A reconnaissance project completed in 2009 identified intersex and elevated plasma vitellogenin in male smallmouth bass inhabiting the Missisquoi River, VT. In an attempt to identify the presence and seasonality of putative endocrine disrupting chemicals or other factors associated with these observations, a comprehensive reevaluation was conducted between September 2012 and June 2014. Here, we collected smallmouth bass from three physically partitioned reaches along the river to measure biomarkers of estrogenic endocrine disruption in smallmouth bass. In addition, polar organic chemical integrative samples (POCIS) were deployed to identify specific chemicals associated with biological observations. We did not observe biological differences across reaches indicating the absence of clear point source contributions to the observation of intersex. Interestingly, intersex prevalence and severity decreased in a stepwise manner over the timespan of the project. Intersex decreased from 92.8% to 28.1%. The only significant predictor of intersex prevalence was year of capture, based on logistic regression analysis. The mixed model of fish length and year-of-capture best predicted intersex severity. Intersex severity was also significantly different across late summer and early spring collections indicating seasonal changes in this metric. Plasma vitellogenin and liver vitellogenin Aa transcript abundance in males did not indicate exposure to estrogenic endocrine disrupting chemicals at any of the four sample collections. Analysis of chemicals captured by the POCIS as well as results of screening discrete water samples or POCIS extracts did not indicate the contribution of appreciable estrogenic chemicals. It is possible that unreported changes in land-use activity have ameliorated the problem, and our observations indicate recovery. Regardless, this work clearly emphasizes that single, snap shot sampling for intersex may not yield representative data given that the manifestation of this condition within a population can change dramatically over time.
","language":"English","publisher":"Elsever","doi":"10.1016/j.scitotenv.2018.07.167","usgsCitation":"Iwanowicz, L.R., Pinkney, A., Guy, C., Major, A., Munney, K., Blazer, V., Alvarez, D., Walsh, H.L., Sperry, A.J., Sanders, L., and Smith, D., 2018, Temporal evaluation of estrogenic endocrine disruption markers in smallmouth bass (Micropterus dolomieu) reveals seasonal variability in intersex: Science of the Total Environment, v. 646, p. 245-256, https://doi.org/10.1016/j.scitotenv.2018.07.167.","productDescription":"12 p.","startPage":"245","endPage":"256","ipdsId":"IP-095285","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":359860,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Vermont","otherGeospatial":"Missisquoi River","volume":"646","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c064ee3e4b0815414cecb10","contributors":{"authors":[{"text":"Iwanowicz, Luke R. 0000-0002-1197-6178 liwanowicz@usgs.gov","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":190787,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke","email":"liwanowicz@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":752925,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pinkney, A.E.","contributorId":150385,"corporation":false,"usgs":false,"family":"Pinkney","given":"A.E.","affiliations":[{"id":6927,"text":"USFWS, National Wildlife Refuge System","active":true,"usgs":false}],"preferred":false,"id":752926,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guy, C.P.","contributorId":22983,"corporation":false,"usgs":true,"family":"Guy","given":"C.P.","email":"","affiliations":[],"preferred":false,"id":752927,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Major, A.M.","contributorId":150387,"corporation":false,"usgs":false,"family":"Major","given":"A.M.","email":"","affiliations":[{"id":6927,"text":"USFWS, National Wildlife Refuge System","active":true,"usgs":false}],"preferred":false,"id":752928,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Munney, K.","contributorId":150388,"corporation":false,"usgs":false,"family":"Munney","given":"K.","affiliations":[{"id":6927,"text":"USFWS, National Wildlife Refuge System","active":true,"usgs":false}],"preferred":false,"id":752929,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blazer, Vicki S. 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":150384,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":752930,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Alvarez, David 0000-0002-6918-2709 dalvarez@usgs.gov","orcid":"https://orcid.org/0000-0002-6918-2709","contributorId":150499,"corporation":false,"usgs":true,"family":"Alvarez","given":"David","email":"dalvarez@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":752931,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Walsh, Heather L. 0000-0001-6392-4604 hwalsh@usgs.gov","orcid":"https://orcid.org/0000-0001-6392-4604","contributorId":4696,"corporation":false,"usgs":true,"family":"Walsh","given":"Heather","email":"hwalsh@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":752932,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sperry, Adam J. 0000-0002-4815-3730 asperry@usgs.gov","orcid":"https://orcid.org/0000-0002-4815-3730","contributorId":5872,"corporation":false,"usgs":true,"family":"Sperry","given":"Adam","email":"asperry@usgs.gov","middleInitial":"J.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":752933,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Sanders, Lakyn R. lsanders@usgs.gov","contributorId":5714,"corporation":false,"usgs":true,"family":"Sanders","given":"Lakyn R.","email":"lsanders@usgs.gov","affiliations":[],"preferred":true,"id":752934,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Smith, D. R. 0000-0001-6074-9257","orcid":"https://orcid.org/0000-0001-6074-9257","contributorId":44108,"corporation":false,"usgs":true,"family":"Smith","given":"D. 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In addition to the traditional sources of errors that affect more permeable formations (e.g. sample selection, non-representative specimens, disturbance introduced during sample acquisition and preparation), tight rocks can be particularly prone to solid–fluid interactions and thus more sensitive to the methods, procedures and techniques used to measure permeability. To address this problem, it is desirable to collect, for a single material, measurements obtained by different methods and pore fluids. For that purpose, a benchmarking exercise involving 24 laboratories was organized for measuring and modelling the permeability of a single low-permeability material, the Grimsel granodiorite. The objectives of the benchmark were: (i) to compare the results for a given method, (ii) to compare the results between different methods, (iii) to analyse the accuracy of each method, (iv) to study the influence of experimental conditions (especially the nature of pore fluid), (v) to discuss the relevance of indirect methods and models and finally (vi) to suggest good practice for low-permeability measurements. To complement the data set of permeability measurements presented in a companion paper, we focus here on (i) quantitative analysis of microstructures and pore size distribution, (ii) permeability modelling and (iii) complementary measurements of permeability anisotropy and poroelastic parameters. Broad ion beam—scanning electron microscopy, micro-computerized tomography, mercury injection capillary pressure (MICP) and nuclear magnetic resonance (NMR) methods were used to characterize the microstructures and provided the input parameters for permeability modelling. Several models were used: (i) basic statistical models, (ii) 3-D pore network and effective medium models, (iii) percolation model using MICP data and (iv) free-fluid model using NMR data. The models were generally successful in predicting the actual range of measured permeability. Statistical models overestimate the permeability because they do not adequately account for the heterogeneity of the crack network. Pore network and effective medium models provide additional constraints on crack parameters such as aspect ratio, aperture, density and connectivity. MICP and advanced microscopy techniques are very useful tools providing important input data for permeability estimation. Permeability measured—orthogonal to foliation is lower that—parallel to foliation. Combining the experimental and modelling results provide a unique and rich data set.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/gji/ggy305","usgsCitation":"David, C., Wassermann, J., Amann, F., Klaver, J., Davy, C., Sarout, J., Esteban, L., Rutter, E., Hu, Q., Louis, L., Delage, P., Lockner, D.A., Selvadurai, A., Vanorio, T., Amann Hildenbrand, A., Meredith, P., Browning, J., Mitchell, T., Madonna, C., Billiotte, J., Reuschle, T., Lasseux, D., Fortin, J., Lenormand, R., Loggia, D., Nono, F., Boitnott, G., Jahns, E., M., F., Berthe, G., Braun, P., Gregoire, D., Perrier, L., Polito, P., Jannot, Y., Sommier, A., Krooss, B., Fink, R., and Clark, A., 2018, KG²B, a collaborative benchmarking exercise for estimating the permeability of the Grimsel granodiorite - Part 2: modeling, microstructures and complementary data: Geophysical Journal International, v. 215, no. 2, p. 825-843, https://doi.org/10.1093/gji/ggy305.","productDescription":"29 p.","startPage":"825","endPage":"843","ipdsId":"IP-093307","costCenters":[{"id":237,"text":"Earthquake Science 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immune function, and antioxidant capacity of sea otters (Enhydra lutris)","interactions":[],"lastModifiedDate":"2020-02-10T06:21:01","indexId":"70208432","displayToPublicDate":"2018-07-25T12:28:54","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Lactation and resource limitation affect stress responses, thyroid hormones, immune function, and antioxidant capacity of sea otters (Enhydra lutris)","docAbstract":"Lactation is the most energetically demanding stage of reproduction in female mammals. Increased energetic allocation toward current reproduction may result in fitness costs, although the mechanisms underlying these trade‐offs are not well understood. Trade‐offs during lactation may include reduced energetic allocation to cellular maintenance, immune response, and survival and may be influenced by resource limitation. As the smallest marine mammal, sea otters (Enhydra lutris) have the highest mass‐specific metabolic rate necessitating substantial energetic requirements for survival. To provide the increased energy needed for lactation, female sea otters significantly increase foraging effort, especially during late‐lactation. Caloric insufficiency during lactation is reflected in the high numbers of maternal deaths due to End‐Lactation Syndrome in the California subpopulation. We investigated the effects of lactation and resource limitation on maternal stress responses, metabolic regulation, immune function, and antioxidant capacity in two subspecies of wild sea otters (northern: E. l. nereis and southern: E. l. kenyoni) within the California, Washington, and Alaska subpopulations. Lactation and resource limitation were associated with reduced glucocorticoid responses to acute capture stress. Corticosterone release was lower in lactating otters. Cortisol release was lower under resource limitation and suppression during lactation was only evident under resource limitation. Lactation and resource limitation were associated with alterations in thyroid hormones. Immune responses and total antioxidant capacity were not reduced by lactation or resource limitation. Southern sea otters exhibited higher concentrations of antioxidants, immunoglobulins, and thyroid hormones than northern sea otters. These data provide evidence for allocation trade‐offs during reproduction and in response to nutrient limitation but suggest self‐maintenance of immune function and antioxidant defenses despite energetic constraints. Income‐breeding strategists may be especially vulnerable to the consequences of stress and modulation of thyroid function when food resources are insufficient to support successful reproduction and may come at a cost to survival, and thereby influence population trends.","language":"English","publisher":"Wiley","doi":"10.1002/ece3.4280","usgsCitation":"Chinn, S., Monson, D., Tinker, M., Staedler, M.M., and Crocker, D.E., 2018, Lactation and resource limitation affect stress responses, thyroid hormones, immune function, and antioxidant capacity of sea otters (Enhydra lutris): Ecology and Evolution, v. 8, no. 16, p. 8433-8447, https://doi.org/10.1002/ece3.4280.","productDescription":"15 p.","startPage":"8433","endPage":"8447","ipdsId":"IP-091093","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":468567,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.4280","text":"Publisher Index Page"},{"id":372171,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California 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\"}}]}","volume":"8","issue":"16","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Chinn, Sarah M.","contributorId":222316,"corporation":false,"usgs":false,"family":"Chinn","given":"Sarah M.","affiliations":[{"id":40519,"text":"Department of Biology, Sonoma State University","active":true,"usgs":false}],"preferred":false,"id":781859,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Monson, Daniel 0000-0002-4593-5673 dmonson@usgs.gov","orcid":"https://orcid.org/0000-0002-4593-5673","contributorId":196670,"corporation":false,"usgs":true,"family":"Monson","given":"Daniel","email":"dmonson@usgs.gov","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":781858,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tinker, M. Tim 0000-0002-3314-839X","orcid":"https://orcid.org/0000-0002-3314-839X","contributorId":214291,"corporation":false,"usgs":true,"family":"Tinker","given":"M. Tim","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":781862,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Staedler, Michelle M. 0000-0002-1101-6580","orcid":"https://orcid.org/0000-0002-1101-6580","contributorId":222317,"corporation":false,"usgs":true,"family":"Staedler","given":"Michelle","email":"","middleInitial":"M.","affiliations":[{"id":6953,"text":"Monterey Bay Aquarium","active":true,"usgs":false}],"preferred":true,"id":781860,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Crocker, Daniel E.","contributorId":222318,"corporation":false,"usgs":false,"family":"Crocker","given":"Daniel","email":"","middleInitial":"E.","affiliations":[{"id":40519,"text":"Department of Biology, Sonoma State University","active":true,"usgs":false}],"preferred":false,"id":781861,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70259590,"text":"70259590 - 2018 - Caldera life-cycles of the Yellowstone hotspot track: Death and rebirth of the Heise Caldera","interactions":[],"lastModifiedDate":"2024-10-16T12:13:23.196883","indexId":"70259590","displayToPublicDate":"2018-07-25T07:10:48","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2420,"text":"Journal of Petrology","active":true,"publicationSubtype":{"id":10}},"title":"Caldera life-cycles of the Yellowstone hotspot track: Death and rebirth of the Heise Caldera","docAbstract":"As one of the most geochemically unique drill cores recovered within the Yellowstone–Snake River Plain (YSRP) province, the Sugar City geothermal test well was drilled into intra-caldera rhyolite lavas and tuffs erupted during the middle to late Pliocene and the resurgent basaltic volcanism erupted during the Pleistocene. This sequence parallels the two main stages proposed for YSRP hotspot calderas: i.e. the eruption of several large-volume, ash-flow tuff sheets followed by caldera collapse, then cessation of major rhyolitic activity and gradual subsidence accompanied by filling and eventual burial of the caldera by basalt lava flows. We employ stratigraphic relationships, paleomagnetism, and major, trace element, and Sr–Nd isotope geochemistry to develop models for the origin of the basaltic and rhyolitic magmas within a geographical and temporal context. The basalts are characterized by distinct groupings based on depth and geochemistry and reflect the dominant compositions observed on the surface, e.g. Snake River olivine tholeiite (SROT) and evolved type (e.g. Craters of the Moon). We also observe contaminated basalts that interacted with rhyolite/granite. The basaltic magma formed by shallow partial melting in the plume channel carved into the lithosphere. The older rhyolites preserve the classical characteristics of A-type granites and display major element and trace element concentrations typical for Eastern SRP caldera centres and minimal stratigraphic variation. Multiple lines of evidence document extensive magmatic differentiation and coupled basalt–rhyolite interactions. We find that the most plausible origin for the rhyolites is via partial melting of a hybrid source, comprising Archean crustal components and younger juvenile mafic intrusions. Assimilation of hydrothermally altered material is also required for some eruptive units. The rhyolites did not evolve from residual magma left over from the climactic Kilgore eruption (4·0 Ma), but instead represent discrete magma generation events in the course of a few hundred thousand years between 4·0 to 3·8 Ma. Beginning at approximately 3.3 Ma, basalts were able to erupt through the solidified composite pluton that formed below the caldera. The transition from rhyolite to basalt is tied to the declining flux of basaltic magma as North America moved away from the Yellowstone hotspot core.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/petrology/egy074","usgsCitation":"Jean, M.M., Christiansen, E.H., Champion, D.E., Vetter, S.K., Phillips, W.M., Schuth, S., and Shervais, J., 2018, Caldera life-cycles of the Yellowstone hotspot track: Death and rebirth of the Heise Caldera: Journal of Petrology, v. 59, no. 8, p. 1643-1670, https://doi.org/10.1093/petrology/egy074.","productDescription":"28 p.","startPage":"1643","endPage":"1670","ipdsId":"IP-101148","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":468568,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/petrology/egy074","text":"Publisher Index Page"},{"id":462907,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"59","issue":"8","noUsgsAuthors":false,"publicationDate":"2018-07-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Jean, Marlon M.","contributorId":296059,"corporation":false,"usgs":false,"family":"Jean","given":"Marlon","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":915835,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Christiansen, Eric H.","contributorId":206801,"corporation":false,"usgs":false,"family":"Christiansen","given":"Eric","email":"","middleInitial":"H.","affiliations":[{"id":6681,"text":"Brigham Young University","active":true,"usgs":false}],"preferred":false,"id":915836,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Champion, Duane E. 0000-0001-7854-9034","orcid":"https://orcid.org/0000-0001-7854-9034","contributorId":345150,"corporation":false,"usgs":true,"family":"Champion","given":"Duane","email":"","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":915837,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vetter, Scott K.","contributorId":345151,"corporation":false,"usgs":false,"family":"Vetter","given":"Scott","email":"","middleInitial":"K.","affiliations":[{"id":82501,"text":"Centenary College","active":true,"usgs":false}],"preferred":false,"id":915838,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Phillips, William M.","contributorId":9690,"corporation":false,"usgs":true,"family":"Phillips","given":"William","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":915839,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schuth, Stephan","contributorId":345153,"corporation":false,"usgs":false,"family":"Schuth","given":"Stephan","email":"","affiliations":[{"id":64319,"text":"Leibniz University","active":true,"usgs":false}],"preferred":false,"id":915840,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shervais, John W.","contributorId":237914,"corporation":false,"usgs":false,"family":"Shervais","given":"John W.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":915841,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70198172,"text":"sir20185073 - 2018 - Geochemistry and microbiology of groundwater and solids from extraction and monitoring wells and their relation to well efficiency at a Federally operated confined disposal facility, East Chicago, Indiana","interactions":[],"lastModifiedDate":"2018-07-24T12:44:39","indexId":"sir20185073","displayToPublicDate":"2018-07-24T11:00:00","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":"2018-5073","title":"Geochemistry and microbiology of groundwater and solids from extraction and monitoring wells and their relation to well efficiency at a Federally operated confined disposal facility, East Chicago, Indiana","docAbstract":"In cooperation with the U.S. Army Corps of Engineers, Chicago District, the U.S. Geological Survey investigated the processes affecting water quality, geochemistry, and microbiology in representative extraction and monitoring wells at a confined disposal facility (CDF) in East Chicago, Indiana. The CDF is a 140-acre Federally-managed facility that was the former location of an oil refinery and is now used for the long-term disposal and storage of dredge material from the Indiana Harbor and Indiana Harbor Canal. Residual petroleum hydrocarbons and leachate from the CDF are contained within the facility by use of a groundwater cutoff wall. The wall consists of a soil-bentonite slurry and a gradient control system made up of an automated network of 96 extraction wells, 42 monitoring wells, and 2 ultrasonic sensors that maintain an inward hydraulic gradient at the site. The pumps in the extraction wells require vigilant maintenance and must be replaced when unable to withdraw water at a rate sufficient to maintain the required inward gradient. The wells are screened in the Calumet aquifer, a coarse-grained sand and gravel unit that extends approximately 35 feet below the land surface and is not utilized for drinking-water supply at the CDF or in the surrounding area. This study was initiated to identify the cause of decreased pump discharges and to identify potential mitigation strategies.
For this study, the U.S. Geological Survey collected groundwater and solids from monitoring and extraction wells. Groundwater samples were collected during June 2014 for precautionary health screening and on four occasions during September 2014 through November 2014. Groundwater samples collected from two extraction wells during June 2014 were analyzed for concentrations of anthropogenic organic constituents. During September through November 2014, groundwater samples were collected from one additional extraction well, and samples from three monitoring wells were analyzed for concentrations of inorganic and organic constituents, dissolved gases, and bacterial abundance and diversity. Solid samples were collected during April 2014, during September 2014 through November 2014, and during November 2016. Solid samples were collected from the exterior of extraction-well pumps and as flocculent from water samples. Solid samples were collected from 10 wells, including 1 extraction well and 3 monitoring wells sampled for water quality. Solid samples were analyzed for mineralogy, solid-phase habit, geochemistry, and organic composition.
The following is a list of observations that were made during this study: (1) the water quality is substantially variable among the six well locations sampled as part of this study—lower (more negative) redox values and higher concentrations of many constituents (including calcium, magnesium, sodium, and sulfate) and properties (including dissolved solids, hardness, and turbidity) were detected in sampled wells located near the extraction wells with the highest frequency of failure; (2) water-level drawdown is variable between extraction wells—wells with the greatest drawdown may pull deeper groundwater into the borehole; (3) dissolved gas results indicate reducing oxidation-reduction processes in the aquifer material that can feasibly contribute iron, carbon dioxide, and other byproducts from hydrocarbon degradation to precipitates and solids that accumulate on and impair pump operation; (4) crystalline and amorphous solid-phase minerals are precipitating in the borehole; (5) several types of bacteria are present in water pumped from extraction wells and are likely responsible for bonding mineral and microbiologic matter to the pump (and other well components); and (6) bacteria may create microenvironments that facilitate precipitation of solids or inhibit dissolution of unstable minerals once the bacteria adhere to biofilm attached to the pump. Results of the study indicate that bacteria may be accumulating and entrapping solid material on the exterior of pumps. This accumulation reduces heat transfer and water discharge from the pump and may lead to decreased efficiency or mechanical failure. Observations could not be made on the well screen, gravel pack, or surrounding geologic formation; therefore, mitigating measures in the borehole may not solve well-productivity issues.
Remedies for the pump fouling problems were derived from the review and interpretation of data collected during this study and from information documented in other sources about groundwater well fouling. Potential remedies to problems associated with pump fouling at the CDF may include the following: (1) reducing attractiveness of the extraction wells for microbiological growth by modifying the chemical or physical environment of the well, (2) modifying the pump exterior to decrease microbiological adherence, (3) changing the pumping regime to control the chemistry of water entering the well from the surrounding aquifer material, (4) modifying the pumps to be less physically and thermally attractive, and (5) removing hydrocarbons from groundwater and the aquifer material surrounding the wells or adding surfactants to make them more mobile. Pilot scale testing may be necessary to identify the most effective treatment or combination of treatments.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185073","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Bayless, E.R., Cole, T.R., Lampe, D.C., Travis, R.E., Schulz, M.S, and Buszka, P.M., 2018, Geochemistry and microbiology of groundwater and solids from extraction and monitoring wells and their relation to well efficiency at a Federally operated confined disposal facility, East Chicago, Indiana: U.S. Geological Survey Scientific Investigations Report 2018–5073, 134 p., https://doi.org/10.3133/sir20185073.","productDescription":"Report: xi, 134 p.","numberOfPages":"150","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-077148","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":355818,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5073/coverthb.jpg"},{"id":355819,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5073/sir20185073.pdf","text":"Report","size":"20.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5073"},{"id":355825,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/5b1feed8e4b092d96525b0a2","text":"USGS data release","description":"USGS data release","linkHelpText":"X-ray diffraction trace analysis of solid phase samples collected from groundwater wells at a confined disposal facility in East Chicago, Indiana"}],"country":"United States","state":"Indiana","city":"East Chicago","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.52395629882812,\n 41.59105362325491\n ],\n [\n -87.32585906982422,\n 41.59105362325491\n ],\n [\n -87.32585906982422,\n 41.71444263601197\n ],\n [\n -87.52395629882812,\n 41.71444263601197\n ],\n [\n -87.52395629882812,\n 41.59105362325491\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
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5957 Lakeside Boulevard
Indianapolis, IN 46278
Ground‐motion prediction equations (GMPEs) are critical elements of probabilistic seismic hazard analysis (PSHA), as well as for other applications of ground motions. To isolate the path component for the purpose of building nonergodic GMPEs, we compute a regional GMPE using a large dataset of peak ground accelerations (PGAs) from small‐magnitude earthquakes (0.5 ≤ M ≤ 4.5 with > 10,000 events, yielding ∼120,000 recordings) that occurred in 2013 centered around the ANZA seismic network (hypocentral distances ≤180 km) in southern California. We examine two separate methods of obtaining residuals from the observed and predicted ground motions: a pooled ordinary least‐squares model and a mixed‐effects maximum‐likelihood model. Whereas the former is often used by the broader seismological community, the latter is widely used by the ground‐motion and engineering seismology community. We confirm that mixed‐effects models are the preferred and most statistically robust method to obtain event, path, and site residuals and discuss the reasoning behind this. Our results show that these methods yield different consequences for the uncertainty of the residuals, particularly for the event residuals. Finally, our results show no correlation (correlation coefficient [CC] <0.03) between site residuals and the classic site‐characterization term VS30, the time‐averaged shear‐wave velocity in the top 30 m at a site. We propose that this is due to the relative homogeneity of the site response in the region and perhaps due to shortcomings in the formulation of VS30 and suggest applying the provided PGA site correction terms to future ground‐motion studies for increased accuracy.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120170376","usgsCitation":"Sahakian, V.J., Baltay Sundstrom, A.S., Hanks, T.C., Buehler, J., Vernon, F.L., and Kilb, D.L., 2018, Decomposing leftovers: Event, path, and site residuals for a small magnitude ANZA region GMPE: Bulletin of the Seismological Society of America, v. 108, no. 5A, p. 2478-2492, https://doi.org/10.1785/0120170376.","startPage":"2478","endPage":"2492","ipdsId":"IP-092976","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482280,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118,\n 34.5\n ],\n [\n -118,\n 32.5\n ],\n [\n -115.45,\n 32.5\n ],\n [\n -115.45,\n 34.5\n ],\n [\n -118,\n 34.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"108","issue":"5A","noUsgsAuthors":false,"publicationDate":"2018-07-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Sahakian, Valerie Jean 0000-0002-3278-4458","orcid":"https://orcid.org/0000-0002-3278-4458","contributorId":296738,"corporation":false,"usgs":true,"family":"Sahakian","given":"Valerie","email":"","middleInitial":"Jean","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927864,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baltay, Annemarie S. 0000-0002-6514-852X abaltay@usgs.gov","orcid":"https://orcid.org/0000-0002-6514-852X","contributorId":4932,"corporation":false,"usgs":true,"family":"Baltay","given":"Annemarie","email":"abaltay@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":927865,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hanks, Thomas C. 0000-0003-0928-0056 thanks@usgs.gov","orcid":"https://orcid.org/0000-0003-0928-0056","contributorId":3065,"corporation":false,"usgs":true,"family":"Hanks","given":"Thomas","email":"thanks@usgs.gov","middleInitial":"C.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927866,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Buehler, Janine S.","contributorId":351082,"corporation":false,"usgs":false,"family":"Buehler","given":"Janine S.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":927867,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vernon, Frank L. 0000-0002-9379-4000","orcid":"https://orcid.org/0000-0002-9379-4000","contributorId":333114,"corporation":false,"usgs":false,"family":"Vernon","given":"Frank","email":"","middleInitial":"L.","affiliations":[{"id":79734,"text":"Institute of Geophysics and Planetary Science, University of California at San Diego","active":true,"usgs":false}],"preferred":false,"id":927868,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kilb, Deborah L.","contributorId":216380,"corporation":false,"usgs":false,"family":"Kilb","given":"Deborah","email":"","middleInitial":"L.","affiliations":[{"id":37799,"text":"SCRIPPS","active":true,"usgs":false}],"preferred":false,"id":927869,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70277008,"text":"70277008 - 2018 - Review: Past and future fault rupture lengths in seismic source characterization—The long and short of it","interactions":[],"lastModifiedDate":"2026-07-02T14:53:04.326607","indexId":"70277008","displayToPublicDate":"2018-07-24T09:47:31","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Review: Past and future fault rupture lengths in seismic source characterization—The long and short of it","docAbstract":"The potential rupture length of an active fault is primary input, and an uncertainty, in source characterization for seismic hazard analysis. The past several decades have seen source models in which faults are divided into potential rupture segments based on fault‐specific behavioral and geometric observations. These models (prescribed segmentation) produced single and multisegment ruptures for use in earthquake probability and regional ground‐motion estimates. The 2013 Uniform California Earthquake Rupture Forecast, Version 3 (UCERF3), relaxed segmentation through modeling of fault‐to‐fault jumps that result in ruptures along the San Andreas fault system as long as 1200 km. Principle controls of UCERF3 rupture length are the stepover distance between different faults or fault sections, and their orientation relative to modeled coulomb stress changes. Observations of surface faulting worldwide since the mid‐1800s in shallow continental crust show that only 30 of the reported ruptures, about 12% of the reported examples, have been longer than 100 km; only 6 have been longer than 300 km and none has exceeded 500 km. A review of characteristics of long ruptures shows that, in general, they occur along essentially continuous traces with limited stepping or branching from one fault to another as opposed to rupture propagation on linkages of different faults with highly variable physical characteristics. These commonly occupy from 10% to 70% of the total host fault length. Neither segmented nor relaxed models of rupture length have been tested by the occurrence of actual ruptures. There is no reason why segmentation models incorporating timing, dynamic, and rheological factors cannot provide reasonable approximations of future rupture length. For many faults of concern worldwide, this may be the most effective approach.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120160110","usgsCitation":"Schwartz, D.P., 2018, Review: Past and future fault rupture lengths in seismic source characterization—The long and short of it: Bulletin of the Seismological Society of America, v. 108, no. 5A, p. 2493-2520, https://doi.org/10.1785/0120160110.","productDescription":"28 p.","startPage":"2493","endPage":"2520","ipdsId":"IP-065016","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":506443,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.7989001,\n 36.2752757\n ],\n [\n -120.5908258,\n 34.6040264\n ],\n [\n -116.8526336,\n 32.5340778\n ],\n [\n -114.5504543,\n 32.8027103\n ],\n [\n -114.755599,\n 34.7165193\n ],\n [\n -119.7474532,\n 38.4311694\n ],\n [\n -121.7989001,\n 36.2752757\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"108","issue":"5A","noUsgsAuthors":false,"publicationDate":"2018-07-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Schwartz, David P. 0000-0001-5193-9200","orcid":"https://orcid.org/0000-0001-5193-9200","contributorId":372917,"corporation":false,"usgs":false,"family":"Schwartz","given":"David","middleInitial":"P.","affiliations":[{"id":88467,"text":"Formerly with the Earthquake Science Center","active":true,"usgs":false}],"preferred":false,"id":963875,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70197779,"text":"sir20185072 - 2018 - Refinement of a regression-based method for prediction of flow-duration curves of daily streamflow in the conterminous United States","interactions":[],"lastModifiedDate":"2018-07-24T10:32:22","indexId":"sir20185072","displayToPublicDate":"2018-07-23T00:00:00","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":"2018-5072","title":"Refinement of a regression-based method for prediction of flow-duration curves of daily streamflow in the conterminous United States","docAbstract":"Regional regression is a common tool used to estimate daily flow-duration curves (FDCs) at ungaged locations. In this report, several refinements to a particular implementation of the regional regression method for estimating FDCs are evaluated by consideration of different methodological options through a leave-one-out cross-validation procedure in the 19 major river basins of the conterminous United States. Regression analyses in this report are based on streamflow data from water years 1981–2013 (October 1, 1980 to September 30, 2013) from 1,378 mostly undisturbed watersheds. Linear regression using selected basin characteristics at 27 quantiles with nonexceedance probabilities ranging from 0.02 to 99.98 percent was applied. The regression computations were primarily by weighted least squares, with left-censored Gaussian regression solved by maximum likelihood in the presence of zero-valued quantiles.
The regional regression method as applied to the FDC estimation problem includes several methodological options that require determination of the better of two or more choices. The options considered in this report include (1) the setting of the maximum number of basin characteristics considered in the regression models for each region, (2) the method of placing the quantiles into groups (“flow regimes”) having the same basin characteristics used as independent variables, (3) the maximum number of candidate models retained from regressions at the single-quantile level that are retained for testing of the best model at the flow-regime scale, and (4) whether drainage area should be forced into the models. In all, 5 binary options were considered for most regions, resulting in 32 methodological combinations. Leave-one-out cross-validation predictions of FDC quantiles at each streamgage used in the study were used to evaluate compared options. Various performance measures were computed based on the predicted quantiles; these were combined by region and the methods were ranked for each measure.
Based on examination of the ranked methods compared across the measures, the following treatments produced the more accurate results: (1) using fewer basin characteristics (of the two options considered), (2) utilizing a variance of the unit FDC-based method of determining the flow regimes rather than fixed regimes, (3) retaining more models from the quantile-level regressions regime-wide consideration, and (4) forcing drainage area into the regression models. Results of analyses also indicate that performance varies more by region than by methodological option, with FDCs in arid regions and those with a large value of a measure of intraregional FDC heterogeneity being harder to predict, particularly with respect to the low-flow quantiles.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185072","collaboration":"Water Availability and Use Science Program","usgsCitation":"Over, T.M., Farmer, W.H., and Russell, A.M., 2018, Refinement of a regression-based method for prediction of flow-duration curves of daily streamflow in the conterminous United States: U.S. Geological Survey Scientific Investigations Report 2018–5072, 34 p., https://doi.org/10.3133/sir20185072.","productDescription":"Report: vi, 34 p.; Appendixes 1–3; Data Release","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-085859","costCenters":[{"id":344,"text":"Illinois Water Science 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\"}}]}\n\n\n","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
405 N. Goodwin Ave.
Urbana, Illinois 61801
Deep-sea corals can create a highly complex, three-dimensional structure that facilitates sediment accumulation and influences adjacent sediment environments through altered hydrodynamic regimes. Infaunal communities adjacent to different coral types, including reef-building scleractinian corals and individual colonies of octocorals, are known to exhibit higher macrofaunal densities and distinct community structure when compared to non-coral soft-sediment communities. However, the coral types have different morphologies, which may modify the adjacent sediment communities in discrete ways. Here we address: (1) how infaunal communities and their associated sediment geochemistry compare among deep-sea coral types (Lophelia pertusa, Madrepora oculata, and octocorals) and (2) do infaunal communities adjacent to coral habitats exhibit typical regional and depth-related patterns observed in the Gulf of Mexico (GOM). Sediment push cores were collected to assess diversity, composition, numerical abundance, and functional traits of macrofauna (>300 µm) across 450 kilometers in the GOM at depths ranging from 263–1,095 m. Macrofaunal density was highest in L. pertusa habitats, but similar between M. oculata and octocorals habitats. Density overall exhibited a unimodal relationship with depth, with maximum densities between 600 and 800 m. Diversity and evenness were highest in octocoral habitats; however, there was no relationship between diversity and depth. Infaunal assemblages and functional traits differed among coral habitats, with L. pertusa habitats the most distinct from both M. oculata and octocorals. These patterns could relate to differences in sediment geochemistry as L. pertusa habitats contained high organic carbon content but low proportions of mud compared to both M. oculata and octocoral habitats. Distance-based linear modeling revealed depth, mud content, and organic carbon as the primary factors in driving coral infaunal community structure, while geographic location (longitude) was the primary factor in functional trait composition, highlighting both the location and ecological differences of L. pertusa habitats from other coral habitats. Enhanced habitat structural complexity associated with L. pertusa and differences in localized hydrodynamic flow may contribute to the dissimilarities in the communities found among the coral types. Our results suggest a decoupling for infaunal coral communities from the typical depth-related density and diversity patterns present throughout soft-sediment habitats in the GOM, highlighting the importance of deep-sea corals in structuring unique communities in the nearby benthos.
","language":"English","publisher":"PeerJ","doi":"10.7717/peerj.5276","usgsCitation":"Bourque, J.R., and Demopoulos, A.W., 2018, The influence of different deep-sea coral habitats on sediment macrofaunal community structure and function: PeerJ, v. 6, p. 1-32, https://doi.org/10.7717/peerj.5276.","productDescription":"e5276; 32 p.","startPage":"1","endPage":"32","ipdsId":"IP-094605","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":468571,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.5276","text":"Publisher Index Page"},{"id":437820,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TH8KXD","text":"USGS data release","linkHelpText":"Sediment macrofaunal composition, sediment grain size, and taxa functional traits of multiple deep-sea coral habitats in the Gulf of Mexico, 2009-2014"},{"id":356203,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gulf of Mexico","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 27\n ],\n [\n -87.5,\n 27\n ],\n [\n -87.5,\n 30\n ],\n [\n -90.5,\n 30\n ],\n [\n -90.5,\n 27\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-20","publicationStatus":"PW","scienceBaseUri":"5b6fc3f5e4b0f5d57878e97f","contributors":{"authors":[{"text":"Bourque, Jill R. 0000-0003-3809-2601 jbourque@usgs.gov","orcid":"https://orcid.org/0000-0003-3809-2601","contributorId":5452,"corporation":false,"usgs":true,"family":"Bourque","given":"Jill","email":"jbourque@usgs.gov","middleInitial":"R.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":741401,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Demopoulos, Amanda W.J. 0000-0003-2096-4694 ademopoulos@usgs.gov","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":196216,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","email":"ademopoulos@usgs.gov","middleInitial":"W.J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":741402,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70197289,"text":"sir20185065 - 2018 - Prioritization of oil and gas fields for regional groundwater monitoring based on a preliminary assessment of petroleum resource development and proximity to California’s groundwater resources","interactions":[],"lastModifiedDate":"2021-07-23T16:32:31.463125","indexId":"sir20185065","displayToPublicDate":"2018-07-20T00:00:00","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":"2018-5065","title":"Prioritization of oil and gas fields for regional groundwater monitoring based on a preliminary assessment of petroleum resource development and proximity to California’s groundwater resources","docAbstract":"The California State Water Resources Control Board initiated a regional monitoring program in July 2015 to determine where and to what degree groundwater quality may be adversely impacted by oil and gas development activities. A key issue in the implementation of the regional groundwater monitoring program is that each year, detailed characterization work can be done in only a few of California’s 487 onshore oil and gas fields. The first step in monitoring groundwater near petroleum development is to prioritize oil and gas fields using consistent statewide analysis of available data that indicate potential risk of groundwater to oil and gas development.
The U.S. Geological Survey compiled data for four factors that characterize the intensity of petroleum resource development and proximity to groundwater resources: petroleum-well density, volume of water injected in oil fields, vertical proximity of groundwater resources to oil and gas resource development, and water-well density. An overall priority ranking for each field was determined by computing summary metrics, analyzing statewide distributions of summary metrics for all oil and gas fields, using those distributions to define relative categories of potential risk for each factor, and combining relative risk rankings for different factors into an overall priority ranking. This preliminary assessment does not represent an evaluation of groundwater risk to oil and gas development, which needs to be based on detailed analysis and data related to development activities including well stimulation, well integrity issues, produced water ponds, and underground injection.
Based on the prioritization analysis, 22 percent (107 fields) of the total number of oil and gas fields in California were ranked as high priority, 23 percent (114 fields) as moderate priority, and 55 percent (266 fields) as low priority. These results indicate that between 100 and 200 oil fields are principal candidates for the next steps in the regional monitoring program. The land area of fields that ranked high priority accounted for 41 percent of the total field area (3,392 square miles). More than half of the high priority fields were in the southern San Joaquin Valley and the Los Angeles Basin. Some of the larger fields tended to have higher rankings because of greater intensity of petroleum development, sometimes coupled with proximity to groundwater resources.
The U.S. Geological Survey, in collaboration with the California State Water Resources Control Board and other agencies, has begun regional groundwater monitoring near oil and gas fields selected for study through the California Oil, Gas, and Groundwater cooperative program. Groundwater monitoring includes compiling, analyzing, and developing three-dimensional visualizations of existing data, including geological frameworks, salinity mapping, identification of surface features that could potentially affect groundwater quality, locations and depths of oil/gas and water wells, cataloging well-construction integrity issues, and evaluating the directions of groundwater flow. These analyses are required to determine where existing wells should be monitored and where new monitoring wells may need to be drilled.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185065","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Davis, T.A., Landon, M.K., and Bennett, G.L., 2018, Prioritization of oil and gas fields for regional groundwater monitoring based on a preliminary assessment of petroleum resource development and proximity to California’s groundwater resources: U.S. Geological Survey Scientific Investigations Report 2018–5065, 115 p.,\nhttps://doi.org/10.3133/sir20185065.","productDescription":"Report: viii, 115 p.; Tables 1-6; Appendix Tables 1-7","numberOfPages":"128","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-073272","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":437823,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7FJ2DV3","text":"USGS data release","linkHelpText":"Data analyzed for the preliminary prioritization of California oil and gas fields for regional groundwater monitoring"},{"id":355611,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2018/5065/sir20185065_appendixtables_.xlsx","text":"Appendix Tables 1–7","size":"500 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2018-5065"},{"id":355610,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2018/5065/sir20185065_tables_.xlsx","text":"Tables 1–6","size":"23 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2018-5065"},{"id":355609,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5065/sir20185065.pdf","text":"Report","size":"62 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5065"},{"id":355608,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5065/coverthb.jpg"}],"country":"United 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\"}}]}","contact":"The giant gartersnake (Thamnophis gigas) is a semi-aquatic species of snake precinctive to the Central Valley of California. Because the Central Valley has experienced a substantial loss of wetland habitat, giant gartersnake populations are largely found in aquatic habitats associated with rice agriculture. In dry years, less water may be available for rice agriculture, resulting in less aquatic habitat, which could have cascading effects on giant gartersnake populations. We present 2 years of data intended to examine how the demography of giant gartersnakes is affected by the availability of aquatic habitat on the landscape (2016–17), along with 2 years of (sparse) preliminary data (2014–15) collected as part of an earlier radio-telemetry study on giant gartersnake movement behavior. We sampled agricultural canals near rice fields for giant gartersnakes at 8 sites distributed throughout the Sacramento Valley. Five sites were sampled from 2014–17, and 3 sites were sampled from 2015–17. In total, we made 2,995 captures of 1,011 snakes from 2014–17. We used these capture data to fit a multi-site Jolly-Seber model to estimate the abundance of giant gartersnakes as well as the daily and annual probability of capture at each site. We used remotely sensed Landsat data to characterize the extent of flooded rice fields surrounding each site in each year. In addition, we collected 175 females from 2014–17 and delivered them to the Sacramento Zoo for health assessments and reproductive exams.
The abundance of giant gartersnakes varied among sites, and abundance estimates were more precise in 2016 and 2017 when sampling effort was greatest. The probability of a giant gartersnake being captured at least once in a year was higher in 2016 and 2017 than 2014 and 2015, and recaptures of snakes marked the previous year were highest in 2016 and 2017 as well. Mean annual apparent survival was estimated to be 0.40 but varied among sites from a low of 0.14 to a high of 0.63. Five sites had diverse size distributions that included abundant sub-adult and large adult female snakes. One site had a truncated size distribution with few large adult female snakes, and 2 sites had mostly large adult-sized snakes and few small individuals. Both the probability a female was gravid and a female’s litter size were positively related to the female’s snout-vent length. Somatic growth rates varied more among years than among sites, and females grew faster (in millimeters per day) than male snakes.
The proportion of the landscape around each site under active rice cultivation fluctuated over time (generally between 60–90 percent of the landscape was active rice growing, although this proportion was lower for some sites in some years), and variation in rice growing was asynchronous among sites. This study demonstrates that intensive demographic sampling enables estimation of several key demographic variables at each study site. Continued sampling would allow for investigating potential relationships between the amount of rice growing at a site and demographic parameters such as growth, survival, and reproduction.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181114","collaboration":"Prepared in cooperation with the California Department of Water Resources","usgsCitation":"Rose, J.P., Ersan, J.S.M., Reyes, G.A., Gustafson, K.B., Fulton, A.M., Fouts, K.J., Wack, R.F., Wylie, G.D., Casazza, M.L., and Halstead, B.J., 2018, Findings from a preliminary investigation of the effects of aquatic habitat (water) availability on giant gartersnake (Thamnophis gigas) demography in the Sacramento Valley, California, 2014–17: U.S. Geological Survey Open-File Report 2018–1114, 48 p., https://doi.org/10.3133/ofr20181114.","productDescription":"vi, 48 p.","numberOfPages":"58","onlineOnly":"Y","ipdsId":"IP-097068","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":355890,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1114/coverthb.jpg"},{"id":355891,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1114/ofr20181114.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1114"}],"country":"United States","state":"California","otherGeospatial":"Sacramento Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.33,\n 38.8333\n ],\n [\n -121.5833,\n 38.8333\n ],\n [\n -121.5833,\n 39.6667\n ],\n [\n -122.33,\n 39.6667\n ],\n [\n -122.33,\n 38.8333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Maps of extreme value, horizontal component geoelectric field amplitude are constructed for the Pacific Northwest United States (and parts of neighboring Canada). Multidecade long geoelectric field time series are calculated by convolving Earth surface impedance tensors from 71 discrete magnetotelluric survey sites across the region with historical 1‐min (2‐min Nyquist) geomagnetic variation time series obtained from two nearby observatories. After fitting statistical models to 1‐min geoelectric amplitudes realized during magnetic storms, extrapolations are made to estimate threshold amplitudes that are only exceeded, on average, once per century. One hundred‐year geoelectric exceedance amplitudes range from 0.06 V/km at a survey site in western Washington State to 9.47 V/km at a site in southeast British Columbia; 100‐year geoelectric exceedance amplitudes equal 7.10 V/km at a site north of Seattle and 2.28 V/km at a site north of Portland. Systematic and random errors are estimated to be less than 20%, much less than site‐to‐site differences in geoelectric amplitude that arise from site‐to‐site differences in surface impedance. Maps of 100‐year exceedance amplitudes are compared with the peak geoelectric amplitudes realized during the March 1989 magnetic superstorm; it is noted that some storms of relatively modest intensity can generate localized geoelectric fields of relatively high amplitude. The geography of geoelectric hazard across the Pacific Northwest is closely related to known geologic and tectonic structures.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018SW001844","usgsCitation":"Love, J.J., Lucas, G.M., Kelbert, A., and Bedrosian, P.A., 2018, Geoelectric hazard maps for the Pacific Northwest: Space Weather, v. 16, no. 8, p. 1114-1127, https://doi.org/10.1029/2018SW001844.","productDescription":"13 p.","startPage":"1114","endPage":"1127","ipdsId":"IP-097864 ","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":468573,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018sw001844","text":"Publisher Index Page"},{"id":359152,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States, Canada","otherGeospatial":"Pacific Northwest","volume":"16","issue":"8","noUsgsAuthors":false,"publicationDate":"2018-08-29","publicationStatus":"PW","scienceBaseUri":"5be16511e4b0b3fc5cf3ffbc","contributors":{"authors":[{"text":"Love, Jeffrey J. 0000-0002-3324-0348 jlove@usgs.gov","orcid":"https://orcid.org/0000-0002-3324-0348","contributorId":760,"corporation":false,"usgs":true,"family":"Love","given":"Jeffrey","email":"jlove@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":750774,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lucas, Greg M. 0000-0003-1331-1863","orcid":"https://orcid.org/0000-0003-1331-1863","contributorId":202808,"corporation":false,"usgs":true,"family":"Lucas","given":"Greg","email":"","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":750775,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelbert, Anna 0000-0003-4395-398X akelbert@usgs.gov","orcid":"https://orcid.org/0000-0003-4395-398X","contributorId":184053,"corporation":false,"usgs":true,"family":"Kelbert","given":"Anna","email":"akelbert@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":750776,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":750777,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70198122,"text":"ofr20181101 - 2018 - Modeling managed flows in the Sacramento/San Joaquin watershed, California, under scenarios of future change for CASCaDE2","interactions":[],"lastModifiedDate":"2018-07-19T16:33:05","indexId":"ofr20181101","displayToPublicDate":"2018-07-19T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1101","title":"Modeling managed flows in the Sacramento/San Joaquin watershed, California, under scenarios of future change for CASCaDE2","docAbstract":"Projections of managed flows from the Sacramento River/San Joaquin River watershed, California, into the San Francisco Bay and Sacramento-San Joaquin Delta under scenarios of future climate change are needed for evaluations of potential impacts on water supply and estuarine ecosystems. A new, multiple-model approach for achieving this is described. First, downscaled global climate model outputs are used to drive an existing Variable Infiltration Capacity/Variable Infiltration Capacity Routing (VIC/RVIC) model of Sacramento/San Joaquin hydrology, resulting in projections of daily, unimpaired flows throughout the watershed. A management model, Computational Assessments of Scenarios of Change for the Delta Ecosystem phase 2 (CASCaDE2) modified CalSim (C2-CalSim), uses these projections as inputs and produces monthly estimates of reservoir and other infrastructure operations and resulting downstream managed flows. A historical resampling algorithm, CASCaDE2 resampling algorithm (CRESPI), also uses the projected daily unimpaired flows, along with historical managed flows, to estimate the daily variability in managed flows throughout the watershed. The monthly and daily managed-flow estimates are combined in a way that preserves the multi-decadal variability and century-scale trends produced by the C2-CalSim model and the day-to-day variability produced by the CRESPI algorithm. The performance of the new modeling approach is evaluated at major inflows to the Bay-Delta estuary using multiple metrics and found to be satisfactory for the purposes of future scenario evaluation.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181101","usgsCitation":"Knowles, Noah, and Cronkite-Ratcliff, Collin, 2018, Modeling managed flows in the Sacramento/San Joaquin watershed, California, under scenarios of future change for CASCaDE2: U.S. Geological Survey Open-File Report 2018–1101, 38 p., https://doi.org/10.3133/ofr20181101.","productDescription":"vi, 38 p.","numberOfPages":"45","onlineOnly":"Y","ipdsId":"IP-079699","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":355844,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1101/coverthb.jpg"},{"id":355845,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1101/ofr20181101.pdf","text":"Report","size":"1.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1101"}],"country":"United States","state":"California","otherGeospatial":"Sacramento basin, San Joaquin basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.52978515625001,\n 37.91820111976663\n ],\n [\n -119.77294921874999,\n 37.91820111976663\n ],\n [\n -119.77294921874999,\n 42.07376224008719\n ],\n [\n -125.52978515625001,\n 42.07376224008719\n ],\n [\n -125.52978515625001,\n 37.91820111976663\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"National Research Program
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025
Trace-metal concentrations in sediment and in the clam Macoma petalum (formerly reported as Macoma balthica), clam reproductive activity, and benthic macroinvertebrate community structure were investigated in a mudflat 1 kilometer south of the discharge of the Palo Alto Regional Water Quality Control Plant (PARWQCP) in south San Francisco Bay, Calif. This report includes the data collected by U.S. Geological Survey (USGS) scientists for the period January 2017 to December 2017. These append to long-term datasets extending back to 1974. A major focus of the report is an integrated description of the 2017 data within the context of the longer, multi-decadal dataset. This dataset supports the City of Palo Alto’s Near-Field Receiving Water Monitoring Program, initiated in 1994.
Significant reductions in silver and copper concentrations in sediment and M. petalum occurred at the site in the 1980s following the implementation by PARWQCP of advanced wastewater treatment and source control measures. Since the 1990s, concentrations of these elements appear to have stabilized at concentrations somewhat above silver (Ag) or near copper (Cu) regional background concentrations. Data for other metals, including chromium (Cr), mercury (Hg), nickel (Ni), selenium (Se), and zinc (Zn), have been collected since 1994. Over this period, concentrations of these elements have remained relatively constant, aside from seasonal variation that is common to all elements. In 2017, concentrations of silver and copper in M. petalum varied seasonally in response to a combination of site-specific metal exposures and annual growth and reproduction, as reported previously. Seasonal patterns for other elements, including Cr, Ni, Zn, Hg, and Se, were generally similar in timing and magnitude as those for Ag and Cu. This record suggests that legacy contamination and regional-scale factors now largely control sedimentary and bioavailable concentrations of silver and copper, as well as other elements of regulatory interest, at the Palo Alto site.
Analyses of the benthic community structure of a mudflat in south San Francisco Bay over a 40-year period show that changes in the community have occurred concurrent with reduced concentrations of metals in the sediment and in the tissues of the biosentinel clam, M. petalum, from the same area. Analysis of M. petalum shows increases in reproductive activity concurrent with the decline in metal concentrations in the tissues of this organism. Reproductive activity is presently stable (2017), with almost all animals initiating reproduction in the fall and spawning the following spring. The entire infaunal community has shifted from being dominated by several opportunistic species to a community where the species are more similar in abundance, a pattern that indicates a more stable community that is subjected to fewer stressors. In addition, two of the opportunistic species (Ampelisca abdita and Streblospio benedicti) that brood their young and live on the surface of the sediment in tubes have shown a continual decline in dominance coincident with the decline in metals; both species had short-lived rebounds in abundance in 2008, 2009, and 2010 and showed signs of increasing abundance in 2017. Heteromastus filiformis (a subsurface polychaete worm that lives in the sediment, consumes sediment and organic particles residing in the sediment, and reproduces by laying its eggs on or in the sediment) showed a concurrent increase in dominance and, in the last several years before 2008, showed a stable population. H. filiformis abundance increased slightly in 2011–2012 and returned to pre-2011 numbers in 2017. An unidentified disturbance occurred on the mudflat in early 2008 that resulted in the loss of the benthic animals, except for deep-dwelling animals like M. petalum. However, within two months of this event animals returned to the mudflat. The resilience of the community suggested that the disturbance was not due to a persistent toxin or anoxia. The reproductive mode of most species that were present in 2017 is reflective of species that were available either as pelagic larvae or as mobile adults. Although oviparous species were lower in number in this group, the authors hypothesize that these species will return slowly as more species move back into the area. The use of functional ecology was highlighted in the 2017 benthic community data, which showed that the animals that have now returned to the mudflat are those that can respond successfully to a physical, nontoxic disturbance. Today, community data show a mix of species that consume the sediment, or filter feed, have pelagic larvae that must survive landing on the sediment, and those that brood their young. USGS scientists view the 2008 disturbance event as a response by the infaunal community to an episodic natural stressor (possibly sediment accretion or a pulse of freshwater), in contrast to the long-term recovery from metal contamination. We will compare this recovery to the long-term recovery observed after the 1970s when the decline in sediment pollutants was the dominating factor.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181107","collaboration":"Prepared in cooperation with the City of Palo Alto, California","usgsCitation":"Cain, D.J., Thompson, J.K., Parchaso, F., Pearson, S., Stewart, R., Turner, M., Barasch, D., Slabic, A., and Luoma, S.N., 2018, Near-field receiving-water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California—2017: U.S. Geological Survey Open-File Report 2018–1107, 71 p., https://doi.org/10.3133/ofr20181107.","productDescription":"vi, 71 p.","numberOfPages":"79","onlineOnly":"Y","ipdsId":"IP-098497","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":416196,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20231017","text":"Open-File Report 2023-1017","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2020"},{"id":416195,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20211079","text":"Open-File Report 2021-1079","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2019"},{"id":416197,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20191084","text":"Open-File Report 2019-1084","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2018"},{"id":416194,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20171135","text":"Open-File Report 2017-1135","linkHelpText":"- Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California; 2016"},{"id":416193,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20161118","text":"Open-File Report 2016-1118","linkHelpText":"- Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California; 2015"},{"id":355780,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1107/ofr20181107_.pdf","text":"Report","size":"3.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1107"},{"id":355779,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1107/coverthb.jpg"}],"country":"United States","state":"California","city":"Palo Alto","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 -122.27371215820312,\n 37.315567502511044\n ],\n [\n -121.827392578125,\n 37.315567502511044\n ],\n [\n -121.827392578125,\n 37.655557695625056\n ],\n [\n -122.27371215820312,\n 37.655557695625056\n ],\n [\n -122.27371215820312,\n 37.315567502511044\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Hydro-Eco Interactions Branch
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025
Empirical nutrient models that describe lake nutrient, productivity, and water clarity relationships among lakes play a prominent role in limnology. Landscape-based regressions are also used to understand macroscale variability of lake nutrients, clarity, and productivity (hereafter referred to as nutrient-productivity). Predictions from both models are used to inform eutrophication management globally. To date, these two classes of models are generally conducted separately, which ignores the known dependencies among nutrient-productivity variables. We present a statistical model that integrates nutrient-productivity and landscape-based regressions—where lake nutrients, productivity, and clarity variables are modeled jointly. We fitted a joint nutrient-productivity model to over 7000 lakes with three nutrients (total phosphorus, total nitrogen, nitrate concentrations), chlorophyll a concentrations, and Secchi disk depth as response variables and landscape features as predictor variables. Because lakes in different regions respond to landscape features differently, we focused our analysis on two subregions with different dominant land uses, the agricultural Midwest and the forested Northeast U.S. Predictive performance was enhanced by modeling nutrient-productivity variables jointly. We also found strong evidence that nutrient-productivity variables were coupled, and that only nitrate may be decoupled from other nutrient-productivity variables in the forested region. We speculate that these regional differences may be related to differences in the strength of biogeochemical cycles and stoichiometric controls between these regions. Jointly modeling nutrient-productivity variables in lakes effectively integrates the two dominant approaches for studying lakes nutrient-productivity relationships and provides novel insight into macroscale patterns of the coupling of nutrients, chlorophyll, and water clarity in lakes.
","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lno.10944","usgsCitation":"Wagner, T., and Schliep, E.M., 2018, Combining nutrient, productivity, and landscape-based regressions improves predictions of lake nutrients and provides insight into nutrient coupling at macroscales: Limnology and Oceanography, v. 63, no. 6, p. 2372-2383, https://doi.org/10.1002/lno.10944.","productDescription":"12 p.","startPage":"2372","endPage":"2383","ipdsId":"IP-093432","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468575,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lno.10944","text":"Publisher Index Page"},{"id":395248,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"63","issue":"6","noUsgsAuthors":false,"publicationDate":"2018-07-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":832425,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schliep, Erin M.","contributorId":171525,"corporation":false,"usgs":false,"family":"Schliep","given":"Erin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":832536,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70197647,"text":"sir20185077 - 2018 - Trends in water quality of selected streams and reservoirs used for water supply in the Triangle area of North Carolina, 1989–2013","interactions":[],"lastModifiedDate":"2018-07-20T10:23:35","indexId":"sir20185077","displayToPublicDate":"2018-07-18T12:30:00","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":"2018-5077","displayTitle":"Trends in water quality of selected streams and reservoirs used for water supply in the Triangle area of North Carolina, 1989–2013","title":"Trends in water quality of selected streams and reservoirs used for water supply in the Triangle area of North Carolina, 1989–2013","docAbstract":"As the population of the Triangle area in central North Carolina increases, the demand for good quality drinking water from streams and lakes within the upper Neuse and upper Cape Fear River Basins also increases. The Triangle area includes Raleigh, Cary, Research Triangle Park, Durham, Chapel Hill, and the surrounding communities. The U.S. Geological Survey examined temporal trends in water quality for 13 stream and 8 reservoir sites in the two basins on the basis of data collected during 1989–2013. Trends were analyzed using a fitted time-series model that accommodated for shifting trends and variations in streamflow at multiple time scales. Seventeen water-quality properties and constituents were evaluated, including specific conductance and major ions, nutrients, and organic carbon. Suspended solids and suspended sediment were examined at stream sites; chlorophyll a and Secchi transparency were examined at lake sites.
The investigation identified considerable changes in population, land cover, streamflow, and selected water-quality characteristics in the study area over the 25-year period. Specific conductance and concentrations of calcium, magnesium, potassium, sodium, and chloride tended to increase throughout the study area. Area-wide increases were also observed for organic nitrogen. Trends for other water-quality constituents varied on a more site-specific basis because of local watershed influences such as changes to wastewater-treatment processes and substantial shifts from rural to urban land use. Water quality is influenced by multiple, often confounding factors, and thus may change in a non-uniform manner over time. Long-term monitoring is critical for tracking these trends and ensuring resiliency of water supplies for the future. Results from this study may promote the understanding of water-quality response to a growing population and land-cover changes and can assist water-resource managers in the Triangle area in tracking progress toward water-quality goals.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185077","collaboration":"Prepared in cooperation with the Triangle Area Water Supply Monitoring Project Steering Committee","usgsCitation":"Giorgino, M.J., Cuffney, T.F., Harden, S.L., and Feaster, T.D., 2018, Trends in water quality of selected streams and reservoirs used for water supply in the Triangle area of North Carolina, 1989–2013: U.S. Geological Survey Scientific Investigations Report 2018–5077, 67 p., https://doi.org/10.3133/sir20185077.","productDescription":"Report: viii, 67 p.; Data release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-095343","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":355697,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5077/coverthb.jpg"},{"id":355698,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5077/sir20185077.pdf","text":"Report","size":"10.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5077"},{"id":355835,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7MS3S17","text":"USGS data release","description":"USGS data release","linkHelpText":"Datasets for trends in water quality of selected streams and reservoirs used for water supply in the Triangle area of North Carolina, 1989-2013"}],"country":"United States","state":"North Carolina","otherGeospatial":"Cape Fear River basin, Neuse River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.79919433593749,\n 35.02099970111467\n ],\n [\n -77.84912109375,\n 35.02099970111467\n ],\n [\n -77.84912109375,\n 36.32397712011264\n ],\n [\n -79.79919433593749,\n 36.32397712011264\n ],\n [\n -79.79919433593749,\n 35.02099970111467\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Suite 129
Columbia, SC 29210
The purpose of this study was to evaluate the effects of irrigation and cover crops as conservation practices on water quality in groundwater and streams. Bucks Branch, a stream in the Nanticoke River watershed in southwestern Delaware, was identified as having one of the highest concentrations of nitrate in all surface-water sites sampled by the Delaware Department of Natural Resources and Environmental Control (DNREC). The study site is on two adjacent fields bordering Bucks Branch, one that has used irrigation since 2000 and one with dryland farming; both under conservation tillage and long-term rotation of corn, soybean, and small grain crops. A streamgage was installed near the study site fields to measure streamflow and water quality. The study area is typical of farming practices and environmental conditions throughout much of the intensively farmed agricultural land of the Coastal Plain of Delaware and surrounding parts of Maryland. Monitoring was conducted from January 2014 through June 2016. Corn was grown on both fields during the two growing seasons of the study period, and cover crops were planted before or shortly after harvest on both fields. During the second year of data collection, the effects of radish and rye grass cover crops on nutrient transport were studied.
The combined results from data collected for this study show that water and nitrate moved below the root zone year round when soil moisture was high, especially after significant rainfall and frequently after irrigation. Soil water sampled 2 to 3 weeks after nutrients were applied had nitrate concentrations greater than 50 milligrams per liter as nitrogen (mg/L as N) and may be a significant source of nitrate to groundwater. Whereas recharge containing elevated nitrate concentrations also occurred under the dryland field, it was less frequent and of lower concentration than recharge under the irrigated field.
Nitrate was present in all groundwater samples from these sites. Groundwater estimated to have recharged within 10 years or less had higher median concentrations of nitrate than in older water samples. The oldest groundwater encountered was over 30 years old, and had traveled along the longest, deep flowpaths from upland fields to the stream. The median nitrate concentration was 18 mg/L as N in younger water (less than 10 years old) beneath the irrigated field, compared to about 10 mg/L as N in younger water beneath the dryland field. Samples from the shallow upland wells in both study fields showed little, if any, evidence of denitrification. Several samples from deeper wells and from wells near forested riparian zone wetlands that border both fields did show partial denitrification.
A mixing model estimated that between 12 and 22 percent of the nitrate discharging to the stream was lost through uptake and denitrification upstream of the streamgage on Bucks Branch. Continuous data collected at this site and evidence of denitrification in the surface-water samples showed a greater potential for loss of nitrate during the warmer months than the colder months. This pattern was similar to that seen below the streamgage at the most downstream site in the watershed.
A mixed cover crop of radishes and rye was planted prior to removal (radishes) and just after harvest (rye) of the corn crop on the irrigated field. Rye grass was planted shortly after crop harvest on the dryland field. Cover crop biomass samples collected while radishes were growing and after they were killed by freezing temperatures indicates that the early planted radish crop effectively scavenged available nitrogen from the soil. Whereas radish biomass initially held more nitrogen than rye, at 55 to 8 pounds per acre, respectively, leaching of inorganic nitrate following radish die-off was minimal. Soil-water nitrate concentrations during the cover-crop growing period were lower than during the growing season prior to planting of the cover crop. There also was an increase in soil fertility and dissolved organic nitrate in samples of soil water that was likely related to increased soil microbial metabolism. Results indicate that cover crops stored plant nutrients over the winter and did not increase shallow groundwater concentrations of nitrate.
Although conservation practices such as cover crops and nutrient management have been applied to these fields, there was still significant leaching of nitrate to groundwater, especially under the irrigated field. This will likely continue to be a challenge in this area and other parts of the Coastal Plain where soil moisture capacity is relatively low and managing irrigation around rainfall is difficult. Cover crops, when planted in standing corn, are one practice that can effectively pull nitrate from below the root zone to the top layer of soil, thus limiting the amount of potential nitrate leaching to groundwater. Irrigation management that would lower average soil moisture conditions during the growing season also could potentially limit nitrogen transport.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185020","collaboration":"Prepared in cooperation with the Delaware Department of Natural Resources and Environmental Control and the Delaware Geological Survey","usgsCitation":"Denver, J.M., Soroka, A.M., Reyes, B., Lester, T.R., Bringman, D.A., and Brownley, M.S., 2018, Monitoring the water-quality response of agricultural conservation practices in the Bucks Branch watershed, Sussex County, Delaware, 2014–16: U.S. Geological Survey Scientific Investigations Report 2018–5020, 43 p., https://doi.org/10.3133/sir20185020.","productDescription":"ix, 43 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-088518","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":355731,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5020/sir20185020.pdf","text":"Report","size":"8.50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5020"},{"id":355732,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77H1HK5","text":"USGS data release","description":"USGS data release","linkHelpText":"Chemistry analysis results for groundwater, soil-pore water, soil and plant material collected from two agricultural sites in the Nanticoke and Chester River watersheds on the Delmarva Peninsula from 2013 to 2016"},{"id":355730,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5020/coverthb.jpg"}],"country":"United States","state":"Delaware","county":"Sussex County","otherGeospatial":"Bucks Branch Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.6833,\n 38.6833\n ],\n [\n -75.6167,\n 38.6833\n ],\n [\n -75.6167,\n 38.7333\n ],\n [\n -75.6833,\n 38.7333\n ],\n [\n -75.6833,\n 38.6833\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, MD-DE-DC Water Science Center
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An understanding of the spatial and temporal extent of groundwater recharge is critical for many types of hydrologic assessments involving water quality, contaminant transport, ecosystem health, and sustainable use of groundwater. Annual potential groundwater recharge was simulated at a 1-kilometer resolution with the Soil-Water-Balance (SWB) model for the glacial aquifer system east of the Rocky Mountains, from central Montana east to Maine, for calendar years 1980–2011. The SWB model used high resolution meteorological, land cover, and soil hydrology datasets that are nationally consistent and publicly available. The SWB model computed daily potential groundwater recharge as precipitation in excess of interception, runoff, evapotranspiration, and soil-water storage capacity. Daily potential recharge values within each year of the simulation were summed to produce annual potential recharge rates. Potential recharge as described in this report is water that infiltrates vertically below the plant rooting zone and is assumed to reach the water table.
The calibrated SWB model in this report is called the glacial SWB model. Model calibration assumed that the area contributing to groundwater discharge equaled the surface watershed. The model was calibrated to stream base flows from 39 watersheds throughout the model domain that had hydrologic conditions appropriate for hydrograph separation. Base flows were calculated from daily streamflow records with the HYSEP local minimum hydrograph separation method The glacial SWB model reproduced the mean annual base-flow calibration targets well; the Nash-Sutcliffe efficiency coefficient was 0.94, and the root mean squared error was 1.28 inches per year.
The glacial SWB model provides insight into the spatial and temporal variability in potential annual recharge across the glacial aquifer system. About 20 percent of the active model area had an average potential recharge rate of less than 1 inch per year. Total precipitation, total recharge, and recharge as a percentage of precipitation increased from west to east. A substantial amount of the recharge water (39 percent) entering the glacial aquifer system travels through developed (urbanized) and agricultural landscapes, which are known to cause water-quality impairments. Regional climatic events, such as the 1988 to 1989 drought, are apparent in the potential recharge time series. Potential recharge generally increased across the glacial aquifer system between 2001 and 2011.
A comparison of the potential recharge from the glacial SWB model to previous broad-scale recharge estimates reveals several important considerations for future SWB modeling applications. Shifts in the overall distribution of potential recharge between separate models can be explained by methods used to generate base-flow calibration target datasets. Spatial patterns in potential recharge simulated by SWB models are strongly dependent on the data and assumptions used to assign model cells to hydrologic soil groups. A review of several SWB models used to estimate groundwater recharge (and not surface runoff) revealed that model results are most sensitive to input climatic data, followed by surface runoff (curve number) and root-zone depth parameters.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185080","collaboration":"Prepared as part of the Glacial Aquifer System Groundwater Availability Study, a cooperative effort between the U.S. Department of the Interior’s WaterSMART Initiative and the U.S. Geological Survey’s Water Availability and Use Science Program","usgsCitation":"Trost, J.J., Roth, J.L., Westenbroek, S.M., and Reeves, H.W., 2018, Simulation of potential groundwater recharge for the glacial aquifer system east of the Rocky Mountains, 1980–2011, using the Soil-Water-Balance model: U.S. Geological Survey Scientific Investigations Report 2018–5080, 51 p., https://doi.org/10.3133/sir20185080.","productDescription":"Report: vii, 51 p.; Tables; Data Release","numberOfPages":"64","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-088856","costCenters":[{"id":392,"text":"Minnesota Water Science 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Upper Midwest Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, MN 55112
Human dependence on insect pollinators continues to grow even as pollinators face global declines. The Northern Great Plains (NGP), a region often referred to as America’s last honey bee (Apis mellifera) refuge, has undergone rapid land-cover change due to cropland expansion and weakened land conservation programs. We conducted a trend analysis and estimated conversion rates of Conservation Reserve Program (CRP) enrollments around bee apiaries from 2006 to 2016 and developed models to identify areas of habitat loss. Our analysis revealed that NGP apiaries lost over 53% of lands enrolled in the CRP, and the rate of loss was highest in areas of high apiary density. We estimated over 163,000 ha of CRP lands in 2006 within 1.6 km of apiaries was converted to row crops by 2012. We also evaluated how alternative scenarios of future CRP acreage caps may affect habitat suitability for supporting honey bee colonies. Our scenario revealed that a further reduction in CRP lands to 7.7 million ha nationally would reduce the number of apiaries in the NGP that meet defined forage criteria by 28% on average. Alternatively, increasing the national cap to 15 million ha would increase the number of NGP apiaries that meet defined forage criteria by 155%. Our scenarios also show that strategic placement of CRP lands near existing apiaries increased the number of apiaries that meet forage criteria by 182%. Our research will be useful for informing the potential consequences of future US farm bill policy and land management in the epicenter of the US beekeeping industry.
","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.1800057115","usgsCitation":"Otto, C., Zheng, H., Gallant, A.L., Iovanna, R., Carlson, B.L., Smart, M., and Hyberg, S., 2018, Past role and future outlook of the Conservation Reserve Program for supporting honey bees in the Great Plains: Proceedings of the National Academy of Sciences, v. 115, no. 29, p. 7629-7634, https://doi.org/10.1073/pnas.1800057115.","productDescription":"6 p.","startPage":"7629","endPage":"7634","ipdsId":"IP-092994","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":468581,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://digitalcommons.unl.edu/usgsstaffpub/1219","text":"Publisher Index 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L.","contributorId":207530,"corporation":false,"usgs":false,"family":"Carlson","given":"Benjamin","email":"","middleInitial":"L.","affiliations":[{"id":37554,"text":"Xerces Society","active":true,"usgs":false}],"preferred":false,"id":744067,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smart, Matthew 0000-0003-0711-3035 msmart@usgs.gov","orcid":"https://orcid.org/0000-0003-0711-3035","contributorId":174424,"corporation":false,"usgs":true,"family":"Smart","given":"Matthew","email":"msmart@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":744068,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hyberg, Skip","contributorId":90407,"corporation":false,"usgs":true,"family":"Hyberg","given":"Skip","email":"","affiliations":[],"preferred":false,"id":744066,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70198145,"text":"70198145 - 2018 - Statistical approach to neural network imaging of karst systems in 3D seismic reflection data","interactions":[],"lastModifiedDate":"2018-07-18T09:53:59","indexId":"70198145","displayToPublicDate":"2018-07-17T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3906,"text":"Interpretation","active":true,"publicationSubtype":{"id":10}},"title":"Statistical approach to neural network imaging of karst systems in 3D seismic reflection data","docAbstract":"The current lack of a robust, standardized technique for geophysical mapping of karst systems can be attributed to both the complexity of the environment and prior technological limitations. Abrupt lateral variations in physical properties that are inherent to karst systems generate significant geophysical noise, challenging conventional seismic signal processing and interpretation. Modern application of neural networks to multi-attribute seismic interpretation now provide a semiautomated method for identifying and leveraging the nonlinear relationships exhibited among seismic attributes. The ambiguity generally associated with designing neural networks for seismic object detection can be reduced via statistical analysis of the extracted attribute data. A data-driven approach to selecting the appropriate set of input seismic attributes, as well as the locations and minimum number of training examples, provides a more objective and computationally efficient method for identifying karst systems using reflection seismology. This statistically optimized neural network technique is thoroughly demonstrated using three-dimensional seismic reflection data collected from the southeastern portion of the Florida carbonate platform. Several dimensionality reduction methods are applied and the resulting karst probability models are evaluated relative to one another based on both quantitative and qualitative criteria. Comparing the preferred model, using quadratic discriminant analysis, to previously available seismic object detection workflows demonstrates the karst-specific nature of the tool. Results suggest that the karst multi-attribute workflow presented is capable of approximating the structural boundaries of karst systems with more accuracy and efficiency than a human counterpart or previously presented seismic interpretation schemes. This objective technique, using solely three-dimensional seismic reflection data, likely represents the most practical approach to mapping karst systems for subsequent hydrogeological modeling.","language":"English","publisher":"Society of Exploration Geophysicists","doi":"10.1190/int-2017-0197.1","usgsCitation":"Ebuna, D., Kluesner, J., Cunningham, K.J., and Edwards, J.H., 2018, Statistical approach to neural network imaging of karst systems in 3D seismic reflection data: Interpretation, v. 6, no. 3, p. B15-B35, https://doi.org/10.1190/int-2017-0197.1.","productDescription":"21 p.","startPage":"B15","endPage":"B35","ipdsId":"IP-090061","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":355752,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc411e4b0f5d57878e9c1","contributors":{"authors":[{"text":"Ebuna, Daniel","contributorId":201729,"corporation":false,"usgs":true,"family":"Ebuna","given":"Daniel","email":"","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":740229,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kluesner, Jared W. 0000-0003-1701-8832","orcid":"https://orcid.org/0000-0003-1701-8832","contributorId":206367,"corporation":false,"usgs":true,"family":"Kluesner","given":"Jared W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":740228,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cunningham, Kevin J. 0000-0002-2179-8686 kcunning@usgs.gov","orcid":"https://orcid.org/0000-0002-2179-8686","contributorId":1689,"corporation":false,"usgs":true,"family":"Cunningham","given":"Kevin","email":"kcunning@usgs.gov","middleInitial":"J.","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"preferred":true,"id":740230,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Edwards, Joel H.","contributorId":202599,"corporation":false,"usgs":false,"family":"Edwards","given":"Joel","email":"","middleInitial":"H.","affiliations":[{"id":27155,"text":"University of California Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":740231,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}