-shift has been primarily the result of a sustained wet climate that has influenced timing and magnitude of surface-water inputs to wetlands, connections to groundwater, and inputs of dissolved salts. As climate influences continue to change in the PPR, it is important to understand the potential of these changes to impact wetland habitats important for waterfowl production. Previous model simulations of prairie-pothole wetlands under future climate scenarios projected decreases in the ability of wetlands to facilitate waterfowl production throughout the majority of what is currently the most productive portion of the region. Results from these modeling efforts also suggested that suitable waterfowl breeding-habitat would be limited mostly to the southeastern portion of the PPR, a portion of the region in which most depressional wetlands (> 90%) have been drained. Thus, if these modeled outcomes materialize, a significant restoration effort would be needed in the southeastern PPR to support waterfowl production. However, the models used in earlier efforts were developed from a small number of wetlands using data from a relatively dry period and did not allow for changing mechanisms influencing surface-water, groundwater and dissolved salt inputs to prairie-pothole wetlands.
The primary objective of our research is to improve our understanding of future climate change on impacts to wetland ecosystems and breeding waterfowl habitat in the PPR. We used a newly developed Pothole Hydrology Linked Systems Simulator (PHyLiSS) model to estimate wetland ecosystem responses to 32 distinct climate models under 2 different emissions scenarios. Unlike previous wetland hydrology models, the PHyLiSS model allows for shifting hydrological and geochemical mechanisms influencing wetland ecosystems. We modeled one average-sized seasonal wetland basin at 18 different geographic locations (hereafter “sites”) across the PPR with 3 sites represented for each of 6 ecoregions coincident to early research. We applied the PHyLiSS model using historical daily precipitation and temperature data from 1982–2015 and developed linear models relative to ponded water depth in the simulated wetlands and the observed regional WBPHS May Pond count number for 16 of the 18 sites. Based on the output of 32 climate models and 2 emission scenarios we found a projected change in May pond numbers from -23% to +.02% when comparing the most recent climate period (1989–2018) to the end of the 21st century (2070–2099). We also found no evidence that the distribution of May ponds will shift in the future. These results suggest that management and conservation strategies for wetlands in the PPR should continue to focus on areas where high densities of intact wetland basins support large numbers of breeding duck pairs.
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2019 - Controls on eolian landscape evolution in fractured bedrock","interactions":[],"lastModifiedDate":"2020-10-06T15:52:57.416752","indexId":"70215004","displayToPublicDate":"2019-10-17T10:40:29","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Controls on eolian landscape evolution in fractured bedrock","docAbstract":"Wind abrasion is important for planetary landscape evolution, and wind‐abraded bedrock landscapes contain many landforms that are difficult to interpret. Here we exploit a natural experiment in Chile where topographic shielding by an upwind lava flow yields diverse erosional landforms in a downwind ignimbrite. Using a 3‐D topographic wind model, we find that low velocities in the wake of a lava lobe coincide with a transition from landforms reflecting fracture‐parallel erosion to flow‐parallel erosion. Erosion rates across these landforms vary with shear velocity and abrasion susceptibility of the windward escarpment. We hypothesize that this morphologic threshold is controlled by whether particles can be lofted in suspension and overcome topographic steering imposed by fractured bedrock blocks. Within a phase space set by Rouse and Stokes numbers, our data illustrate that wind‐abraded landforms reflect a competition between the material skeleton of the landscape and the strength of the flow that shapes it.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019GL083955","usgsCitation":"Perkins, J.P., Finnegan, N.J., de Silva, S.L., and Willis, M.J., 2019, Controls on eolian landscape evolution in fractured bedrock: Geophysical Research Letters, v. 46, no. 21, p. 12012-12020, https://doi.org/10.1029/2019GL083955.","productDescription":"9 p.","startPage":"12012","endPage":"12020","ipdsId":"IP-107187","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":459479,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2019gl083955","text":"External Repository"},{"id":379084,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Chile","otherGeospatial":"Antofogasta region, Central Andes Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.6640625,\n -23.94609601499837\n ],\n [\n -70.11474609375,\n -23.94609601499837\n ],\n [\n -70.11474609375,\n -23.443088931121775\n ],\n [\n -70.6640625,\n -23.443088931121775\n ],\n [\n -70.6640625,\n -23.94609601499837\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"46","issue":"21","noUsgsAuthors":false,"publicationDate":"2019-11-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Perkins, Jonathan P. 0000-0002-6113-338X","orcid":"https://orcid.org/0000-0002-6113-338X","contributorId":237053,"corporation":false,"usgs":true,"family":"Perkins","given":"Jonathan","email":"","middleInitial":"P.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":800519,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Finnegan, Noah J.","contributorId":198803,"corporation":false,"usgs":false,"family":"Finnegan","given":"Noah","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":800520,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"de Silva, Shanaka L. 0000-0002-0310-5516","orcid":"https://orcid.org/0000-0002-0310-5516","contributorId":242616,"corporation":false,"usgs":false,"family":"de Silva","given":"Shanaka","email":"","middleInitial":"L.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":800521,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Willis, Michael J. 0000-0003-1308-2888","orcid":"https://orcid.org/0000-0003-1308-2888","contributorId":242617,"corporation":false,"usgs":false,"family":"Willis","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":13693,"text":"University of Colorado Boulder","active":true,"usgs":false}],"preferred":false,"id":800522,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70206010,"text":"70206010 - 2019 - Variability in results from mineralogical and organic geochemical interlaboratory testing of U. S. Geological Survey shale reference materials","interactions":[],"lastModifiedDate":"2019-10-17T08:01:22","indexId":"70206010","displayToPublicDate":"2019-10-17T08:00:08","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":18,"text":"Abstract or summary"},"title":"Variability in results from mineralogical and organic geochemical interlaboratory testing of U. S. Geological Survey shale reference materials","docAbstract":"The expansion of unconventional petroleum resource exploration and production in the United States has led to an increase in source rock characterization efforts, particularly related to bulk organic and mineralogical properties. To support the analytical and research needs of industry and academia, as well as internal work, the U.S. Geological Survey (USGS) has collected and prepared shale geochemical reference materials (GRMs) from several major shale petroleum systems in the U.S. The sources of these materials are the Late Cretaceous Boquillas (lower Eagle Ford-equivalent) Formation (roadcut near Del Rio, TX), Late Cretaceous Mancos Shale (outcrop near Delta, CO), Devonian–Mississippian Woodford Shale (outcrop near Ardmore, OK), Late Cretaceous Niobrara Formation (quarry near Lyons, CO), Middle Devonian Marcellus Shale (creek bed in LeRoy, NY), and Eocene Mahogany zone oil shale of the Green River Formation (oil shale mine near Rifle, CO). Of particular interest in the development of these GRMs has been the examination of variability between laboratories and specific methods or instruments in commonly made measurements, including major- and trace-element concentrations, X-ray diffraction (XRD) mineralogy, total organic carbon (TOC) content, and programmed pyrolysis (PP) parameters. For the component concentrations and parameters we measured, the techniques and instrument types included: (1) elemental analysis by X-ray fluorescence, inductively coupled plasma mass spectrometry, and instrumental neutron activation analysis; (2) XRD mineralogy with various preparatory methods (spray drying or micronizing with or without internal standard); (3) TOC by combustion with infrared detection after carbonate removal or the PP approach; (4) PP by Rock-Eval 2 or more recently developed instruments (Rock-Eval 6, Source Rock Analyzer or SRA, and Hydrocarbon Analyzer With Kinetics or HAWK). Overall, the results showed that the selected shales cover a wide range of source rock organic and mineralogical properties. Major- and trace-element chemistry results showed low heterogeneity consistent with other USGS GRMs. Comparison of TOC results showed coefficients of variation (COV) of around 5% and the most consistent organic geochemical results between different laboratories and methods. Arguably the most relevant PP measurement, S2 or kerogen hydrocarbon-generating potential (mg-HC/g-rock), showed a somewhat wider range of variability than TOC (COV ~10%), but was consistent between the three modern instruments and the industry-standard Rock-Eval 2. Major phase mineralogy (mineral concentrations ≥10 wt. %, organic-free basis) were comparable between laboratories, but variability in minor phase identification and quantification was observed. Utilization of these shale GRMs as quality control samples and testing materials is expected to help support analytical and experimental efforts in the continued development of unconventional petroleum resources.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 7th Unconventional Resources Technology Conference","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Unconventional Resources Technology Conference","conferenceDate":"July 22-24, 2019","conferenceLocation":"Denver, CO","language":"English","publisher":"American Association of Petroleum Geologists ","doi":"10.15530/urtec-2019-457","usgsCitation":"Birdwell, J.E., and Wilson, S., 2019, Variability in results from mineralogical and organic geochemical interlaboratory testing of U. S. 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Science Center","active":true,"usgs":true}],"preferred":true,"id":773282,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70206093,"text":"70206093 - 2019 - Evolutionary history predicts high-impact invasions by herbivorous insects","interactions":[],"lastModifiedDate":"2020-09-01T13:55:59.07044","indexId":"70206093","displayToPublicDate":"2019-10-17T07:39:29","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Evolutionary history predicts high-impact invasions by herbivorous insects","docAbstract":"A long‐standing goal of invasion biology is to identify factors driving highly variable impacts of non‐native species. Although hypotheses exist that emphasize the role of evolutionary history (e.g., enemy release hypothesis & defense‐free space hypothesis), predicting the impact of non‐native herbivorous insects has eluded scientists for over a century.\nUsing a census of all 58 non‐native conifer‐specialist insects in North America, we quantified the contribution of over 25 factors that could affect the impact they have on their novel hosts, including insect traits (fecundity, voltinism, native range, etc.), host traits (shade tolerance, growth rate, wood density, etc.), and evolutionary relationships (between native and novel hosts and insects).\nWe discovered that divergence times between native and novel hosts, the shade and drought tolerance of the novel host, and the presence of a coevolved congener on a shared host, were more predictive of impact than the traits of the invading insect. These factors built upon each other to strengthen our ability to predict the risk of a non‐native insect becoming invasive. This research is the first to empirically support historically assumed hypotheses about the importance of evolutionary history as a major driver of impact of non‐native herbivorous insects.\nOur novel, integrated model predicts whether a non‐native insect not yet present in North America will have a one in 6.5 to a one in 2,858 chance of causing widespread mortality of a conifer species if established (R2 = 0.91)\nSynthesis and applications. With this advancement, the risk to other conifer host species and regions can be assessed, and regulatory and pest management efforts can be more efficiently prioritized.","language":"English","publisher":"Wiley","doi":"10.1002/ece3.5709","usgsCitation":"Mech, A.M., Thomas, K.A., Marsico, T.D., Herms, D.A., Allen, C., Ayres, M.P., Gandhi, K., Gurevitch, J., Havill, N.P., Hufbauer, R.A., Liebhold, A.M., Raffa, K.F., Schulz, A.N., Uden, D.R., and Tobin, P.C., 2019, Evolutionary history predicts high-impact invasions by herbivorous insects: Ecology and Evolution, v. 9, no. 21, p. 12216-12230, https://doi.org/10.1002/ece3.5709.","productDescription":"15 p.","startPage":"12216","endPage":"12230","ipdsId":"IP-098825","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":459482,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.5709","text":"Publisher Index Page"},{"id":437302,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CLFQMI","text":"USGS data release","linkHelpText":"Traits and Factors Catalog (TRAFAC): Conifer specialists of North America"},{"id":368476,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"21","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-10-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Mech, Angela M.","contributorId":219892,"corporation":false,"usgs":false,"family":"Mech","given":"Angela","email":"","middleInitial":"M.","affiliations":[{"id":40087,"text":"School of Environmental and Forest Sciences, University of Washington, Seattle, WA. Corresponding email: ammech@wcu.edu. Present address: Department of Geosciences and Natural Resources, Western Carolina University, Cullowhee, NC","active":true,"usgs":false}],"preferred":false,"id":773543,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thomas, Kathryn A. 0000-0002-7131-8564 kathryn_a_thomas@usgs.gov","orcid":"https://orcid.org/0000-0002-7131-8564","contributorId":167,"corporation":false,"usgs":true,"family":"Thomas","given":"Kathryn","email":"kathryn_a_thomas@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":773544,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marsico, Travis D.","contributorId":219893,"corporation":false,"usgs":false,"family":"Marsico","given":"Travis","email":"","middleInitial":"D.","affiliations":[{"id":40088,"text":"Department of Biological Sciences, Arkansas State University, Jonesboro, AR","active":true,"usgs":false}],"preferred":false,"id":773545,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Herms, Daniel A.","contributorId":219895,"corporation":false,"usgs":false,"family":"Herms","given":"Daniel","email":"","middleInitial":"A.","affiliations":[{"id":40089,"text":"The Davey Tree Expert Company, Kent, OH","active":true,"usgs":false}],"preferred":false,"id":773547,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Allen, Craig 0000-0001-8655-8227 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8227","contributorId":219896,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":773548,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ayres, Matthew P.","contributorId":219897,"corporation":false,"usgs":false,"family":"Ayres","given":"Matthew","email":"","middleInitial":"P.","affiliations":[{"id":35787,"text":"Department of Biological Sciences, Dartmouth College, Hanover, NH","active":true,"usgs":false}],"preferred":false,"id":773549,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gandhi, Kamal J.K.","contributorId":219898,"corporation":false,"usgs":false,"family":"Gandhi","given":"Kamal J.K.","affiliations":[{"id":40090,"text":"D.B. Warnell School of Forestry and Natural Resources, University of Georgia, Athens, GA","active":true,"usgs":false}],"preferred":false,"id":773550,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gurevitch, Jessica","contributorId":219899,"corporation":false,"usgs":false,"family":"Gurevitch","given":"Jessica","email":"","affiliations":[{"id":33447,"text":"Department of Ecology and Evolution, Stony Brook University, Stony Brook, NY","active":true,"usgs":false}],"preferred":false,"id":773551,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Havill, Nathan P.","contributorId":219900,"corporation":false,"usgs":false,"family":"Havill","given":"Nathan","email":"","middleInitial":"P.","affiliations":[{"id":40091,"text":"Northern Research Station, USDA Forest Service, Hamden, CT","active":true,"usgs":false}],"preferred":false,"id":773552,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hufbauer, Ruth A.","contributorId":219901,"corporation":false,"usgs":false,"family":"Hufbauer","given":"Ruth","email":"","middleInitial":"A.","affiliations":[{"id":40092,"text":"Department of Bioagricultural Science and Pest Management, Colorado State University, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":773553,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Liebhold, Andrew M.","contributorId":219902,"corporation":false,"usgs":false,"family":"Liebhold","given":"Andrew","email":"","middleInitial":"M.","affiliations":[{"id":40093,"text":"USDA Forest Service Northern Research Station, Morgantown, WV","active":true,"usgs":false}],"preferred":false,"id":773554,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Raffa, Kenneth F.","contributorId":219903,"corporation":false,"usgs":false,"family":"Raffa","given":"Kenneth","email":"","middleInitial":"F.","affiliations":[{"id":40094,"text":"Department of Entomology, University of Wisconsin, Madison, WI","active":true,"usgs":false}],"preferred":false,"id":773555,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Schulz, Ashley N.","contributorId":219894,"corporation":false,"usgs":false,"family":"Schulz","given":"Ashley","email":"","middleInitial":"N.","affiliations":[{"id":40088,"text":"Department of Biological Sciences, Arkansas State University, Jonesboro, AR","active":true,"usgs":false}],"preferred":false,"id":773546,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Uden, Daniel R.","contributorId":219904,"corporation":false,"usgs":false,"family":"Uden","given":"Daniel","email":"","middleInitial":"R.","affiliations":[{"id":40095,"text":"Nebraska Cooperative Fish and Wildlife Unit, School of Natural Resources, University of Nebraska-Lincoln, Lincoln, NE","active":true,"usgs":false}],"preferred":false,"id":773556,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Tobin, Patrick C.","contributorId":200172,"corporation":false,"usgs":false,"family":"Tobin","given":"Patrick","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":773557,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70206015,"text":"70206015 - 2019 - Competitive interactions among H, CU, and Zn ion moderate aqueous uptake of Cu and Zn by an aquatic insect","interactions":[],"lastModifiedDate":"2019-10-17T07:34:48","indexId":"70206015","displayToPublicDate":"2019-10-17T07:32:45","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1555,"text":"Environmental Pollution","active":true,"publicationSubtype":{"id":10}},"title":"Competitive interactions among H, CU, and Zn ion moderate aqueous uptake of Cu and Zn by an aquatic insect","docAbstract":"The absorption of aqueous copper (Cu) and zinc (Zn) by aquatic insects, a group widely used to assess water quality, is unresolved. This study examined interactions among Cu, Zn, and protons that potentially moderate Cu and Zn uptake by the acid-tolerant stonefly Zapada sp. Saturation uptake kinetics was imposed to identify competitive mechanisms. Decreasing pH reduced the maximum transport capacity, Jmax, in both metals, had little effect on the Cu dissociation constant, KD, and increased the Zn KD. Partial noncompetitive (Cu) and partial mixed competitive (Zn) inhibitor models most closely tracked the observed Cu and Zn influx across pH treatments. The estimated values for acid dissociation constants for the binary (proton-receptor) and ternary (proton-metal-receptor) complexes indicated the strong inhibitory effect of protons on Cu and Zn. In neutral pH water, Cu inhibited Zn uptake, but Zn had little effect on Cu uptake. The mechanism of Cu-Zn interaction was not identified. Results from separate Zn experiments suggested that the insect’s developmental stage may affect the apparent Jmax. The study underscores some of the challenges of modeling metal bioaccumulation and informs future research directions.","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2019.113220","usgsCitation":"Cain, D.J., Croteau, M.N., and Fuller, C.C., 2019, Competitive interactions among H, CU, and Zn ion moderate aqueous uptake of Cu and Zn by an aquatic insect: Environmental Pollution, v. 255, no. Part 1, 113220, https://doi.org/10.1016/j.envpol.2019.113220.","productDescription":"113220","ipdsId":"IP-111255","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":368359,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"255","issue":"Part 1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cain, Daniel J. 0000-0002-3443-0493 djcain@usgs.gov","orcid":"https://orcid.org/0000-0002-3443-0493","contributorId":1784,"corporation":false,"usgs":true,"family":"Cain","given":"Daniel","email":"djcain@usgs.gov","middleInitial":"J.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":773298,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Croteau, Marie Noele 0000-0003-0346-3580 mcroteau@usgs.gov","orcid":"https://orcid.org/0000-0003-0346-3580","contributorId":895,"corporation":false,"usgs":true,"family":"Croteau","given":"Marie","email":"mcroteau@usgs.gov","middleInitial":"Noele","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":773299,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fuller, Christopher C. 0000-0002-2354-8074 ccfuller@usgs.gov","orcid":"https://orcid.org/0000-0002-2354-8074","contributorId":1831,"corporation":false,"usgs":true,"family":"Fuller","given":"Christopher","email":"ccfuller@usgs.gov","middleInitial":"C.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","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},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":773300,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70206951,"text":"70206951 - 2019 - Mechanics of inflationary deformation during Caldera collapse: Evidence from the 2018 Kīlauea Eruption","interactions":[],"lastModifiedDate":"2019-12-02T07:06:50","indexId":"70206951","displayToPublicDate":"2019-10-17T07:06:08","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Mechanics of inflationary deformation during Caldera collapse: Evidence from the 2018 Kīlauea Eruption","docAbstract":"During the 2018 Kilauea eruption the caldera ffloor dropped 500 meters in 62 nearly periodic events of up to 8 meters. Caldera collapse maintains pressure in the magma reservoir necessary to sustain high-rate eruptions. The 2018 collapses were accompanied by inflationary tilts and displacements, similar to observations at other basaltic calderas. Collapse is modeled in 2D by uniform slip dislocations intersecting a magma chamber. Collapses occurred rapidly, such that mass within the chamber was constant. For vertical faults surface deformation outside the collapse results only from chamber pressurization with displacements anti-parallel to pre-collapse deflation, similar to observations. For inward dipping faults the predicted ratio of horizontal to vertical displacements during collapse is greater than for the pre-collapse deflation, as observed. For outward dipping faults the horizontal displacements are inward, contrary to data. The average deformation trends during the eruption depend on fault dip and whether stress required to trigger collapses was constant or changed with time.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019GL084689","usgsCitation":"Paul Segall, Anderson, K.R., Johanson, I.A., and Miklius, A., 2019, Mechanics of inflationary deformation during Caldera collapse: Evidence from the 2018 Kīlauea Eruption: Geophysical Research Letters, v. 46, no. 21, p. 11782-11789, https://doi.org/10.1029/2019GL084689.","productDescription":"8 p.","startPage":"11782","endPage":"11789","ipdsId":"IP-110422","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":369784,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.38238525390625,\n 19.137384001472565\n ],\n [\n -155.07476806640625,\n 19.137384001472565\n ],\n [\n -155.07476806640625,\n 19.414792438099557\n ],\n [\n -155.38238525390625,\n 19.414792438099557\n ],\n [\n -155.38238525390625,\n 19.137384001472565\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"46","issue":"21","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Paul Segall","contributorId":200979,"corporation":false,"usgs":false,"family":"Paul Segall","affiliations":[],"preferred":false,"id":776355,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Kyle R. 0000-0001-8041-3996 kranderson@usgs.gov","orcid":"https://orcid.org/0000-0001-8041-3996","contributorId":3522,"corporation":false,"usgs":true,"family":"Anderson","given":"Kyle","email":"kranderson@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":776354,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johanson, Ingrid A. 0000-0002-6049-2225","orcid":"https://orcid.org/0000-0002-6049-2225","contributorId":215613,"corporation":false,"usgs":true,"family":"Johanson","given":"Ingrid","email":"","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":776356,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miklius, Asta 0000-0002-2286-1886","orcid":"https://orcid.org/0000-0002-2286-1886","contributorId":215615,"corporation":false,"usgs":true,"family":"Miklius","given":"Asta","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":776357,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70209062,"text":"70209062 - 2019 - A geographic hot spot of Ichthyophonus infection in the southern Salish Sea, USA","interactions":[],"lastModifiedDate":"2020-03-13T07:07:25","indexId":"70209062","displayToPublicDate":"2019-10-17T07:04:51","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1396,"text":"Diseases of Aquatic Organisms","active":true,"publicationSubtype":{"id":10}},"title":"A geographic hot spot of Ichthyophonus infection in the southern Salish Sea, USA","docAbstract":"The prevalence of Ichthyophonus infection in Pacific herring Clupea pallasii was spatially heterogeneous in the southern Salish Sea, Washington State, USA. Over the course of 13 mo, 2232 Pacific herring were sampled from 38 midwater trawls throughout the region. Fork length was positively correlated with Ichthyophonus infection at all sites. After controlling for the positive relationship between host size and Ichthyophonus infection, the probability of infection was approximately 6-fold higher in North Hood Canal than in Puget Sound and the northern Straits (12 vs. 2% predicted probability for a 100 mm fish and 30 vs. 7% predicted probability for a 180 mm fish). Temporal changes in Ichthyophonus infection probability were explained by seasonal differences in fish length, owing to Pacific herring life history and movement patterns. Reasons for the spatial heterogeneity remain uncertain but may be associated with density-dependent factors inherent to the boom-bust cycles that commonly occur in clupeid populations.","language":"English","publisher":"Inter-Research","doi":"10.3354/dao03399","usgsCitation":"Hershberger, P., MacKenzie, A., Gregg, J., Lindquist, A., Sandell, T., Groner, M.L., and Lowry, D., 2019, A geographic hot spot of Ichthyophonus infection in the southern Salish Sea, USA: Diseases of Aquatic Organisms, v. 136, no. 2, p. 157-162, https://doi.org/10.3354/dao03399.","productDescription":"6 p.","startPage":"157","endPage":"162","ipdsId":"IP-108749","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":459487,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/dao03399","text":"Publisher Index Page"},{"id":373232,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Salish Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.82714843749999,\n 48.00830020485928\n ],\n [\n -123.2720947265625,\n 47.48380086737799\n ],\n [\n -123.21716308593749,\n 47.21956811231547\n ],\n [\n -122.8875732421875,\n 47.00647991252098\n ],\n [\n -122.25036621093749,\n 47.23821935972681\n ],\n [\n -122.16247558593751,\n 48.004625021133904\n ],\n [\n -122.82714843749999,\n 48.00830020485928\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"136","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hershberger, Paul 0000-0002-2261-7760 phershberger@usgs.gov","orcid":"https://orcid.org/0000-0002-2261-7760","contributorId":150816,"corporation":false,"usgs":true,"family":"Hershberger","given":"Paul","email":"phershberger@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":784675,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"MacKenzie, Ashley 0000-0002-7402-7877 amackenzie@usgs.gov","orcid":"https://orcid.org/0000-0002-7402-7877","contributorId":150817,"corporation":false,"usgs":true,"family":"MacKenzie","given":"Ashley","email":"amackenzie@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":784676,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gregg, Jacob jgregg@usgs.gov","contributorId":140132,"corporation":false,"usgs":true,"family":"Gregg","given":"Jacob","email":"jgregg@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":784677,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lindquist, A","contributorId":223246,"corporation":false,"usgs":false,"family":"Lindquist","given":"A","affiliations":[{"id":40691,"text":"Washington Department of Fish and Wildlife, Marine Fish Program, Olympia, WA 98501","active":true,"usgs":false}],"preferred":false,"id":784678,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sandell, T","contributorId":223247,"corporation":false,"usgs":false,"family":"Sandell","given":"T","email":"","affiliations":[{"id":40691,"text":"Washington Department of Fish and Wildlife, Marine Fish Program, Olympia, WA 98501","active":true,"usgs":false}],"preferred":false,"id":784679,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Groner, Maya L. 0000-0002-3381-6415","orcid":"https://orcid.org/0000-0002-3381-6415","contributorId":213541,"corporation":false,"usgs":true,"family":"Groner","given":"Maya","email":"","middleInitial":"L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":784680,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lowry, D","contributorId":223249,"corporation":false,"usgs":false,"family":"Lowry","given":"D","email":"","affiliations":[{"id":40691,"text":"Washington Department of Fish and Wildlife, Marine Fish Program, Olympia, WA 98501","active":true,"usgs":false}],"preferred":false,"id":784681,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70205580,"text":"ofr20191095 - 2019 - Hurricane Matthew: Predictions, observations, and an analysis of coastal change","interactions":[],"lastModifiedDate":"2019-10-16T16:26:40","indexId":"ofr20191095","displayToPublicDate":"2019-10-16T17:40:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1095","displayTitle":"Hurricane Matthew: Predictions, Observations, and an Analysis of Coastal Change","title":"Hurricane Matthew: Predictions, observations, and an analysis of coastal change","docAbstract":"Hurricane Matthew, the strongest Atlantic hurricane of the 2016 hurricane season, made land-fall south of McClellanville, S.C., around 1500 Coordinated Universal Time (UTC) on October 8, 2016. Hurricane Matthew affected the States of Florida, Georgia, South Carolina, and North Carolina along the U.S. Atlantic coastline. Numerous barrier islands were breached, and the erosion of beaches and dunes occurred along most of the South Atlantic coast. The U.S. Geological Survey (USGS) fore-casted potential coastal-change effects—including dune erosion and overwash that can threaten coastal resources and infrastructure—to assist with pre-storm management decisions. Following the storm, oblique aerial photography was collected, and lidar topographic survey missions were flown. These two datasets were used to document the changes that resulted from the storm and to validate coastal change forecasts. Comparisons of pre- and post-storm photographs were used to characterize the nature, extent, and spatial variability of hurricane-induced coastal changes. Analyses of pre- and post-storm lidar eleva-tions were used to quantify magnitudes of change in shoreline positions, dune elevations, and beach volumes. Erosion was observed along the coast from Florida to North Carolina; however, the coastal response exhibited extensive spatial variability, as would be expected over such a large region.
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\"}}]}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
The spatial and temporal distribution of Pliocene to Holocene Colorado River deposits (southwestern USA and northwestern Mexico) form a primary data set that records the evolution of a continental-scale river system and helps to delineate and quantify the magnitude of regional deformation. We focus in particular on the age and distribution of ancestral Colorado River deposits from field observations, geologic mapping, and subsurface studies in the area downstream from Grand Canyon (Arizona, USA). A new 4.73 ± 0.17 Ma age is reported for a basalt that flowed down Grand Wash to near its confluence with the Colorado River at the eastern end of what is now Lake Mead (Arizona and Nevada). That basalt flow, which caps tributary gravels, another previously dated 4.49 ± 0.46 Ma basalt flow that caps Colorado River gravel nearby, and previously dated speleothems (2.17 ± 0.34 and 3.87 ± 0.1 Ma) in western Grand Canyon allow for the calculation of long-term incision rates. Those rates are ~90 m/Ma in western Grand Canyon and ~18–64 m/Ma in the eastern Lake Mead area. In western Lake Mead and downstream, the base of 4.5–3.5 Ma ancestral Colorado River deposits, called the Bullhead Alluvium, is generally preserved below river level, suggesting little if any bedrock incision since deposition. Paleoprofiles reconstructed using ancestral river deposits indicate that the lower Colorado River established a smooth profile that has been graded to near sea level since ca. 4.5 Ma. Steady incision rates in western Grand Canyon over the past 0.6–4 Ma also suggest that the lower Colorado River has remained in a quasi–steady state for millions of years with respect to bedrock incision. Differential incision between the lower Colorado River corridor and western Grand Canyon is best explained by differential uplift across the Lake Mead region, as the overall 4.5 Ma profile of the Colorado River remains graded to Pliocene sea level, suggesting little regional subsidence or uplift. Cumulative estimates of ca. 4 Ma offsets across faults in the Lake Mead region are similar in magnitude to the differential incision across the area during the same approximate time frame. This suggests that in the past ~4 Ma, vertical deformation in the Lake Mead area has been localized along faults, which may be a surficial response to more deep-seated processes. Together these data sets suggest ~140–370m of uplift in the past 2–4 Ma across the Lake Mead region.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02020.1","usgsCitation":"Crow, R.S., Howard, K.A., Beard, L.S., Pearthree, P., House, K., Karlstrom, K., Lisa Peters, McIntosh, W.C., Cassidy, C., Felger, T.J., and Block, D., 2019, Insights into post-Miocene uplift of the western margin of the Colorado Plateau from the stratigraphic record of the lower Colorado River: Geosphere, v. 15, no. 6, p. 1826-1845, https://doi.org/10.1130/GES02020.1.","productDescription":"20 p.","startPage":"1826","endPage":"1845","ipdsId":"IP-072908","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":459490,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02020.1","text":"Publisher Index Page"},{"id":368729,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","state":"Arizona, California, Nevada","otherGeospatial":"Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.97167968750001,\n 31.541089879585808\n ],\n [\n -112.236328125,\n 31.541089879585808\n ],\n [\n -112.236328125,\n 36.94989178681327\n ],\n [\n -115.97167968750001,\n 36.94989178681327\n ],\n [\n -115.97167968750001,\n 31.541089879585808\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-10-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Crow, Ryan S. 0000-0002-2403-6361 rcrow@usgs.gov","orcid":"https://orcid.org/0000-0002-2403-6361","contributorId":5792,"corporation":false,"usgs":true,"family":"Crow","given":"Ryan","email":"rcrow@usgs.gov","middleInitial":"S.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":768521,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Howard, Keith A. 0000-0002-6462-2947 khoward@usgs.gov","orcid":"https://orcid.org/0000-0002-6462-2947","contributorId":3439,"corporation":false,"usgs":true,"family":"Howard","given":"Keith","email":"khoward@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":768523,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beard, L. Sue 0000-0001-9552-1893 sbeard@usgs.gov","orcid":"https://orcid.org/0000-0001-9552-1893","contributorId":152,"corporation":false,"usgs":true,"family":"Beard","given":"L.","email":"sbeard@usgs.gov","middleInitial":"Sue","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":768524,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pearthree, Phil","contributorId":218167,"corporation":false,"usgs":false,"family":"Pearthree","given":"Phil","email":"","affiliations":[{"id":39771,"text":"AZGS","active":true,"usgs":false}],"preferred":false,"id":768528,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"House, Kyle 0000-0002-0019-8075 khouse@usgs.gov","orcid":"https://orcid.org/0000-0002-0019-8075","contributorId":2293,"corporation":false,"usgs":true,"family":"House","given":"Kyle","email":"khouse@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":768525,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Karlstrom, Karl","contributorId":218165,"corporation":false,"usgs":false,"family":"Karlstrom","given":"Karl","affiliations":[{"id":16658,"text":"UNM","active":true,"usgs":false}],"preferred":false,"id":768522,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lisa Peters","contributorId":179357,"corporation":false,"usgs":false,"family":"Lisa Peters","affiliations":[],"preferred":false,"id":768529,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McIntosh, William C.","contributorId":191163,"corporation":false,"usgs":false,"family":"McIntosh","given":"William","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":768526,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cassidy, Colleen 0000-0003-2963-9185","orcid":"https://orcid.org/0000-0003-2963-9185","contributorId":207193,"corporation":false,"usgs":true,"family":"Cassidy","given":"Colleen","email":"","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":768530,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Felger, Tracey J. 0000-0003-0841-4235 tfelger@usgs.gov","orcid":"https://orcid.org/0000-0003-0841-4235","contributorId":1117,"corporation":false,"usgs":true,"family":"Felger","given":"Tracey","email":"tfelger@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":768531,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Block, Debra 0000-0001-7348-3064 dblock@usgs.gov","orcid":"https://orcid.org/0000-0001-7348-3064","contributorId":198448,"corporation":false,"usgs":true,"family":"Block","given":"Debra","email":"dblock@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":768527,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70227813,"text":"70227813 - 2019 - Evaluating the effects of barriers on Slimy Sculpin movement and population connectivity using novel sibship-based and traditional genetic metrics","interactions":[],"lastModifiedDate":"2022-02-01T20:24:48.776105","indexId":"70227813","displayToPublicDate":"2019-10-16T15:24:21","publicationYear":"2019","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":"Evaluating the effects of barriers on Slimy Sculpin movement and population connectivity using novel sibship-based and traditional genetic metrics","docAbstract":"Population genetics-based approaches can provide robust and cost-effective ways to assess the effects of potential barriers, including dams and road-stream crossings, on the passage and population connectivity of aquatic organisms. Determining the best way to apply and modify genetic tools for different species and situations is essential for making these genetics-based approaches broadly applicable to fisheries and aquatic habitat management. Here, we used multiple genetic approaches to assess the movement and population structure of Slimy Sculpin Cottus cognatus at two road-stream crossings in Michigan and one dam in Massachusetts, USA. We captured and genotyped individual sculpin and assessed movement and population connectivity by using (1) a sibship-based approach, where the presence and proportional distribution of siblings on either side of a barrier indicates population connectivity and the possible direction of movement (i.e., presumed movement from higher to lower proportions), and (2) two Bayesian genetic assignment approaches (STRUCTURE and BayesAss) to identify migrants across potential barriers based on individual population assignment probabilities. We also used traditional genetic metrics to assess within-population genetic variation and among-population genetic divergence. At all three locations, we found evidence for sculpin movement across the potential barrier based on sibship reconstruction, but small family sizes limited the ability of this approach to provide robust estimates of the rate and direction of movement. At two sites, a lack of genetic differentiation between above- and below-barrier populations limited the effectiveness of the genetic assignment methods for identifying possible migrants. At the third site, reduced upstream allelic diversity and effective number of breeders resulted in high genetic differentiation (FST) between above- and below-barrier populations, and both sibship and genetic assignment methods provided strong evidence of limited connectivity and bias against upstream movement. Overall, combining approaches and metrics may help overcome the limitations of any one method and maximize the value of datasets for genetics-based monitoring and assessment.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10202","usgsCitation":"Weinstein, S.Y., Coombs, J.A., Nislow, K., Riley, C., Roy, A.H., and Whiteley, A., 2019, Evaluating the effects of barriers on Slimy Sculpin movement and population connectivity using novel sibship-based and traditional genetic metrics: Transactions of the American Fisheries Society, v. 148, no. 6, p. 1117-1131, https://doi.org/10.1002/tafs.10202.","productDescription":"15 p.","startPage":"1117","endPage":"1131","ipdsId":"IP-098904","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":459494,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/tafs.10202","text":"Publisher Index Page"},{"id":395240,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts, Michigan","otherGeospatial":"Arquilla Creek, Fall River, Peterson Creek","volume":"148","issue":"6","noUsgsAuthors":false,"publicationDate":"2019-10-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Weinstein, Spencer Y.","contributorId":272869,"corporation":false,"usgs":false,"family":"Weinstein","given":"Spencer","email":"","middleInitial":"Y.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":832352,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coombs, Jason A.","contributorId":270745,"corporation":false,"usgs":false,"family":"Coombs","given":"Jason","email":"","middleInitial":"A.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":832353,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nislow, Keith H.","contributorId":60106,"corporation":false,"usgs":true,"family":"Nislow","given":"Keith H.","affiliations":[],"preferred":false,"id":832354,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Riley, Chris","contributorId":272875,"corporation":false,"usgs":false,"family":"Riley","given":"Chris","email":"","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":832355,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":832351,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Whiteley, Andrew R.","contributorId":272876,"corporation":false,"usgs":false,"family":"Whiteley","given":"Andrew R.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":832356,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70206117,"text":"70206117 - 2019 - The 30 November 2018 Mw7.1 Anchorage Earthquake","interactions":[],"lastModifiedDate":"2020-01-05T14:07:00","indexId":"70206117","displayToPublicDate":"2019-10-16T12:57:07","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"The 30 November 2018 Mw7.1 Anchorage Earthquake","docAbstract":"The
Landsat satellites have been operating since 1972, providing a continuous global record of the Earth’s land surface. The imagery is currently available at no cost through the U.S. Geological Survey (USGS). A previous USGS study estimated that Landsat imagery provided users an annual benefit of $2.19 billion in 2011, with U.S. users accounting for $1.79 billion of those benefits. That study, published in 2013, surveyed users in 2012 about Landsat imagery they retrieved in 2011. But since then, many changes have altered the demand for and supply of remotely sensed imagery and have made the analysis complex. This report updates these estimates, surveying users in 2018 about Landsat images they retrieved in 2017. The report discusses changes in the value per scene in 2017 when compared to 2011 and analyzes the potential consequences of charging fees. Landsat imagery has been available at no cost to the public since 2008, resulting in the distribution of millions of scenes each subsequent year. In addition, tens of thousands of Landsat users have registered with the USGS to access the data. Considering the number of Landsat data users worldwide and the broad range of Landsat data applications, it is difficult to quantify the cascading benefits to society provided by Landsat imagery. The value of Landsat imagery to these users was demonstrated by the substantial aggregated annual economic benefit from the imagery. Landsat imagery provided domestic and international users an estimated $3.45 billion in benefits in 2017 compared to $2.19 billion in 2011, with U.S. users accounting for $2.06 billion of those benefits. Much of the societal value of Landsat stems from the free and open data policy that allows users to access as much imagery as is necessary for their analysis at no cost. Charging even small fees would result in a loss of users and, most likely, a steep decline in the amount of imagery downloaded. It is reasonable that more than 50 percent of users will decline to pay. The consequences of charging for Landsat imagery would be felt by downstream users as well, through increased prices for value-added products as well as more intangible effects, such as reduced monitoring of environmental hazards.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191112","usgsCitation":"Straub, C.L., Koontz, S.R., and Loomis, J.B., 2019, Economic valuation of Landsat imagery: U.S. Geological Survey Open-File Report 2019–1112, 13 p., https://doi.org/10.3133/ofr20191112.","productDescription":"iv, 13 p.","onlineOnly":"Y","ipdsId":"IP-110993","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":368280,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1112/coverthb.jpg"},{"id":368281,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1112/ofr20191112.pdf","text":"Report","size":"3.19 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1112"}],"contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Building C
Fort Collins, CO 80526-8118
Gas hydrates possess lower electrical conductivity (inverse of resistivity) than either seawater or ice, but higher than clastic silts and sands, such that electromagnetic methods can be employed to help identify their natural formation in marine and permafrost environments. Controlled laboratory studies offer a means to isolate and quantify the effects of changing individual components within gas‐hydrate‐bearing systems, in turn yielding insight into the behavior of natural systems. Here we investigate the electrical properties of polycrystalline methane hydrate with ≥25% gas‐filled porosity and in mixture with brine. Initially, pure methane hydrate was synthesized from H2O ice and CH4 gas while undergoing electrical impedance measurement, then partially dissociated to assess the effects of pure pore water accumulation on electrical conductivity. Methane hydrate + brine mixtures were then formed by either adding NaCl (0.25–2.5 wt %) to high‐purity ice or by using frozen seawater as a reactant. Conductivity was obtained from impedance measurements made in situ throughout synthesis while temperature cycled between +15 °C and −25 °C. Several possible conduction mechanisms were subsequently determined using equivalent circuit modeling. Samples with low NaCl concentration show a doping/impurity effect and a log linear conductivity response as a function of temperature. For higher salt content samples, conductivity increases exponentially with temperature and the log linear relationship no longer holds; instead, we observe phase changes within the samples that follow NaCl–H2O–CH4 phase equilibrium predictions. Final samples were quenched in liquid nitrogen and imaged by cryogenic scanning electron microscopy (cryo‐SEM) to assess grain‐scale characteristics.