The biogeochemical cycling of metals and other contaminants in river-floodplain corridors is controlled by microbial activity responding to dynamic redox conditions. Riverine flooding thus has the potential to affect speciation of redox-sensitive metals such as mercury (Hg). Therefore, inundation history over a period of decades potentially holds information on past production of bioavailable Hg. We investigate this within a Northern California river system with a legacy of landscape-scale 19th century hydraulic gold mining. We combine hydraulic modeling, Hg measurements in sediment and biota, and first-order calculations of mercury transformation to assess the potential role of river floodplains in producing monomethylmercury (MMHg), a neurotoxin which accumulates in local and migratory food webs. We identify frequently inundated floodplain areas, as well as floodplain areas inundated for long periods. We quantify the probability of MMHg production potential (MPP) associated with hydrology in each sector of the river system as a function of the spatial patterns of overbank inundation and drainage, which affect long-term redox history of contaminated sediments. Our findings identify river floodplains as periodic, temporary, yet potentially important, loci of biogeochemical transformation in which contaminants may undergo change during limited periods of the hydrologic record. We suggest that inundation is an important driver of MPP in river corridors and that the entire flow history must be analyzed retrospectively in terms of inundation magnitude and frequency in order to accurately assess biogeochemical risks, rather than merely highlighting the largest floods or low-flow periods. MMHg bioaccumulation within the aquatic food web in this system may pose a major risk to humans and waterfowl that eat migratory salmonids, which are being encouraged to come up these rivers to spawn. There is a long-term pattern of MPP under the current flow regime that is likely to be accentuated by increasingly common large floods with extended duration.
","language":"English","publisher":"ScienceDirect","doi":"10.1016/j.scitotenv.2016.03.005","usgsCitation":"Singer, M.B., Harrison, L.R., Donovan, P.M., Blum, J.D., and Marvin-DiPasquale, M.C., 2016, Hydrologic indicators of hot spots and hot moments of mercury methylation potential along river corridors: Science of the Total Environment, v. 568, p. 697-711, https://doi.org/10.1016/j.scitotenv.2016.03.005.","productDescription":"15 p.","startPage":"697","endPage":"711","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071066","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":471145,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.03.005","text":"Publisher Index Page"},{"id":328234,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Bear River, Feather River, Sacramento River, Yuba River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.01965332031249,\n 38.13887716726548\n ],\n [\n -122.01965332031249,\n 39.317300373271024\n ],\n [\n -121.2451171875,\n 39.317300373271024\n ],\n [\n -121.2451171875,\n 38.13887716726548\n ],\n [\n -122.01965332031249,\n 38.13887716726548\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"568","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57cd45abe4b0f2f0cec4cb4e","contributors":{"authors":[{"text":"Singer, Michael B.","contributorId":168369,"corporation":false,"usgs":false,"family":"Singer","given":"Michael","email":"","middleInitial":"B.","affiliations":[{"id":25268,"text":"University of St Andrews, UK","active":true,"usgs":false}],"preferred":false,"id":647993,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harrison, Lee R.","contributorId":174322,"corporation":false,"usgs":false,"family":"Harrison","given":"Lee","email":"","middleInitial":"R.","affiliations":[{"id":6710,"text":"University of California, Santa Barbara, CA","active":true,"usgs":false}],"preferred":false,"id":647994,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Donovan, Patrick M.","contributorId":168368,"corporation":false,"usgs":false,"family":"Donovan","given":"Patrick","email":"","middleInitial":"M.","affiliations":[{"id":25267,"text":"Univ. of Michigan","active":true,"usgs":false}],"preferred":false,"id":647995,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blum, Joel D.","contributorId":83657,"corporation":false,"usgs":true,"family":"Blum","given":"Joel","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":647996,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Marvin-DiPasquale, Mark C. 0000-0002-8186-9167 mmarvin@usgs.gov","orcid":"https://orcid.org/0000-0002-8186-9167","contributorId":1485,"corporation":false,"usgs":true,"family":"Marvin-DiPasquale","given":"Mark","email":"mmarvin@usgs.gov","middleInitial":"C.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":647992,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70168418,"text":"sir20165021 - 2016 - Groundwater hydrology and estimation of horizontal groundwater flux from the Rio Grande at selected locations in Albuquerque, New Mexico, 2009–10","interactions":[],"lastModifiedDate":"2016-03-18T08:13:50","indexId":"sir20165021","displayToPublicDate":"2016-03-17T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5021","title":"Groundwater hydrology and estimation of horizontal groundwater flux from the Rio Grande at selected locations in Albuquerque, New Mexico, 2009–10","docAbstract":"The Albuquerque area of New Mexico has two principal sources of water: (1) groundwater from the Santa Fe Group aquifer system, and (2) surface water from the Rio Grande. From 1960 to 2002, pumping from the Santa Fe Group aquifer system caused groundwater levels to decline more than 120 feet while water-level declines along the Rio Grande in Albuquerque were generally less than 40 feet. These differences in water-level declines in the Albuquerque area have resulted in a great deal of interest in quantifying the river-aquifer interaction associated with the Rio Grande.
In 2003, the U.S. Geological Survey, in cooperation with the Bureau of Reclamation, acting as fiscal agent for the Middle Rio Grande Endangered Species Collaborative Program, and the U.S. Army Corps of Engineers, began a study to characterize the hydrogeology of the Rio Grande inner valley alluvial aquifer in the Albuquerque area of New Mexico. The study provides hydrologic data in order to enhance the understanding of rates of water leakage from the Rio Grande to the alluvial aquifer, groundwater flow through the aquifer, and discharge of water from the aquifer to riverside drains. The study area extends about 20 miles along the Rio Grande in the Albuquerque area. Piezometers and surface-water gages were installed in paired transects at eight locations. Nested piezometers, completed at various depths in the alluvial aquifer, and surface-water gages, installed in the Rio Grande and riverside drains, were instrumented with pressure transducers. Water-level and water-temperature data were collected from 2009 to 2010.
Water levels from the piezometers indicated that groundwater movement was usually away from the river towards the riverside drains. Annual mean horizontal groundwater gradients in the inner valley alluvial aquifer ranged from 0.0024 (I-25 East) to 0.0144 (Pajarito East). The median hydraulic conductivity values of the inner valley alluvial aquifer, determined from slug tests, ranged from 30 feet per day (ft/d) (Montaño) to 120 ft/d (Central) for paired transects, with a median hydraulic conductivity for all transects of 50 ft/d. Daily mean groundwater fluxes from the river through the inner valley alluvial aquifer computed using Darcy’s Law and the slug test results ranged from about 0.01 ft/d (Montaño West) to between 1.0 and 2.0 ft/d (Central East). Median annual groundwater fluxes from the river through the inner valley alluvial aquifer determined using the Suzuki-Stallman method was greatest at Alameda East (0.50 ft/d) and lowest at Alameda West (0.25 ft/d). The results from both methods agreed reasonably well.
Seepage investigations conducted by measuring discharge in the east and west riverside drains provided information for computing changes in flow within the drains and for evaluating results from Darcy’s Law and Suzuki-Stallman method flux calculations. Discharge measured in the east riverside drain between the Barelas Bridge and the I-25 bridge indicated that the flow in the east riverside drain increased by an average of 56.5 cubic feet per day per linear foot (ft3/d/ft) of drain. Discharge measured in the west riverside drain between the Central bridge and the I-25 bridge indicated that flow increased between west drain miles 0 and 4, an average of 53.8 ft3/d/ft of drain, and that flow increased between west drain miles 7 and 10, an average of 44.9 ft3/d/ft of drain. In comparison to the seepage measurement results, the groundwater fluxes from the river through the inner valley alluvial aquifer calculated from Darcy’s Law (qslug) and by the Suzuki-Stallman method (qheat) would account for 20–36 percent or 53–95 percent, respectively, of the total flow in the east riverside drain and 22–31 percent or 19–26 percent, respectively, of the total flow in the west drain. These results indicate that the drains likely also receive water from outside the inner valley.
The spatial variability of horizontal hydraulic gradients and groundwater fluxes can be primarily attributed to variability in the distances between the river and riverside drains throughout the study area and geologic heterogeneities in the alluvial aquifer. Temporal variability in the water levels, which control the horizontal hydraulic gradients and fluxes between the Rio Grande and the riverside drains, can be primarily attributed to seasonal fluctuations in river stage and irrigation practices.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165021","collaboration":"Prepared in cooperation with Bureau of Reclamation acting as fiscal agent for the Middle Rio Grande Endangered Species Collaborative Program","usgsCitation":"Rankin, D.R., Oelsner, G.P., McCoy, K.J., Moret, G.J.M., Worthington, J.A., and Bandy-Baldwin, K.M., 2016, Groundwater hydrology and estimation of horizontal groundwater flux from the Rio Grande at selected locations in Albuquerque, New Mexico, 2009–10: U.S. Geological Survey Scientific Investigations Report 2016–5021, 89 p., https://dx.doi.org/10.3133/sir20165021.","productDescription":"viii, 89 p.","numberOfPages":"101","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-033038","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":318926,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5021/sir20165021.pdf","text":"Report","size":"5.15 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5021"},{"id":318925,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5021/coverthb.jpg"}],"country":"United States","state":"New Mexico","city":"Albuquerque","otherGeospatial":"Rio Grande","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.7266845703125,\n 34.95011635301367\n ],\n [\n -106.7266845703125,\n 35.290468565908775\n ],\n [\n -106.56051635742188,\n 35.290468565908775\n ],\n [\n -106.56051635742188,\n 34.95011635301367\n ],\n [\n -106.7266845703125,\n 34.95011635301367\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
5338 Montogmery Blvd., NE Suite 400
Albuquerque, NM 87109–1311
Estimates of the magnitude and frequency of floods are needed across Alaska for engineering design of transportation and water-conveyance structures, flood-insurance studies, flood-plain management, and other water-resource purposes. This report updates methods for estimating flood magnitude and frequency in Alaska and conterminous basins in Canada. Annual peak-flow data through water year 2012 were compiled from 387 streamgages on unregulated streams with at least 10 years of record. Flood-frequency estimates were computed for each streamgage using the Expected Moments Algorithm to fit a Pearson Type III distribution to the logarithms of annual peak flows. A multiple Grubbs-Beck test was used to identify potentially influential low floods in the time series of peak flows for censoring in the flood frequency analysis.
For two new regional skew areas, flood-frequency estimates using station skew were computed for stations with at least 25 years of record for use in a Bayesian least-squares regression analysis to determine a regional skew value. The consideration of basin characteristics as explanatory variables for regional skew resulted in improvements in precision too small to warrant the additional model complexity, and a constant model was adopted. Regional Skew Area 1 in eastern-central Alaska had a regional skew of 0.54 and an average variance of prediction of 0.45, corresponding to an effective record length of 22 years. Regional Skew Area 2, encompassing coastal areas bordering the Gulf of Alaska, had a regional skew of 0.18 and an average variance of prediction of 0.12, corresponding to an effective record length of 59 years. Station flood-frequency estimates for study sites in regional skew areas were then recomputed using a weighted skew incorporating the station skew and regional skew. In a new regional skew exclusion area outside the regional skew areas, the density of long-record streamgages was too sparse for regional analysis and station skew was used for all estimates. Final station flood frequency estimates for all study streamgages are presented for the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities.
Regional multiple-regression analysis was used to produce equations for estimating flood frequency statistics from explanatory basin characteristics. Basin characteristics, including physical and climatic variables, were updated for all study streamgages using a geographical information system and geospatial source data. Screening for similar-sized nested basins eliminated hydrologically redundant sites, and screening for eligibility for analysis of explanatory variables eliminated regulated peaks, outburst peaks, and sites with indeterminate basin characteristics. An ordinary least‑squares regression used flood-frequency statistics and basin characteristics for 341 streamgages (284 in Alaska and 57 in Canada) to determine the most suitable combination of basin characteristics for a flood-frequency regression model and to explore regional grouping of streamgages for explaining variability in flood-frequency statistics across the study area. The most suitable model for explaining flood frequency used drainage area and mean annual precipitation as explanatory variables for the entire study area as a region. Final regression equations for estimating the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probability discharge in Alaska and conterminous basins in Canada were developed using a generalized least-squares regression. The average standard error of prediction for the regression equations for the various annual exceedance probabilities ranged from 69 to 82 percent, and the pseudo-coefficient of determination (pseudo-R2) ranged from 85 to 91 percent.
The regional regression equations from this study were incorporated into the U.S. Geological Survey StreamStats program for a limited area of the State—the Cook Inlet Basin. StreamStats is a national web-based geographic information system application that facilitates retrieval of streamflow statistics and associated information. StreamStats retrieves published data for gaged sites and, for user-selected ungaged sites, delineates drainage areas from topographic and hydrographic data, computes basin characteristics, and computes flood frequency estimates using the regional regression equations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165024","collaboration":"Prepared in cooperation with the Alaska Department of Transportation and Public Facilities, Alaska Department of Natural Resources, and U.S. Army Corps of Engineers","usgsCitation":"Curran, J.H., Barth, N.A., Veilleux, A.G., and Ourso, R.T., 2016, Estimating flood magnitude and frequency at gaged and ungaged sites on streams in Alaska and conterminous basins in Canada, based on data through water year 2012: U.S. Geological Survey Scientific Investigations Report 2016–5024, 47 p., https://dx.doi.org/10.3133/sir20165024.","productDescription":"Report: vi, 47 p.; 3 Tables; 1 Appendix; Companion File; Database","numberOfPages":"58","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2011-10-01","ipdsId":"IP-068358","costCenters":[{"id":114,"text":"Alaska Science 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2011-2021"},{"id":438632,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JEL0UU","text":"USGS data release","linkHelpText":"Flood Frequency Data and 2020 Observed Flood Probability for Selected Streamgages in the Fortymile River Basin, Alaska, 1911-2020"},{"id":318921,"rank":7,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5024/sir20165024_table09.xlsx","text":"Table 9","size":"78 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":318920,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5024/sir20165024_appendixa.xlsx","text":"Appendix A","size":"99 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":318919,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5024/sir20165024_table04.xlsx","text":"Table 4","size":"88 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http://alaska.usgs.gov
Long-term fish sampling data from the San Francisco Estuary were combined with detailed three dimensional hydrodynamic modeling to investigate the relationship between historical fish catch and hydrodynamic complexity. Delta Smelt catch data at 45 stations from the Fall Midwater Trawl (FMWT) survey in the vicinity of Suisun Bay were used to develop a quantitative catch-based station index. This index was used to rank stations based on historical Delta Smelt catch. The correlations between historical Delta Smelt catch and 35 quantitative metrics of environmental complexity were evaluated at each station. Eight metrics of environmental conditions were derived from FMWT data and 27 metrics were derived from model predictions at each FMWT station. To relate the station index to conceptual models of Delta Smelt habitat, the metrics were used to predict the station ranking based on the quantified environmental conditions. Salinity, current speed, and turbidity metrics were used to predict the relative ranking of each station for Delta Smelt catch. Including a measure of the current speed at each station improved predictions of the historical ranking for Delta Smelt catch relative to similar predictions made using only salinity and turbidity. Current speed was also found to be a better predictor of historical Delta Smelt catch than water depth. The quantitative approach developed using the FMWT data was validated using the Delta Smelt catch data from the San Francisco Bay Study. Complexity metrics in Suisun Bay were-evaluated during 2010 and 2011. This analysis indicated that a key to historical Delta Smelt catch is the overlap of low salinity, low maximum velocity, and low Secchi depth regions. This overlap occurred in Suisun Bay during 2011, and may have contributed to higher Delta Smelt abundance in 2011 than in 2010 when the favorable ranges of the metrics did not overlap in Suisun Bay.
","language":"English","publisher":"University of California at Davis John Muir Institute of the Environment and the Delta Stewardship Council","doi":"10.15447/sfews.2016v14iss1art3","usgsCitation":"Bever, A.J., MacWilliams, M.L., Herbold, B., Brown, L.R., and Feyrer, F.V., 2016, Linking hydrodynamic complexity to delta smelt (Hypomesus transpacificus) distribution in the San Francisco Estuary, USA: San Francisco Estuary and Watershed Science, v. 14, no. 1, p. 1-27, https://doi.org/10.15447/sfews.2016v14iss1art3.","productDescription":"27 p.","startPage":"1","endPage":"27","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-063936","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true}],"links":[{"id":471146,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.15447/sfews.2016v14iss1art3","text":"Publisher Index Page"},{"id":325464,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.6845703125,\n 38.1734326790354\n ],\n [\n -121.6680908203125,\n 38.14103736644331\n ],\n [\n -121.64611816406249,\n 38.089174937729794\n ],\n [\n -121.66259765625001,\n 38.035112420612975\n ],\n [\n -121.67495727539061,\n 37.99724489645483\n ],\n [\n -121.75048828124999,\n 38.00049145082287\n ],\n [\n -121.86447143554686,\n 38.01888587738773\n ],\n [\n -121.96197509765625,\n 38.034030762875844\n ],\n [\n -122.05535888671875,\n 38.037275688165614\n ],\n [\n -122.09793090820311,\n 38.031867399480674\n ],\n [\n -122.14187622070311,\n 38.024295124443995\n ],\n [\n -122.19680786132812,\n 38.034030762875844\n ],\n [\n -122.21054077148438,\n 38.04700960141592\n ],\n [\n -122.22702026367188,\n 38.06647354576796\n ],\n [\n -122.2119140625,\n 38.0729603768343\n ],\n [\n -122.14462280273436,\n 38.052416771864834\n ],\n [\n -122.12265014648438,\n 38.064311140919\n ],\n [\n -122.08694458007812,\n 38.09782123329514\n ],\n [\n -122.07046508789062,\n 38.129155479572624\n ],\n [\n -122.05261230468751,\n 38.23386541556983\n ],\n [\n -122.02926635742188,\n 38.25004423627535\n ],\n [\n -122.00042724609374,\n 38.23170796744926\n ],\n [\n -121.99630737304688,\n 38.182068998322094\n ],\n [\n -121.97708129882812,\n 38.155077102180655\n ],\n [\n -121.87408447265625,\n 38.134556577054134\n ],\n [\n -121.761474609375,\n 38.1334763895322\n ],\n [\n -121.6845703125,\n 38.1734326790354\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-23","publicationStatus":"PW","scienceBaseUri":"5790a183e4b030378fb4743b","contributors":{"authors":[{"text":"Bever, Aaron J.","contributorId":173009,"corporation":false,"usgs":false,"family":"Bever","given":"Aaron","email":"","middleInitial":"J.","affiliations":[{"id":27140,"text":"Delta Modeling Associates, Inc.","active":true,"usgs":false}],"preferred":false,"id":642984,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"MacWilliams, Michael L.","contributorId":173010,"corporation":false,"usgs":false,"family":"MacWilliams","given":"Michael","email":"","middleInitial":"L.","affiliations":[{"id":27140,"text":"Delta Modeling Associates, Inc.","active":true,"usgs":false}],"preferred":false,"id":642985,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herbold, Bruce","contributorId":51223,"corporation":false,"usgs":false,"family":"Herbold","given":"Bruce","email":"","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":642986,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Larry R. 0000-0001-6702-4531 lrbrown@usgs.gov","orcid":"https://orcid.org/0000-0001-6702-4531","contributorId":1717,"corporation":false,"usgs":true,"family":"Brown","given":"Larry","email":"lrbrown@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":642983,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Feyrer, Frederick V. 0000-0003-1253-2349 ffeyrer@usgs.gov","orcid":"https://orcid.org/0000-0003-1253-2349","contributorId":5901,"corporation":false,"usgs":true,"family":"Feyrer","given":"Frederick","email":"ffeyrer@usgs.gov","middleInitial":"V.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":642987,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70169068,"text":"70169068 - 2016 - Spatial and temporal patterns of cloud cover and fog inundation in coastal California: Ecological implications","interactions":[],"lastModifiedDate":"2016-06-24T11:08:13","indexId":"70169068","displayToPublicDate":"2016-03-16T10:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1421,"text":"Earth Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Spatial and temporal patterns of cloud cover and fog inundation in coastal California: Ecological implications","docAbstract":"The presence of low-lying stratocumulus clouds and fog has been known to modify biophysical and ecological properties in coastal California where forests are frequently shaded by low-lying clouds or immersed in fog during otherwise warm and dry summer months. Summer fog and stratus can ameliorate summer drought stress and enhance soil water budgets, and often have different spatial and temporal patterns. Here we use remote sensing datasets to characterize the spatial and temporal patterns of cloud cover over California’s northern Channel Islands. We found marine stratus to be persistent from May through September across the years 2001-2012. Stratus clouds were both most frequent and had the greatest spatial extent in July. Clouds typically formed in the evening, and dissipated by the following early afternoon. We present a novel method to downscale satellite imagery using atmospheric observations and discriminate patterns of fog from those of stratus and help explain patterns of fog deposition previously studied on the islands. The outcomes of this study contribute significantly to our ability to quantify the occurrence of coastal fog at biologically meaningful spatial and temporal scales that can improve our understanding of cloud-ecosystem interactions, species distributions and coastal ecohydrology.
","language":"English","publisher":"American Meterorological Society","doi":"10.1175/EI-D-15-0033.1","usgsCitation":"Rastogi, B., Williams, A.P., Fischer, D.T., Iacobellis, S.F., McEachern, K., Carvalho, L., Jones, C.L., Baguskas, S.A., and Still, C.J., 2016, Spatial and temporal patterns of cloud cover and fog inundation in coastal California: Ecological implications: Earth Interactions, v. 20, Paper 15; 19 p., https://doi.org/10.1175/EI-D-15-0033.1.","productDescription":"Paper 15; 19 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073097","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":471148,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/ei-d-15-0033.1","text":"Publisher Index Page"},{"id":318897,"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 -120.45959472656249,\n 33.880677127838844\n ],\n [\n -120.45959472656249,\n 34.08564930273551\n ],\n [\n -119.32662963867188,\n 34.08564930273551\n ],\n [\n -119.32662963867188,\n 33.880677127838844\n ],\n [\n -120.45959472656249,\n 33.880677127838844\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"20","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-24","publicationStatus":"PW","scienceBaseUri":"56ea759ce4b0f59b85d8979f","contributors":{"authors":[{"text":"Rastogi, Bharat","contributorId":167577,"corporation":false,"usgs":false,"family":"Rastogi","given":"Bharat","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":622755,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, A. Park","contributorId":88456,"corporation":false,"usgs":true,"family":"Williams","given":"A.","email":"","middleInitial":"Park","affiliations":[],"preferred":false,"id":622756,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fischer, Douglas T.","contributorId":167578,"corporation":false,"usgs":false,"family":"Fischer","given":"Douglas","email":"","middleInitial":"T.","affiliations":[{"id":24759,"text":"Strategic Environmental Consulting; University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":622758,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Iacobellis, Sam F.","contributorId":11502,"corporation":false,"usgs":true,"family":"Iacobellis","given":"Sam","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":622757,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McEachern, Kathryn 0000-0003-2631-8247 kathryn_mceachern@usgs.gov","orcid":"https://orcid.org/0000-0003-2631-8247","contributorId":146324,"corporation":false,"usgs":true,"family":"McEachern","given":"Kathryn","email":"kathryn_mceachern@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":622754,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Carvalho, Leila","contributorId":167579,"corporation":false,"usgs":false,"family":"Carvalho","given":"Leila","affiliations":[{"id":6710,"text":"University of California, Santa Barbara, CA","active":true,"usgs":false}],"preferred":false,"id":622759,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jones, Charles Leslie","contributorId":27790,"corporation":false,"usgs":true,"family":"Jones","given":"Charles","email":"","middleInitial":"Leslie","affiliations":[],"preferred":false,"id":622760,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Baguskas, Sara A.","contributorId":167580,"corporation":false,"usgs":false,"family":"Baguskas","given":"Sara","email":"","middleInitial":"A.","affiliations":[{"id":24760,"text":"University of California, Santa Barbara and Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":622761,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Still, Christopher J.","contributorId":167581,"corporation":false,"usgs":false,"family":"Still","given":"Christopher","email":"","middleInitial":"J.","affiliations":[{"id":24761,"text":"University of California, Santa Barbara; Oregon State University","active":true,"usgs":false}],"preferred":false,"id":622762,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70164510,"text":"sir20165022 - 2016 - Potential effects of alterations to the hydrologic system on the distribution of salinity in the Biscayne aquifer in Broward County, Florida","interactions":[],"lastModifiedDate":"2019-12-30T14:41:27","indexId":"sir20165022","displayToPublicDate":"2016-03-15T16:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5022","title":"Potential effects of alterations to the hydrologic system on the distribution of salinity in the Biscayne aquifer in Broward County, Florida","docAbstract":"To address concerns about the effects of water-resource management practices and rising sea level on saltwater intrusion, the U.S. Geological Survey in cooperation with the Broward County Environmental Planning and Community Resilience Division, initiated a study to examine causes of saltwater intrusion and predict the effects of future alterations to the hydrologic system on salinity distribution in eastern Broward County, Florida. A three-dimensional, variable-density solute-transport model was calibrated to conditions from 1970 to 2012, the period for which data are most complete and reliable, and was used to simulate historical conditions from 1950 to 2012. These types of models are typically difficult to calibrate by matching to observed groundwater salinities because of spatial variability in aquifer properties that are unknown, and natural and anthropogenic processes that are complex and unknown; therefore, the primary goal was to reproduce major trends and locally generalized distributions of salinity in the Biscayne aquifer. The methods used in this study are relatively new, and results will provide transferable techniques for protecting groundwater resources and maximizing groundwater availability in coastal areas. The model was used to (1) evaluate the sensitivity of the salinity distribution in groundwater to sea-level rise and groundwater pumping, and (2) simulate the potential effects of increases in pumping, variable rates of sea-level rise, movement of a salinity control structure, and use of drainage recharge wells on the future distribution of salinity in the aquifer.
\nResults from the simulation of historical conditions indicate that the model generally represents the observed greater westward extent of elevated salinity in the central part of the intruded area relative to the northern and southernmost parts of the intruded area. Results of sensitivity testing indicate that the extent of elevated salinity is most sensitive to pumping in areas where the source of saltwater is largely offshore, from the Atlantic Ocean, and is most sensitive to sea-level rise in areas where the source of salinity is downward leakage of brackish water from canals.
\nSimulations of future scenarios indicate that increases in pumping near the existing interface may cause the interface to advance and decreases in pumping may cause it to retreat. Climatic effects, such as periods of prolonged drought or high precipitation, may augment or counteract long-term effects of changes in pumping on aquifer salinity at well fields. With increasing rates of sea-level rise, the freshwater-saltwater interface advances progressively inland, and flow-averaged salinities at well fields near the existing interface increase commensurately. Hypothetical southeastward (downstream) re-positioning of the existing G–54 salinity-control structure may prevent the interface from moving northwestward along and near the North New River canal, but beneficial effects are localized. Implementation of freshwater recharge wells in the city of Hallandale Beach may also have only a localized freshening effect in the aquifer and little appreciable effect on the freshwater-saltwater interface or on concentrations of salinity at well fields.
\nModel accuracy and use are limited by uncertainty in the physical properties and boundary conditions of the system, uncertainty in historical and future conditions, and generalizations made in the mathematical relationships used to describe the physical processes of groundwater flow and transport. Because of these limitations, model results should be considered in relative rather than absolute terms. Nonetheless, model results do provide useful information on the relative scale of response of the system to changes in pumping distribution, sea-level rise, and mitigation activities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165022","collaboration":"Prepared in cooperation with the Broward County Environmental Planning and Community Resilience Division","usgsCitation":"Hughes, J.D., Sifuentes, D.F., and White, J.T., 2016, Potential effects of alterations to the hydrologic system on the distribution of salinity in the Biscayne aquifer in Broward County, Florida: U.S. Geological Survey Scientific Investigations Report 2016–5022, 114 p., https://dx.doi.org/10.3133/sir20165022.","productDescription":"Report: x, 114 p.; Data Release","numberOfPages":"128","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-056536","costCenters":[{"id":269,"text":"FLWSC-Ft. 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Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
http://fl.water.usgs.gov/
The U.S. Geological Survey (USGS) collected data and simulated groundwater flow to increase understanding of the hydrology and the effects of drainage alterations on the water table in the vicinity of Great Marsh, near Beverly Shores and Town of Pines, Indiana. Prior land-management practices have modified drainage and caused changes in the distribution of open water, streams and ditches, and groundwater abundance and flow paths.
\nCollected hydrologic data indicate that the majority of water entering Great Marsh flows from the southern dune ridge beneath Town of Pines, Indiana. Groundwater flow is intercepted by Brown Ditch in the eastern portion of the study area and Derby Ditch in the western portion of the study area. A smaller amount of groundwater from the northern dune ridge beneath Beverly Shores also contributed water to Great Marsh. Continuous groundwater-level data collected indicate that the predominant north-south groundwater-flow gradients vary during the course of the year due to increased levels of precipitation or during periods of drainage obstructions. Continuous surface-water discharge and surface-water elevation were measured at three USGS streamgages, one each on Brown, Kintzele and Derby Ditches. The monthly mean discharge statistics indicate that during the period of record— June 2012 to September 2013—streamflow in Kintzele Ditch was lowest during July 2012 and highest during April 2013. In Derby Ditch, streamflow also was lowest during July 2012 and highest during April 2013.
\nPeriods of relatively high and low groundwater levels during August 1982, March 2013, and April 2014 were examined and simulated by using MODFLOW and companion software. Results from the simulation of conditions during March 2013 include that nearly 100 percent of all water entering the area simulating Town of Pines is from recharge. Of all the water simulated to enter the eastern and western portions of Great Marsh, nearly 20 and 18 percent, respectively, flows from Town of Pines to the western and eastern portions of Great Marsh. The dune ridges beneath Town of Pines and to a lesser extent beneath Beverly Shores are a major source of recharge to the surficial aquifer and Great Marsh.
\nResults from the simulation of the conditions of April 2014 include that, despite increases in the amount of water entering Great Marsh due to a beaver-dam-modified hydrologic condition, there is still virtually zero simulated groundwater flow from Great Marsh to Town of Pines. The volume of water simulated to be entering the zone representing Beverly Shores decreased by 0.43 cubic foot per second from the results of the March 2013 simulation. This simulated difference in water budgets can be attributed to increased simulated recharge in Great Marsh and Town of Pines. Effects of the inclusion of the beaver dam included the increase of the simulated water table and simulated inundated area upstream of the beaver dam due to the effects of ponding surface water.
\nResults from the simulation scenario that includes six proposed pool-riffle control structures in Brown Ditch under the hydrologic conditions of March 2013 indicate areas inundated by water are larger, including areas just to the north of the entrance of Brown Ditch into Great Marsh, and areas north of the confluence of Brown and Kintzele Ditches.
\nResults from the scenario simulating the increase of the Lake Michigan water level to the historical high of May 31, 1998, showed inundated areas of Great Marsh south of Beverly Shores enlarged on both sides of Lakeshore County Road with the greatest enlargement simulated to be southeast of the intersection of Lakeshore County Road and Beverly Drive. For the scenario simulating the decrease of the Lake Michigan water level to the historical low of December 23, 2007, results show little change from the original March 2013 inundated area.
\nThe results of this study can be used by water-resource managers to understand how surrounding ditches affect water levels in Great Marsh and other inland wetlands and residential areas. The groundwater model developed can be applied to answer questions about how alterations to the drainage system in the area affects water levels in the public and residential areas surrounding Great Marsh. The modeling methods developed in this study provide a template for other studies of groundwater flow and groundwater/surface-water interactions within the shallow surficial aquifer in northern Indiana, and in similar hydrologic settings that include surficial sand aquifers in coastal areas.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155141","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Lampe, D.C., 2015, Hydrologic data and groundwater-flow simulations in the Brown Ditch Watershed, Indiana Dunes National Lakeshore, near Beverly Shores and Town of Pines, Indiana: U.S. Geological Survey Scientific Investigations Report 2015– 5141, 97 p., https://dx.doi.org/10.3133/sir20155141.","productDescription":"xi, 97 p.","numberOfPages":"116","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-055857","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":318807,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5141/coverthb.jpg"},{"id":318808,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5141/sir20155141.pdf","text":"Report","size":"34 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5141"}],"country":"United States","state":"Indiana","otherGeospatial":"Brown Ditch Watershed, Indiana Dunes National Lakeshore","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.1,\n 41.65\n ],\n [\n -87.1,\n 41.73\n ],\n [\n -86.9,\n 41.73\n ],\n [\n -86.9,\n 41.65\n ],\n [\n -87.1,\n 41.65\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Indiana Water Science Center
U.S. Geological Survey
5957 Lakeside Blvd
Indianapolis, IN 46278
Phone: (317) 290-3333
http://in.water.usgs.gov/
Drought conditions during the study period of January 1, 2009, to September 30, 2013, caused a reduction in surface-water releases from water-supply storage infrastructure of the Rio Grande Project, which led to changes in surface-water and groundwater (conjunctive) use in downstream agricultural alluvial valleys. Surface water and groundwater in the agriculturally dominated alluvial Rincon and Mesilla Valleys were investigated in this study to measure the influence of drought and subsequent change in conjunctive water use on quantity and quality of these water resources. In 2013, the U.S. Geological Survey, in cooperation with the New Mexico Environment Department and the New Mexico Interstate Stream Commission, began a study to (1) calculate dissolved-solids loads over the study period at streamgages in the study area where data are available, (2) assess the temporal variability of dissolved-solids loads at and between each streamgage where data are available, and (3) relate the spatiotemporal variability of shallow groundwater data (groundwater levels and quality) within the alluvial valleys of the study area to spatiotemporal variability of surface-water data over the study period. This assessment included the calculation of surface-water dissolved-solids loads at streamgages as well as a mass-balance approach to measure the change in salt load between these streamgages. Bimodal surface-water discharge data led to a temporally-dynamic volumetric definition of release and nonrelease seasons. Continuous surface-water discharge and water-quality data from three streamgages on the Rio Grande were used to calculate daily dissolved-solids loads over the study period, and the results were aggregated annually and seasonally. Results show the majority of dissolved-solids loading occurs during release season; however, decreased duration of the release season over the 5-year study period has resulted in a decrease of the total annual loads at each streamgage. Calculation of the change of salt loads using a mass-balance approach was applied between streamgages. Results from these calculations suggest differing responses to releases in the Rincon and Mesilla Valleys over the period of study; there is a decreasing sink of salt in the Rincon Valley whereas there is an increasing sink of salt in the Mesilla Valley. Daily groundwater-level and water-quality data from shallow wells within the two alluvial valleys show spatial heterogeneity of water quality over the study period. Mass-balance salt-loading trends during the study period are similar to previous trends during the 1950s drought as well as a wet period in the 1980s. The similarity of salt-loading trends from the 1950s, 1980s, and 2000s independent of the climate indicates salt loading in this hydrologic setting may be driven by water-use practices rather than a single climatic variable.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165006","collaboration":"Prepared in cooperation with the New Mexico Environment Department and the New Mexico Interstate Stream Commission","usgsCitation":"Driscoll, J.M., and Sherson, L.R., 2016, Variability of surface-water quantity and quality and shallow groundwater levels and quality within the Rio Grande Project area, New Mexico and Texas, 2009–13: U.S. Geological Survey Scientific Investigations Report 2016–5006, 33 p., https://dx.doi.org/10.3133/sir20165006.","productDescription":"vi, 33 p.","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-065706","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":318886,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5006/coverthb.jpg"},{"id":318887,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5006/sir20165006.pdf","text":"Report","size":"1.66 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5006"}],"country":"United States","state":"New Mexico, Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.46826171874999,\n 31.076460800121122\n ],\n [\n -107.46826171874999,\n 33.367237465838315\n ],\n [\n -105.6060791015625,\n 33.367237465838315\n ],\n [\n -105.6060791015625,\n 31.076460800121122\n ],\n [\n -107.46826171874999,\n 31.076460800121122\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
5338 Montgomery, NE
Albuquerque, NM 87109–1311
Effective and responsible management of water resources relies on a thorough understanding of the quantity and quality of available water; however, streamgages cannot be installed at every location where streamflow information is needed. Therefore, methods for estimating streamflow at ungaged stream locations need to be developed. This report presents a statewide study to develop methods to estimate the structure of historical daily streamflow at ungaged stream locations in Minnesota. Historical daily mean streamflow at ungaged locations in Minnesota can be estimated by transferring streamflow data at streamgages to the ungaged location using the QPPQ method. The QPPQ method uses flow-duration curves at an index streamgage, relying on the assumption that exceedance probabilities are equivalent between the index streamgage and the ungaged location, and estimates the flow at the ungaged location using the estimated flow-duration curve. Flow-duration curves at ungaged locations can be estimated using recently developed regression equations that have been incorporated into StreamStats (http://streamstats.usgs.gov/), which is a U.S. Geological Survey Web-based interactive mapping tool that can be used to obtain streamflow statistics, drainage-basin characteristics, and other information for user-selected locations on streams.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155181","collaboration":"Prepared in cooperation with the Minnesota Pollution Control Agency","usgsCitation":"Lorenz, D.L., and Ziegeweid, J.R., 2016, Methods to estimate historical daily streamflow for ungaged stream locations in Minnesota: U.S. Geological Survey Scientific Investigations Report 2015–5181, 18 p., https://dx.doi.org/10.3133/sir20155181.","productDescription":"iv, 18 p.","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-068751","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":318797,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5181/coverthb.jpg"},{"id":318798,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5181/sir20155181.pdf","text":"Report","size":"2.91 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\"}}]}","contact":"Director, Minnesota Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, Minnesota 55112
Large-scale atmospheric pressure centers, such as the Aleutian and Icelandic Low, have a demonstrated relationship with physical lake characteristics in contemporary monitoring studies, but the responses to these phenomena are rarely observed in lake records. We observe coherent changes in the stratification patterns of three deep (>30 m) lakes inferred from fossil diatom assemblages as a response to shifts in the location and intensity of the Aleutian Low and compare these changes with similar long-term changes observed in the δ18O record from the Yukon. Specifically, these records indicate that between 3.2 and 1.4 ka, the Aleutian Low shifted westward, resulting in an increased frequency of storm tracks across the Pacific Northwest during winter and spring. This change in atmospheric circulation ultimately produced deeper mixing in the upper waters of these three lake systems. Enhanced stratification between 4.5 and 3.3 ka and from 1.3 ka to present suggests a strengthened Aleutian Low and more meridional circulation.
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Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Hydrologic controls on nitrogen cycling processes and functional gene abundance in sediments of a groundwater flow-through lake","docAbstract":"The fate and transport of inorganic nitrogen (N) is a critically important issue for human and aquatic ecosystem health because discharging N-contaminated groundwater can foul drinking water and cause algal blooms. Factors controlling N-processing were examined in sediments at three sites with contrasting hydrologic regimes at a lake on Cape Cod, MA. These factors included water chemistry, seepage rates and direction of groundwater flow, and the abundance and potential rates of activity of N-cycling microbial communities. Genes coding for denitrification, anaerobic ammonium oxidation (anammox), and nitrification were identified at all sites regardless of flow direction or groundwater dissolved oxygen concentrations. Flow direction was, however, a controlling factor in the potential for N-attenuation via denitrification in the sediments. Potential rates of denitrification varied from 6 to 4500 pmol N/g/h from the inflow to the outflow side of the lake, owing to fundamental differences in the supply of labile organic matter. The results of laboratory incubations suggested that when anoxia and limiting labile organic matter prevailed, the potential existed for concomitant anammox and denitrification. Where oxic lake water was downwelling, potential rates of nitrification at shallow depths were substantial (1640 pmol N/g/h). Rates of anammox, denitrification, and nitrification may be linked to rates of organic N-mineralization, serving to increase N-mobility and transport downgradient.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.5b06155","usgsCitation":"Stoliker, D., Repert, D.A., Smith, R.L., Song, B., LeBlanc, D.R., McCobb, T.D., Conaway, C.H., Hyun, S.P., Koh, D., Moon, H.S., and Kent, D.B., 2016, Hydrologic controls on nitrogen cycling processes and functional gene abundance in sediments of a groundwater flow-through lake: Environmental Science & Technology, v. 50, no. 7, p. 3649-3657, https://doi.org/10.1021/acs.est.5b06155.","productDescription":"9 p.","startPage":"3649","endPage":"3657","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071251","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology 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On average, 3,000 inland lake eTSI values are represented in each of the datasets by a process that relates field-measured Secchi-disk transparency (SDT) to Landsat satellite imagery to provide eTSI values for unsampled inland lakes. The correlation between eTSI values and field-measured Trophic State Index (TSI) values from SDT was strong as shown by R2 values from 0.71 to 0.83. Mean eTSI values ranged from 42.7 to 46.8 units, which when converted to estimated SDT (eSDT) ranged from 8.9 to 12.5 feet for the datasets. Most eTSI values for Michigan inland lakes are in the mesotrophic TSI class. The Environmental Protection Agency (EPA) Level III Ecoregions were used to illustrate and compare the spatial distribution of eTSI classes for Michigan inland lakes. Lakes in the Northern Lakes and Forests, North Central Hardwood Forests, and Southern Michigan/Northern Indiana Drift Plains ecoregions are predominantly in the mesotrophic TSI class. The Huron/Erie Lake Plains and Eastern Corn Belt Plains ecoregions, had predominantly eutrophic class lakes and also the highest percent of hypereutrophic lakes than other ecoregions in the State. Data from multiple sampling programs—including data collected by volunteers with the Cooperative Lakes Monitoring Program (CLMP) through the Michigan Department of Environmental Quality (MDEQ), and the 2007 National Lakes Assessment (NLA)—were compiled to compare the distribution of lake TSI classes between each program. The seven eTSI datasets are available for viewing and download with eSDT from the Michigan Lake Water Clarity Interactive Map Viewer at http://mi.water.usgs.gov/projects/RemoteSensing/index.html.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165023","collaboration":"Prepared in cooperation with the Michigan Department of Environmental Quality","usgsCitation":"Fuller, L.M., and Jodoin, R.S., 2016, Estimation of a Trophic State Index for selected inland lakes in Michigan, 1999–2013: U.S. Geological Survey Scientific Investigations Report 2016–5023, 16 p., https://dx.doi.org/10.3133/sir20165023.","productDescription":"vii, 16 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-067016","costCenters":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"links":[{"id":318806,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5023/sir20165023.pdf","text":"Report","size":"1.31 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 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\"}}]}","contact":"Director, Michigan Water Science Center
U.S. Geological Survey
6520 Mercantile Way, Suite 5
Lansing, MI 48911-5991
http://mi.water.usgs.gov/
Information on lake sturgeon (Acipenser fulvescens) depth and thermal habitat use during non-spawning periods is unavailable due to the difficulty of observing lake sturgeon away from shallow water spawning sites. In 2002 and 2003, lake sturgeon captured in commercial trap nets near Sarnia, Ontario were implanted with archival tags and released back into southern Lake Huron. Five of the 40 tagged individuals were recaptured and were at large for 32, 57, 286, 301, and 880 days. Temperatures and depths recorded by archival tags ranged from 0 to 23.5 ºC and 0.1 to 42.4 m, respectively. For the three lake sturgeon that were at large for over 200 days, temperatures occupied emulated seasonal fluctuations. Two of these fish occupied deeper waters during winter than summer while the other occupied similar depths during non-spawning periods. This study provides important insight into depth and thermal habitat use of lake sturgeon throughout the calendar year along with exploring the feasibility of using archival tags to obtain important physical habitat attributes during non-spawning periods.
","language":"English","publisher":"Oikos Publishers","publisherLocation":"La Crosse, WI","doi":"10.1080/02705060.2016.1152321","usgsCitation":"Briggs, A., Hondorp, D.W., Quinlan, H.R., Boase, J., and Mohr, L.C., 2016, Electronic archival tags provide first glimpse of bathythermal habitat use by free-ranging adult lake sturgeon Acipenser fulvescens: Journal of Freshwater Ecology, v. 31, no. 3, p. 477-483, https://doi.org/10.1080/02705060.2016.1152321.","productDescription":"7 p.","startPage":"477","endPage":"483","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071324","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":471154,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/02705060.2016.1152321","text":"Publisher Index Page"},{"id":326097,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Huron","volume":"31","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-11","publicationStatus":"PW","scienceBaseUri":"57a46731e4b0ebae89b63caf","contributors":{"authors":[{"text":"Briggs, Andrew S.","contributorId":32796,"corporation":false,"usgs":true,"family":"Briggs","given":"Andrew S.","affiliations":[],"preferred":false,"id":644695,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hondorp, Darryl W. 0000-0002-5182-1963 dhondorp@usgs.gov","orcid":"https://orcid.org/0000-0002-5182-1963","contributorId":5376,"corporation":false,"usgs":true,"family":"Hondorp","given":"Darryl","email":"dhondorp@usgs.gov","middleInitial":"W.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":644694,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Quinlan, Henry R.","contributorId":117465,"corporation":false,"usgs":false,"family":"Quinlan","given":"Henry","email":"","middleInitial":"R.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":644696,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boase, James C.","contributorId":72713,"corporation":false,"usgs":true,"family":"Boase","given":"James C.","affiliations":[],"preferred":false,"id":644697,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mohr, Lloyd C.","contributorId":77493,"corporation":false,"usgs":false,"family":"Mohr","given":"Lloyd","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":644698,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70184235,"text":"70184235 - 2016 - Illuminating wildfire erosion and deposition patterns with repeat terrestrial lidar","interactions":[],"lastModifiedDate":"2017-03-06T10:51:56","indexId":"70184235","displayToPublicDate":"2016-03-11T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2318,"text":"Journal of Geophysical Research F: Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Illuminating wildfire erosion and deposition patterns with repeat terrestrial lidar","docAbstract":"Erosion following a wildfire is much greater than background erosion in forests because of wildfire-induced changes to soil erodibility and water infiltration. While many previous studies have documented post-wildfire erosion with point and small plot-scale measurements, the spatial distribution of post-fire erosion patterns at the watershed scale remains largely unexplored. In this study lidar surveys were collected periodically in a small, first-order drainage basin over a period of 2 years following a wildfire. The study site was relatively steep with slopes ranging from 17° to > 30°. During the study period, several different types of rain storms occurred on the site including low-intensity frontal storms (2.4 mm h−1) and high-intensity convective thunderstorms (79 mm h−1). These storms were the dominant drivers of erosion. Erosion resulting from dry ravel and debris flows was notably absent at the site. Successive lidar surveys were subtracted from one another to obtain digital maps of topographic change between surveys. The results show an evolution in geomorphic response, such that the erosional response after rain storms was strongly influenced by the previous erosional events and pre-fire site morphology. Hillslope and channel roughness increased over time, and the watershed armored as coarse cobbles and boulders were exposed. The erosional response was spatially nonuniform; shallow erosion from hillslopes (87% of the study area) contributed 3 times more sediment volume than erosion from convergent areas (13% of the study area). However, the total normalized erosion depth (volume/area) was highest in convergent areas. From a detailed understanding of the spatial locations of erosion, we made inferences regarding the processes driving erosion. It appears that hillslope erosion is controlled by rain splash (for detachment) and overland flow (for transport and quasi-channelized erosion), with the sites of highest erosion corresponding to locations with the lowest roughness. By contrast, in convergent areas we found erosion caused by overland flow. Soil erosion was locally interrupted by immobile objects such as boulders, bedrock, or tree trunks, resulting in a patchy erosion network with increasing roughness over time.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Richmond, VA","doi":"10.1002/2015JF003600","usgsCitation":"Rengers, F.K., Tucker, G., Moody, J., and Ebel, B., 2016, Illuminating wildfire erosion and deposition patterns with repeat terrestrial lidar: Journal of Geophysical Research F: Earth Surface, v. 121, no. 3, p. 588-608, https://doi.org/10.1002/2015JF003600.","productDescription":"21 p.","startPage":"588","endPage":"608","ipdsId":"IP-068620","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":471157,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jf003600","text":"Publisher Index Page"},{"id":336854,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.403611,\n 40.030833\n ],\n [\n -105.402222,\n 40.030833\n ],\n [\n -105.402222,\n 40.032222\n ],\n [\n -105.403611,\n 40.032222\n ],\n [\n -105.403611,\n 40.030833\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"121","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-11","publicationStatus":"PW","scienceBaseUri":"58be8339e4b014cc3a3a99e5","contributors":{"authors":[{"text":"Rengers, Francis K. 0000-0002-1825-0943 frengers@usgs.gov","orcid":"https://orcid.org/0000-0002-1825-0943","contributorId":150422,"corporation":false,"usgs":true,"family":"Rengers","given":"Francis","email":"frengers@usgs.gov","middleInitial":"K.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":680682,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tucker, G.E.","contributorId":150423,"corporation":false,"usgs":false,"family":"Tucker","given":"G.E.","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":680683,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moody, J. A.","contributorId":187515,"corporation":false,"usgs":false,"family":"Moody","given":"J. A.","affiliations":[],"preferred":false,"id":680684,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ebel, Brian","contributorId":187516,"corporation":false,"usgs":false,"family":"Ebel","given":"Brian","affiliations":[],"preferred":false,"id":680685,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70170764,"text":"70170764 - 2016 - Application of effective discharge analysis to environmental flow decision-making","interactions":[],"lastModifiedDate":"2016-05-02T15:14:07","indexId":"70170764","displayToPublicDate":"2016-03-10T16:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Application of effective discharge analysis to environmental flow decision-making","docAbstract":"Well-informed river management decisions rely on an explicit statement of objectives, repeatable analyses, and a transparent system for assessing trade-offs. These components may then be applied to compare alternative operational regimes for water resource infrastructure (e.g., diversions, locks, and dams). Intra- and inter-annual hydrologic variability further complicates these already complex environmental flow decisions. Effective discharge analysis (developed in studies of geomorphology) is a powerful tool for integrating temporal variability of flow magnitude and associated ecological consequences. Here, we adapt the effectiveness framework to include multiple elements of the natural flow regime (i.e., timing, duration, and rate-of-change) as well as two flow variables. We demonstrate this analytical approach using a case study of environmental flow management based on long-term (60 years) daily discharge records in the Middle Oconee River near Athens, GA, USA. Specifically, we apply an existing model for estimating young-of-year fish recruitment based on flow-dependent metrics to an effective discharge analysis that incorporates hydrologic variability and multiple focal taxa. We then compare three alternative methods of environmental flow provision. Percentage-based withdrawal schemes outcompete other environmental flow methods across all levels of water withdrawal and ecological outcomes.
","language":"English","publisher":"Springer-Verlag","publisherLocation":"New York","doi":"10.1007/s00267-016-0684-4","usgsCitation":"McKay, S.K., Freeman, M., and Covich, A., 2016, Application of effective discharge analysis to environmental flow decision-making: Environmental Management, v. 575, no. 6, p. 1153-1165, https://doi.org/10.1007/s00267-016-0684-4.","productDescription":"13 p.","startPage":"1153","endPage":"1165","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073347","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":320849,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"575","issue":"6","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-10","publicationStatus":"PW","scienceBaseUri":"57287a2be4b0b13d391865af","contributors":{"authors":[{"text":"McKay, S. Kyle","contributorId":169086,"corporation":false,"usgs":false,"family":"McKay","given":"S.","email":"","middleInitial":"Kyle","affiliations":[],"preferred":false,"id":628390,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":628391,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Covich, A.P.","contributorId":14965,"corporation":false,"usgs":true,"family":"Covich","given":"A.P.","email":"","affiliations":[],"preferred":false,"id":628392,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70169085,"text":"70169085 - 2016 - Ecology, distribution, and predictive occurrence modeling of Palmers chipmunk (Tamias palmeri): a high-elevation small mammal endemic to the Spring Mountains in southern Nevada, USA","interactions":[],"lastModifiedDate":"2016-12-16T11:08:53","indexId":"70169085","displayToPublicDate":"2016-03-10T14:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2373,"text":"Journal of Mammalogy","onlineIssn":"1545-1542","printIssn":"0022-2372","active":true,"publicationSubtype":{"id":10}},"title":"Ecology, distribution, and predictive occurrence modeling of Palmers chipmunk (Tamias palmeri): a high-elevation small mammal endemic to the Spring Mountains in southern Nevada, USA","docAbstract":"Although montane sky islands surrounded by desert scrub and shrub steppe comprise a large part of the biological diversity of the Basin and Range Province of southwestern North America, comprehensive ecological and population demographic studies for high-elevation small mammals within these areas are rare. Here, we examine the ecology and population parameters of the Palmer’s chipmunk (Tamias palmeri) in the Spring Mountains of southern Nevada, and present a predictive GIS-based distribution and probability of occurrence model at both home range and geographic spatial scales. Logistic regression analyses and Akaike Information Criterion model selection found variables of forest type, slope, and distance to water sources as predictive of chipmunk occurrence at the geographic scale. At the home range scale, increasing population density, decreasing overstory canopy cover, and decreasing understory canopy cover contributed to increased survival rates.
","language":"English","publisher":"American Society of Mammalogists","publisherLocation":"Lawrence, KS","doi":"10.1093/jmammal/gyw026","usgsCitation":"Lowrey, C.E., Longshore, K.M., Riddle, B., and Mantooth, S., 2016, Ecology, distribution, and predictive occurrence modeling of Palmers chipmunk (Tamias palmeri): a high-elevation small mammal endemic to the Spring Mountains in southern Nevada, USA: Journal of Mammalogy, v. 97, no. 4, p. 1033-1043, https://doi.org/10.1093/jmammal/gyw026.","productDescription":"11 p.","startPage":"1033","endPage":"1043","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-028807","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":471159,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jmammal/gyw026","text":"Publisher Index Page"},{"id":318914,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Spring Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.08428955078125,\n 36.53832942872816\n ],\n [\n -116.070556640625,\n 36.45884507478879\n ],\n [\n -115.99090576171875,\n 36.34610265300638\n ],\n [\n -115.95520019531249,\n 36.27085020723905\n ],\n [\n -115.9002685546875,\n 36.24870331653198\n ],\n [\n -115.81512451171876,\n 36.16448788632064\n ],\n [\n -115.74920654296874,\n 36.06686213257888\n ],\n [\n -115.67230224609374,\n 36.01133890448606\n ],\n [\n -115.59814453125001,\n 35.96022296929667\n ],\n [\n -115.56243896484374,\n 35.88237433729238\n ],\n [\n -115.4168701171875,\n 35.84230806912384\n ],\n [\n -115.32073974609375,\n 35.82226734114509\n ],\n [\n -115.33172607421876,\n 35.89795019335754\n ],\n [\n -115.33721923828125,\n 35.96022296929667\n ],\n [\n -115.33447265625,\n 36.06464195517141\n ],\n [\n -115.31249999999999,\n 36.16005298551354\n ],\n [\n -115.29052734375,\n 36.24648828212654\n ],\n [\n -115.29602050781249,\n 36.33725319397006\n ],\n [\n -115.3839111328125,\n 36.348314860643015\n ],\n [\n -115.3839111328125,\n 36.416862115300304\n ],\n [\n -115.39764404296875,\n 36.485348924361425\n ],\n [\n -115.49652099609375,\n 36.48314061639213\n ],\n [\n -115.5706787109375,\n 36.416862115300304\n ],\n [\n -115.6475830078125,\n 36.405810193726765\n ],\n [\n -115.72174072265626,\n 36.41465185677698\n ],\n [\n -115.76843261718751,\n 36.50301312197295\n ],\n [\n -115.84259033203124,\n 36.52950186333475\n ],\n [\n -115.93872070312499,\n 36.52950186333475\n ],\n [\n -116.01562499999999,\n 36.542742833547834\n ],\n [\n -116.08428955078125,\n 36.53832942872816\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"97","issue":"4","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-10","publicationStatus":"PW","scienceBaseUri":"56ea83ace4b0f59b85d90ce2","chorus":{"doi":"10.1093/jmammal/gyw026","url":"http://dx.doi.org/10.1093/jmammal/gyw026","publisher":"Oxford University Press (OUP)","authors":"Lowrey Christopher, Longshore Kathleen, Riddle Brett, Mantooth Stacy","journalName":"Journal of Mammalogy","publicationDate":"3/10/2016"},"contributors":{"authors":[{"text":"Lowrey, Chris E. 0000-0001-5084-7275 clowrey@usgs.gov","orcid":"https://orcid.org/0000-0001-5084-7275","contributorId":3225,"corporation":false,"usgs":true,"family":"Lowrey","given":"Chris","email":"clowrey@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":622836,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Longshore, Kathleen M. 0000-0001-6621-1271 longshore@usgs.gov","orcid":"https://orcid.org/0000-0001-6621-1271","contributorId":2677,"corporation":false,"usgs":true,"family":"Longshore","given":"Kathleen","email":"longshore@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":622835,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Riddle, Brett R.","contributorId":93016,"corporation":false,"usgs":true,"family":"Riddle","given":"Brett R.","affiliations":[],"preferred":false,"id":622837,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mantooth, Stacy","contributorId":167608,"corporation":false,"usgs":false,"family":"Mantooth","given":"Stacy","email":"","affiliations":[{"id":24777,"text":"Nevada State College","active":true,"usgs":false}],"preferred":false,"id":622838,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70169123,"text":"70169123 - 2016 - Stress in mangrove forests: early detection and preemptive rehabilitation are essential for future successful worldwide mangrove forest management","interactions":[],"lastModifiedDate":"2016-08-25T10:26:16","indexId":"70169123","displayToPublicDate":"2016-03-10T12:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2676,"text":"Marine Pollution Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Stress in mangrove forests: early detection and preemptive rehabilitation are essential for future successful worldwide mangrove forest management","docAbstract":"Mangrove forest rehabilitation should begin much sooner than at the point of catastrophic loss. We describe the need for “mangrove forest heart attack prevention”, and how that might be accomplished in a general sense by embedding plot and remote sensing monitoring within coastal management plans. The major cause of mangrove stress at many sites globally is often linked to reduced tidal flows and exchanges. Blocked water flows can reduce flushing not only from the seaward side, but also result in higher salinity and reduced sediments when flows are blocked landward. Long-term degradation of function leads to acute mortality prompted by acute events, but created by a systematic propensity for long-term neglect of mangroves. Often, mangroves are lost within a few years; however, vulnerability is re-set decades earlier when seemingly innocuous hydrological modifications are made (e.g., road construction, blocked tidal channels), but which remain undetected without reasonable large-scale monitoring.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Marine Pollution Bulletin","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.marpolbul.2016.03.006","usgsCitation":"Lewis, R.R., Milbrandt, E.C., Brown, B., Krauss, K.W., Rovai, A.S., Beever, J.W., and Flynn, L., 2016, Stress in mangrove forests: early detection and preemptive rehabilitation are essential for future successful worldwide mangrove forest management: Marine Pollution Bulletin, v. 109, no. 2, p. 764-771, https://doi.org/10.1016/j.marpolbul.2016.03.006.","productDescription":"8 p.","startPage":"764","endPage":"771","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070524","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":319080,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Worldwide","volume":"109","issue":"2","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56f11b70e4b0f59b85ddc517","contributors":{"authors":[{"text":"Lewis, Roy R","contributorId":167668,"corporation":false,"usgs":false,"family":"Lewis","given":"Roy","email":"","middleInitial":"R","affiliations":[{"id":24798,"text":"Coastal Resources Group, Salt Springs, FL","active":true,"usgs":false}],"preferred":false,"id":623077,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Milbrandt, Eric C","contributorId":167669,"corporation":false,"usgs":false,"family":"Milbrandt","given":"Eric","email":"","middleInitial":"C","affiliations":[{"id":24799,"text":"Sanibel-Captiva Conservation Foundation, Sanibel, FL","active":true,"usgs":false}],"preferred":false,"id":623078,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Benjamin","contributorId":167670,"corporation":false,"usgs":false,"family":"Brown","given":"Benjamin","email":"","affiliations":[{"id":24800,"text":"Charles Darwin University, Research Institute for Environment and Livelihoolds, AUS","active":true,"usgs":false}],"preferred":false,"id":623079,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":623076,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rovai, Andre S.","contributorId":167671,"corporation":false,"usgs":false,"family":"Rovai","given":"Andre","email":"","middleInitial":"S.","affiliations":[{"id":24801,"text":"Federal University of Santa Catarina, Dept. Ecology and Zoology, Brazil","active":true,"usgs":false}],"preferred":false,"id":623080,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Beever, James W.","contributorId":167672,"corporation":false,"usgs":false,"family":"Beever","given":"James","email":"","middleInitial":"W.","affiliations":[{"id":24802,"text":"Southwest Florida Regional Planning Council, Fort Myers, FL","active":true,"usgs":false}],"preferred":false,"id":623081,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Flynn, Laura L","contributorId":167673,"corporation":false,"usgs":false,"family":"Flynn","given":"Laura L","affiliations":[{"id":24798,"text":"Coastal Resources Group, Salt Springs, FL","active":true,"usgs":false}],"preferred":false,"id":623082,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70169007,"text":"70169007 - 2016 - Online induction heating for determination of isotope composition of woody stem water with laser spectrometry: A methods assessment","interactions":[],"lastModifiedDate":"2017-11-22T17:39:15","indexId":"70169007","displayToPublicDate":"2016-03-10T11:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2114,"text":"Isotopes in Environmental and Health Studies","active":true,"publicationSubtype":{"id":10}},"title":"Online induction heating for determination of isotope composition of woody stem water with laser spectrometry: A methods assessment","docAbstract":"Application of stable isotopes of water to studies of plant–soil interactions often requires a substantial preparatory step of extracting water from samples without fractionating isotopes. Online heating is an emerging approach for this need, but is relatively untested and major questions of how to best deliver standards and assess interference by organics have not been evaluated. We examined these issues in our application of measuring woody stem xylem of sagebrush using a Picarro laser spectrometer with online induction heating. We determined (1) effects of cryogenic compared to induction-heating extraction, (2) effects of delivery of standards on filter media compared to on woody stem sections, and (3) spectral interference from organic compounds for these approaches (and developed a technique to do so). Our results suggest that matching sample and standard media improves accuracy, but that isotopic values differ with the extraction method in ways that are not due to spectral interference from organics.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/10256016.2016.1141205","usgsCitation":"Lazarus, B.E., Germino, M., and Vander Veen, J.L., 2016, Online induction heating for determination of isotope composition of woody stem water with laser spectrometry: A methods assessment: Isotopes in Environmental and Health Studies, v. 52, no. 3, p. 309-325, https://doi.org/10.1080/10256016.2016.1141205.","productDescription":"17 p.","startPage":"309","endPage":"325","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063959","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":318824,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-10","publicationStatus":"PW","scienceBaseUri":"56e3fa58e4b0f59b85d4946d","contributors":{"authors":[{"text":"Lazarus, Brynne E. 0000-0002-6352-486X blazarus@usgs.gov","orcid":"https://orcid.org/0000-0002-6352-486X","contributorId":4901,"corporation":false,"usgs":true,"family":"Lazarus","given":"Brynne","email":"blazarus@usgs.gov","middleInitial":"E.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":622488,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Germino, Matthew J. 0000-0001-6326-7579 mgermino@usgs.gov","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":152582,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","email":"mgermino@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":622487,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vander Veen, Jessica L.","contributorId":167500,"corporation":false,"usgs":false,"family":"Vander Veen","given":"Jessica","email":"","middleInitial":"L.","affiliations":[{"id":24728,"text":"USGS FRESC","active":true,"usgs":false}],"preferred":false,"id":622489,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70168923,"text":"70168923 - 2016 - Does water chemistry limit the distribution of New Zealand mud snails in Redwood National Park?","interactions":[],"lastModifiedDate":"2016-06-02T11:02:21","indexId":"70168923","displayToPublicDate":"2016-03-10T11:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Does water chemistry limit the distribution of New Zealand mud snails in Redwood National Park?","docAbstract":"New Zealand mud snails (NZMS) are exotic mollusks present in many waterways of the western United States. In 2009, NZMS were detected in Redwood Creek in Redwood National Park, CA. Although NZMS are noted for their ability to rapidly increase in abundance and colonize new areas, after more than 5 years in Redwood Creek, their distribution remains limited to a ca. 300 m reach. Recent literature suggests that low specific conductivity and environmental calcium can limit NZMS distribution. We conducted laboratory experiments, exposing NZMS collected from Redwood Creek to both natural waters and artificial treatment solutions, to determine if low conductivity and calcium concentration limit the distribution of NZMS in Redwood National Park. For natural water exposures, we held NZMS in water from their source location (conductivity 135 μS/cm, calcium 13 mg/L) or water from four other locations in the Redwood Creek watershed encompassing a range of conductivity (77–158 μS/cm) and calcium concentration (<5–13 mg/L). For exposures in treatment solutions, we manipulated both conductivity (range 20–200 μS/cm) and calcium concentration (range <5–17.5 mg/L) in a factorial design. Response variables measured included mortality and reproductive output. Adult NZMS survived for long periods (>4 months) in the lowest conductivity waters from Redwood Creek and all but the lowest-conductivity treatment solutions, regardless of calcium concentration. However, reproductive output was very low in all natural waters and all low-calcium treatment solutions. Our results suggest that water chemistry may inhibit the spread of NZMS in Redwood National Park by reducing their reproductive output.
","language":"English","publisher":"Springer","doi":"10.1007/s10530-016-1098-1","usgsCitation":"Vazquez, R., Ward, D.M., and Sepulveda, A.J., 2016, Does water chemistry limit the distribution of New Zealand mud snails in Redwood National Park?: Biological Invasions, v. 18, no. 6, p. 1523-1531, https://doi.org/10.1007/s10530-016-1098-1.","productDescription":"9 p.","startPage":"1523","endPage":"1531","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070980","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":318785,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Redwood Creek, Redwood National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.05349731445312,\n 41.10470834043821\n ],\n [\n -124.05349731445312,\n 41.30411857136123\n ],\n [\n -123.91891479492186,\n 41.30411857136123\n ],\n [\n -123.91891479492186,\n 41.10470834043821\n ],\n [\n -124.05349731445312,\n 41.10470834043821\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"18","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-05","publicationStatus":"PW","scienceBaseUri":"56e29aade4b0f59b85d32753","contributors":{"authors":[{"text":"Vazquez, Ryan","contributorId":167388,"corporation":false,"usgs":false,"family":"Vazquez","given":"Ryan","email":"","affiliations":[{"id":24705,"text":"Department of Fisheries Biology, Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":622122,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ward, Darren M.","contributorId":167389,"corporation":false,"usgs":false,"family":"Ward","given":"Darren","email":"","middleInitial":"M.","affiliations":[{"id":24705,"text":"Department of Fisheries Biology, Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":622123,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sepulveda, Adam J. 0000-0001-7621-7028 asepulveda@usgs.gov","orcid":"https://orcid.org/0000-0001-7621-7028","contributorId":150628,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Adam","email":"asepulveda@usgs.gov","middleInitial":"J.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":622121,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70168968,"text":"70168968 - 2016 - The differing biogeochemical and microbial signatures of glaciers and rock glaciers","interactions":[],"lastModifiedDate":"2018-02-22T11:30:49","indexId":"70168968","displayToPublicDate":"2016-03-10T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2319,"text":"Journal of Geophysical Research G: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"The differing biogeochemical and microbial signatures of glaciers and rock glaciers","docAbstract":"Glaciers and rock glaciers supply water and bioavailable nutrients to headwater mountain lakes and streams across all regions of the American West. Here we present a comparative study of the metal, nutrient, and microbial characteristics of glacial and rock glacial influence on headwater ecosystems in three mountain ranges of the contiguous U.S.: The Cascade Mountains, Rocky Mountains, and Sierra Nevada. Several meltwater characteristics (water temperature, conductivity, pH, heavy metals, nutrients, complexity of dissolved organic matter (DOM), and bacterial richness and diversity) differed significantly between glacier and rock glacier meltwaters, while other characteristics (Ca2+, Fe3+, SiO2 concentrations, reactive nitrogen, and microbial processing of DOM) showed distinct trends between mountain ranges regardless of meltwater source. Some characteristics were affected both by glacier type and mountain range (e.g. temperature, ammonium (NH4+) and nitrate (NO3- ) concentrations, bacterial diversity). Due to the ubiquity of rock glaciers and the accelerating loss of the low latitude glaciers our results point to the important and changing influence that these frozen features place on headwater ecosystems.
","language":"English","publisher":"Wiley","doi":"10.1002/2015JG003236","usgsCitation":"Fegel, T.S., Baron, J., Fountain, A.G., Johnson, G.F., and Hall, E.K., 2016, The differing biogeochemical and microbial signatures of glaciers and rock glaciers: Journal of Geophysical Research G: Biogeosciences, v. 121, no. 3, p. 919-932, https://doi.org/10.1002/2015JG003236.","productDescription":"14 p.","startPage":"919","endPage":"932","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069738","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":471161,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jg003236","text":"Publisher Index Page"},{"id":318781,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Colorado, Oregon, Washington, Wyoming","otherGeospatial":"Cascade Mountains, Sierra Nevada, Rocky Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.8046875,\n 34.08906131584996\n ],\n [\n -124.8046875,\n 49.03786794532644\n ],\n [\n -105.46875,\n 49.03786794532644\n ],\n [\n -105.46875,\n 34.08906131584996\n ],\n [\n -124.8046875,\n 34.08906131584996\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"121","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-29","publicationStatus":"PW","scienceBaseUri":"56e29aafe4b0f59b85d3275b","contributors":{"authors":[{"text":"Fegel, Timothy S.","contributorId":167462,"corporation":false,"usgs":false,"family":"Fegel","given":"Timothy","email":"","middleInitial":"S.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":622415,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baron, Jill 0000-0002-5902-6251 jill_baron@usgs.gov","orcid":"https://orcid.org/0000-0002-5902-6251","contributorId":194124,"corporation":false,"usgs":true,"family":"Baron","given":"Jill","email":"jill_baron@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":622414,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fountain, Andrew G.","contributorId":10410,"corporation":false,"usgs":false,"family":"Fountain","given":"Andrew","email":"","middleInitial":"G.","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":622416,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Gunnar F.","contributorId":167464,"corporation":false,"usgs":false,"family":"Johnson","given":"Gunnar","email":"","middleInitial":"F.","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":622417,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hall, Edward K. ehall@usgs.gov","contributorId":4837,"corporation":false,"usgs":true,"family":"Hall","given":"Edward","email":"ehall@usgs.gov","middleInitial":"K.","affiliations":[],"preferred":true,"id":622418,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70169000,"text":"70169000 - 2016 - Organic contaminants in Great Lakes tributaries: Prevalence and potential aquatic toxicity","interactions":[],"lastModifiedDate":"2016-03-10T09:59:17","indexId":"70169000","displayToPublicDate":"2016-03-10T10:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Organic contaminants in Great Lakes tributaries: Prevalence and potential aquatic toxicity","docAbstract":"Organic compounds used in agriculture, industry, and households make their way into surface waters through runoff, leaking septic-conveyance systems, regulated and unregulated discharges, and combined sewer overflows, among other sources. Concentrations of these organic waste compounds (OWCs) in some Great Lakes tributaries indicate a high potential for adverse impacts on aquatic organisms. During 2010–13, 709 water samples were collected at 57 tributaries, together representing approximately 41% of the total inflow to the lakes. Samples were collected during runoff and low-flow conditions and analyzed for 69 OWCs, including herbicides, insecticides, polycyclic aromatic hydrocarbons, plasticizers, antioxidants, detergent metabolites, fire retardants, non-prescription human drugs, flavors/fragrances, and dyes. Urban-related land cover characteristics were the most important explanatory variables of concentrations of many OWCs. Compared to samples from nonurban watersheds (< 15% urban land cover) samples from urban watersheds (> 15% urban land cover) had nearly four times the number of detected compounds and four times the total sample concentration, on average. Concentration differences between runoff and low-flow conditions were not observed, but seasonal differences were observed in atrazine, metolachlor, DEET, and HHCB concentrations. Water quality benchmarks for individual OWCs were exceeded at 20 sites, and at 7 sites benchmarks were exceeded by a factor of 10 or more. The compounds with the most frequent water quality benchmark exceedances were the PAHs benzo[a]pyrene, pyrene, fluoranthene, and anthracene, the detergent metabolite 4-nonylphenol, and the herbicide atrazine. Computed estradiol equivalency quotients (EEQs) using only nonsteroidal endocrine-active compounds indicated medium to high risk of estrogenic effects (intersex or vitellogenin induction) at 10 sites. EEQs at 3 sites were comparable to values reported in effluent. This multifaceted study is the largest, most comprehensive assessment of the occurrence and potential effects of OWCs in the Great Lakes Basin to date.
","language":"English","doi":"10.1016/j.scitotenv.2016.02.137","usgsCitation":"Baldwin, A.K., Corsi, S., De Cicco, L., Lenaker, P.L., Lutz, M.A., Sullivan, D.J., and Richards, K.D., 2016, Organic contaminants in Great Lakes tributaries: Prevalence and potential aquatic toxicity: Science of the Total Environment, v. 554-555, p. 42-52, https://doi.org/10.1016/j.scitotenv.2016.02.137.","productDescription":"11 p.","startPage":"42","endPage":"52","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073075","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":471162,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.02.137","text":"Publisher Index Page"},{"id":318776,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.63671875,\n 41.44272637767212\n ],\n [\n -92.63671875,\n 48.951366470947725\n ],\n [\n -75.76171875,\n 48.951366470947725\n ],\n [\n -75.76171875,\n 41.44272637767212\n ],\n [\n -92.63671875,\n 41.44272637767212\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"554-555","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56e29aaee4b0f59b85d32759","contributors":{"authors":[{"text":"Baldwin, Austin K. 0000-0002-6027-3823 akbaldwi@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3823","contributorId":4515,"corporation":false,"usgs":true,"family":"Baldwin","given":"Austin","email":"akbaldwi@usgs.gov","middleInitial":"K.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":622453,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Corsi, Steven R. srcorsi@usgs.gov","contributorId":511,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven R.","email":"srcorsi@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":622454,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"De Cicco, Laura A. 0000-0002-3915-9487 ldecicco@usgs.gov","orcid":"https://orcid.org/0000-0002-3915-9487","contributorId":4814,"corporation":false,"usgs":true,"family":"De Cicco","given":"Laura A.","email":"ldecicco@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":622455,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lenaker, Peter L. 0000-0002-9469-6285 plenaker@usgs.gov","orcid":"https://orcid.org/0000-0002-9469-6285","contributorId":5572,"corporation":false,"usgs":true,"family":"Lenaker","given":"Peter","email":"plenaker@usgs.gov","middleInitial":"L.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":622456,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lutz, Michelle A. malutz@usgs.gov","contributorId":167259,"corporation":false,"usgs":true,"family":"Lutz","given":"Michelle","email":"malutz@usgs.gov","middleInitial":"A.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":622457,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sullivan, Daniel J. 0000-0003-2705-3738 djsulliv@usgs.gov","orcid":"https://orcid.org/0000-0003-2705-3738","contributorId":1703,"corporation":false,"usgs":true,"family":"Sullivan","given":"Daniel","email":"djsulliv@usgs.gov","middleInitial":"J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":622458,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Richards, Kevin D. krichard@usgs.gov","contributorId":280,"corporation":false,"usgs":true,"family":"Richards","given":"Kevin","email":"krichard@usgs.gov","middleInitial":"D.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":622459,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70169001,"text":"70169001 - 2016 - Application of lime (CaCO3) to promote forest recovery from severe acidification increases potential for earthworm invasion","interactions":[],"lastModifiedDate":"2016-08-17T11:06:43","indexId":"70169001","displayToPublicDate":"2016-03-10T10:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Application of lime (CaCO3) to promote forest recovery from severe acidification increases potential for earthworm invasion","docAbstract":"The application of lime (calcium carbonate) may be a cost-effective strategy to promote forest ecosystem recovery from acid impairment, under contemporary low levels of acidic deposition. However, liming acidified soils may create more suitable habitat for invasive earthworms that cause significant damage to forest floor communities and may disrupt ecosystem processes. We investigated the potential effects of liming in acidified soils where earthworms are rare in conjunction with a whole-ecosystem liming experiment in the chronically acidified forests of the western Adirondacks (USA). Using a microcosm experiment that replicated the whole-ecosystem treatment, we evaluated effects of soil liming on Lumbricus terrestris survivorship and biomass growth. We found that a moderate lime application (raising pH from 3.1 to 3.7) dramatically increased survival and biomass of L. terrestris, likely via increases in soil pH and associated reductions in inorganic aluminum, a known toxin. Very few L. terrestris individuals survived in unlimed soils, whereas earthworms in limed soils survived, grew, and rapidly consumed leaf litter. We supplemented this experiment with field surveys of extant earthworm communities along a gradient of soil pH in Adirondack hardwood forests, ranging from severely acidified (pH < 3) to well-buffered (pH > 5). In the field, no earthworms were observed where soil pH < 3.6. Abundance and species richness of earthworms was greatest in areas where soil pH > 4.4 and human dispersal vectors, including proximity to roads and public fishing access, were most prevalent. Overall our results suggest that moderate lime additions can be sufficient to increase earthworm invasion risk where dispersal vectors are present.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2016.03.002","usgsCitation":"Homan, C., Beirer, C.M., McCay, T.S., and Lawrence, G.B., 2016, Application of lime (CaCO3) to promote forest recovery from severe acidification increases potential for earthworm invasion: Forest Ecology and Management, v. 368, p. 39-44, https://doi.org/10.1016/j.foreco.2016.03.002.","productDescription":"6 p.","startPage":"39","endPage":"44","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071766","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":471165,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2016.03.002","text":"Publisher Index Page"},{"id":318768,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Honnedaga Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.87268447875977,\n 43.50423881694708\n ],\n [\n -74.87268447875977,\n 43.53672718543221\n ],\n [\n -74.79852676391602,\n 43.53672718543221\n ],\n [\n -74.79852676391602,\n 43.50423881694708\n ],\n [\n -74.87268447875977,\n 43.50423881694708\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"368","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56e29aaae4b0f59b85d3274d","chorus":{"doi":"10.1016/j.foreco.2016.03.002","url":"http://dx.doi.org/10.1016/j.foreco.2016.03.002","publisher":"Elsevier BV","authors":"Homan Caitlin, Beier Colin, McCay Timothy, Lawrence Gregory","journalName":"Forest Ecology and Management","publicationDate":"5/2016"},"contributors":{"authors":[{"text":"Homan, Caitlin","contributorId":167484,"corporation":false,"usgs":false,"family":"Homan","given":"Caitlin","email":"","affiliations":[{"id":24722,"text":"Graduate Student, SUNY College of Environmental Science & Forestry","active":true,"usgs":false}],"preferred":false,"id":622462,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beirer, Colin M","contributorId":167485,"corporation":false,"usgs":false,"family":"Beirer","given":"Colin","email":"","middleInitial":"M","affiliations":[{"id":24723,"text":"Associate Professor, Forest & Natural Resources, SUNY College of ESF","active":true,"usgs":false}],"preferred":false,"id":622463,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCay, Timothy S","contributorId":167486,"corporation":false,"usgs":false,"family":"McCay","given":"Timothy","email":"","middleInitial":"S","affiliations":[{"id":24724,"text":"Professor of Biology & Environmental Studies, Colgate University","active":true,"usgs":false}],"preferred":false,"id":622464,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lawrence, Gregory B. 0000-0002-8035-2350 glawrenc@usgs.gov","orcid":"https://orcid.org/0000-0002-8035-2350","contributorId":867,"corporation":false,"usgs":true,"family":"Lawrence","given":"Gregory","email":"glawrenc@usgs.gov","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":622461,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70157168,"text":"ds69GG - 2016 - Assessment of undiscovered hydrocarbon resources of sub-Saharan Africa","interactions":[],"lastModifiedDate":"2016-06-08T09:28:17","indexId":"ds69GG","displayToPublicDate":"2016-03-10T10:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"69","chapter":"GG","title":"Assessment of undiscovered hydrocarbon resources of sub-Saharan Africa","docAbstract":"The main objective of the U.S. Geological Survey’s (USGS) National and Global Petroleum Assessment Project is to assess the potential for undiscovered, technically recoverable oil and natural gas resources of the United States and the world (U.S. Geological Survey World Conventional Resources Assessment Team, 2012). The USGS updated assessments that were completed during the USGS World Petroleum Assessment 2000 (U.S. Geological Survey World Energy Assessment Team, 2000) and conducted new assessments in areas around the world that were not previously examined (U.S. Geological Survey World Conventional Resources Assessment Team, 2012). These assessments used the latest geology-based assessment methodology for conventional oil and gas resources. The new assessments are available at the USGS website, (http://energy.usgs.gov/OilGas/AssessmentsData/WorldPetroleumAssessment.aspx).
\nAs part of this project, the USGS assessed 13 geologic provinces located in sub-Saharan Africa (U.S. Geological Survey World Conventional Resources Assessment Team, 2012). Coastal provinces were extended offshore to water depths ranging from 2,000 to 4,000 meters (m). Within these 13 geologic provinces 18 assessment units (figs. 1, 2) were identified.
\nThe west Africa provinces are (1) the Senegal, containing the passive-margin Senegal Basin of Middle Jurassic to Holocene age; (2) the West African Coastal, characterized by rift, passive-margin, and transform tectonics; (3) the Gulf of Guinea, characterized by transform tectonics; (4) the Niger Delta, containing more than 9,100 m of sedimentary rock and recent sediments; (5) the West-Central Coastal, which contains the Aptian salt basin, is dominated by both rift and sag tectonics, and includes the Congo Basin; and (6) the Orange River Coastal, containing more than 7,000 m of syn-rift and post-rift sedimentary rock. The West African Coastal Province was assessed for the first time, whereas the other five west Africa provinces were reassessed for the 2012 World Oil and Wandrey Gas Resource Assessment (fig. 1 of U.S. Geological Survey World Conventional Resources Assessment Team, 2012). More than 275 new oil and gas fields have been discovered in the six west Africa provinces (IHS Energy, 2008, 2009) since the USGS World Petroleum Assessment in 2000 (U.S. Geological Survey World Energy Assessment Team, 2000). These provinces were assessed because of increased energy exploration activity and new oil and gas discoveries within the provinces.
\nSeven provinces not assessed as part of the World Petroleum Assessment 2000 (U.S. Geological Survey World Energy Assessment Team, 2000) were assessed by the USGS as part of the World Assessment 2012 (U.S. Geological Survey World Conventional Resources Assessment Team, 2012). These provinces are (1) the Chad Province, containing Cretaceous and Cenozoic-age lacustrine, continental, and minor marine rocks; (2) the Sud Province, containing Cretaceous and Paleogene age lacustrine, continental, and minor marine rocks; (3) the South Africa Coastal Province, which contains rift, transform, and passive-margin rocks; (4) the Mozambique Coastal Province, containing rift, drift, and passive-margin rocks; (5) the Morondava Province, which contains failed rift, drift, and passive-margin rocks; (6) the Tanzania Coastal Province, containing rift, drift, and passive-margin rocks; and (7) the Seychelles Province, which contains rift and drift rocks. At the time of this assessment 157 oil and gas fields had been discovered in the seven provinces (IHS Energy, 2009). These provinces were assessed because of increased interest and new oil and gas discoveries within the provinces.
\nThe assessment was geology-based and used the total petroleum system (TPS) concept. The geologic elements of a TPS are hydrocarbon source rocks (source rock maturation and hydrocarbon generation and migration), reservoir rocks (quality and distribution), and traps where hydrocarbon accumulates. Using these geologic criteria, 16 conventional total petroleum systems and 18 assessment units in the 13 provinces were defined. The undiscovered, technically recoverable oil and gas resources were assessed for all assessment units.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds69GG","usgsCitation":"Brownfield, M.E., 2016, Assessment of undiscovered hydrocarbon resources of sub-Saharan Africa: U.S. Geological Survey Data Series 69, 16 Chapters, https://doi.org/10.3133/ds69GG.","productDescription":"16 Chapters","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-049174","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":318763,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds69GG.PNG"},{"id":318758,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/dds/dds-069/dds-069-gg/"}],"otherGeospatial":"Africa, Sub-Saharan Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -12.83203125,\n 27.68352808378776\n ],\n [\n -8.4375,\n 27.68352808378776\n ],\n [\n 5.09765625,\n 18.812717856407776\n ],\n [\n 11.25,\n 23.56398712845123\n ],\n [\n 14.765625,\n 22.59372606392931\n ],\n [\n 16.34765625,\n 23.88583769986199\n ],\n [\n 24.2578125,\n 19.31114335506464\n ],\n [\n 25.3125,\n 22.105998799750576\n ],\n [\n 36.38671875,\n 22.26876403907398\n ],\n [\n 38.14453125,\n 17.978733095556183\n ],\n [\n 43.2421875,\n 12.897489183755905\n ],\n [\n 43.9453125,\n 11.178401873711785\n ],\n [\n 48.69140625,\n 12.21118019150401\n ],\n [\n 51.328125,\n 12.554563528593656\n ],\n [\n 50.09765625,\n 7.36246686553575\n ],\n [\n 44.6484375,\n 1.2303741774326145\n ],\n [\n 40.42968749999999,\n -2.986927393334863\n ],\n [\n 39.55078125,\n -6.664607562172573\n ],\n [\n 40.78125,\n -11.005904459659451\n ],\n [\n 40.95703125,\n -14.94478487508836\n ],\n [\n 38.84765625,\n -17.811456088564473\n ],\n [\n 34.98046875,\n -20.13847031245114\n ],\n [\n 35.859375,\n -22.593726063929296\n ],\n [\n 35.15625,\n -25.48295117535531\n ],\n [\n 33.22265625,\n -25.95804467331783\n ],\n [\n 33.046875,\n -28.459033019728043\n ],\n [\n 28.30078125,\n -32.69486597787506\n ],\n [\n 24.08203125,\n -33.87041555094183\n ],\n [\n 19.51171875,\n -34.74161249883172\n ],\n [\n 16.69921875,\n -33.43144133557529\n ],\n [\n 16.875,\n -30.902224705171427\n ],\n [\n 14.94140625,\n -27.059125784374054\n ],\n [\n 13.886718749999998,\n -22.431340156360594\n ],\n [\n 11.25,\n -17.97873309555617\n ],\n [\n 10.8984375,\n -14.264383087562637\n ],\n [\n 13.18359375,\n -11.178401873711785\n ],\n [\n 12.3046875,\n -6.140554782450295\n ],\n [\n 8.4375,\n -1.4061088354351468\n ],\n [\n 8.61328125,\n 1.7575368113083254\n ],\n [\n 8.96484375,\n 4.039617826768437\n ],\n [\n 6.328125,\n 4.039617826768437\n ],\n [\n 3.8671874999999996,\n 6.664607562172585\n ],\n [\n 1.23046875,\n 5.090944175033399\n ],\n [\n -1.9335937499999998,\n 4.390228926463384\n ],\n [\n -4.74609375,\n 5.090944175033399\n ],\n [\n -7.55859375,\n 4.039617826768437\n ],\n [\n -13.18359375,\n 7.536764322084078\n ],\n [\n -14.23828125,\n 9.96885060854611\n ],\n [\n -17.578125,\n 12.897489183755905\n ],\n [\n -17.578125,\n 16.804541076383455\n ],\n [\n -16.875,\n 18.646245142670608\n ],\n [\n -17.578125,\n 22.105998799750576\n ],\n [\n -15.644531250000002,\n 25.958044673317843\n ],\n [\n -12.83203125,\n 27.68352808378776\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56e29aace4b0f59b85d32751","contributors":{"authors":[{"text":"Brownfield, Michael E. 0000-0003-3633-1138 mbrownfield@usgs.gov","orcid":"https://orcid.org/0000-0003-3633-1138","contributorId":1548,"corporation":false,"usgs":true,"family":"Brownfield","given":"Michael","email":"mbrownfield@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":622421,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70174947,"text":"70174947 - 2016 - Changing regional emissions of airborne pollutants reflected in the chemistry of snowpacks and wetfall in the Rocky Mountain region, USA, 1993–2012","interactions":[],"lastModifiedDate":"2018-02-13T10:27:49","indexId":"70174947","displayToPublicDate":"2016-03-10T02:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3728,"text":"Water, Air, & Soil Pollution","onlineIssn":"1573-2932","printIssn":"0049-6979","active":true,"publicationSubtype":{"id":10}},"title":"Changing regional emissions of airborne pollutants reflected in the chemistry of snowpacks and wetfall in the Rocky Mountain region, USA, 1993–2012","docAbstract":"Wintertime precipitation sample data from 55 Snowpack sites and 17 National Atmospheric Deposition Program (NADP)/National Trends Network Wetfall sites in the Rocky Mountain region were examined to identify long-term trends in chemical concentration, deposition, and precipitation using Regional and Seasonal Kendall tests. The Natural Resources Conservation Service snow-telemetry (SNOTEL) network provided snow-water-equivalent data from 33 sites located near Snowpack- and NADP Wetfall-sampling sites for further comparisons. Concentration and deposition of ammonium, calcium, nitrate, and sulfate were tested for trends for the period 1993–2012. Precipitation trends were compared between the three monitoring networks for the winter seasons and downward trends were observed for both Snowpack and SNOTEL networks, but not for the NADP Wetfall network. The dry-deposition fraction of total atmospheric deposition, relative to wet deposition, was shown to be considerable in the region. Potential sources of regional airborne pollutant emissions were identified from the U.S. Environmental Protection Agency 2011 National Emissions Inventory, and from long-term emissions data for the period 1996–2013. Changes in the emissions of ammonia, nitrogen oxides, and sulfur dioxide were reflected in significant trends in snowpack and wetfall chemistry. In general, ammonia emissions in the western USA showed a gradual increase over the past decade, while ammonium concentrations and deposition in snowpacks and wetfall showed upward trends. Emissions of nitrogen oxides and sulfur dioxide declined while regional trends in snowpack and wetfall concentrations and deposition of nitrate and sulfate were downward.
","language":"English","publisher":"Springer","doi":"10.1007/s11270-016-2784-4","usgsCitation":"Ingersoll, G.P., Miller, D.C., Morris, K.H., McMurray, J.A., Port, G.M., and Caruso, B., 2016, Changing regional emissions of airborne pollutants reflected in the chemistry of snowpacks and wetfall in the Rocky Mountain region, USA, 1993–2012: Water, Air, & Soil Pollution, v. 227, p. 1-18, https://doi.org/10.1007/s11270-016-2784-4.","productDescription":"Article 94; 18 p.","startPage":"1","endPage":"18","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-075003","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":325574,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Idaho, Montana, New Mexico, Utah, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117,\n 36\n ],\n [\n -117,\n 47.5\n ],\n [\n -107,\n 47.5\n ],\n [\n -107,\n 36\n ],\n [\n -117,\n 36\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"227","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-29","publicationStatus":"PW","scienceBaseUri":"57934442e4b0eb1ce79e8bdb","contributors":{"authors":[{"text":"Ingersoll, George P. gpingers@usgs.gov","contributorId":1469,"corporation":false,"usgs":true,"family":"Ingersoll","given":"George","email":"gpingers@usgs.gov","middleInitial":"P.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":643270,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Debra C.","contributorId":173088,"corporation":false,"usgs":false,"family":"Miller","given":"Debra","email":"","middleInitial":"C.","affiliations":[{"id":27147,"text":"U.S. Forest Service, Rocky Mountain Region, Golden, CO","active":true,"usgs":false}],"preferred":false,"id":643271,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morris, Kristi H.","contributorId":173089,"corporation":false,"usgs":false,"family":"Morris","given":"Kristi","email":"","middleInitial":"H.","affiliations":[{"id":27148,"text":"National Park Service, Air Resources Division, Denver, CO","active":true,"usgs":false}],"preferred":false,"id":643272,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McMurray, Jill A.","contributorId":173090,"corporation":false,"usgs":false,"family":"McMurray","given":"Jill","email":"","middleInitial":"A.","affiliations":[{"id":27149,"text":"U.S. Forest Service, Northern and Intermountain Regions, Bozeman, MT","active":true,"usgs":false}],"preferred":false,"id":643273,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Port, Garrett M. gport@usgs.gov","contributorId":5158,"corporation":false,"usgs":true,"family":"Port","given":"Garrett","email":"gport@usgs.gov","middleInitial":"M.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":643274,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Caruso, Brian bcaruso@usgs.gov","contributorId":173087,"corporation":false,"usgs":true,"family":"Caruso","given":"Brian","email":"bcaruso@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":643269,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70171467,"text":"70171467 - 2016 - Interannual and long-term changes in the trophic state of a multibasin lake: Effects of morphology, climate, winter aeration, and beaver activity","interactions":[],"lastModifiedDate":"2018-03-27T13:47:13","indexId":"70171467","displayToPublicDate":"2016-03-10T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Interannual and long-term changes in the trophic state of a multibasin lake: Effects of morphology, climate, winter aeration, and beaver activity","docAbstract":"Little St. Germain Lake (LSG), a relatively pristine multibasin lake in Wisconsin, USA, was examined to determine how morphologic (internal), climatic (external), anthropogenic (winter aeration), and natural (beaver activity) factors affect the trophic state (phosphorus, P; chlorophyll, CHL; and Secchi depth, SD) of each of its basins. Basins intercepting the main flow and external P sources had highest P and CHL and shallowest SD. Internal loading in shallow, polymictic basins caused P and CHL to increase and SD to decrease as summer progressed. Winter aeration used to eliminate winterkill increased summer internal P loading and decreased water quality, while reductions in upstream beaver impoundments had little effect on water quality. Variations in air temperature and precipitation affected each basin differently. Warmer air temperatures increased productivity throughout the lake and decreased clarity in less eutrophic basins. Increased precipitation increased P in the basins intercepting the main flow but had little effect on the isolated deep West Bay. These relations are used to project effects of future climatic changes on LSG and other temperate lakes.
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