Coastal lagoons are common features of the Puerto Rico shoreline that provide habitat for commercial and recreational species and serve important roles in the nutrient cycle of the ecosystems. The U.S. Geological Survey, in cooperation with the Puerto Rico Environmental Quality Board, conducted a limnological study at Caño Boquerón in Cabo Rojo and at Puerto Mosquito on Isla de Vieques, Puerto Rico, to assess the principal mechanisms affecting the hydrology and water-quality characteristics of these coastal lagoons and provide baseline information to the regulatory agencies responsible for the management and conservation of these coastal waters and the preservation of their aquatic life.
Field measurements and water samples were collected and processed during July 2015–July 2016 for analysis of physical, chemical, biological, and bacteriological characteristics. In addition, bathymetric surveys were made and sediment cores were collected in each lagoon to determine water volume and sediment deposition rate. Physicochemical properties assessed at Caño Boquerón indicated values were generally in compliance with Puerto Rico Environmental Quality Board standards; turbidity was occasionally slightly greater than the established standards, and dissolved oxygen concentration at bottom depths was lower than standards limits. Water transparency was evaluated through the Secchi disk method, and the average depth of disappearance was 1.0 meter (m) for Caño Boquerón and 1.9 m for Puerto Mosquito.
Assessment of biological characteristics at both sites included primary productivity calculations as well as carbon production equivalents and monthly water sampling for bacteriological and nutrient analyses. For Caño Boquerón, gross plankton primary productivity averaged 3.38 grams of oxygen per cubic meter per day (gO2/m3-d); this value was computed as the sum of net phytoplankton primary productivity (0.74 gO2/m3-d) and plankton respiration (2.64 gO2/m3-d). Net community primary productivity averaged 1.44 gO2/m3-d, and the community respiration rate averaged 8.10 gO2/m3-d, which indicates that the biological community, aside from phytoplankton, acts as a net consumer rather than a net producer of biomass. In Puerto Mosquito, gross plankton primary productivity averaged 2.07 gO2/m3-d, of which 0.39 gO2/m3-d could be ascribed to net phytoplankton primary productivity, and 1.68 gO2/m3-d could be ascribed to plankton respiration. Diel studies conducted at Puerto Mosquito reflected an average net community primary productivity of 2.43 gO2/m3-d, and the average respiration rate was 6.72 gO2/m3-d.
In a bathymetric survey conducted in August 2015, the water volume for the Caño Boquerón lagoon was calculated as 967,000 cubic meters (m3), and the water volume at Puerto Mosquito was calculated as 1,182,200 m3, with an average depth of 1.5 m for Caño Boquerón and 1.8 m for Puerto Mosquito. The daily seawater exchange for Caño Boquerón and Puerto Mosquito was 13 and 5 percent of their water volumes referenced to mean sea level, respectively. A total of 20 sediment samples were processed and analyzed for cesium-137 (137Cs) and lead-210 (210Pb) radioisotopes. Analyses indicated that the sediment deposition rate at Caño Boquerón ranged from 0.32 to 0.36 centimeter per year, based on age dating analysis of 137Cs and 210Pb data; in Puerto Mosquito, the sediment deposition rate ranged from 0.26 to 0.27 centimeter per year, based on 137Cs and 210Pb data.
Bacteriological analyses at Caño Boquerón and Puerto Mosquito indicated that fecal coliform and enterococci concentrations were below Puerto Rico Environmental Quality Board standards during the study. The highest concentrations of fecal coliform (22 colonies per 100 milliliters) and enterococci (9 colonies per 100 milliliters) at Caño Boquerón occurred in July, which coincided with the busiest season of vacation rentals near the lagoon. Bacteria concentrations were generally lower in Puerto Mosquito than in Caño Boquerón; maximum concentrations of fecal coliform and enterococci bacteria were measured in November 2015. The potential sources of contamination for Puerto Mosquito are limited, because it is within a conservation area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185018","collaboration":"Prepared in cooperation with the Puerto Rico Environmental Quality Board","usgsCitation":"Gómez-Fragoso, J.M., and Santiago-Sáez, J.A., 2018, Hydrologic and water-quality characteristics of Caño Boquerón, Cabo Rojo, and Puerto Mosquito, Isla de Vieques, Puerto Rico, July 2015–July 2016: U.S. Geological Survey Scientific Investigations Report 2018–5018, 34 p., https://doi.org/10.3133/sir20185018.","productDescription":"Report: ix, 34 p.; Data Release","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-078162","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":437920,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7WH2P6K","text":"USGS data release","linkHelpText":"Gomez-Fragoso, Julieta, 2017, Data for the Hydrologic and Water-Quality Characterization of Cano Boqueron, Cabo Rojo, and Puerto Mosquito, Isla de Vieques, Puerto Rico, July 2015-July 2016: U.S. Geological Survey data release"},{"id":353903,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7WH2P6K","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data for the Hydrologic and Water-Quality Characterization of Puerto Mosquito, Vieques and Caño Boquerón, Cabo Rojo, Puerto Rico, July 2015–July 2016"},{"id":353901,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5018/coverthb2.jpg"},{"id":353902,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5018/sir20185018.pdf","text":"Report","size":"10.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5018"}],"country":"United States","otherGeospatial":"Caño Boquerón, Cabo Rojo, Puerto Mosquito, Isla de Vieques, Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.2167,\n 17.9833\n ],\n [\n -67.1333,\n 17.9833\n ],\n [\n -67.1333,\n 18.04\n ],\n [\n -67.2167,\n 18.04\n ],\n [\n -67.2167,\n 17.9833\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -65.4833,\n 18.0833\n ],\n [\n -65.4,\n 18.0833\n ],\n [\n -65.4,\n 18.1333\n ],\n [\n -65.4833,\n 18.1333\n ],\n [\n -65.4833,\n 18.0833\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
The hydrogeologic setting and groundwater flow system in Florida and parts of Georgia, Alabama, and South Carolina is dominated by the highly transmissive Floridan aquifer system. This principal aquifer is a vital source of freshwater for public and domestic supply, as well as for industrial and agricultural uses throughout the southeastern United States. Population growth, increased tourism, and increased agricultural production have led to increased demand on groundwater from the Floridan aquifer system, particularly since 1950. The response of the Floridan aquifer system to these stresses often poses regional challenges for water-resource management that commonly transcend political or jurisdictional boundaries. To help water-resource managers address these regional challenges, the U.S. Geological Survey (USGS) Water Availability and Use Science Program began assessing groundwater availability of the Floridan aquifer system in 2009.
The current conceptual groundwater flow system was developed for the Floridan aquifer system and adjacent systems partly on the basis of previously published USGS Regional Aquifer-System Analysis (RASA) studies, specifically many of the potentiometric maps and the modeling efforts in these studies. The Floridan aquifer system extent was divided into eight hydrogeologically distinct subregional groundwater basins delineated on the basis of the estimated predevelopment (circa 1880s) potentiometric surface: (1) Panhandle, (2) Dougherty Plain-Apalachicola, (3) Thomasville-Tallahassee, (4) Southeast Georgia-Northeast Florida-South South Carolina, (5) Suwannee, (6) West-central Florida, (7) East-central Florida, and (8) South Florida. The use of these subregions allows for a more detailed analysis of the individual basins and the groundwater flow system as a whole.
The hydrologic conditions and associated groundwater budget were updated relative to previous RASA studies to include additional data collected since the 1980s and to reflect the entire groundwater flow system, including the surficial, intermediate, and Floridan aquifer systems for a contemporary period (1995–2010). Inflow to the groundwater flow system of 33,700 million gallons per day (Mgal/d) was assumed to be exclusively from net recharge (precipitation minus evapotranspiration and surface runoff). Outflow from the groundwater flow system included spring discharge (7,700 Mgal/d) and groundwater withdrawals (5,200 Mgal/d). Estimates for all components of the groundwater system were not possible because of large uncertainties associated with internal leakage, coastal discharge, and discharge to streams and lakes. A numerical modeling analysis is required to improve this hydrologic budget calculation and to forecast future changes in groundwater levels and aquifer storage caused by groundwater withdrawals, land-use change, and the effects of climate variability and change.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185030","collaboration":"Water Availability and Use Science Program","usgsCitation":"Bellino, J.C., Kuniansky, E.L., O’Reilly, A.M., and Dixon, J.F., 2018, Hydrogeologic setting, conceptual groundwater flow system, and hydrologic conditions 1995–2010 in Florida and parts of Georgia, Alabama, and South Carolina: U.S. Geological Survey Scientific Investigations Report 2018–5030, 103 p., https://doi.org/10.3133/sir20185030.","productDescription":"Report: viii, 103 p.; Plate: 36.0 x 49.0 inches; Data Releases","numberOfPages":"115","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-056534","costCenters":[{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"links":[{"id":353934,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2018/5030/sir20185030_plate.pdf","text":"Plate 1","size":"3.02 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5030 Plate 1"},{"id":353936,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7CJ8BMS","text":"USGS data release","description":"USGS Data Release","linkHelpText":" Soil-Water-Balance model datasets used to estimate mean groundwater recharge in Florida and parts of Georgia, Alabama, and South Carolina, 1995–2010"},{"id":353933,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5030/sir20185030.pdf","text":"Report","size":"46.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5030"},{"id":353932,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5030/coverthb2.jpg"},{"id":353937,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75Q4TZD","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Potentiometric Surface Contours, Wells, and Groundwater Basin Divides for the Upper Floridan Aquifer in Florida and Parts of Georgia, South Carolina, and Alabama, May–June 2010—Updated"},{"id":353935,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78K7749","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Groundwater Withdrawals in Florida and parts of Georgia, Alabama, and South Carolina, 1995–2010"}],"country":"United States","state":"Alabama, Florida, Georgia, South Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.17626953125,\n 24.467150664739002\n ],\n [\n -79.6728515625,\n 24.467150664739002\n ],\n [\n -79.6728515625,\n 32.85190345738802\n ],\n [\n -88.17626953125,\n 32.85190345738802\n ],\n [\n -88.17626953125,\n 24.467150664739002\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane
Lutz, FL 33559
Wetlands in the Prairie Pothole Region (PPR) of North America support macroinvertebrate communities that are integral to local food webs and important to breeding waterfowl. Macroinvertebrates in PPR wetlands are primarily generalists and well adapted to within and among year changes in water permanence and salinity. The Williston Basin, a major source of U.S. energy production, underlies the southwest portion of the PPR. Development of oil and gas results in the coproduction of large volumes of highly saline, sodium chloride dominated water (brine) and the introduction of brine can alter wetland salinity. To assess potential effects of brine contamination on macroinvertebrate communities, 155 PPR wetlands spanning a range of hydroperiods and salinities were sampled between 2014 and 2016. Brine contamination was documented in 34 wetlands with contaminated wetlands having significantly higher chloride concentrations, specific conductance and percent dominant taxa, and significantly lower taxonomic richness, Shannon diversity, and Pielou evenness scores compared to uncontaminated wetlands. Non-metric multidimensional scaling found significant correlations between several water quality parameters and macroinvertebrate communities. Chloride concentration and specific conductance, which can be elevated in naturally saline wetlands, but are also associated with brine contamination, had the strongest correlations. Five wetland groups were identified from cluster analysis with many of the highly contaminated wetlands located in a single cluster. Low or moderately contaminated wetlands were distributed among the remaining clusters and had macroinvertebrate communities similar to uncontaminated wetlands. While aggregate changes in macroinvertebrate community structure were observed with brine contamination, systematic changes were not evident, likely due to the strong and potentially confounding influence of hydroperiod and natural salinity. Therefore, despite the observed negative response of macroinvertebrate communities to brine contamination, macroinvertebrate community structure alone is likely not the most sensitive indicator of brine contamination in PPR wetlands.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2018.04.088","usgsCitation":"Preston, T.M., Borgreen, M.J., and Ray, A.M., 2018, Effects of brine contamination from energy development on wetland macroinvertebrate community structure in the Prairie Pothole Region: Environmental Pollution, v. 239, p. 722-732, https://doi.org/10.1016/j.envpol.2018.04.088.","productDescription":"11 p.","startPage":"722","endPage":"732","ipdsId":"IP-093113","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":437922,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7DB8141","text":"USGS data release","linkHelpText":"Macroinvertebrate and water quality data from the Prairie Pothole Region of the Williston Basin (2014-2016)"},{"id":353964,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, North Dakota","otherGeospatial":"Williston Basin","volume":"239","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6c3e4b0da30c1bfbde2","contributors":{"authors":[{"text":"Preston, Todd M. 0000-0002-8812-9233","orcid":"https://orcid.org/0000-0002-8812-9233","contributorId":204676,"corporation":false,"usgs":true,"family":"Preston","given":"Todd","email":"","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":734648,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Borgreen, Michael J. 0000-0002-5879-6414","orcid":"https://orcid.org/0000-0002-5879-6414","contributorId":204677,"corporation":false,"usgs":false,"family":"Borgreen","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":734649,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ray, Andrew M.","contributorId":167601,"corporation":false,"usgs":false,"family":"Ray","given":"Andrew","email":"","middleInitial":"M.","affiliations":[{"id":5106,"text":"National Park Service, Yellowstone National Park, Mammoth, Wyoming 82190","active":true,"usgs":false}],"preferred":false,"id":734650,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196406,"text":"ds1083 - 2018 - Soil moisture datasets at five sites in the central Sierra Nevada and northern Coast Ranges, California","interactions":[],"lastModifiedDate":"2018-05-04T10:15:17","indexId":"ds1083","displayToPublicDate":"2018-05-03T00:00:00","publicationYear":"2018","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":"1083","title":"Soil moisture datasets at five sites in the central Sierra Nevada and northern Coast Ranges, California","docAbstract":"In situ soil moisture datasets are important inputs used to calibrate and validate watershed, regional, or statewide modeled and satellite-based soil moisture estimates. The soil moisture dataset presented in this report includes hourly time series of the following: soil temperature, volumetric water content, water potential, and total soil water content. Data were collected by the U.S. Geological Survey at five locations in California: three sites in the central Sierra Nevada and two sites in the northern Coast Ranges. This report provides a description of each of the study areas, procedures and equipment used, processing steps, and time series data from each site in the form of comma-separated values (.csv) tables.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1083","collaboration":"Prepared in cooperation with the California Department of Water Resources, National Park Service, and Pepperwood Preserve","usgsCitation":"Stern, M.A., Anderson, F.A., Flint, L.E., and Flint, A.L., 2018, Soil moisture datasets at five sites in the central Sierra Nevada and northern Coast Ranges, California: U.S. Geological Survey Data Series 1083, 23 p., https://doi.org/10.3133/ds1083.","productDescription":"Report: viii, 23 p.; 5 Tables","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-080152","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":353696,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1083/coverthb.jpg"},{"id":353697,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1083/ds1083_.pdf","text":"Report","size":"6.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Data Series 1083"},{"id":353698,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/ds/1083/ds1083_tables12-15_17.zip","text":"Tables 12, 13, 14, 15, and 17","size":"5.3 MB","linkFileType":{"id":6,"text":"zip"},"description":"Data Series 1083 table files"}],"country":"United States","state":"California","otherGeospatial":"Central Sierra Nevada Range, Northern Coast Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.83612060546874,\n 37.73379707124429\n ],\n [\n -119.20852661132812,\n 37.73379707124429\n ],\n [\n -119.20852661132812,\n 37.965854128749434\n ],\n [\n -119.83612060546874,\n 37.965854128749434\n ],\n [\n -119.83612060546874,\n 37.73379707124429\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.6963424682617,\n 38.56887107621966\n ],\n [\n -122.68930435180664,\n 38.56887107621966\n ],\n [\n -122.68930435180664,\n 38.57256189519067\n ],\n [\n -122.6963424682617,\n 38.57256189519067\n ],\n [\n -122.6963424682617,\n 38.56887107621966\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, CA 95819
Understanding the spatial and temporal variability in life-history traits among populations is essential for the management of recreational fisheries. However, valuable freshwater recreational fish species often suffer from a lack of catch information. In this study, we demonstrated the use of an approach to estimate the spatial and temporal variability in growth and mortality in the absence of catch data and apply the method to riverine smallmouth bass (Micropterus dolomieu) populations in Pennsylvania, USA. Our approach included a growth analysis and a length-based analysis that estimates mortality. Using a hierarchical Bayesian approach, we examined spatial variability in growth and mortality by assuming parameters vary spatially but remain constant over time and temporal variability by assuming parameters vary spatially and temporally. The estimated growth and mortality of smallmouth bass showed substantial variability over time and across rivers. We explored the relationships of the estimated growth and mortality with spring water temperature and spring flow. Growth rate was likely to be positively correlated with these two factors, while young mortality was likely to be positively correlated with spring flow. The spatially and temporally varying growth and mortality suggest that smallmouth bass populations across rivers may respond differently to management plans and disturbance such as environmental contamination and land-use change. The analytical approach can be extended to other freshwater recreational species that also lack of catch data. The approach could also be useful in developing population assessments with erroneous catch data or be used as a model sensitivity scenario to verify traditional models even when catch data are available.
","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2017-0052","usgsCitation":"Li, Y., Wagner, T., Jiao, Y., Lorantas, R.M., and Murphy, C., 2018, Evaluating spatial and temporal variability in growth and mortality for recreational fisheries with limited catch data: Canadian Journal of Fisheries and Aquatic Sciences, v. 75, no. 9, p. 1436-1452, https://doi.org/10.1139/cjfas-2017-0052.","productDescription":"17 p.","startPage":"1436","endPage":"1452","ipdsId":"IP-084291","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468778,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10919/99273","text":"External Repository"},{"id":353912,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Yan","contributorId":204633,"corporation":false,"usgs":false,"family":"Jiao","given":"Yan","email":"","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":734529,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lorantas, Robert M.","contributorId":204631,"corporation":false,"usgs":false,"family":"Lorantas","given":"Robert","email":"","middleInitial":"M.","affiliations":[{"id":36966,"text":"Pennsylvania Fish and Boat Commission","active":true,"usgs":false}],"preferred":false,"id":734527,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Murphy, Cheryl","contributorId":204632,"corporation":false,"usgs":false,"family":"Murphy","given":"Cheryl","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":734528,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196809,"text":"70196809 - 2018 - Bioactive contaminants of emerging concern in National Park waters of the northern Colorado Plateau, USA","interactions":[],"lastModifiedDate":"2018-05-02T11:32:49","indexId":"70196809","displayToPublicDate":"2018-05-02T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Bioactive contaminants of emerging concern in National Park waters of the northern Colorado Plateau, USA","docAbstract":"Pharmaceuticals and personal care products (PPCPs), wastewater indicators (WWIs), and pesticides (herein, Contaminants of Emerging Concern [CECs]) have been documented in surface waters throughout the world and have associated risks to aquatic life. While much research has focused on temperate and urbanized watersheds, less is known about CEC presence in semi-arid landscapes, where water availability is limited and populations are low. CEC presence in water and sediment is reported for 21 sites in eight U.S. national parks in the northern Colorado Plateau region. From 2012 to 2016, at least one PPCP and/or WWI was detected at most sites on over half of sampling visits, indicating that CECs are not uncommon even in isolated areas. CEC detections were generally fewer and at lower concentrations than in urbanized or agricultural watersheds. Consistent with studies from other U.S. regions, the most frequently detected CECs in this study include DEET, caffeine, organophosphorus flame retardants, and bisphenol A in water and fecal indicators and polycyclic aromatic hydrocarbons in sediment. Maximum concentrations in this study were generally below available water quality benchmarks, sediment quality guidelines, and risk assessment thresholds associated with vertebrates. Additional work is needed to assess the potential activity of hormones, which had high reporting limits in our study, and potential bioactivity of environmental concentrations for invertebrates, microbial communities, and algae. Potential sources of CEC contamination include upstream wastewater effluent discharges and National Park Service invasive-plant-control herbicide applications. CEC occurrence patterns and similarities between continuous and isolated flow locations suggest that direct contamination from individual visitors may also occur. While our data indicate there is little aquatic health risk associated with CECs at our sites, our results demonstrate the ubiquity of CECs on the landscape and a continued need for public outreach concerning resource-use ethics and the potential effects of upstream development.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2018.04.332","usgsCitation":"Weissinger, R.H., Blackwell, B., Keteles, K., Battaglin, W., and Bradley, P.M., 2018, Bioactive contaminants of emerging concern in National Park waters of the northern Colorado Plateau, USA: Science of the Total Environment, v. 636, p. 910-918, https://doi.org/10.1016/j.scitotenv.2018.04.332.","productDescription":"9 p.","startPage":"910","endPage":"918","ipdsId":"IP-095083","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":460929,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6794149","text":"Publisher Index Page"},{"id":437924,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7NP23PC","text":"USGS data release","linkHelpText":"Bioactive Contaminants of Emerging Concern in National Park Waters of the Northern Colorado Plateau, USA, 2012-2016"},{"id":353916,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Colorado Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.2965087890625,\n 37.17344871200958\n ],\n [\n -108.48999023437499,\n 37.17344871200958\n ],\n [\n -108.48999023437499,\n 40.63479884404164\n ],\n [\n -113.2965087890625,\n 40.63479884404164\n ],\n [\n -113.2965087890625,\n 37.17344871200958\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"636","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6c3e4b0da30c1bfbdea","contributors":{"authors":[{"text":"Weissinger, Rebecca H","contributorId":204637,"corporation":false,"usgs":false,"family":"Weissinger","given":"Rebecca","email":"","middleInitial":"H","affiliations":[{"id":36968,"text":"US National Parks Service","active":true,"usgs":false}],"preferred":false,"id":734538,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blackwell, Brett R.","contributorId":173601,"corporation":false,"usgs":false,"family":"Blackwell","given":"Brett R.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":734539,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keteles, Kristen","contributorId":200072,"corporation":false,"usgs":false,"family":"Keteles","given":"Kristen","email":"","affiliations":[],"preferred":false,"id":734540,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Battaglin, William A. 0000-0001-7287-7096","orcid":"https://orcid.org/0000-0001-7287-7096","contributorId":204638,"corporation":false,"usgs":true,"family":"Battaglin","given":"William A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":734541,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bradley, Paul M. 0000-0001-7522-8606 pbradley@usgs.gov","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":204639,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul","email":"pbradley@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":734542,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70198427,"text":"70198427 - 2018 - Thermal tolerance limits of the Chinese mystery snail (Bellamya chinensis): Implications for management","interactions":[],"lastModifiedDate":"2018-08-06T14:48:34","indexId":"70198427","displayToPublicDate":"2018-05-01T14:48:23","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":735,"text":"American Malacological Bulletin","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Thermal tolerance limits of the Chinese mystery snail (Bellamya chinensis): Implications for management","title":"Thermal tolerance limits of the Chinese mystery snail (Bellamya chinensis): Implications for management","docAbstract":"The Chinese mystery snail, Bellamya chinensis (Gray, 1834) is a gastropod native to East Asia and is considered an invasive species in North America where its impacts on native species and ecosystems are not well understood. Scientific literature describing its biology and life history are sparse. Thermal tolerance limits, or the maximum and minimum temperature under which a species can survive, are key to identifying the potential geographical range of a species. The ability of managers to control invasive species is directly impacted by the thermal tolerance limits of a species. We attempted to identify the thermal tolerance limits of B. chinensis in a laboratory setting. Using a random sampling design, we exposed groups of wild-caught B. chinensis to either extreme high or low temperature treatments. We identified the upper temperature tolerance limit as between 40 and 45 °C. This result indicates some hot water management techniques may successfully prevent spread of B. chinensis among waterways. Despite exposing B. chinensis to freezing temperatures for extended periods of time we did not identify a lower temperature limit. Identifying the thermal tolerance limits of this and other invasive species informs predictions of range expansion and identification of potential prevention efforts.
","language":"English","publisher":"American Malacological Society","doi":"10.4003/006.036.0106","usgsCitation":"Burnett, J., Pope, K.L., Wong, A., Allen, C.R., Haak, D.M., Stephen, B.J., and Uden, D.R., 2018, Thermal tolerance limits of the Chinese mystery snail (Bellamya chinensis): Implications for management: American Malacological Bulletin, v. 36, no. 1, p. 140-144, https://doi.org/10.4003/006.036.0106.","productDescription":"5 p.","startPage":"140","endPage":"144","ipdsId":"IP-086958","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":356207,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc450e4b0f5d57878ea53","contributors":{"authors":[{"text":"Burnett, Jessica","contributorId":189224,"corporation":false,"usgs":false,"family":"Burnett","given":"Jessica","affiliations":[],"preferred":false,"id":741392,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pope, Kevin L. 0000-0003-1876-1687 kpope@usgs.gov","orcid":"https://orcid.org/0000-0003-1876-1687","contributorId":1574,"corporation":false,"usgs":true,"family":"Pope","given":"Kevin","email":"kpope@usgs.gov","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":741390,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wong, Alec","contributorId":79005,"corporation":false,"usgs":true,"family":"Wong","given":"Alec","email":"","affiliations":[],"preferred":false,"id":741393,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":741391,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haak, Danielle M.","contributorId":73078,"corporation":false,"usgs":true,"family":"Haak","given":"Danielle","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":741394,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stephen, Bruce J.","contributorId":206665,"corporation":false,"usgs":false,"family":"Stephen","given":"Bruce","email":"","middleInitial":"J.","affiliations":[{"id":16587,"text":"University of Nebraska Lincoln","active":true,"usgs":false}],"preferred":false,"id":741395,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Uden, Daniel R.","contributorId":74258,"corporation":false,"usgs":true,"family":"Uden","given":"Daniel","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":741396,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70198990,"text":"70198990 - 2018 - Numerical model of geochronological tracers for deposition and reworking applied to the Mississippi subaqueous delta","interactions":[],"lastModifiedDate":"2018-08-28T13:49:01","indexId":"70198990","displayToPublicDate":"2018-05-01T13:48:56","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"title":"Numerical model of geochronological tracers for deposition and reworking applied to the Mississippi subaqueous delta","docAbstract":"Measurements of naturally occurring, short-lived radioisotopes from sediment cores on the Mississippi subaqueous delta have been used to infer event bed characteristics such as depositional thicknesses and accumulation rates. Specifically, the presence of Beryllium-7 (7Be) indicates recent riverine-derived terrestrial sediment deposition; while Thorium-234 (234Th) provides evidence of recent suspension in marine waters. Sediment transport models typically represent coastal flood and storm deposition via estimated grain size patterns and deposit thicknesses, however, and do not directly calculate radioisotope activities and profiles, which leads to a disconnect between the numerical model and field observations. Here, observed radioisotopic profiles from the Mississippi subaqueous delta cores were directly related to a numerical model that represented resuspension and deposition using a new approach to account for the behavior of short-lived radioisotopes. Appropriate selection of parameters such as the biodiffusion coefficient, sediment accumulation rate, and radioisotopic source terms enabled a good match between the modeled and observed cores. Comparisons of modelled profiles with geochronological analytical models that estimate accumulation rate and flood layer thickness revealed potential avenues for refining these tools, and highlight the importance of constraining the biodiffusion coefficient.
","language":"English","publisher":"Coastal Education and Research Foundation","doi":"10.2112/SI85-092.1","usgsCitation":"Birchler, J.J., Harris, C.K., Kniskern, T.A., and Sherwood, C.R., 2018, Numerical model of geochronological tracers for deposition and reworking applied to the Mississippi subaqueous delta: Journal of Coastal Research, v. Special Issue 85, p. 456-460, https://doi.org/10.2112/SI85-092.1.","productDescription":"5 p.","startPage":"456","endPage":"460","ipdsId":"IP-092729","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468783,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2112/si85-092.1","text":"Publisher Index Page"},{"id":356848,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Gulf of Mexico, Mississippi River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.5,\n 28.5\n ],\n [\n -88,\n 28.5\n ],\n [\n -88,\n 30.5\n ],\n [\n -90.5,\n 30.5\n ],\n [\n -90.5,\n 28.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"Special Issue 85","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b98a2cfe4b0702d0e842ff1","contributors":{"authors":[{"text":"Birchler, Justin J. 0000-0002-0379-2192 jbirchler@usgs.gov","orcid":"https://orcid.org/0000-0002-0379-2192","contributorId":169117,"corporation":false,"usgs":true,"family":"Birchler","given":"Justin","email":"jbirchler@usgs.gov","middleInitial":"J.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":743670,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harris, Courtney K.","contributorId":19620,"corporation":false,"usgs":false,"family":"Harris","given":"Courtney","email":"","middleInitial":"K.","affiliations":[{"id":6708,"text":"Virginia Institute of Marine Science","active":true,"usgs":false}],"preferred":false,"id":743671,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kniskern, Tara A.","contributorId":207384,"corporation":false,"usgs":false,"family":"Kniskern","given":"Tara","email":"","middleInitial":"A.","affiliations":[{"id":37527,"text":"Virginia Institute of Marine Sciences, College of William & Mary","active":true,"usgs":false}],"preferred":false,"id":743672,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":743673,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70194712,"text":"ds1075 - 2018 - Groundwater-level data from an earthen dam site in southern Westchester County, New York","interactions":[],"lastModifiedDate":"2018-05-01T16:08:23","indexId":"ds1075","displayToPublicDate":"2018-05-01T13:45:00","publicationYear":"2018","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":"1075","title":"Groundwater-level data from an earthen dam site in southern Westchester County, New York","docAbstract":"In 2005, the U.S. Geological Survey began a cooperative study with New York City Department of Environmental Protection to characterize the local groundwater-flow system and identify potential sources of seeps on the southern embankment of the Hillview Reservoir in Westchester County, New York. Groundwater levels were collected at 49 wells at Hillview Reservoir, and 1 well in northern Bronx County, from April 2005 through November 2016. Groundwater levels were measured discretely with a chalked steel or electric tape, or continuously with a digital pressure transducer, or both, in accordance with U.S. Geological Survey groundwatermeasurement standards. These groundwater-level data were plotted as time series and are presented in this report as hydrographs. Twenty-eight of the 50 hydrographs have continuous record and discrete field groundwater-level measurements, 22 of the hydrographs contain only discrete measurements.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1075","isbn":"978-1-4113-4200-2","collaboration":"Prepared in cooperation with the New York City Department of Environmental Protection","usgsCitation":"Noll, M.L., and Chu, Anthony, 2018, Groundwater-level data from an earthen dam site in southern Westchester County, New York: U.S. Geological Survey Data Series 1075, 35 p., https://doi.org/10.3133/ds1075.","productDescription":"Report: vii, 35 p.; Appendix 1","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-084388","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":351582,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1075/ds1075.pdf","text":"Report","size":"15.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1075"},{"id":351583,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1075/ds1075_app1.zip","text":"Appendix 1","size":"8.55 MB","linkHelpText":"- Groundwater-level measurements"},{"id":351581,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1075/coverthb.jpg"}],"country":"United States","state":"New York","county":"Westchester County","otherGeospatial":"Hillview Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.87460231781006,\n 40.90598813645525\n ],\n [\n -73.86430263519287,\n 40.90598813645525\n ],\n [\n -73.86430263519287,\n 40.917760911653126\n ],\n [\n -73.87460231781006,\n 40.917760911653126\n ],\n [\n -73.87460231781006,\n 40.90598813645525\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
2045 Route 112, Building 4
Coram, NY 11727
From 2009 to 2015 the U.S. Geological Survey (USGS) systematically monitored hydrothermal behavior at selected Cascade Range volcanoes in order to define baseline hydrothermal and geochemical conditions. Gas and water data were collected regularly at 25 sites on 10 of the highest-risk volcanoes in the Cascade Range. These sites include near-summit fumarole groups and springs/streams that show clear evidence of magmatic influence (high 3He/4He ratios and/or large fluxes of magmatic CO2 or heat). Site records consist mainly of hourly temperature and hydrothermal-flux data. Having established baseline conditions during a multiyear quiescent period, the USGS reduced monitoring frequency from 2015 to present. The archived monitoring data are housed at (doi:10.5066/F72N5088). These data (1) are suitable for retrospective comparison with other continuous geophysical monitoring data and (2) will provide context during future episodes of volcanic unrest, such that unrest-related variations at these thoroughly characterized sites will be more clearly recognizable. Relatively high-frequency year-round data are essential to achieve these objectives, because many of the time series reveal significant diurnal, seasonal, and inter-annual variability that would tend to mask unrest signals in the absence of baseline data. Here we characterize normal variability for each site, suggest strategies to detect future volcanic unrest, and explore deviations from background associated with recent unrest.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2018.02.014","usgsCitation":"Crankshaw, I., Archfield, S.A., Newman, A.C., Bergfeld, D., Clor, L., Kelly, P.J., Evans, W.C., Spicer, K.R., and Ingebritsen, S.E., 2018, Multi-year high-frequency hydrothermal monitoring of selected high-threat Cascade Range volcanoes: Journal of Volcanology and Geothermal Research, v. 356, p. 24-35, https://doi.org/10.1016/j.jvolgeores.2018.02.014.","productDescription":"12 p.","startPage":"24","endPage":"35","ipdsId":"IP-091030","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":468784,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2018.02.014","text":"Publisher Index Page"},{"id":360459,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon, Washington","otherGeospatial":"Cascades Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124,\n 40\n ],\n [\n -120,\n 40\n ],\n [\n -120,\n 49\n ],\n [\n -124,\n 49\n ],\n [\n -124,\n 40\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"356","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c1a1534e4b0708288c2353b","contributors":{"authors":[{"text":"Crankshaw, I.M. 0000-0003-0736-5478","orcid":"https://orcid.org/0000-0003-0736-5478","contributorId":211588,"corporation":false,"usgs":false,"family":"Crankshaw","given":"I.M.","email":"","affiliations":[{"id":17863,"text":"Sonoma County Water Agency","active":true,"usgs":false}],"preferred":false,"id":754436,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Archfield, Stacey A. 0000-0002-9011-3871 sarch@usgs.gov","orcid":"https://orcid.org/0000-0002-9011-3871","contributorId":1874,"corporation":false,"usgs":true,"family":"Archfield","given":"Stacey","email":"sarch@usgs.gov","middleInitial":"A.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":754438,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Newman, A. C. 0000-0001-6621-2717","orcid":"https://orcid.org/0000-0001-6621-2717","contributorId":211589,"corporation":false,"usgs":false,"family":"Newman","given":"A.","email":"","middleInitial":"C.","affiliations":[{"id":38269,"text":"Aarhus, Denmark","active":true,"usgs":false}],"preferred":false,"id":754437,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bergfeld, Deborah 0000-0003-4570-7627 dbergfel@usgs.gov","orcid":"https://orcid.org/0000-0003-4570-7627","contributorId":152531,"corporation":false,"usgs":true,"family":"Bergfeld","given":"Deborah","email":"dbergfel@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":754439,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Clor, Laura E. 0000-0003-2633-5100","orcid":"https://orcid.org/0000-0003-2633-5100","contributorId":209969,"corporation":false,"usgs":true,"family":"Clor","given":"Laura E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":754440,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kelly, Peter J. 0000-0002-3868-1046 pkelly@usgs.gov","orcid":"https://orcid.org/0000-0002-3868-1046","contributorId":5931,"corporation":false,"usgs":true,"family":"Kelly","given":"Peter","email":"pkelly@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":754540,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Evans, William C. 0000-0001-5942-3102 wcevans@usgs.gov","orcid":"https://orcid.org/0000-0001-5942-3102","contributorId":2353,"corporation":false,"usgs":true,"family":"Evans","given":"William","email":"wcevans@usgs.gov","middleInitial":"C.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"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":754539,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Spicer, Kurt R. 0000-0001-5030-3198 krspicer@usgs.gov","orcid":"https://orcid.org/0000-0001-5030-3198","contributorId":2684,"corporation":false,"usgs":true,"family":"Spicer","given":"Kurt","email":"krspicer@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":754441,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ingebritsen, Steven E. 0000-0001-6917-9369 seingebr@usgs.gov","orcid":"https://orcid.org/0000-0001-6917-9369","contributorId":818,"corporation":false,"usgs":true,"family":"Ingebritsen","given":"Steven","email":"seingebr@usgs.gov","middleInitial":"E.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":754435,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70197548,"text":"70197548 - 2018 - Estimating fluvial discharges coincident with 21st century coastal storms modeled with CoSMoS","interactions":[],"lastModifiedDate":"2018-09-26T12:40:44","indexId":"70197548","displayToPublicDate":"2018-05-01T12:40:37","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"title":"Estimating fluvial discharges coincident with 21st century coastal storms modeled with CoSMoS","docAbstract":"On the open coast, flooding is largely driven by tides, storm surge, waves, and in areas near coastal inlets, the magnitude and co-occurrence of high fluvial discharges. Statistical methods are typically used to estimate the individual probability of coastal storm and fluvial discharge occurrences for use in sophisticated flood hazard models. A challenge arises when considering possible future climate changes and the relation between the intensity of extreme coastal water levels and high fluvial discharges.
In this study, the Coastal Storm Modeling System (CoSMoS) is used to dynamically downscale global climate projections to local-scale storm-driven coastal water levels, including associated fluvial discharges. An efficient approach to derive 21st century projected fluvial discharges for rivers within San Francisco Bay was developed, leveraging a readily-available time-series of projected (2010 – 2100) discharge rates of the predominant river system (the “Delta”). Delta projections were used to estimate flow rates of 8 Bay rivers for the IPCC's CMIP5 RCP4.5 climate scenario. Relationships describing discharge rates, normalized by respective watershed areas, were developed and applied to projected data to generate 21st century fluvial discharge time-series for each river. Results indicate decreasing discharge rates throughout the 21st century with the exception of extreme flows.
","language":"English","publisher":"Coastal Education and Research Foundation","doi":"10.2112/SI85-159.1","usgsCitation":"Erikson, L.H., O'Neill, A., and Barnard, P., 2018, Estimating fluvial discharges coincident with 21st century coastal storms modeled with CoSMoS: Journal of Coastal Research, v. Special Issue No. 85, p. 791-795, https://doi.org/10.2112/SI85-159.1.","productDescription":"5 p.","startPage":"791","endPage":"795","ipdsId":"IP-092829","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":357779,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.387451171875,\n 36.94989178681327\n ],\n [\n -121.201171875,\n 36.94989178681327\n ],\n [\n -121.201171875,\n 38.565347844885466\n ],\n [\n -123.387451171875,\n 38.565347844885466\n ],\n [\n -123.387451171875,\n 36.94989178681327\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"Special Issue No. 85","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02ff9e4b0fc368eb539b6","contributors":{"authors":[{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":737616,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O'Neill, Andrea C. 0000-0003-1656-4372 aoneill@usgs.gov","orcid":"https://orcid.org/0000-0003-1656-4372","contributorId":5351,"corporation":false,"usgs":true,"family":"O'Neill","given":"Andrea C.","email":"aoneill@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":737617,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":147147,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","email":"pbarnard@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":746347,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70198040,"text":"70198040 - 2018 - Interaction between hydraulic fracture and a preexisting fracture under triaxial stress conditions","interactions":[],"lastModifiedDate":"2018-08-07T12:07:51","indexId":"70198040","displayToPublicDate":"2018-05-01T12:07:45","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Interaction between hydraulic fracture and a preexisting fracture under triaxial stress conditions","docAbstract":"Enhanced reservoir connectivity generally requires maximizing the intersection between hydraulic fracture (HF) and preexisting underground natural fractures (NF), while having the hydraulic fracture cross the natural fractures (and not arrest). We have studied the interaction between a hydraulic fracture and a polished saw-cut fault. The experiments include a hydraulic fracture initiating from a pressurized axial borehole (using water) that approaches a dry fault that is inclined at an angle θ with respect to the borehole axis. The experiments are conducted on Poly(methyl) Meta Acrylate (PMMA) and Solnhofen limestone, a finely grained (<5 μm grain), low permeability (<10 nD) carbonate. The confining pressure in all experiments is 5 MPa, while the differential stress (1-80 MPa) and approach angle, θ (30, 45, 60, 90°) are experimental variables. During the hydraulic fracture, acoustic emissions (AE), slip velocity, slip magnitude, stress drop and pore pressure are recorded at a 5 MHz sampling rate. A Doppler laser vibrometer measures piston velocity outside the pressure vessel to infer fault slip duration and a strain gauge adjacent to the saw-cut provides a near-field measure of axial stress.
For PMMA, the coefficient of friction was 0.30 and sliding was unstable (stick-slip). The approaching HF in PMMA created a tensile fracture detected by AE transducers ~100 μs before the significant stick-slip event (45% stress drop and slip velocity of ~60 mm/s) and was arrested by the fault at all fault orientations and differential stresses, even at 90° fault orientation and 80 MPa differential stress. For Solnhofen limestone, we observed stable sliding at a coefficient of friction of 0.12. In contrast to PMMA, the HF in Solnhofen consistently crossed to the other side of the fault. When the HF crossed the fault, it produced a small stress drop (<10%) and slip velocity of only 0.5 mm/s. Theoretical models by Blanton (1986) and Renshaw and Pollard (1995) predict that HF will be arrested for Solnhofen limestone and cross PMMA 90° fault at 80 MPa differential stress. Although the exact cause for the discrepancy between experiments and the theory is not known, one feature present in the experiments but not considered in the models, is the diffusion of fluid driven by the fault slip. Thus, the formation of a \"fluid-filled patch\" on the fault surface as it is intersected by the HF may substantially impact the crossing/arrest behavior. The approach angle and differential stress also influence the HF initiation azimuth and breakdown pressure. In most cases, the HF initiation azimuth was normal to the fault strike. These observations suggest that the presence of natural fractures could result in rotation of hydraulic fractures to be more normal to their strike and a subsequent change in the downhole pressure recordings. The latter could be used as a diagnostic tool for predicting this interaction.
","largerWorkTitle":"SPE Hydraulic Fracturing Technology Conference and Exhibition","conferenceTitle":"SPE Hydraulic Fracturing Technology Conference and Exhibition","conferenceDate":"January 23-25, 2018","conferenceLocation":"The Woodlands, TX","language":"English","publisher":"Society of Petroleum Engineers","doi":"10.2118/189901-MS","usgsCitation":"Mighani, S., Lockner, D.A., Kilgore, B.D., Sheibani, F., and Evans, B., 2018, Interaction between hydraulic fracture and a preexisting fracture under triaxial stress conditions, in SPE Hydraulic Fracturing Technology Conference and Exhibition, The Woodlands, TX, January 23-25, 2018, 26 p., https://doi.org/10.2118/189901-MS.","productDescription":"26 p.","ipdsId":"IP-095560","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":437926,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DQOE6D","text":"USGS data release","linkHelpText":"Data Release for "Interaction between hydraulic fracture and a preexisting fracture under triaxial stress conditions""},{"id":356278,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-23","publicationStatus":"PW","scienceBaseUri":"5b6fc45ce4b0f5d57878ea61","contributors":{"authors":[{"text":"Mighani, Saied","contributorId":206821,"corporation":false,"usgs":false,"family":"Mighani","given":"Saied","email":"","affiliations":[],"preferred":false,"id":741866,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lockner, David A. 0000-0001-8630-6833 dlockner@usgs.gov","orcid":"https://orcid.org/0000-0001-8630-6833","contributorId":567,"corporation":false,"usgs":true,"family":"Lockner","given":"David","email":"dlockner@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":741867,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kilgore, Brian D. 0000-0003-0530-7979 bkilgore@usgs.gov","orcid":"https://orcid.org/0000-0003-0530-7979","contributorId":3887,"corporation":false,"usgs":true,"family":"Kilgore","given":"Brian","email":"bkilgore@usgs.gov","middleInitial":"D.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":741868,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sheibani, Farrokh 0000-0002-5105-4792","orcid":"https://orcid.org/0000-0002-5105-4792","contributorId":205992,"corporation":false,"usgs":false,"family":"Sheibani","given":"Farrokh","email":"","affiliations":[{"id":37205,"text":"Post-Doctoral researcher at M.I.T. Cambridge MA","active":true,"usgs":false}],"preferred":false,"id":741869,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Evans, Brian 0000-0003-0324-0969","orcid":"https://orcid.org/0000-0003-0324-0969","contributorId":205993,"corporation":false,"usgs":false,"family":"Evans","given":"Brian","email":"","affiliations":[{"id":37206,"text":"Professor, Massachusetts Institute of Technology: Cambridge, MA","active":true,"usgs":false}],"preferred":false,"id":741870,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70200075,"text":"70200075 - 2018 - Identifying and eliminating sources of recreational water quality degradation along an urban coast","interactions":[],"lastModifiedDate":"2018-10-11T10:48:41","indexId":"70200075","displayToPublicDate":"2018-05-01T10:48:35","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2262,"text":"Journal of Environmental Quality","active":true,"publicationSubtype":{"id":10}},"title":"Identifying and eliminating sources of recreational water quality degradation along an urban coast","docAbstract":"Restoration of highly degraded urban coastal waters often requires large-scale, complex projects, but in the interim, smaller-scale efforts can provide immediate improvements to water quality conditions for visitor use. We examined short-term efforts to improve recreational water quality near the Grand Calumet River (GC) in the Laurentian Great Lakes. Identified as an Area of Concern (AOC) by the International Joint Commission, the GC has experienced years of industrial and municipal waste discharges, and as a result, coastal beaches have some of the highest rates of beach closings (>70%) in the United States. Project objectives were to identify sources of microbial contamination and to evaluate a short-term management solution to decrease beach closings: during 2015 (partial) and 2016 (season-long), canines were used to deter gull presence. Water samples were analyzed for Escherichia coli in 2015 and 2016, and fecal sources were evaluated using microbial source tracking markers (2015): human (Bacteroides HF183, Methanobrevibacter nifH), gull (Gull2), and dog (DogBact). Hydrometeorological conditions were simultaneously measured. Results indicated that human, gull, and canine fecal sources were present, with gulls being the dominant source. Escherichia coli densities were highly correlated with number of gulls present, Gull2 marker, and turbidity. Gull deterrence decreased E. coli and Gull2 marker detection during 2015, but numbers rebounded after program completion. The full-season program in 2016 resulted in lower E. coli densities and fewer beach closings. Large-scale restoration efforts are underway at this location, but short-term, small-scale projects can be useful for reducing beach closings and restoring ecosystem services.
","language":"English","publisher":"American Society of Agronomy, Crop Science Society of America, Soil Science Society of America","doi":"10.2134/jeq2017.11.0461","usgsCitation":"Nevers, M., Byappanahalli, M., Shively, D., Buszka, P.M., Jackson, P.R., and Phanikumar, M.S., 2018, Identifying and eliminating sources of recreational water quality degradation along an urban coast: Journal of Environmental Quality, v. 47, no. 5, p. 1042-1050, https://doi.org/10.2134/jeq2017.11.0461.","productDescription":"9 p.","startPage":"1042","endPage":"1050","ipdsId":"IP-092824","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":437928,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9M8Y8F3","text":"USGS data release","linkHelpText":"Identify sources of high E. coli concentrations, Grand Calumet River Area of Concern beaches of southern Lake Michigan, 2016-2018"},{"id":437927,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7H70F3D","text":"USGS data release","linkHelpText":"Identify sources of high E. coli concentrations, beaches of southern Lake Michigan, 2015, (version 2.0, July 2020)"},{"id":358271,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Indiana","otherGeospatial":"Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.52464294433594,\n 41.580525125613846\n ],\n [\n -87.24655151367188,\n 41.580525125613846\n ],\n [\n -87.24655151367188,\n 41.72725537359254\n ],\n [\n -87.52464294433594,\n 41.72725537359254\n ],\n [\n -87.52464294433594,\n 41.580525125613846\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","issue":"5","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02ff9e4b0fc368eb539b8","contributors":{"authors":[{"text":"Nevers, Meredith B. 0000-0001-6963-6734","orcid":"https://orcid.org/0000-0001-6963-6734","contributorId":201531,"corporation":false,"usgs":true,"family":"Nevers","given":"Meredith B.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":748279,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Byappanahalli, Muruleedhara 0000-0001-5376-597X byappan@usgs.gov","orcid":"https://orcid.org/0000-0001-5376-597X","contributorId":147923,"corporation":false,"usgs":true,"family":"Byappanahalli","given":"Muruleedhara","email":"byappan@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":748280,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shively, Dawn 0000-0002-6119-924X dshively@usgs.gov","orcid":"https://orcid.org/0000-0002-6119-924X","contributorId":201533,"corporation":false,"usgs":true,"family":"Shively","given":"Dawn","email":"dshively@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":748281,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Buszka, Paul M. 0000-0001-8218-826X pmbuszka@usgs.gov","orcid":"https://orcid.org/0000-0001-8218-826X","contributorId":1786,"corporation":false,"usgs":true,"family":"Buszka","given":"Paul","email":"pmbuszka@usgs.gov","middleInitial":"M.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":748282,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jackson, P. Ryan 0000-0002-3154-6108 pjackson@usgs.gov","orcid":"https://orcid.org/0000-0002-3154-6108","contributorId":194529,"corporation":false,"usgs":true,"family":"Jackson","given":"P.","email":"pjackson@usgs.gov","middleInitial":"Ryan","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":748283,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Phanikumar, Mantha S.","contributorId":208872,"corporation":false,"usgs":false,"family":"Phanikumar","given":"Mantha","email":"","middleInitial":"S.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":748284,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70199214,"text":"70199214 - 2018 - The influence of sea level rise on the regional interdependence of coastal infrastructure","interactions":[],"lastModifiedDate":"2018-09-11T10:18:00","indexId":"70199214","displayToPublicDate":"2018-05-01T10:17:53","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5053,"text":"Earth's Future","active":true,"publicationSubtype":{"id":10}},"title":"The influence of sea level rise on the regional interdependence of coastal infrastructure","docAbstract":"Sea level rise (SLR) is placing both immediate and long‐term pressures on coastal communities to take protective actions. Projects in the United States, and in many locations throughout the world, generally involve local jurisdictions raising the elevation of shoreline protection elements, with limited or no analysis of the feedback between shoreline management decisions and the impacts to water levels regionally. Our study examines the impact of local shoreline development on regional flood risk and considers SLR scenarios up to 1.5 m using a large‐scale numerical model, as an example, for San Francisco Bay. Here we show that measures to prevent flooding along an embayment shoreline in one location or subregion may increase inundation elsewhere in the system. The network of interactions occurs not only within subbasins of the Bay but also across the greater geographic extent from one end of the Bay to the other, and local jurisdiction may have either reciprocal relationships with or asymmetric impacts on one other. Importantly, the nature of the interaction network is seen to evolve with SLR: interactions are purely subregional at current sea level but with higher sea level (e.g., 1 m of SLR), not only do the subregional interdependencies strengthen but also regional interdependences emerge.
","language":"English","publisher":"AGU","doi":"10.1002/2017EF000742","usgsCitation":"Wang, R., Stacey, M., Herdman, L.M., Barnard, P., and Erikson, L.H., 2018, The influence of sea level rise on the regional interdependence of coastal infrastructure: Earth's Future, v. 6, no. 5, p. 677-688, https://doi.org/10.1002/2017EF000742.","productDescription":"12 p.","startPage":"677","endPage":"688","ipdsId":"IP-086793","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468786,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017ef000742","text":"Publisher Index Page"},{"id":357219,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.67333984374999,\n 37.391981943533544\n ],\n [\n -121.75872802734375,\n 37.391981943533544\n ],\n [\n -121.75872802734375,\n 38.26406296833961\n ],\n [\n -122.67333984374999,\n 38.26406296833961\n ],\n [\n -122.67333984374999,\n 37.391981943533544\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-02","publicationStatus":"PW","scienceBaseUri":"5b98a2cfe4b0702d0e842ff3","contributors":{"authors":[{"text":"Wang, Ruo-Quian","contributorId":206190,"corporation":false,"usgs":false,"family":"Wang","given":"Ruo-Quian","email":"","affiliations":[{"id":37278,"text":"University of Dundee","active":true,"usgs":false}],"preferred":false,"id":744708,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stacey, Mark T.","contributorId":94531,"corporation":false,"usgs":false,"family":"Stacey","given":"Mark T.","affiliations":[{"id":12776,"text":"Department of Civil and Environmental Engineering, University of California, Berkeley, California, USA","active":true,"usgs":false}],"preferred":false,"id":744709,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herdman, Liv M. 0000-0002-5444-6441 lherdman@usgs.gov","orcid":"https://orcid.org/0000-0002-5444-6441","contributorId":149964,"corporation":false,"usgs":true,"family":"Herdman","given":"Liv","email":"lherdman@usgs.gov","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":744707,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":147147,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","email":"pbarnard@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":744710,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":744711,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70227668,"text":"70227668 - 2018 - Effects of water-level management and hatchery supplementation on kokanee recruitment in Lake Pend Oreille, Idaho","interactions":[],"lastModifiedDate":"2022-01-26T15:33:15.901065","indexId":"70227668","displayToPublicDate":"2018-05-01T09:31:59","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"title":"Effects of water-level management and hatchery supplementation on kokanee recruitment in Lake Pend Oreille, Idaho","docAbstract":"Resource managers have been attempting to recover the kokanee (Oncorhynchus nerka) population in Lake Pend Oreille, Idaho for more than three decades using an annual stocking program and an experimental water-level management strategy. This study evaluated the effect of both management actions on kokanee recruitment. A bootstrap-based generalized Ricker model was used to test if wild kokanee recruitment was significantly influenced by water-level management, while accounting for error due to sampling variability and differential survival of wild- and hatchery-origin fish within age-classes. Wild kokanee exhibited a compensatory stock-recruitment relationship, whereas hatchery recruitment was positively and linearly related to stocking. The model did not identify a significant relationship between water level and wild kokanee recruitment. Density dependence and variable stocking appeared to explain the synchronized and cyclic recruitment of wild and hatchery fry.
","language":"English","publisher":"Washington State University Press","doi":"10.3955/046.092.0206","usgsCitation":"Whitlock, S., Quist, M.C., and Dux, A.M., 2018, Effects of water-level management and hatchery supplementation on kokanee recruitment in Lake Pend Oreille, Idaho, v. 92, no. 2, p. 136-148, https://doi.org/10.3955/046.092.0206.","productDescription":"13 p.","startPage":"136","endPage":"148","ipdsId":"IP-053519","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":394866,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Lake Pend Oreille","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.69677734375,\n 47.93934692855592\n ],\n [\n -116.19415283203125,\n 47.93934692855592\n ],\n [\n -116.19415283203125,\n 48.32612605157941\n ],\n [\n -116.69677734375,\n 48.32612605157941\n ],\n [\n -116.69677734375,\n 47.93934692855592\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"92","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Whitlock, Steven L.","contributorId":267708,"corporation":false,"usgs":false,"family":"Whitlock","given":"Steven L.","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":831780,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quist, Michael C. 0000-0001-8268-1839","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":207142,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":831668,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dux, Andrew M.","contributorId":212798,"corporation":false,"usgs":false,"family":"Dux","given":"Andrew","email":"","middleInitial":"M.","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":831781,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70236152,"text":"70236152 - 2018 - Warming is driving decreases in snow fractions while runoff efficiency remains mostly unchanged in snow-covered areas of the western United States","interactions":[],"lastModifiedDate":"2022-08-30T14:26:41.124038","indexId":"70236152","displayToPublicDate":"2018-05-01T09:19:40","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2344,"text":"Journal of Hydrometeorology","active":true,"publicationSubtype":{"id":10}},"title":"Warming is driving decreases in snow fractions while runoff efficiency remains mostly unchanged in snow-covered areas of the western United States","docAbstract":"Winter snowfall and accumulation is an important component of the surface water supply in the western United States. In these areas, increasing winter temperatures T associated with global warming can influence the amount of winter precipitation P that falls as snow S. In this study we examine long-term trends in the fraction of winter P that falls as S (Sfrac) for 175 hydrologic units (HUs) in snow-covered areas of the western United States for the period 1951–2014. Because S is a substantial contributor to runoff R across most of the western United States, we also examine long-term trends in water-year runoff efficiency [computed as water-year R/water-year P (Reff)] for the same 175 HUs. In that most S records are short in length, we use model-simulated S and R from a monthly water balance model. Results for Sfrac indicate long-term negative trends for most of the 175 HUs, with negative trends for 139 (~79%) of the HUs being statistically significant at a 95% confidence level (p = 0.05). Additionally, results indicate that the long-term negative trends in Sfrac have been largely driven by increases in T. In contrast, time series of Reff for the 175 HUs indicate a mix of positive and negative long-term trends, with few trends being statistically significant (at p = 0.05). Although there has been a notable shift in the timing of R to earlier in the year for most HUs, there have not been substantial decreases in water-year R for the 175 HUs.
","language":"English","publisher":"American Meteorological Society","doi":"10.1175/JHM-D-17-0227.1","usgsCitation":"McCabe, G.J., Wolock, D.M., and Valentin, M., 2018, Warming is driving decreases in snow fractions while runoff efficiency remains mostly unchanged in snow-covered areas of the western United States: Journal of Hydrometeorology, v. 19, p. 803-814, https://doi.org/10.1175/JHM-D-17-0227.1.","productDescription":"12 p.","startPage":"803","endPage":"814","ipdsId":"IP-080058","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":468787,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jhm-d-17-0227.1","text":"Publisher Index Page"},{"id":405909,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.7734375,\n 32.39851580247402\n ],\n [\n -107.70996093749999,\n 31.840232667909365\n ],\n [\n -106.69921875,\n 33.394759218577995\n ],\n [\n -106.4794921875,\n 35.209721645221386\n ],\n [\n -104.67773437499999,\n 35.92464453144099\n ],\n [\n -104.7216796875,\n 37.64903402157866\n ],\n [\n -104.5458984375,\n 38.89103282648846\n ],\n [\n -104.94140625,\n 39.80853604144591\n ],\n [\n -104.80957031249999,\n 40.48038142908172\n ],\n [\n -105.64453124999999,\n 41.343824581185686\n ],\n [\n -104.94140625,\n 42.19596877629178\n ],\n [\n -106.787109375,\n 43.35713822211053\n ],\n [\n -106.6552734375,\n 44.308126684886126\n ],\n [\n -107.9296875,\n 45.36758436884978\n ],\n [\n -110.25878906249999,\n 45.85941212790755\n ],\n [\n -111.09374999999999,\n 46.76996843356982\n ],\n [\n -112.67578124999999,\n 47.66538735632654\n ],\n [\n -113.51074218749999,\n 49.06666839558117\n ],\n [\n -123.53027343749999,\n 49.06666839558117\n ],\n [\n -123.26660156249999,\n 48.37084770238366\n ],\n [\n -125.3759765625,\n 48.60385760823255\n ],\n [\n -124.4091796875,\n 45.336701909968134\n ],\n [\n -124.93652343749999,\n 43.004647127794435\n ],\n [\n -124.76074218749999,\n 40.38002840251183\n ],\n [\n -124.18945312500001,\n 38.75408327579141\n ],\n [\n -122.3876953125,\n 36.35052700542763\n ],\n [\n -120.9375,\n 34.19817309627726\n ],\n [\n -117.7734375,\n 32.39851580247402\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"19","noUsgsAuthors":false,"publicationDate":"2018-05-17","publicationStatus":"PW","contributors":{"authors":[{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":200854,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory","email":"gmccabe@usgs.gov","middleInitial":"J.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":850262,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wolock, David M. 0000-0002-6209-938X","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":219213,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":850263,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Valentin, Melissa","contributorId":202218,"corporation":false,"usgs":false,"family":"Valentin","given":"Melissa","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":850264,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70200606,"text":"70200606 - 2018 - Research, monitoring, and evaluation of emerging issues and measures to recover the Snake River fall Chinook salmon ESU","interactions":[],"lastModifiedDate":"2018-11-21T09:14:01","indexId":"70200606","displayToPublicDate":"2018-05-01T09:13:26","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Research, monitoring, and evaluation of emerging issues and measures to recover the Snake River fall Chinook salmon ESU","docAbstract":"The portion of the Snake River fall Chinook Salmon Oncorhynchus tshawytscha ESU that spawns upstream of Lower Granite Dam transitioned from low to high abundance during 1992–2017 in association with U.S. Endangered Species Act recovery efforts and other federally mandated actions. This annual report focuses on (1) numeric and habitat use responses by natural- and hatchery-origin spawners, (2) phenotypic and numeric responses by natural-origin juveniles, (3) USGS use of a small unmanned aerial system (sUAS) to search for fall Chinook salmon redds and carcasses, and (4) the detection of 8-mm PIT tags at Lower Granite Dam. Spawners have located and used most of the available spawning habitat and that habitat is gradually approaching redd capacity. Timing of spawning and fry emergence has been relatively stable; whereas the timing of parr dispersal from riverine rearing habitat into Lower Granite Reservoir has become earlier as apparent abundance of juveniles has increased. Growth rate (g/d) and dispersal size of parr also declined as apparent abundance of juveniles increased. Passage timing of smolts from the two Snake River reaches has become earlier and downstream movement rate faster as estimated abundance of fall Chinook Salmon smolts in Lower Granite Reservoir has increased. These findings coupled with stock-recruitment analyses presented in this report provide evidence for density-dependence in the Snake River reaches and in Lower Granite Reservoir that was influenced by the expansion of the recovery program. The long-term goal is to use the information covered here in a comprehensive modeling effort to conduct action effectiveness and uncertainty research and to inform Fish Population, Hydrosystem, Harvest, Hatchery, and Predation and Invasive Species Management RM&E.\n\nIn 2017, the USGS searched 15 shallow water spawning sites in conjunction with the Idaho Power Company (IPC). Redd counts agreed with those of IPC for a little more than half the sites suggesting that we need more training in redd counting. We recovered 67 carcasses, and tissue samples are currently being analyzed for parentage to ultimately determine the percentage of hatchery-origin spawners on the spawning grounds. Redd fading was examined to determine the frequency at which aerial surveys should be conducted. Most redds surveyed through time were visible for at least 4 weeks after the redd was initially constructed. Redd fading was variable amongst sites and depended on location.\n\nIn 2017, we conducted a second year of evaluating detection efficiency of 8-mm PIT tags in the Lower Granite Dam juvenile fish collection system. Groups of 75–78 fish were tagged\nwith 8-mm Biomark, 8-mm Oregon RFID, 9-mm Biomark, and 12-mm Biomark PIT tags and released into the bypass upstream of the upwell. From 97.4 to 100% (depending on tag type) of tagged fish were detected on at least one antenna in the Lower Granite Dam bypass system. Mean detection efficiency within the predominant passage route (i.e., diversion river exit) exceeded 0.98 for all tag types in both years. These results suggest that fish tagged in the field with 8-mm PIT tags should be detected at rates similar to larger tags at main-stem hydroelectric dams.","language":"English","publisher":"Bonneville Power Administration","usgsCitation":"Tiffan, K., Plumb, J.M., Perry, R.W., Erhardt, J., Hemingway, R.J., Bickford, B., Rhodes, T., Connor, W., and Mullins, F.L., 2018, Research, monitoring, and evaluation of emerging issues and measures to recover the Snake River fall Chinook salmon ESU, 67 p.","productDescription":"67 p.","ipdsId":"IP-097295","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":359627,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":358776,"type":{"id":15,"text":"Index Page"},"url":"https://www.cbfish.org/Document.mvc/DocumentViewer/P160478/75986-1.pdf"}],"country":"United States","otherGeospatial":"Snake River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.35546875000001,\n 44.715513732021336\n ],\n [\n -114.6478271484375,\n 44.715513732021336\n ],\n [\n -114.6478271484375,\n 47.10378387099161\n ],\n [\n -119.35546875000001,\n 47.10378387099161\n ],\n [\n -119.35546875000001,\n 44.715513732021336\n ]\n ]\n ]\n }\n }\n ]\n}","tableOfContents":"","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bf67cf5e4b045bfcae2cffe","contributors":{"authors":[{"text":"Tiffan, Kenneth 0000-0002-5831-2846 ktiffan@usgs.gov","orcid":"https://orcid.org/0000-0002-5831-2846","contributorId":210058,"corporation":false,"usgs":true,"family":"Tiffan","given":"Kenneth","email":"ktiffan@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":749719,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plumb, John M. 0000-0003-4255-1612 jplumb@usgs.gov","orcid":"https://orcid.org/0000-0003-4255-1612","contributorId":3569,"corporation":false,"usgs":true,"family":"Plumb","given":"John","email":"jplumb@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":751889,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":751890,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Erhardt, John 0000-0002-5170-285X jerhardt@usgs.gov","orcid":"https://orcid.org/0000-0002-5170-285X","contributorId":210059,"corporation":false,"usgs":true,"family":"Erhardt","given":"John","email":"jerhardt@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":749720,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hemingway, Rulon J. 0000-0001-8143-0325 rhemingway@usgs.gov","orcid":"https://orcid.org/0000-0001-8143-0325","contributorId":194697,"corporation":false,"usgs":true,"family":"Hemingway","given":"Rulon","email":"rhemingway@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":751891,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bickford, Brad 0000-0003-3756-6588 bbickford@usgs.gov","orcid":"https://orcid.org/0000-0003-3756-6588","contributorId":210056,"corporation":false,"usgs":true,"family":"Bickford","given":"Brad","email":"bbickford@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":749717,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rhodes, Tobyn N. 0000-0002-4023-4827","orcid":"https://orcid.org/0000-0002-4023-4827","contributorId":210057,"corporation":false,"usgs":true,"family":"Rhodes","given":"Tobyn N.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":749718,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Connor, William P.","contributorId":115438,"corporation":false,"usgs":true,"family":"Connor","given":"William P.","affiliations":[{"id":16677,"text":"U.S. Fish and Wildlife Service, Idaho Fishery Resource Office, 276 Dworshak Complex Drive, Orofino, ID 83544","active":true,"usgs":false}],"preferred":false,"id":751892,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mullins, Frank L.","contributorId":146343,"corporation":false,"usgs":false,"family":"Mullins","given":"Frank","email":"","middleInitial":"L.","affiliations":[{"id":16677,"text":"U.S. Fish and Wildlife Service, Idaho Fishery Resource Office, 276 Dworshak Complex Drive, Orofino, ID 83544","active":true,"usgs":false}],"preferred":false,"id":751893,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70198860,"text":"70198860 - 2018 - Wetlands receiving water treated with coagulants improve water quality by removing dissolved organic carbon and disinfection byproduct precursors","interactions":[],"lastModifiedDate":"2018-08-24T12:12:27","indexId":"70198860","displayToPublicDate":"2018-05-01T07:55:36","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Wetlands receiving water treated with coagulants improve water quality by removing dissolved organic carbon and disinfection byproduct precursors","docAbstract":"
Constructed wetlands are used worldwide to improve water quality while also providing critical wetland habitat. However, wetlands have the potential to negatively impact drinking water quality by exporting dissolved organic carbon (DOC) that upon disinfection can form disinfection byproducts (DBPs) like trihalomethanes (THMs) and haloacetic acids (HAAs). We used a replicated field-scale study located on organic rich soils in California's Sacramento-San Joaquin Delta to test whether constructed flow-through wetlands which receive water high in DOC that is treated with either iron- or aluminum-based coagulants can improve water quality with respect to DBP formation. Coagulation alone removed DOC (66–77%) and THM (67–70%) precursors, and was even more effective at removing HAA precursors (77–90%). Passage of water through the wetlands increased DOC concentrations (1.5–7.5 mg L− 1), particularly during the warmer summer months, thereby reversing some of the benefits from coagulant addition. Despite this addition, water exiting the wetlands treated with coagulants had lower DOC and DBP precursor concentrations relative to untreated source water. Benefits of the coagulation-wetland systems were greatest during the winter months (approx. 50–70% reduction in DOC and DBP precursor concentrations) when inflow water DOC concentrations were higher and wetland DOC production was lower. Optical properties suggest DOC in this system is predominantly comprised of high molecular weight, aromatic compounds, likely derived from degraded peat soils.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2017.11.205","usgsCitation":"Hansen, A., Kraus, T.E., Bachand, S.M., Horwath, W.R., and Bachand, P., 2018, Wetlands receiving water treated with coagulants improve water quality by removing dissolved organic carbon and disinfection byproduct precursors: Science of the Total Environment, v. 622-623, p. 603-613, https://doi.org/10.1016/j.scitotenv.2017.11.205.","productDescription":"11 p.","startPage":"603","endPage":"613","ipdsId":"IP-084915","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":468789,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2017.11.205","text":"Publisher Index Page"},{"id":356678,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"622-623","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b98a2d0e4b0702d0e842ff5","contributors":{"authors":[{"text":"Hansen, Angela M. 0000-0003-0938-7611","orcid":"https://orcid.org/0000-0003-0938-7611","contributorId":204702,"corporation":false,"usgs":true,"family":"Hansen","given":"Angela M.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":743114,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kraus, Tamara E. C. 0000-0002-5187-8644 tkraus@usgs.gov","orcid":"https://orcid.org/0000-0002-5187-8644","contributorId":147560,"corporation":false,"usgs":true,"family":"Kraus","given":"Tamara","email":"tkraus@usgs.gov","middleInitial":"E. C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":743115,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bachand, Sandra M.","contributorId":147304,"corporation":false,"usgs":false,"family":"Bachand","given":"Sandra","email":"","middleInitial":"M.","affiliations":[{"id":12526,"text":"Bachand & Associates","active":true,"usgs":false}],"preferred":false,"id":743116,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Horwath, William R.","contributorId":147305,"corporation":false,"usgs":false,"family":"Horwath","given":"William","email":"","middleInitial":"R.","affiliations":[{"id":7246,"text":"University of California, Davis, CA, USA","active":true,"usgs":false}],"preferred":false,"id":743118,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bachand, Philip","contributorId":81013,"corporation":false,"usgs":false,"family":"Bachand","given":"Philip","email":"","affiliations":[{"id":12526,"text":"Bachand & Associates","active":true,"usgs":false}],"preferred":false,"id":743117,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70197451,"text":"70197451 - 2018 - Book review: Handbook of cyanobacterial monitoring and cyanotoxin analysis","interactions":[],"lastModifiedDate":"2018-06-05T10:37:08","indexId":"70197451","displayToPublicDate":"2018-05-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5706,"text":"Limnology and Oceanography Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Book review: Handbook of cyanobacterial monitoring and cyanotoxin analysis","docAbstract":"Review of Meriluoto, Jussi, Lisa Spoof, and GeoffreyA. Codd [eds.]. 2017. Handbook of Cyanobacterial Monitoring and Cyanotoxin Analysis. John Wiley & Sons, Ltd.: Chichester, West Sussex, UK, ISBN 978‐1‐119‐06868‐6 (978‐1‐119‐06876‐1 eBook), DOI 10.1002/9781119068761.
","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lob.10227","usgsCitation":"Graham, J., and Loftin, K.A., 2018, Book review: Handbook of cyanobacterial monitoring and cyanotoxin analysis: Limnology and Oceanography Bulletin, v. 27, no. 2, p. 61-62, https://doi.org/10.1002/lob.10227.","productDescription":"2 p.","startPage":"61","endPage":"62","ipdsId":"IP-092798","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":468798,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lob.10227","text":"Publisher Index Page"},{"id":354718,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-17","publicationStatus":"PW","scienceBaseUri":"5b46e58ee4b060350a15d1d8","contributors":{"authors":[{"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":737200,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":737201,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70196457,"text":"sir20185050 - 2018 - Discharge, sediment, and water chemistry in Clear Creek, western Nevada, water years 2013–16","interactions":[],"lastModifiedDate":"2018-05-02T10:35:24","indexId":"sir20185050","displayToPublicDate":"2018-05-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5050","title":"Discharge, sediment, and water chemistry in Clear Creek, western Nevada, water years 2013–16","docAbstract":"Clear Creek is a small stream that drains the eastern Carson Range near Lake Tahoe, flows roughly parallel to the Highway 50 corridor, and discharges to the Carson River near Carson City, Nevada. Historical and ongoing development in the drainage basin is thought to be affecting Clear Creek and its sediment-transport characteristics. Previous studies from water years (WYs) 2004 to 2007 and from 2010 to 2012 evaluated discharge, selected water-quality parameters, and suspended-sediment concentrations, loads, and yields at three Clear Creek sampling sites. This report serves as a continuation of the data collection and analyses of the Clear Creek discharge regime and associated water-chemistry and sediment concentrations and loads during WYs 2013–16.
Total annual sediment loads ranged from 870 to 5,300 tons during WYs 2004–07, from 320 to 1,770 tons during WYs 2010–12, and from 50 to 200 tons during WYs 2013–16. Ranges in annual loads during the three study periods were not significantly different; however, total loads were greater during 2004–07 than they were during 2013–16. Annual suspended-sediment loads in WYs 2013–16 showed no significant change since WYs 2010–12 at sites 1 (U.S. Geological Survey reference site 10310485; Clear Creek above Highway 50, near Spooner Summit, Nevada) or 2 (U.S. Geological Survey streamgage 10310500; Clear Creek above Highway 50, near Spooner Summit, Nevada), but significantly lower loads at site 3 (U.S. Geological Survey site 10310518; Clear Creek at Fuji Park, at Carson City, Nevada), supporting the theory of sediment deposition between sites 2 and 3 where the stream gradient becomes more gradual. Currently, a threshold discharge of about 3.3 cubic feet per second is required to mobilize streambed sediment (bedload) from site 2 in Clear Creek. Mean daily discharge was significantly lower in 2010–12 than in 2004–07 and also significantly lower in 2013–16 than in 2010–12. During this study, lower bedload, and therefore lower total sediment load in Clear Creek was primarily due to significantly lower discharge and cannot be directly attributed to sediment mitigation work in the basin.
Water chemistry in Clear Creek shows that the general water type of the creek under base-flow conditions in autumn is a dilute calcium bicarbonate. During winter and spring, the chemistry shifts toward a slightly more sodium and chloride character. Though the chemical characteristics show seasonal change, the water chemistries examined as part of this investigation remain within ecological criteria as adopted by the Nevada Division of Environmental Protection. There was no evidence of aqueous polynuclear aromatic hydrocarbons (PAHs) present in Clear Creek water during this study. Concentrations of PAHs, as determined in one bed-sediment sample and multiple semi-permeable membrane device extracts, were either less than quantifiable limits of analysis or were found at similar concentrations as blank samples.
In July 2014, a 250–300-acre fire burned in the Clear Creek drainage basin. One day after the fire was extinguished, a thunderstorm washed sediment into the creek. A water chemistry sample collected as part of the post-fire storm event showed that the stormwater entering the creek had increased the concentrations of ammonium and organic nitrogen, phosphorus, manganese, and potassium; a similar finding of many other studies evaluating the effects of fires in small drainage basins. Subsequent chemical analyses of Clear Creek water in August 2014 (one month later) showed that these constituents had returned to pre-fire concentrations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185050","collaboration":"Prepared in cooperation with the Nevada Department of Transportation","usgsCitation":"Huntington, J.M., Riddle, D.J., and Paul, A.P., 2018, Discharge, sediment, and water chemistry in Clear Creek, western Nevada, water years 2013–16: U.S. Geological Survey Scientific-Investigations Report 2018–5050, 55 p., https://doi.org/10.3133/sir20185050.","productDescription":"vii, 55 p.","onlineOnly":"Y","ipdsId":"IP-067971","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":353895,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5050/sir20185050.pdf","text":"Report","size":"6.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5050"},{"id":353894,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5050/coverthb.jpg"}],"country":"United States","state":"Nevada","city":"Carson City","otherGeospatial":"Clear Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.9,\n 39.19\n ],\n [\n -119.7,\n 39.19\n ],\n [\n -119.7,\n 39.06\n ],\n [\n -119.9,\n 39.06\n ],\n [\n -119.9,\n 39.19\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Rd.
Carson City, Nevada 89701
Understanding the controls of agriculture and climate change on recharge rates is critically important to develop appropriate sustainable management plans for groundwater resources and coupled irrigated agricultural systems. In this study, several physical (total potential (ψT) time series) and chemical tracer and dating (3H, Cl−, Br−, CFCs, SF6, and 3H/3He) methods were used to quantify diffuse recharge rates beneath two rangeland sites and irrigation recharge rates beneath two irrigated corn sites along an east-west (wet-dry) transect of the northern High Plains aquifer, Platte River Basin, central Nebraska. The field-based recharge estimates and historical climate were used to calibrate site-specific Hydrus-1D models, and irrigation requirements were estimated using the Crops Simulation Model (CROPSIM). Future model simulations were driven by an ensemble of 16 global climate models and two global warming scenarios to project a 2050 climate relative to the historical baseline 1990 climate, and simulate changes in precipitation, irrigation, evapotranspiration, and diffuse and irrigation recharge rates. Although results indicate statistical differences between the historical variables at the eastern and western sites and rangeland and irrigated sites, the low warming scenario (+1.0 °C) simulations indicate no statistical differences between 2050 and 1990. However, the high warming scenarios (+2.4 °C) indicate a 25% and 15% increase in median annual evapotranspiration and irrigation demand, and decreases in future diffuse recharge by 53% and 98% and irrigation recharge by 47% and 29% at the eastern and western sites, respectively. These results indicate an important threshold between the low and high warming scenarios that if exceeded could trigger a significant bidirectional shift in 2050 hydroclimatology and recharge gradients. The bidirectional shift is that future northern High Plains temperatures will resemble present central High Plains temperatures and future recharge rates in the east will resemble present recharge rates in the western part of the northern High Plains aquifer. The reductions in recharge rates could accelerate declining water levels if irrigation demand and other management strategies are not implemented. Findings here have important implications for future management of irrigation practices and to slow groundwater depletion in this important agricultural region.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.agwat.2018.03.022","usgsCitation":"Lauffenburger, Z.H., Gurdak, J., Hobza, C.M., Woodward, D., and Wolf, C., 2018, Irrigated agriculture and future climate change effects on groundwater recharge, northern High Plains aquifer, USA: Agricultural Water Management, v. 204, p. 69-80, https://doi.org/10.1016/j.agwat.2018.03.022.","productDescription":"12 p.","startPage":"69","endPage":"80","ipdsId":"IP-095074","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":468796,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.agwat.2018.03.022","text":"Publisher Index Page"},{"id":353879,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Northern High Plains Aquifer","volume":"204","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6cce4b0da30c1bfbe18","contributors":{"authors":[{"text":"Lauffenburger, Zachary H.","contributorId":204545,"corporation":false,"usgs":false,"family":"Lauffenburger","given":"Zachary","email":"","middleInitial":"H.","affiliations":[{"id":6690,"text":"San Francisco State University","active":true,"usgs":false}],"preferred":false,"id":734307,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gurdak, Jason J.","contributorId":189822,"corporation":false,"usgs":false,"family":"Gurdak","given":"Jason J.","affiliations":[],"preferred":false,"id":734308,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hobza, Christopher M. 0000-0002-6239-934X cmhobza@usgs.gov","orcid":"https://orcid.org/0000-0002-6239-934X","contributorId":2393,"corporation":false,"usgs":true,"family":"Hobza","given":"Christopher","email":"cmhobza@usgs.gov","middleInitial":"M.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":734306,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Woodward, Duane","contributorId":204547,"corporation":false,"usgs":false,"family":"Woodward","given":"Duane","affiliations":[{"id":36954,"text":"Central Platte Natural Resources District","active":true,"usgs":false}],"preferred":false,"id":734310,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wolf, Cassandra","contributorId":204546,"corporation":false,"usgs":false,"family":"Wolf","given":"Cassandra","email":"","affiliations":[{"id":6690,"text":"San Francisco State University","active":true,"usgs":false}],"preferred":false,"id":734309,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196788,"text":"70196788 - 2018 - Rivers are social–ecological systems: Time to integrate human dimensions into riverscape ecology and management","interactions":[],"lastModifiedDate":"2018-07-03T11:23:17","indexId":"70196788","displayToPublicDate":"2018-05-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5067,"text":"WIREs Water","active":true,"publicationSubtype":{"id":10}},"title":"Rivers are social–ecological systems: Time to integrate human dimensions into riverscape ecology and management","docAbstract":"Incorporation of concepts from landscape ecology into understanding and managing riverine ecosystems has become widely known as riverscape ecology. Riverscape ecology emphasizes interactions among processes at different scales and their consequences for valued ecosystem components, such as riverine fishes. Past studies have focused strongly on understanding the ecological processes in riverscapes and how human actions modify those processes. It is increasingly clear, however, that an understanding of the drivers behind actions that lead to human modification also merit consideration, especially regarding how those drivers influence management efficacy. These indirect drivers of riverscape outcomes can be understood in the context of a diverse array of social processes, which we collectively refer to as human dimensions. Like ecological phenomena, social processes also exhibit complex interactions across spatiotemporal scales. Greater emphasis on feedbacks between social and ecological processes will lead scientists and managers to more completely understand riverscapes as complex, dynamic, interacting social–ecological systems. Emerging applications in riverscapes, as well as studies of other ecosystems, provide examples that can lead to stronger integration of social and ecological science. We argue that conservation successes within riverscapes may not come from better ecological science, improved ecosystem service analyses, or even economic incentives if the fundamental drivers of human behaviors are not understood and addressed in conservation planning and implementation.
","language":"English","publisher":"Wiley","doi":"10.1002/wat2.1291","usgsCitation":"Dunham, J.B., Angermeier, P.L., Crausbay, S.D., Cravens, A.E., Gosnell, H., McEvoy, J., Moritz, M.A., Raheem, N., and Sanford, T., 2018, Rivers are social–ecological systems: Time to integrate human dimensions into riverscape ecology and management: WIREs Water, v. 5, no. 4, p. 1-10, https://doi.org/10.1002/wat2.1291.","productDescription":"e1291; 10 p.","startPage":"1","endPage":"10","ipdsId":"IP-086232","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":353886,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-23","publicationStatus":"PW","scienceBaseUri":"5afee6cce4b0da30c1bfbe0c","contributors":{"authors":[{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":734406,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Angermeier, Paul L. biota@usgs.gov","contributorId":1432,"corporation":false,"usgs":true,"family":"Angermeier","given":"Paul","email":"biota@usgs.gov","middleInitial":"L.","affiliations":[{"id":613,"text":"Virginia Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"preferred":false,"id":734407,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crausbay, Shelley D.","contributorId":197220,"corporation":false,"usgs":false,"family":"Crausbay","given":"Shelley","email":"","middleInitial":"D.","affiliations":[{"id":54831,"text":"Conservation Science Partners, Inc","active":true,"usgs":false}],"preferred":false,"id":734408,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cravens, Amanda E. 0000-0002-0271-7967 aecravens@usgs.gov","orcid":"https://orcid.org/0000-0002-0271-7967","contributorId":196752,"corporation":false,"usgs":true,"family":"Cravens","given":"Amanda","email":"aecravens@usgs.gov","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":734409,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gosnell, Hannah","contributorId":192214,"corporation":false,"usgs":false,"family":"Gosnell","given":"Hannah","email":"","affiliations":[],"preferred":false,"id":734410,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McEvoy, Jamie","contributorId":204581,"corporation":false,"usgs":false,"family":"McEvoy","given":"Jamie","email":"","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":734411,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Moritz, Max A.","contributorId":182434,"corporation":false,"usgs":false,"family":"Moritz","given":"Max","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":734412,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Raheem, Nejem","contributorId":197227,"corporation":false,"usgs":false,"family":"Raheem","given":"Nejem","email":"","affiliations":[],"preferred":false,"id":734413,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sanford, Todd","contributorId":197228,"corporation":false,"usgs":false,"family":"Sanford","given":"Todd","email":"","affiliations":[],"preferred":false,"id":734414,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70196796,"text":"70196796 - 2018 - Demographic response of Louisiana Waterthrush, a stream obligate songbird of conservation concern, to shale gas development","interactions":[],"lastModifiedDate":"2018-05-01T15:45:19","indexId":"70196796","displayToPublicDate":"2018-05-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1318,"text":"Condor","active":true,"publicationSubtype":{"id":10}},"title":"Demographic response of Louisiana Waterthrush, a stream obligate songbird of conservation concern, to shale gas development","docAbstract":"Shale gas development continues to outpace the implementation of best management practices for wildlife affected by development. We examined demographic responses of the Louisiana Waterthrush (Parkesia motacilla) to shale gas development during 2009–2011 and 2013–2015 in a predominantly forested landscape in West Virginia, USA. Forest cover across the study area decreased from 95% in 2008 to 91% in 2015, while the area affected by shale gas development increased from 0.4% to 3.9%. We quantified nest survival and productivity, a source–sink threshold, riparian habitat quality, territory density, and territory length by monitoring 58.1 km of forested headwater streams (n = 14 streams). Across years, we saw annual variability in nest survival, with a general declining trend over time. Of 11 a priori models tested to explain nest survival (n = 280 nests), 4 models that included temporal, habitat, and shale gas covariates were supported, and 2 of these models accounted for most of the variation in daily nest survival rate. After accounting for temporal effects (rainfall, nest age, and time within season), shale gas development had negative effects on nest survival. Population-level nest productivity declined and individual productivity was lower in areas disturbed by shale gas development than in undisturbed areas, and a source–sink threshold suggested that disturbed areas were more at risk of being sink habitat. Riparian habitat quality scores, as measured by a U.S. Environmental Protection Agency index and a waterthrush-specific habitat suitability index, differed by year and were negatively related to the amount of each territory disturbed by shale gas development. Territory density was not related to the amount of shale gas disturbance, but decreased over time as territory lengths increased. Overall, our results suggest a decline in waterthrush site quality as shale gas development increases, despite relatively small site-wide forest loss.
","language":"English","publisher":"American Ornithological Society","doi":"10.1650/CONDOR-17-130.1","usgsCitation":"Frantz, M.W., Wood, P.B., Sheehan, J., and George, G., 2018, Demographic response of Louisiana Waterthrush, a stream obligate songbird of conservation concern, to shale gas development: Condor, v. 120, no. 2, p. 265-282, https://doi.org/10.1650/CONDOR-17-130.1.","productDescription":"18 p.","startPage":"265","endPage":"282","ipdsId":"IP-081181","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468794,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.bioone.org/doi/10.1650/CONDOR-17-130.1","text":"External Repository"},{"id":353898,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","otherGeospatial":"Lewis Wetzel Wildlife Management Area","volume":"120","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6c5e4b0da30c1bfbe0a","contributors":{"authors":[{"text":"Frantz, Mack W.","contributorId":191486,"corporation":false,"usgs":false,"family":"Frantz","given":"Mack","email":"","middleInitial":"W.","affiliations":[{"id":34541,"text":"West Virginia Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false},{"id":34542,"text":"Department of Biology. Indiana University of Pennsylvania","active":true,"usgs":false}],"preferred":false,"id":734475,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wood, Petra B. 0000-0002-8575-1705 pbwood@usgs.gov","orcid":"https://orcid.org/0000-0002-8575-1705","contributorId":199090,"corporation":false,"usgs":true,"family":"Wood","given":"Petra","email":"pbwood@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":734431,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sheehan, James","contributorId":169745,"corporation":false,"usgs":false,"family":"Sheehan","given":"James","email":"","affiliations":[],"preferred":false,"id":734476,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"George, Gregory","contributorId":204601,"corporation":false,"usgs":false,"family":"George","given":"Gregory","affiliations":[],"preferred":false,"id":734477,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196986,"text":"70196986 - 2018 - The non-linear, interactive effects of population density and climate drive the geographical patterns of waterfowl survival","interactions":[],"lastModifiedDate":"2018-05-15T16:34:47","indexId":"70196986","displayToPublicDate":"2018-05-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"The non-linear, interactive effects of population density and climate drive the geographical patterns of waterfowl survival","docAbstract":"On-going climate change has major impacts on ecological processes and patterns. Understanding the impacts of climate on the geographical patterns of survival can provide insights to how population dynamics respond to climate change and provide important information for the development of appropriate conservation strategies at regional scales. It is challenging to understand the impacts of climate on survival, however, due to the fact that the non-linear relationship between survival and climate can be modified by density-dependent processes. In this study we extended the Brownie model to partition hunting and non-hunting mortalities and linked non-hunting survival to covariates. We applied this model to four decades (1972–2014) of waterfowl band-recovery, breeding population survey, and precipitation and temperature data covering multiple ecological regions to examine the non-linear, interactive effects of population density and climate on waterfowl non-hunting survival at a regional scale. Our results showed that the non-linear effect of temperature on waterfowl non-hunting survival was modified by breeding population density. The concave relationship between non-hunting survival and temperature suggested that the effects of warming on waterfowl survival might be multifaceted. Furthermore, the relationship between non-hunting survival and temperature was stronger when population density was higher, suggesting that high-density populations may be less buffered against warming than low-density populations. Our study revealed distinct relationships between waterfowl non-hunting survival and climate across and within ecological regions, highlighting the importance of considering different conservation strategies according to region-specific population and climate conditions. Our findings and associated novel modelling approach have wide implications in conservation practice.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2018.02.024","usgsCitation":"Zhao, Q., Boomer, G., and Kendall, W.L., 2018, The non-linear, interactive effects of population density and climate drive the geographical patterns of waterfowl survival: Biological Conservation, v. 221, p. 1-9, https://doi.org/10.1016/j.biocon.2018.02.024.","productDescription":"9 p.","startPage":"1","endPage":"9","ipdsId":"IP-091712","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":354197,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"221","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6c4e4b0da30c1bfbdf6","contributors":{"authors":[{"text":"Zhao, Qing","contributorId":174370,"corporation":false,"usgs":false,"family":"Zhao","given":"Qing","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":735451,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boomer, G. Scott","contributorId":84603,"corporation":false,"usgs":true,"family":"Boomer","given":"G. Scott","affiliations":[],"preferred":false,"id":735452,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kendall, William L. 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":204844,"corporation":false,"usgs":true,"family":"Kendall","given":"William","email":"","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":735184,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196821,"text":"70196821 - 2018 - Reduced arctic tundra productivity linked with landform and climate change interactions","interactions":[],"lastModifiedDate":"2018-05-03T13:48:20","indexId":"70196821","displayToPublicDate":"2018-05-01T00:00:00","publicationYear":"2018","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":"Reduced arctic tundra productivity linked with landform and climate change interactions","docAbstract":"Arctic tundra ecosystems have experienced unprecedented change associated with climate warming over recent decades. Across the Pan-Arctic, vegetation productivity and surface greenness have trended positively over the period of satellite observation. However, since 2011 these trends have slowed considerably, showing signs of browning in many regions. It is unclear what factors are driving this change and which regions/landforms will be most sensitive to future browning. Here we provide evidence linking decadal patterns in arctic greening and browning with regional climate change and local permafrost-driven landscape heterogeneity. We analyzed the spatial variability of decadal-scale trends in surface greenness across the Arctic Coastal Plain of northern Alaska (~60,000 km²) using the Landsat archive (1999–2014), in combination with novel 30 m classifications of polygonal tundra and regional watersheds, finding landscape heterogeneity and regional climate change to be the most important factors controlling historical greenness trends. Browning was linked to increased temperature and precipitation, with the exception of young landforms (developed following lake drainage), which will likely continue to green. Spatiotemporal model forecasting suggests carbon uptake potential to be reduced in response to warmer and/or wetter climatic conditions, potentially increasing the net loss of carbon to the atmosphere, at a greater degree than previously expected.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-018-20692-8","usgsCitation":"Lara, M.J., Nitze, I., Grosse, G., Martin, P., and McGuire, A.D., 2018, Reduced arctic tundra productivity linked with landform and climate change interactions: Scientific Reports, v. 8, Article 2345; 10 p., https://doi.org/10.1038/s41598-018-20692-8.","productDescription":"Article 2345; 10 p.","ipdsId":"IP-085871","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":468793,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-018-20692-8","text":"Publisher Index Page"},{"id":353942,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-05","publicationStatus":"PW","scienceBaseUri":"5afee6c4e4b0da30c1bfbe02","contributors":{"authors":[{"text":"Lara, Mark J.","contributorId":194640,"corporation":false,"usgs":false,"family":"Lara","given":"Mark","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":734605,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nitze, Ingmar","contributorId":191057,"corporation":false,"usgs":false,"family":"Nitze","given":"Ingmar","affiliations":[],"preferred":false,"id":734606,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grosse, Guido","contributorId":101475,"corporation":false,"usgs":true,"family":"Grosse","given":"Guido","affiliations":[{"id":34291,"text":"University of Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":734607,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martin, Philip","contributorId":204661,"corporation":false,"usgs":false,"family":"Martin","given":"Philip","affiliations":[{"id":27594,"text":"Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":734608,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McGuire, A. David 0000-0003-4646-0750 ffadm@usgs.gov","orcid":"https://orcid.org/0000-0003-4646-0750","contributorId":166708,"corporation":false,"usgs":true,"family":"McGuire","given":"A.","email":"ffadm@usgs.gov","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":734604,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}