Crystalline bedrock aquifers in New England and parts of New Jersey and New York (NECR aquifers) are a major source of drinking water. Because the quality of water in these aquifers is highly variable, the U.S. Geological Survey (USGS) statistically analyzed chemical data on samples of untreated groundwater collected from 117 domestic bedrock wells in New England, New York, and New Jersey, and from 4,775 public-supply bedrock wells in New England to characterize the quality of the groundwater. The domestic-well data were from samples collected by the USGS National Water-Quality Assessment (NAWQA) Program from 1995 through 2007. The public-supply-well data were from samples collected for the U.S. Environmental Protection Agency (USEPA) Safe Drinking Water Act (SDWA) Program from 1997 through 2007. Chemical data compiled from the domestic wells include pH, specific conductance, dissolved oxygen, alkalinity, and turbidity; 6 nitrogen and phosphorus compounds, 14 major ions, 23 trace elements, 222radon gas (radon), 48 pesticide compounds, and 82 volatile organic compounds (VOCs). Additional samples were collected from the domestic wells for the analysis of gross alpha- and gross beta-particle radioactivity, radium isotopes, chlorofluorocarbon isotopes, and the dissolved gases methane, carbon dioxide, nitrogen, and argon. Chemical data compiled from the public-supply wells include pH, specific conductance, nitrate, iron, manganese, sodium, chloride, fluoride, arsenic, uranium, radon, combined radium (226radium plus 228radium), gross alpha-particle radioactivity, and methyl tert-butyl ether (MtBE).
Patterns in fluoride, arsenic, uranium, and radon distributions were discernable when the data were compared to lithology groupings of the bedrock, indicating that the type of bedrock has an effect on the quality of groundwater from NECR aquifers. Fluoride concentrations were significantly higher in groundwater samples from the alkali granite, peraluminous granite, and metaluminous granite lithology groups than from samples in the other lithology groups. Water samples from 1.4 percent of 2,167 studied wells had fluoride concentrations that were equal to or greater than the maximum contaminant level (MCL) of 4 milligrams per liter (mg/L) and 7.5 percent of the wells had fluoride concentrations that were equal to or greater than the secondary MCL of 2 mg/L. For arsenic, groundwater samples from the calcareous metasedimentary rocks in the New Hampshire-Maine geologic province, peraluminous granite, and pelitic rocks lithology groups had higher concentrations than did samples from the other lithology groups. Water samples from 13.3 percent of 2,054 studied wells had arsenic concentrations that were equal to or greater than the MCL of 10 micrograms per liter (μg/L), about double the national rate of occurrence in community-supply systems and in domestic wells of the United States. Uranium concentrations were significantly higher in groundwater samples from the peraluminous granite, alkali granite, and calcareous metasedimentary rocks in the New Hampshire-Maine geologic province lithology groups than from samples in the other lithology groups. Water samples from 14.2 percent of 556 studied wells had uranium concentrations equal to or greater than the MCL of 30 μg/L. Radon activities were equal to or greater than the proposed MCL of 300 picocuries per liter (pCi/L) in 95 percent of 943 studied wells, and 33 percent of the wells had radon activities were equal to or greater than the proposed alternative maximum contaminant level (AMCL) of 4,000 pCi/L. Radon activities exceeded the proposed AMCL in 20 percent or more of groundwater samples in each of the studied lithology groups with a minimum of 9 samples, but radon activities were significantly higher in groundwater samples from the alkali granite, peraluminous granite, and Narragansett basin metasedimentary rocks lithology groups. Water samples from 3.2 percent of 564 studied wells had combined radium activities equal to or greater than the MCL of 5 pCi/L; however, combined radium activities were not significantly different among the studied lithology groups.
Land use and population density also were evaluated to explain patterns in water quality. Concentrations of nitrate, sodium, chloride, and MtBE from the studied wells were significantly greater in areas of high population density (≥50 persons per square kilometer) than in areas of low population density (<50 persons per square kilometer). Concentrations of sodium, chloride, and MtBE from the studied wells were significantly greater in areas classified as developed (urban lands) than in areas classified as undeveloped (forested), agricultural, or mixed (no dominant land use). Nitrate concentrations from the public-supply wells were not significantly different among the four land use categories, but nitrate concentrations from the domestic wells were significantly greater in areas classified as developed than in areas classified as undeveloped, agricultural, or mixed.
Chloride to bromide mass ratios in the domestic well samples indicate that the groundwater was probably affected by at least three halogen sources: local precipitation and recharge waters, remnant seawater and connate waters evolved from seawater, and recharge waters affected by road salt. The groundwater in the NECR aquifers generally contained low concentrations of nitrate, VOCs, and pesticides. Less than 1 percent of water samples from 4,781 studied wells had concentrations of nitrate greater than the MCL of 10 mg/L. Less than 1 percent of water samples from 1,299 studied wells exceeded the USEPA advisory level of 20 to 40 μg/L for MtBE. None of the other studied VOCs exceeded a human health benchmark. MtBE (36 percent frequency detection) and chloroform (32.9 percent frequency detection) were the most frequently detected (>0.02 μg/L) VOCs in the domestic wells. MtBE was detected more often in water samples with apparent ages of less than 25 years than in water samples with apparent ages greater than 25 years. This finding is consistent with the time period of high MtBE use in areas in the United States where reformulated gasoline was mandated. The largest pesticide concentration was an estimated concentration of 0.06 μg/L for the herbicide metolachlor. Deethylatrazine, a degradate of atrazine, (18 percent frequency detection) and atrazine (8 percent frequency detection) were the only pesticide compounds detected (>0.001 μg/L) in more than 3 percent of the domestic wells. None of the detected pesticide compounds exceeded human health benchmarks.
Concentrations of nitrate and gross alpha-particle activities were significantly greater in the water samples from the domestic wells than in samples from the public-supply wells. Concentrations of sodium, chloride, iron, manganese, and uranium were significantly greater in the water samples from the public-supply wells than in the samples from the domestic wells. One possible explanation may be related to differences in field processing (filtered samples from the domestic wells compared to unfiltered samples from the public-supply wells).
The high frequency of detections for a wide variety of manmade and naturally occurring contaminants in both domestic and public-supply wells shows the vulnerability of NECR aquifers to contamination. The highly variable water quality and the association with highly variable lithology of crystalline bedrock underscores the importance of testing individual wells to determine if concentrations for the most commonly detected contaminants exceed human health benchmarks.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115220","isbn":"ISBN 978-1-411-33417-5","collaboration":"National Water-Quality Assessment Program","usgsCitation":"Flanagan, S.M., Ayotte, J.D., Robinson, G.R., Jr., 2018, Quality of water from crystalline rock aquifers in New England, New Jersey, and New York, 1995–2007 (ver.1.1, April 2018): U.S. Geological Survey 2011–5220, 104 p., https://doi.org/10.3133/sir20115220.\n","productDescription":"Report: xiv, 104 p.","numberOfPages":"122","onlineOnly":"N","additionalOnlineFiles":"Y","temporalStart":"1995-01-01","temporalEnd":"2007-12-31","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":353386,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2011/5220/pdf/sir20115220.pdf","text":"Report","size":"9.15 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2011-5220"},{"id":353387,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2011/5220/versionHist.txt","size":"1.33 KB","linkFileType":{"id":2,"text":"txt"}},{"id":257873,"rank":100,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2011/5220/index.html","text":"Index Page","linkFileType":{"id":5,"text":"html"}},{"id":257884,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2011/5220/images/coverthb.jpg"}],"country":"United States","state":"Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Rhode Island, and Vermont","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.03662109375,\n 40.56389453066509\n ],\n [\n -66.90673828125,\n 40.56389453066509\n ],\n [\n -66.90673828125,\n 47.39834920035926\n ],\n [\n -75.03662109375,\n 47.39834920035926\n ],\n [\n -75.03662109375,\n 40.56389453066509\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally released June 25, 2012; Version 1.1: April 13, 2018","contact":"Director, New England Water Science Center
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Conservation and recovery of species of concern necessitates evaluating forest habitat conditions under changing climate conditions, especially in the early stages of the delisting process. Managers must weigh implications of near-term habitat management activities within the context of changing environmental conditions and a species’ biological traits that may influence their vulnerability to changing conditions. Here we applied established population-habitat relationships based on decades of monitoring and research-management collaborations for the Kirtland’s Warbler (Setophaga kirtlandii) to project potential impacts of changing environmental conditions to breeding habitat distribution, quantity, and quality in the near future. Kirtland’s warblers are habitat-specialists that nest exclusively within dense jack pine (Pinus banksiana) forests between ca. 5–20 years of age. Using Random Forests to predict changes in distribution and growth rate of jack pine under future scenarios, results indicate the projected distribution of jack pine will contract considerably (ca. 75%) throughout the Lake States region, U.S.A. in response to projected environmental conditions in 2099 under RCP 4.5 and 8.5 climate scenarios regardless of climate model. Reduced suitability for jack pine regeneration across the Lake States may constrain management options, especially for creating high stem-density plantations nesting habitat. However, conditions remain suitable for jack pine regeneration within their historical and current core breeding range in northern Lower Michigan and several satellite breeding areas. Projected changes in jack pine growth rates varied within the core breeding area, but altered growth rates did not greatly alter the duration that habitat remained suitable for nesting by the Kirtland’s Warblers. These findings contribute to Kirtland’s Warbler conservation by informing habitat spatial planning of plantation management to provide a constant supply of nesting habitat based on the spatial variability of potential loss or gain of lands environmentally suitable for regenerating jack pine in the long-term.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2018.08.026","usgsCitation":"Donner, D.M., Brown, D., Ribic, C., Nelson, M., and Greco, T., 2018, Managing forest habitat for conservation-reliant species in a changing climate: The case of the endangered Kirtland’s Warbler: Forest Ecology and Management, v. 430, p. 265-279, https://doi.org/10.1016/j.foreco.2018.08.026.","productDescription":"15 p.","startPage":"265","endPage":"279","ipdsId":"IP-094530","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":469210,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2018.08.026","text":"Publisher Index Page"},{"id":380304,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.62744140625,\n 43.8028187190472\n ],\n [\n -83.29833984375,\n 43.8028187190472\n ],\n [\n -83.29833984375,\n 45.583289756006316\n ],\n [\n -85.62744140625,\n 45.583289756006316\n ],\n [\n -85.62744140625,\n 43.8028187190472\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.31982421875,\n 45.78284835197676\n ],\n [\n -83.07861328125,\n 45.78284835197676\n ],\n [\n -83.07861328125,\n 46.70973594407157\n ],\n [\n -85.31982421875,\n 46.70973594407157\n ],\n [\n -85.31982421875,\n 45.78284835197676\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.57177734375,\n 45.75219336063106\n ],\n [\n -85.69335937499999,\n 45.75219336063106\n ],\n [\n -85.69335937499999,\n 47.010225655683485\n ],\n [\n -88.57177734375,\n 47.010225655683485\n ],\n [\n -88.57177734375,\n 45.75219336063106\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.8017578125,\n 46.08847179577592\n ],\n [\n -90.28564453124999,\n 46.08847179577592\n ],\n [\n -90.28564453124999,\n 47.100044694025215\n ],\n [\n -91.8017578125,\n 47.100044694025215\n ],\n [\n -91.8017578125,\n 46.08847179577592\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.681640625,\n 44.91813929958515\n ],\n [\n -87.5830078125,\n 44.91813929958515\n ],\n [\n -87.5830078125,\n 45.85941212790755\n ],\n [\n -88.681640625,\n 45.85941212790755\n ],\n [\n -88.681640625,\n 44.91813929958515\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.04669189453125,\n 43.65594991256823\n ],\n [\n -89.50698852539062,\n 43.65594991256823\n ],\n [\n -89.50698852539062,\n 44.219615400229195\n ],\n [\n -90.04669189453125,\n 44.219615400229195\n ],\n [\n -90.04669189453125,\n 43.65594991256823\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"430","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Donner, Deahn M.","contributorId":171823,"corporation":false,"usgs":false,"family":"Donner","given":"Deahn","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":804353,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Donald J.","contributorId":191568,"corporation":false,"usgs":false,"family":"Brown","given":"Donald J.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":804354,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ribic, Christine 0000-0003-2583-1778 caribic@usgs.gov","orcid":"https://orcid.org/0000-0003-2583-1778","contributorId":147952,"corporation":false,"usgs":true,"family":"Ribic","given":"Christine","email":"caribic@usgs.gov","affiliations":[{"id":5068,"text":"Midwest Regional Director's Office","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":804352,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nelson, Mark","contributorId":244674,"corporation":false,"usgs":false,"family":"Nelson","given":"Mark","affiliations":[{"id":27863,"text":"U. S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":804355,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Greco, Tim","contributorId":244675,"corporation":false,"usgs":false,"family":"Greco","given":"Tim","email":"","affiliations":[{"id":6983,"text":"Michigan DNR","active":true,"usgs":false}],"preferred":false,"id":804356,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":47797,"text":"wri034009 - 2018 - Evaluation of the Source and Transport of High Nitrate Concentrations in Ground Water, Warren Subbasin, California","interactions":[],"lastModifiedDate":"2018-09-19T16:54:36","indexId":"wri034009","displayToPublicDate":"2003-08-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":342,"text":"Water-Resources Investigations Report","code":"WRI","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"2003-4009","title":"Evaluation of the Source and Transport of High Nitrate Concentrations in Ground Water, Warren Subbasin, California","docAbstract":"Ground water historically has been the sole source of water supply for the Town of Yucca Valley in the Warren subbasin of the Morongo ground-water basin, California. An imbalance between ground-water recharge and pumpage caused ground-water levels in the subbasin to decline by as much as 300 feet from the late 1940s through 1994. In response, the local water district, Hi-Desert Water District, instituted an artificial recharge program in February 1995 using imported surface water to replenish the ground water. The artificial recharge program resulted in water-level recoveries of as much as 250 feet in the vicinity of the recharge ponds between February 1995 and December 2001; however, nitrate concentrations in some wells also increased from a background concentration of 10 milligrams per liter to more than the U.S. Environmental Protection Agency (USEPA) maximum contaminant level (MCL) of 44 milligrams per liter (10 milligrams per liter as nitrogen).
The objectives of this study were to: (1) evaluate the sources of the high-nitrate concentrations that occurred after the start of the artificial-recharge program, (2) develop a ground-water flow and solute-transport model to better understand the source and transport of nitrates in the aquifer system, and (3) utilize the calibrated models to evaluate the possible effect of a proposed conjunctive-use project. These objectives were accomplished by collecting water-level and water-quality data for the subbasin and assessing changes that have occurred since artificial recharge began. Collected data were used to calibrate the ground-water flow and solute-transport models.
Data collected for this study indicate that the areal extent of the water-bearing deposits is much smaller (about 5.5 square miles versus 19 square miles) than that of the subbasin. These water-bearing deposits are referred to in this report as the Warren ground-water basin. Faults separate the ground-water basin into five hydrogeologic units: the west, the midwest, the mideast, the east and the northeast hydrogeologic units.
Water-quality analyses indicate that septage from septic tanks is the primary source of the high-nitrate concentrations measured in the Warren ground-water basin. Water-quality and stable-isotope data, collected after the start of the artificial recharge program, indicate that mixing occurs between imported water and native ground water, with the highest recorded nitrate concentrations in the midwest and the mideast hydrogeologic units. In general, the timing of the increase in measured nitrate concentrations in the midwest hydrogeologic unit is directly related to the distance of the monitoring well from a recharge site, indicating that the increase in nitrate concentrations is related to the artificial recharge program. Nitrate-to-chloride and nitrogen-isotope data indicate that septage is the source of the measured increase in nitrate concentrations in the midwest and the mideast hydrogeologic units. Samples from four wells in the Warren ground-water basin were analyzed for caffeine and selected human pharmaceutical products; these analyses suggest that septage is reaching the water table.
There are two possible conceptual models that explain how high-nitrate septage reaches the water table: (1) the continued downward migration of septage through the unsaturated zone to the water table and (2) rising water levels, a result of the artificial recharge program, entraining septage in the unsaturated zone. The observations that nitrate concentrations increase in ground-water samples from wells soon after the start of the artificial recharge program in 1995 and that the largest increase in nitrate concentrations occur in the midwest and mideast hydrogeologic units where the largest increase in water levels occur indicate the validity of the second conceptual model (rising water levels). The potential nitrate concentration resulting from a water-level rise in the midwest and mideast hydrogeologic units was estimated using a simple mixing-cell model. The estimated value is within the range of concentrations measured in samples from wells, further indicating the validity of the second conceptual model.
A ground-water flow model and a solute-transport model were developed for the Warren ground-water basin for the period 1956-2001. MODFLOW-96 was used for the ground-water flow model and MOC3D was used for the solute-transport model. The model cell size is about 500 feet by 500 feet and the models were discretized vertically into three layers. The models were calibrated using a trial-and-error approach using water-level and nitrate-concentration data collected between 1956-2001. In order to better match the measured data, low fault hydraulic characteristic values were required, thereby compartmentalizing the ground-water basin. In addition, it was necessary to parameterize the specific yield distribution for the top model layer where unconfined ground-water conditions occur into three homogeneous zones. Separate sets of specific- yield values were needed to simulate the drawdown and subsequent water-level recovery. In addition, the calibrated natural recharge was about 83 acre-feet per year. The entrainment of unsaturated-zone septage was simulated as recharge having an associated nitrate concentration. The volume of recharge was a function of the measured water-level rise between 1994-98 and the moisture content of the unsaturated zone. The nitrate concentration of the recharge water was a weighted function of the assumed nitrate concentration in the infiltrating water associated with the overlying land use. The simulated hydraulic head and nitrate concentration results were in good agreement with the measured data indicating that the mechanism for the increase in nitrate concentrations was rising water levels entraining high-nitrate septage in the unsaturated-zone.
The calibrated models were used to simulate the possible effects of a planned conjunctive-use project in the western part of the ground-water basin. The simulated project included the addition of a new recharge pond and a new extraction well. In addition, recharge at two existing recharge ponds was increased and three existing production wells were pumped, treated in a nitrate-removal facility, and used for water supply. The simulated hydraulic heads increased in the west, the mideast, and parts of the east hydrogeologic units; however, the simulated hydraulic heads decreased in the midwest and northeast hydrogeologic units. The simulated nitrate concentrations increased to above the MCL of 44 milligrams per liter (10 milligrams per liter as nitrogen) in parts of the west as a result of the increase in simulated hydraulic head. The simulated nitrate concentrations decreased in part of the midwest hydrogeologic unit as a result of the artificial recharge and pumping from the nitrate-removal wells. The simulated nitrate concentrations increased to above the MCL of 44 milligrams per liter in part of the mideast and parts of the east hydrogeologic units beneath commercial land-use areas.
The U.S. Geological Survey currently (2020) publishes information on concentrations and loads of water-quality constituents at 110 sites across the United States as part of the U.S. Geological Survey National Water Quality Network (NWQN). This report details historical and updated methods for computing water-quality loads at NWQN sites. The primary updates to historical load estimation methods include (1) an adaptation to methods for computing loads to the Gulf of Mexico; (2) the inclusion of loads and trends computed using the Weighted Regressions on Time, Discharge, and Season (WRTDS) and Weighted Regressions on Time, Discharge, and Season with Kalman filtering (WRTDS–K) methods; and (3) the inclusion of loads computed using continuous water-quality data. Loads computed using WRTDS and WRTDS–K and continuous water-quality data are provided along with those computed using historical methods. Various aspects of method updates are evaluated in this report to help users of water-quality loading data determine which estimation methods best suit their particular application.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171120","usgsCitation":"Lee, C.J., Murphy, J.C., Crawford, C.G., and Deacon, J.R, 2017, Methods for computing water-quality loads at sites in the U.S. Geological Survey National Water Quality Network (ver. 1.3, August 2021): U.S. Geological Survey Open-File Report 2017–1120, 20 p., https://doi.org/10.3133/ofr20171120.","productDescription":"Report: vii, 20 p.; Version History","onlineOnly":"Y","ipdsId":"IP-086966","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":438099,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93DHTRJ","text":"USGS data release","linkHelpText":"Nutrient and pesticide data collected from the USGS National Water Quality Network and previous networks, 1950-2022"},{"id":438098,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P948Z0VZ","text":"USGS data release","linkHelpText":"Nutrient and pesticide data collected from the USGS National Water Quality Network and previous networks, 1950-2021"},{"id":388566,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2017/1120/versionHist.txt","text":"Version History","size":"9.89 kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2017–1120 Version History"},{"id":388565,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1120/ofr20171120.pdf","text":"Report","size":"14.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1120"},{"id":347239,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1120/coverthb4.jpg"}],"edition":"Version 1.3: August 2021; Version 1.2: November 2020; Version 1.1: January 2020; Version 1.0: October 2017","contact":"Director, Kansas Water Science Center
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We compare changes in low birth weight and child malnutrition in 13 African countries under projected climate change versus socio-economic development scenarios. Climate scenarios are created by linking surface temperature gradients with declines in seasonal rainfall sea along with warming values of 1 °C and 2 °C. Socio-economic scenarios are developed by assigning regionally specific changes in access to household electricity and mother's education. Using these scenarios, in combination with established models of children's health, we investigate and compare the changes in predicted health outcomes. We find that the negative effects of warming and drying on child stunting could be mitigated by positive development trends associated with increasing mothers’ educational status and household access to electricity. We find less potential for these trends to mitigate how warming and drying trends impact birth weights. In short, under warming and drying, the risk of more malnourished children is greater than the risk of more children with low birth weights, but increases in child malnutrition could be averted in regions that increase access to educational resources and basic infrastructure.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gloenvcha.2017.04.009","usgsCitation":"Davenport, F., Grace, K., Funk, C., and Shukla, S., 2017, Child health outcomes in sub-Saharan Africa: A comparison of changes in climate and socio-economic factors: Global Environmental Change, v. 46, p. 72-87, https://doi.org/10.1016/j.gloenvcha.2017.04.009.","productDescription":"16 p.","startPage":"72","endPage":"87","ipdsId":"IP-085021","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":421804,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Kenya, Senegal, Madagascar, Burkina Faso, Ethiopia, Guinea, Malawi, Mali, Niger, Nigeria, Rwanda, Uganda, 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Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Habitat suitability models for groundfish in the Gulf of Alaska","docAbstract":"Identifying and quantifying the major ecosystem processes that regulate recruitment strength of commercially and ecologically important fish species is a central goal of fisheries management research. In the Gulf of Alaska (GOA) five groundfish species are of particular interest: sablefish (Anoplopoma fimbria), Pacific cod (Gadus macrocephalus), walleye pollock (Gadus chalcogrammus), arrowtooth flounder (Atheresthes stomias), and Pacific ocean perch (Sebastes alutus). Habitat suitability models (HSM) were developed for the demersal early juvenile stage to inform survival to recruitment for these species, using catch data and seafloor habitat metrics with presence-only models. Regional-scale maps were produced that predict the probability of suitable habitat available in the GOA from settlement through residency in nursery areas. For example, the HSM for sablefish (150–399 mm) described suitable habitat as bathymetrically low-lying areas with low rocky structure within 25–300 m depth. In contrast, the HSM for Pacific ocean perch (50–200 mm) described suitable habitat as bathymetry rises with rocky structure present on north-south facing slopes within 85–270 m depth. These habitat covariates are useful to refine population estimates for North Pacific groundfish species and to inform life stage-specific definitions of Essential Fish Habitat. This application of MaxEnt models should be applicable for species with low occurrence of spatial data in other marine ecosystems globally.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.dsr2.2017.12.005","usgsCitation":"Pirtle, J.L., Shotwell, S.K., Zimmermann, M., Reid, J.A., and Golden, N.E., 2017, Habitat suitability models for groundfish in the Gulf of Alaska: Deep Sea Research Part II: Topical Studies in Oceanography, v. 165, p. 303-321, https://doi.org/10.1016/j.dsr2.2017.12.005.","productDescription":"19 p.","startPage":"303","endPage":"321","ipdsId":"IP-076374","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":461313,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.dsr2.2017.12.005","text":"Publisher Index Page"},{"id":360155,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Gulf of Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -165.498046875,\n 54.059387886623576\n ],\n [\n -130.2099609375,\n 54.059387886623576\n ],\n [\n -130.2099609375,\n 61.4597705702975\n ],\n [\n -165.498046875,\n 61.4597705702975\n ],\n [\n -165.498046875,\n 54.059387886623576\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"165","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10aa60e4b034bf6a7e57b9","contributors":{"authors":[{"text":"Pirtle, Jodi L.","contributorId":211305,"corporation":false,"usgs":false,"family":"Pirtle","given":"Jodi","email":"","middleInitial":"L.","affiliations":[{"id":38223,"text":"National Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":753605,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shotwell, S. 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In this paper, we focus on recent trends in applying imaging spectrometer data to: 1) airborne imaging of high latitude deposits, 2) field-based imaging of outcrops, and 3) laboratory-level imaging of geologic samples. Comparing mineral information derived from imaging spectrometer data acquired at these three scales in Alaska in areas of exposed porphyry Cu-Au-Mo deposits, Orange Hill and Bond Creek, we find notable consistency in identifications of spectrally predominant minerals, including white mica, chlorite, clays, and gypsum. Variations in the wavelength position of white mica 2200 nm Al-OH absorption seen at the airborne level are echoed by finerscale field and laboratory imaging, with wavelength positions spanning the 2199 to 2207 nm range. The longerwavelength micas associated with porphyry formation are more phengitic in composition, and thus distinct from mica in plutonic and volcanic arc rocks not affected by magmatic-hydrothermal fluids. The hillside imagery, collected on a cloudy day that would have precluded aircraft survey, gave comparable result to airborne and laboratory data, indicating field-based imaging spectroscopy can be a feasible alternative to airborne survey for accessible targets. Direct spectral observation of molybdenite in rocks collected from the Orange Hill deposit demonstratesthat additional important mineral information can be revealed with laboratory level imaging spectroscopy that is difficult to obtain in coarser scale data, commonly due to low areal extent of target minerals. The spatial association of the clinochlore + white mica and long wavelength white mica spectral classes to multi-element Cu-Mo-Au anomalies from geochemical analyses of rocks and sediments support a causative relationship with magmatic-hydrothermal alteration. Mineral maps from the airborne data were used to guide field sampling that found additional CuMo-Au mineralized areas, which were previously unknown or unreported. The results from this study provide support for utilization of imaging spectroscopy for assisting mineral exploration in other portions of the state of Alaska as well as other areas at high latitudes. Imaging spectroscopy has the potential to provide targeting information for follow-up sampling and investigations, potentially reducing subsequent exploration costs.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of Exploration 17: Sixth Decennial International Conference on Mineral Exploration","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Decennial Mineral Exploration Conferences","usgsCitation":"Kokaly, R.F., Graham, G.E., Hoefen, T.M., Kelley, K.D., Johnson, M., Hubbard, B.E., Buchhorn, M., and Prakash, A., 2017, Multiscale hyperspectral imaging of the Orange Hill Porphyry Copper Deposit, Alaska, USA, with laboratory-, field-, and aircraft-based imaging spectrometers, in Proceedings of Exploration 17: Sixth Decennial International Conference on Mineral Exploration, p. 923-943.","productDescription":"21 p.","startPage":"923","endPage":"943","ipdsId":"IP-091448","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science 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PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bfd1472e4b0815414ca3906","contributors":{"authors":[{"text":"Kokaly, Raymond F. 0000-0003-0276-7101","orcid":"https://orcid.org/0000-0003-0276-7101","contributorId":205165,"corporation":false,"usgs":true,"family":"Kokaly","given":"Raymond","email":"","middleInitial":"F.","affiliations":[{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":752000,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graham, Garth E. 0000-0003-0657-0365 ggraham@usgs.gov","orcid":"https://orcid.org/0000-0003-0657-0365","contributorId":1031,"corporation":false,"usgs":true,"family":"Graham","given":"Garth","email":"ggraham@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":752001,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hoefen, Todd M. 0000-0002-3083-5987 thoefen@usgs.gov","orcid":"https://orcid.org/0000-0002-3083-5987","contributorId":403,"corporation":false,"usgs":true,"family":"Hoefen","given":"Todd","email":"thoefen@usgs.gov","middleInitial":"M.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":752002,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kelley, Karen D. 0000-0002-3232-5809 kdkelley@usgs.gov","orcid":"https://orcid.org/0000-0002-3232-5809","contributorId":179012,"corporation":false,"usgs":true,"family":"Kelley","given":"Karen","email":"kdkelley@usgs.gov","middleInitial":"D.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":752003,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Michaela R. 0000-0001-6133-0247 mrjohns@usgs.gov","orcid":"https://orcid.org/0000-0001-6133-0247","contributorId":1013,"corporation":false,"usgs":true,"family":"Johnson","given":"Michaela R.","email":"mrjohns@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":752004,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hubbard, Bernard E. 0000-0002-9315-2032 bhubbard@usgs.gov","orcid":"https://orcid.org/0000-0002-9315-2032","contributorId":2342,"corporation":false,"usgs":true,"family":"Hubbard","given":"Bernard","email":"bhubbard@usgs.gov","middleInitial":"E.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":752005,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Buchhorn, M.","contributorId":210801,"corporation":false,"usgs":false,"family":"Buchhorn","given":"M.","email":"","affiliations":[],"preferred":false,"id":752006,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Prakash, A.","contributorId":81330,"corporation":false,"usgs":true,"family":"Prakash","given":"A.","email":"","affiliations":[],"preferred":false,"id":752007,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70199137,"text":"70199137 - 2017 - Application of paleoflood surveys for the southern Black Hills of South Dakota","interactions":[],"lastModifiedDate":"2018-11-27T11:47:09","indexId":"70199137","displayToPublicDate":"2018-10-01T11:47:04","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":5789,"text":"South Dakota Department of Transportation Office of Research Study","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"2010-04","title":"Application of paleoflood surveys for the southern Black Hills of South Dakota","docAbstract":"Flood-frequency analyses for the Black Hills area have especially large uncertainties and are especially important for planning purposes because of a history of extremely large and damaging floods, such as the extreme floods of June 9–10, 1972. Geology, topography, and climatology are additional complicating factors for flood-frequency characterization for the area. Two previous paleoflood studies for the Black Hills area indicated good potential for improving flood-frequency analyses through implementation of paleoflood investigations. The objectives of this study (SD2010-04) for the southern Black Hills were to (1) develop long-term flood chronologies and associated peak-flow frequency analyses for selected stream reaches by applying paleoflood hydrology approaches; and (2) develop flood-frequency information regarding “high-elevation” stream reaches to help address questions regarding differential potential for generation of exceptionally strong rain-producing thunderstorms across elevation gradients in the area. Neither objective was accomplished because the study was terminated before planned completion.\nSubstantial efforts could be applied for only 2 of the 12 research tasks prior to study termination. These were task 3 (preliminary reconnaissance) and task 4 (activities associated with Section 106 of the National Historic Preservation Act). Field reconnaissance conducted along 10 candidate streams indicated that conditions in the southern Black Hills appear quite favorable for conducting paleoflood investigations. All 10 candidate streams had moderate to good potential for favorable paleoflood evidence, and in general are well constrained in relatively narrow canyon reaches, which provides good sensitivity for changes in stage, relative to discharge.\nTask 4 (Section 106 activities) was needed because alcoves and rock shelters that are well suited for deposition and preservation of paleoflood evidence may have been used as shelters or cache locations by indigenous inhabitants and thus may be eligible for consideration as historic properties because of possible archaeological or cultural materials. The complexity of the Section 106 concerns and issues became progressively more apparent as the study evolved. The study eventually was terminated when it became apparent that the resources needed to address the Section 106 issues would overwhelm the resources available for study implementation. In the event of consideration of future re-implementation, approaches that might help expedite Section 106 issues could include (1) a partnership with another Federal agency that has substantial experience with the Section 106 process; (2) securing assistance from a consultant that could help with both the Section 106 process and the required archaeological component; and (3) partnering with a tribal college with archaeological or earth science/hydrology programs, which could help make this study become part of a learning exercise.","language":"English","publisher":"South Dakota Department of Transportation","usgsCitation":"Driscoll, D.G., 2017, Application of paleoflood surveys for the southern Black Hills of South Dakota: South Dakota Department of Transportation Office of Research Study 2010-04, 21 p.","productDescription":"21 p.","ipdsId":"IP-085944","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":359716,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":357090,"type":{"id":15,"text":"Index Page"},"url":"https://www.sddot.com/business/research/reports/Default.aspx"}],"country":"United States","state":"South Dakota","otherGeospatial":"Black Hills","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bfe65e3e4b0815414ca60fe","contributors":{"authors":[{"text":"Driscoll, Daniel G. 0000-0003-0016-8535 dgdrisco@usgs.gov","orcid":"https://orcid.org/0000-0003-0016-8535","contributorId":207583,"corporation":false,"usgs":true,"family":"Driscoll","given":"Daniel","email":"dgdrisco@usgs.gov","middleInitial":"G.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":744282,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70198901,"text":"70198901 - 2017 - The Peters Hills basin, a Neogene wedge-top basin on the Broad Pass thrust fault, south-central Alaska","interactions":[],"lastModifiedDate":"2023-11-09T17:39:33.741967","indexId":"70198901","displayToPublicDate":"2018-08-09T12:44:49","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"The Peters Hills basin, a Neogene wedge-top basin on the Broad Pass thrust fault, south-central Alaska","docAbstract":"The Neogene Peters Hills basin is a small terrestrial basin that formed along the south flank of the Alaska Range during a time in which there was regional shortening. The formation of the Peters Hills basin is consistent with it being a wedge-top basin that formed on top of the active southeast-vergent Broad Pass thrust fault. Movement along this thrust raised a ridge of Jurassic and Cretaceous metasedimentary rocks, which then trapped behind it Miocene and Pliocene sediments that were derived from the growing Alaska Range. The presence of this thrust fault is consistent with regional structural, stratigraphic, seismicity, gravity, and aeromagnetic data. The Peters Hills basin is no longer a depocenter, but if the Broad Pass thrust remains active, it would help explain the westward decrease in Quaternary slip rate along the Denali fault system, and it may constitute a seismic hazard that could produce earthquakes in the Mw 7.6–7.8 range.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES01487.1","usgsCitation":"Haeussler, P.J., Saltus, R., Stanley, R.G., Ruppert, N., Lewis, K., Karl, S.M., and Bender, A.M., 2017, The Peters Hills basin, a Neogene wedge-top basin on the Broad Pass thrust fault, south-central Alaska: Geosphere, v. 13, no. 5, p. 1464-1488, https://doi.org/10.1130/GES01487.1.","productDescription":"25 p.","startPage":"1464","endPage":"1488","ipdsId":"IP-086120","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":469212,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges01487.1","text":"Publisher Index Page"},{"id":356788,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Peters Hills basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -152.25,\n 61.75\n ],\n [\n -149.5,\n 61.75\n ],\n [\n -149.5,\n 63\n ],\n [\n -152.25,\n 63\n ],\n [\n -152.25,\n 61.75\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-09","publicationStatus":"PW","scienceBaseUri":"5b98a33ee4b0702d0e843039","contributors":{"authors":[{"text":"Haeussler, Peter J. 0000-0002-1503-6247 pheuslr@usgs.gov","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":503,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter","email":"pheuslr@usgs.gov","middleInitial":"J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":743333,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Saltus, Richard W. 0000-0001-6920-2936","orcid":"https://orcid.org/0000-0001-6920-2936","contributorId":207255,"corporation":false,"usgs":false,"family":"Saltus","given":"Richard W.","affiliations":[{"id":37502,"text":"NOAA-NCEI, 325 Broadway, NOAA E/GC3, Office 1B507, Boulder, CO","active":true,"usgs":false}],"preferred":false,"id":743334,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stanley, Richard G. 0000-0001-6192-8783 rstanley@usgs.gov","orcid":"https://orcid.org/0000-0001-6192-8783","contributorId":1832,"corporation":false,"usgs":true,"family":"Stanley","given":"Richard","email":"rstanley@usgs.gov","middleInitial":"G.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":743335,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ruppert, Natalia","contributorId":207257,"corporation":false,"usgs":false,"family":"Ruppert","given":"Natalia","affiliations":[{"id":37504,"text":"University of Alaska/Geophysical Institute, Fairbanks, AK","active":true,"usgs":false}],"preferred":false,"id":743336,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lewis, Kristen 0000-0003-4991-3399","orcid":"https://orcid.org/0000-0003-4991-3399","contributorId":207258,"corporation":false,"usgs":false,"family":"Lewis","given":"Kristen","affiliations":[{"id":37505,"text":"U.S. Geological Survey, CERSC, P.O. Box 25046, Denver, CO","active":true,"usgs":false}],"preferred":false,"id":743337,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Karl, Susan M. 0000-0003-1559-7826 skarl@usgs.gov","orcid":"https://orcid.org/0000-0003-1559-7826","contributorId":502,"corporation":false,"usgs":true,"family":"Karl","given":"Susan","email":"skarl@usgs.gov","middleInitial":"M.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":743338,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bender, Adrian M. 0000-0001-7469-1957 abender@usgs.gov","orcid":"https://orcid.org/0000-0001-7469-1957","contributorId":4963,"corporation":false,"usgs":true,"family":"Bender","given":"Adrian","email":"abender@usgs.gov","middleInitial":"M.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":743339,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70198484,"text":"70198484 - 2017 - Effectiveness of environmental flows for riparian restoration in arid regions: A tale of four rivers","interactions":[],"lastModifiedDate":"2018-08-06T12:17:04","indexId":"70198484","displayToPublicDate":"2018-08-06T12:17:01","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1454,"text":"Ecological Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Effectiveness of environmental flows for riparian restoration in arid regions: A tale of four rivers","docAbstract":"Environmental flows have become important restoration tools on regulated rivers. However, environmental flows are often constrained by other demands within the river system and thus typically are comprised of smaller water volumes than the natural flows they are meant to replace, which can limit their functional efficacy. We review environmental flow programs aimed at restoring riparian vegetation on four arid zone rivers: the Tarim River in China; the Bill Williams River in Arizona, U.S.; the delta of the Colorado River in Mexico; and the Murrumbidgee River in southern Australia. Our goal is to determine what worked and what did not work to accomplish restoration goals. The lower Tarim River in China formerly formed a “green corridor” across the Taklamakan Desert. The riparian zone deteriorated due to diversion of surface and groundwater for irrigated agriculture. A massive restoration program began in 2000 with release of 1038 million cubic meters of water over the first three years. Groundwater levels rose but the ecological response was less than expected politically, socially and within the scientific community. However, releases continued and by 2015 portions of the original iconic Populus euphratica (Euphrates poplar) forest were reestablished. The natural flow regime of the Bill Williams River was disrupted by construction of a dam in 1968, dramatically reducing peak flows along with associated fluvial processes. As a result, the channel narrowed and riparian vegetation expanded and was comprised largely of an introduced shrub species (Tamarix spp.). Environmental flow releases including small, managed floods and sustained base flows have been implemented since the mid 1990’s to promote establishment and maintenance of native riparian trees (cottonwoods and willows) and have been successful, although in a “downsized” portion of the valley bottom. Experience from the Bill Williams was used to help design the Minute 319 environmental flow in the delta of the Colorado River in 2014. Water was released as a short, one-time pulse during spring with the intent of starting new cohorts of cottonwood and willow. However, fluvial disturbance was limited by the relatively small magnitude pulse, low flows did not continue throughout the growing season in some reaches, native tree recruitment was low, and most of the new plants recruited were Tamarix. The inundated portion of the floodplain did respond with a temporary increase in greenness as measured by satellite vegetation indices, however. The Murrumbidgee River in Australia is a tributary in the Murray-Darling River Basin, which supports iconic red gum (Eucalyptus camaldulensis) forests that depend on near-yearly floods for maintenance. During the recent Millennial Drought (2000–2010) environmental flows were provided on an experimental basis to small portions of the Yanga National Forest to see how much water was needed. As with the Colorado River delta, gains in vegetation vigor as measured by satellite vegetation indices following the flows were temporary. Environmental flows in the Bill Williams were able to restore enough overbank flooding and fluvial disturbance to promote some establishment of new cohorts of trees, but on the Colorado and Murrumbidgee Rivers larger volumes of total flows released over longer periods and targeted restoration will be needed to restore the ecosystems. A measure of success in restoring the Euphrates poplar forest on the Tarim and germinating new chorts of willows on the Bill Williams has been achieved after 15–20 years of environmental flows, but the Colorado River delta and Murrumbidgee Rivers have only received one or two flows. Success in enhancing native trees in the Colorado delta has been achieved in restoration plots, but the Murrumbidgee will require large overbank flows on a continuing schedule to rejuvenate the red gum forest.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoleng.2017.01.009","usgsCitation":"Glenn, E., Nagler, P.L., Shafroth, P.B., and Jarchow, C., 2017, Effectiveness of environmental flows for riparian restoration in arid regions: A tale of four rivers: Ecological Engineering, v. 106, no. Part B, p. 695-703, https://doi.org/10.1016/j.ecoleng.2017.01.009.","productDescription":"9 p.","startPage":"695","endPage":"703","ipdsId":"IP-077206","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":469213,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoleng.2017.01.009","text":"Publisher Index Page"},{"id":356190,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"106","issue":"Part B","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc50ae4b0f5d57878eae8","contributors":{"authors":[{"text":"Glenn, Edward P.","contributorId":56542,"corporation":false,"usgs":false,"family":"Glenn","given":"Edward P.","affiliations":[{"id":13060,"text":"Department of Soil, Water and Environmental Science, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":741632,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":741631,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shafroth, Patrick B. 0000-0002-6064-871X shafrothp@usgs.gov","orcid":"https://orcid.org/0000-0002-6064-871X","contributorId":2000,"corporation":false,"usgs":true,"family":"Shafroth","given":"Patrick","email":"shafrothp@usgs.gov","middleInitial":"B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":741633,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jarchow, Christopher 0000-0002-0424-4104 cjarchow@usgs.gov","orcid":"https://orcid.org/0000-0002-0424-4104","contributorId":196069,"corporation":false,"usgs":true,"family":"Jarchow","given":"Christopher","email":"cjarchow@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":741634,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70198094,"text":"70198094 - 2017 - Emulation of long-term changes in global climate: application to the late Pliocene and future","interactions":[],"lastModifiedDate":"2018-07-16T11:35:53","indexId":"70198094","displayToPublicDate":"2018-07-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1250,"text":"Climate of the Past","active":true,"publicationSubtype":{"id":10}},"title":"Emulation of long-term changes in global climate: application to the late Pliocene and future","docAbstract":"Multi-millennial transient simulations of climate changes have a range of important applications, such as for investigating key geologic events and transitions for which high-resolution palaeoenvironmental proxy data are available, or for projecting the long-term impacts of future climate evolution on the performance of geological repositories for the disposal of radioactive wastes. However, due to the high computational requirements of current fully coupled general circulation models (GCMs), long-term simulations can generally only be performed with less complex models and/or at lower spatial resolution. In this study, we present novel longterm “continuous” projections of climate evolution based on the output from GCMs, via the use of a statistical emulator. The emulator is calibrated using ensembles of GCM simulations, which have varying orbital configurations and atmospheric CO2 concentrations and enables a variety of investigations of long-term climate change to be conducted, which would not be possible with other modelling techniques on the same temporal and spatial scales. To illustrate the potential applications, we apply the emulator to the late Pliocene (by modelling surface air temperature – SAT), comparing its results with palaeo-proxy data for a number of global sites, and to the next 200 kyr (thousand years) (by modelling SAT and precipitation). A range of CO2 scenarios are prescribed for each period. During the late Pliocene, we find that emulated SAT varies on an approximately precessional timescale, with evidence of increased obliquity response at times. A comparison of atmospheric CO2 concentration for this period, estimated using the proxy sea surface temperature (SST) data from different sites and emulator results, finds that relatively similar CO2 concentrations are estimated based on sites at lower latitudes, whereas higher-latitude sites show larger discrepancies. In our second illustrative application, spanning the next 200 kyr into the future, we find that SAT oscillations appear to be primarily influenced by obliquity for the first ∼ 120 kyr, whilst eccentricity is relatively low, after which precession plays a more dominant role. Conversely, variations in precipitation over the entire period demonstrate a strong precessional signal. Overall, we find that the emulator provides a useful and powerful tool for rapidly simulating the long-term evolution of climate, both past and future, due to its relatively high spatial resolution and relatively low computational cost. However, there are uncertainties associated with the approach used, including the inability of the emulator to capture deviations from a quasi-stationary response to the forcing, such as transient adjustments of the deep-ocean temperature and circulation, in addition to its limited range of fixed ice sheet configurations and its requirement for prescribed atmospheric CO2 concentrations.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/cp-2017-57","usgsCitation":"Lord, N.S., Crucifix, M., Lunt, D.J., Thorne, M.C., Bounceur, N., Dowsett, H.J., O’Brien, C.L., and Ridgwell, A., 2017, Emulation of long-term changes in global climate: application to the late Pliocene and future: Climate of the Past, v. 13, p. 1539-1571, https://doi.org/10.5194/cp-2017-57.","productDescription":"33 p.","startPage":"1539","endPage":"1571","ipdsId":"IP-083123","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":469214,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/cp-2017-57","text":"Publisher Index Page"},{"id":355675,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc50ae4b0f5d57878eaea","contributors":{"authors":[{"text":"Lord, Natalie S.","contributorId":206300,"corporation":false,"usgs":false,"family":"Lord","given":"Natalie","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":740007,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crucifix, Michel","contributorId":206301,"corporation":false,"usgs":false,"family":"Crucifix","given":"Michel","email":"","affiliations":[],"preferred":false,"id":740008,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lunt, Daniel J.","contributorId":101168,"corporation":false,"usgs":true,"family":"Lunt","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":740009,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thorne, Mike C.","contributorId":206302,"corporation":false,"usgs":false,"family":"Thorne","given":"Mike","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":740010,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bounceur, Nabila","contributorId":206303,"corporation":false,"usgs":false,"family":"Bounceur","given":"Nabila","email":"","affiliations":[],"preferred":false,"id":740011,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dowsett, Harry J. 0000-0003-1983-7524 hdowsett@usgs.gov","orcid":"https://orcid.org/0000-0003-1983-7524","contributorId":949,"corporation":false,"usgs":true,"family":"Dowsett","given":"Harry","email":"hdowsett@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":740012,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"O’Brien, Charlotte L.","contributorId":206304,"corporation":false,"usgs":false,"family":"O’Brien","given":"Charlotte","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":740013,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ridgwell, A.","contributorId":192917,"corporation":false,"usgs":false,"family":"Ridgwell","given":"A.","email":"","affiliations":[],"preferred":false,"id":740014,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70198037,"text":"70198037 - 2017 - Interactions of estuarine shoreline infrastructure with multiscale sea level variability","interactions":[],"lastModifiedDate":"2018-07-16T10:48:25","indexId":"70198037","displayToPublicDate":"2018-07-09T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2321,"text":"Journal of Geophysical Research: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Interactions of estuarine shoreline infrastructure with multiscale sea level variability","docAbstract":"Sea level rise increases the risk of storms and other short‐term water‐rise events, because it sets a higher water level such that coastal surges become more likely to overtop protections and cause floods. To protect coastal communities, it is necessary to understand the interaction among multiday and tidal sea level variabilities, coastal infrastructure, and sea level rise. We performed a series of numerical simulations for San Francisco Bay to examine two shoreline scenarios and a series of short‐term and long‐term sea level variations. The two shoreline configurations include the existing topography and a coherent full‐bay containment that follows the existing land boundary with an impermeable wall. The sea level variability consists of a half‐meter perturbation, with duration ranging from 2 days to permanent (i.e., sea level rise). The extent of coastal flooding was found to increase with the duration of the high‐water‐level event. The nonlinear interaction between these intermediate scale events and astronomical tidal forcing only contributes ∼1% of the tidal heights; at the same time, the tides are found to be a dominant factor in establishing the evolution and diffusion of multiday high water events. Establishing containment at existing shorelines can change the tidal height spectrum up to 5%, and the impact of this shoreline structure appears stronger in the low‐frequency range. To interpret the spatial and temporal variability at a wide range of frequencies, Optimal Dynamic Mode Decomposition is introduced to analyze the coastal processes and an inverse method is applied to determine the coefficients of a 1‐D diffusion wave model that quantify the impact of bottom roughness, tidal basin geometry, and shoreline configuration on the high water events
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017JC012730","usgsCitation":"Wang, R., Herdman, L.M., Erikson, L.H., Barnard, P., Hummel, M., and Stacey, M., 2017, Interactions of estuarine shoreline infrastructure with multiscale sea level variability: Journal of Geophysical Research: Oceans, v. 122, no. 12, p. 9962-9979, https://doi.org/10.1002/2017JC012730.","productDescription":"18 p.","startPage":"9962","endPage":"9979","ipdsId":"IP-086795","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469215,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017jc012730","text":"Publisher Index Page"},{"id":355566,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"122","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-15","publicationStatus":"PW","scienceBaseUri":"5b46e540e4b060350a15d05d","contributors":{"authors":[{"text":"Wang, Ruo-Quian","contributorId":206190,"corporation":false,"usgs":false,"family":"Wang","given":"Ruo-Quian","email":"","affiliations":[{"id":37278,"text":"University of Dundee","active":true,"usgs":false}],"preferred":false,"id":739743,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Herdman, Liv M. 0000-0002-5444-6441 lherdman@usgs.gov","orcid":"https://orcid.org/0000-0002-5444-6441","contributorId":149964,"corporation":false,"usgs":true,"family":"Herdman","given":"Liv","email":"lherdman@usgs.gov","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":739741,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":739744,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":147147,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","email":"pbarnard@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":739742,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hummel, Michelle","contributorId":204476,"corporation":false,"usgs":false,"family":"Hummel","given":"Michelle","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":739745,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stacey, Mark T.","contributorId":94531,"corporation":false,"usgs":false,"family":"Stacey","given":"Mark T.","affiliations":[{"id":12776,"text":"Department of Civil and Environmental Engineering, University of California, Berkeley, California, USA","active":true,"usgs":false}],"preferred":false,"id":739746,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70197816,"text":"70197816 - 2017 - Improvements in absolute seismometer sensitivity calibration using local earth gravity measurements","interactions":[],"lastModifiedDate":"2018-07-03T10:56:23","indexId":"70197816","displayToPublicDate":"2018-06-20T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Improvements in absolute seismometer sensitivity calibration using local earth gravity measurements","docAbstract":"The ability to determine both absolute and relative seismic amplitudes is fundamentally limited by the accuracy and precision with which scientists are able to calibrate seismometer sensitivities and characterize their response. Currently, across the Global Seismic Network (GSN), errors in midband sensitivity exceed 3% at the 95% confidence interval and are the least‐constrained response parameter in seismic recording systems. We explore a new methodology utilizing precise absolute Earth gravity measurements to determine the midband sensitivity of seismic instruments. We first determine the absolute sensitivity of Kinemetrics EpiSensor accelerometers to 0.06% at the 99% confidence interval by inverting them in a known gravity field at the Albuquerque Seismological Laboratory (ASL). After the accelerometer is calibrated, we install it in its normal configuration next to broadband seismometers and subject the sensors to identical ground motions to perform relative calibrations of the broadband sensors. Using this technique, we are able to determine the absolute midband sensitivity of the vertical components of Nanometrics Trillium Compact seismometers to within 0.11% and Streckeisen STS‐2 seismometers to within 0.14% at the 99% confidence interval. The technique enables absolute calibrations from first principles that are traceable to National Institute of Standards and Technology (NIST) measurements while providing nearly an order of magnitude more precision than step‐table calibrations.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120170218","usgsCitation":"Anthony, R.E., Ringler, A.T., and Wilson, D.C., 2017, Improvements in absolute seismometer sensitivity calibration using local earth gravity measurements: Bulletin of the Seismological Society of America, v. 108, no. 1, p. 503-510, https://doi.org/10.1785/0120170218.","productDescription":"8 p.","startPage":"503","endPage":"510","ipdsId":"IP-090884","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":355236,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"108","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-19","publicationStatus":"PW","scienceBaseUri":"5b46e607e4b060350a15d240","contributors":{"authors":[{"text":"Anthony, Robert 0000-0001-7089-8846 reanthony@usgs.gov","orcid":"https://orcid.org/0000-0001-7089-8846","contributorId":202829,"corporation":false,"usgs":true,"family":"Anthony","given":"Robert","email":"reanthony@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":738639,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ringler, Adam T. 0000-0002-9839-4188 aringler@usgs.gov","orcid":"https://orcid.org/0000-0002-9839-4188","contributorId":145576,"corporation":false,"usgs":true,"family":"Ringler","given":"Adam","email":"aringler@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":738640,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilson, David C. 0000-0003-2582-5159 dwilson@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-5159","contributorId":145580,"corporation":false,"usgs":true,"family":"Wilson","given":"David","email":"dwilson@usgs.gov","middleInitial":"C.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":738641,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70197366,"text":"70197366 - 2017 - Environmental influences on the nesting phenology and productivity of Mississippi Kites (Ictinia mississippiensis)","interactions":[],"lastModifiedDate":"2018-05-31T15:13:42","indexId":"70197366","displayToPublicDate":"2018-05-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3551,"text":"The Condor","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Environmental influences on the nesting phenology and productivity of Mississippi Kites (Ictinia mississippiensis)","title":"Environmental influences on the nesting phenology and productivity of Mississippi Kites (Ictinia mississippiensis)","docAbstract":"Identifying sources of annual variation in the reproductive success of a species may provide valuable insights into how the species may be affected by future environmental or climatic conditions. We examined annual variation in the nesting phenology, productivity, and apparent nest success of Mississippi Kites (Ictinia mississippiensis), a species common in urban areas in the southern Great Plains, from May through August. We monitored 498 Mississippi Kite nesting attempts in Lubbock, Texas, USA, between 2004 and 2015, from which we modeled daily survival rate as a function of local weather conditions, drought severity, and the state of the El Niño Southern Oscillation. We observed significant annual variation in median incubation initiation date (range = May 20 to June 5), the probability of nest success (range = 0.31–0.90), and productivity (range = 0.25–1.00 fledglings per nest). Our models of daily survival rate suggested that higher daily temperatures, severe storm events, extreme drought conditions, and La Niña events negatively influenced nest survival. 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Thomas","contributorId":205310,"corporation":false,"usgs":false,"family":"Cichosz","given":"Thomas","email":"","affiliations":[],"preferred":false,"id":736826,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hansen, Gretchen","contributorId":174810,"corporation":false,"usgs":false,"family":"Hansen","given":"Gretchen","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":736827,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Simonson, Timothy D.","contributorId":99439,"corporation":false,"usgs":true,"family":"Simonson","given":"Timothy","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":736828,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hennessy, Joseph M.","contributorId":199495,"corporation":false,"usgs":false,"family":"Hennessy","given":"Joseph 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Here we interpret concurrent time series satellite, meteorological, and aerosol geochemical data from the GoA to examine how interannual variability in regional weather patterns impacts offshore aerosol glacial Fe deposition. In 2011, when a northerly Aleutian Low (AL) was persistent during fall, dust emission was suppressed and highly intermittent due to prevalent wet conditions, low winds, and a deep early season snowpack. Conversely, in 2012, frequent and prolonged fall dust storms and high offshore glacial Fe transport were driven by dry conditions and strong offshore winds generated by persistent strong high pressure over the Alaskan interior and Bering Sea and a southerly AL. Twenty‐five‐fold interannual variability in regional offshore glacial aerosol Fe deposition indicates that glacial dust's impact on GoA nutrient budgets is highly dynamic and particularly sensitive to regional climate forcing.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017GL073565","usgsCitation":"Schroth, A.W., Crusius, J., Gasso, S., Moy, C.M., Buck, N.J., Resing, J.A., and Campbell, R.W., 2017, Atmospheric deposition of glacial iron in the Gulf of Alaska impacted by the position of the Aleutian Low: Geophysical Research Letters, v. 44, no. 10, p. 5053-5061, https://doi.org/10.1002/2017GL073565.","productDescription":"9 p.","startPage":"5053","endPage":"5061","ipdsId":"IP-086628","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":469217,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017gl073565","text":"Publisher Index Page"},{"id":356117,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gulf of Alaska","volume":"44","issue":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-29","publicationStatus":"PW","scienceBaseUri":"5b6fc50be4b0f5d57878eaec","contributors":{"authors":[{"text":"Schroth, Andrew W.","contributorId":192042,"corporation":false,"usgs":false,"family":"Schroth","given":"Andrew","email":"","middleInitial":"W.","affiliations":[{"id":17809,"text":"University of Vermont, Burlington","active":true,"usgs":false}],"preferred":false,"id":741305,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crusius, John 0000-0003-2554-0831 jcrusius@usgs.gov","orcid":"https://orcid.org/0000-0003-2554-0831","contributorId":2155,"corporation":false,"usgs":true,"family":"Crusius","given":"John","email":"jcrusius@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":741304,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gasso, Santiago","contributorId":196444,"corporation":false,"usgs":false,"family":"Gasso","given":"Santiago","email":"","affiliations":[],"preferred":false,"id":741306,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moy, Christopher M.","contributorId":206622,"corporation":false,"usgs":false,"family":"Moy","given":"Christopher","email":"","middleInitial":"M.","affiliations":[{"id":37354,"text":"Geology Department, University of Otago","active":true,"usgs":false}],"preferred":false,"id":741307,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Buck, Nathan J.","contributorId":206623,"corporation":false,"usgs":false,"family":"Buck","given":"Nathan","email":"","middleInitial":"J.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":741308,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Resing, Joseph A.","contributorId":206619,"corporation":false,"usgs":false,"family":"Resing","given":"Joseph","email":"","middleInitial":"A.","affiliations":[{"id":37351,"text":"University of Washington; Joint Institute for the Study of the Atmosphere and the Ocean","active":true,"usgs":false}],"preferred":false,"id":741309,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Campbell, Robert W.","contributorId":206624,"corporation":false,"usgs":false,"family":"Campbell","given":"Robert","email":"","middleInitial":"W.","affiliations":[{"id":13600,"text":"Prince William Sound Science Center","active":true,"usgs":false}],"preferred":false,"id":741310,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70187004,"text":"sir20175013 - 2017 - The HayWired Earthquake Scenario","interactions":[{"subject":{"id":70187003,"text":"sir20175013v1 - 2017 - The HayWired earthquake scenario—Earthquake hazards","indexId":"sir20175013v1","publicationYear":"2017","noYear":false,"chapter":"A–H","displayTitle":"The HayWired Earthquake Scenario—Earthquake Hazards","title":"The HayWired earthquake scenario—Earthquake hazards"},"predicate":"IS_PART_OF","object":{"id":70187004,"text":"sir20175013 - 2017 - The HayWired Earthquake Scenario","indexId":"sir20175013","publicationYear":"2017","noYear":false,"title":"The HayWired Earthquake Scenario"},"id":1},{"subject":{"id":70195667,"text":"sir20175013v2 - 2021 - The HayWired earthquake scenario—Engineering implications","indexId":"sir20175013v2","publicationYear":"2021","noYear":false,"chapter":"I–Q","displayTitle":"The HayWired Earthquake Scenario—Engineering Implications","title":"The HayWired earthquake scenario—Engineering implications"},"predicate":"IS_PART_OF","object":{"id":70187004,"text":"sir20175013 - 2017 - The HayWired Earthquake Scenario","indexId":"sir20175013","publicationYear":"2017","noYear":false,"title":"The HayWired Earthquake Scenario"},"id":2},{"subject":{"id":70206048,"text":"sir20175013V3 - 2019 - The HayWired earthquake scenario—Societal consequences","indexId":"sir20175013V3","publicationYear":"2019","noYear":false,"chapter":"R–W","displayTitle":"The HayWired Earthquake Scenario—Societal Consequences","title":"The HayWired earthquake scenario—Societal consequences"},"predicate":"IS_PART_OF","object":{"id":70187004,"text":"sir20175013 - 2017 - The HayWired Earthquake Scenario","indexId":"sir20175013","publicationYear":"2017","noYear":false,"title":"The HayWired Earthquake Scenario"},"id":3}],"lastModifiedDate":"2022-04-22T20:42:59.787763","indexId":"sir20175013","displayToPublicDate":"2018-04-17T12:00:00","publicationYear":"2017","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":"2017-5013","title":"The HayWired Earthquake Scenario","docAbstract":"The 1906 Great San Francisco earthquake (magnitude 7.8) and the 1989 Loma Prieta earthquake (magnitude 6.9) each motivated residents of the San Francisco Bay region to build countermeasures to earthquakes into the fabric of the region. Since Loma Prieta, bay-region communities, governments, and utilities have invested tens of billions of dollars in seismic upgrades and retrofits and replacements of older buildings and infrastructure. Innovation and state-of-the-art engineering, informed by science, including novel seismic-hazard assessments, have been applied to the challenge of increasing seismic resilience throughout the bay region. However, as long as people live and work in seismically vulnerable buildings or rely on seismically vulnerable transportation and utilities, more work remains to be done.
With that in mind, the U.S. Geological Survey (USGS) and its partners developed the HayWired scenario as a tool to enable further actions that can change the outcome when the next major earthquake strikes. By illuminating the likely impacts to the present-day built environment, well-constructed scenarios can and have spurred officials and citizens to take steps that change the outcomes the scenario describes, whether used to guide more realistic response and recovery exercises or to launch mitigation measures that will reduce future risk.
The HayWired scenario is the latest in a series of like-minded efforts to bring a special focus onto the impacts that could occur when the Hayward Fault again ruptures through the east side of the San Francisco Bay region as it last did in 1868. Cities in the east bay along the Richmond, Oakland, and Fremont corridor would be hit hardest by earthquake ground shaking, surface fault rupture, aftershocks, and fault afterslip, but the impacts would reach throughout the bay region and far beyond. The HayWired scenario name reflects our increased reliance on the Internet and telecommunications and also alludes to the interconnectedness of infrastructure, society, and our economy. How would this earthquake scenario, striking close to Silicon Valley, impact our interconnected world in ways and at a scale we have not experienced in any previous domestic earthquake?
The area of present-day Contra Costa, Alameda, and Santa Clara Counties contended with a magnitude-6.8 earthquake in 1868 on the Hayward Fault. Although sparsely populated then, about 30 people were killed and extensive property damage resulted. The question of what an earthquake like that would do today has been examined before and is now revisited in the HayWired scenario. Scientists have documented a series of prehistoric earthquakes on the Hayward Fault and are confident that the threat of a future earthquake, like that modeled in the HayWired scenario, is real and could happen at any time. The team assembled to build this scenario has brought innovative new approaches to examining the natural hazards, impacts, and consequences of such an event. Such an earthquake would also be accompanied by widespread liquefaction and landslides, which are treated in greater detail than ever before. The team also considers how the now-prototype ShakeAlert earthquake early warning system could provide useful public alerts and automatic actions.
Scientific Investigations Report 2017–5013 and accompanying data releases are the products of an effort led by the USGS, but this body of work was created through the combined efforts of a large team including partners who have come together to form the HayWired Coalition (see chapter A). Use of the HayWired scenario has already begun. More than a full year of intensive partner engagement, beginning in April 2017, is being directed toward producing the most in-depth look ever at the impacts and consequences of a large earthquake on the Hayward Fault. With the HayWired scenario, our hope is to encourage and support the active ongoing engagement of the entire community of the San Francisco Bay region by providing the scientific, engineering, and economic and social science inputs for use in exercises and planning well into the future.
As HayWired volumes are published, they will be made available at https://doi.org/10.3133/sir20175013.
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Office—Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025
https://earthquake.usgs.gov/
This 1:50,000-scale U.S. Geological Survey geologic map represents a compilation of the most recent geologic studies of the upper Arkansas River valley between Leadville and Salida, Colorado. The valley is structurally controlled by an extensional fault system that forms part of the prominent northern Rio Grande rift, an intra-continental region of crustal extension. This report also incorporates new detailed geologic mapping of previously poorly understood areas within the map area and reinterprets previously studied areas. The mapped region extends into the Proterozoic metamorphic and intrusive rocks in the Sawatch Range west of the valley and the Mosquito Range to the east. Paleozoic rocks are preserved along the crest of the Mosquito Range, but most of them have been eroded from the Sawatch Range. Numerous new isotopic ages better constrain the timing of both Proterozoic intrusive events, Late Cretaceous to early Tertiary intrusive events, and Eocene and Miocene volcanic episodes, including widespread ignimbrite eruptions. The uranium-lead ages document extensive about 1,440-million years (Ma) granitic plutonism mostly north of Buena Vista that produced batholiths that intruded an older suite of about 1,760-Ma metamorphic rocks and about 1,700-Ma plutonic rocks. As a result of extension during the Neogene and possibly latest Paleogene, the graben underlying the valley is filled with thick basin-fill deposits (Dry Union Formation and older sediments), which occupy two sub-basins separated by a bedrock high near the town of Granite. The Dry Union Formation has undergone deep erosion since the late Miocene or early Pliocene. During the Pleistocene, ongoing stream incision by the Arkansas River and its major tributaries has been interrupted by periodic aggradation. From Leadville south to Salida as many as seven mapped alluvial depositional units, that range in age from early to late Pleistocene, record periodic aggradational events along these streams that are commonly associated with deposition of glacial outwash or bouldery glacial-flood deposits. Many previously unrecognized Neogene and Quaternary faults, some of the latter with possible Holocene displacement, have been identified on lidar (light detection and ranging) imagery which covers 59 percent of the map area. This imagery has also permitted more accurate remapping of glacial, fluvial, and mass-movement deposits and aided in the determination of their relative ages. Recently published 10beryllium cosmogenic surface-exposure ages, coupled with our new geologic mapping, have revealed the timing and rates of late Pleistocene deglaciation. Glacial dams that impounded the Arkansas River at Clear Creek and possibly at Pine Creek failed at least three times during the middle and late Pleistocene, resulting in catastrophic floods and deposition of enormous boulders and bouldery alluvium downstream; at least two failures occurred during the late Pleistocene during the Pinedale glaciation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3382","usgsCitation":"Kellogg, K.S., Shroba, R.R., Ruleman, C.A., Bohannon, R.G., McIntosh, W. C., Premo, W.R., Cosca, M.A., Moscati, R.J., and Brandt, T.R., 2017, Geologic map of the upper Arkansas River valley region, north-central Colorado: U.S. Geological Survey Scientific Investigations Map 3382, pamphlet 70 p., 2 sheets, scale 1:50,000, https://doi.org/10.3133/sim3382.","productDescription":"Report: vi, 70 p.; 4 Sheets; Data Release; Read Me","numberOfPages":"80","onlineOnly":"Y","ipdsId":"IP-078599","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":348012,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75B00XQ","text":"USGS Data Release","description":"USGS data release","linkHelpText":"Data release for the geologic map of the upper Arkansas River valley region, north-central Colorado"},{"id":351653,"rank":9,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sim/3382/versionHist.txt","size":"4.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3382 Version History"},{"id":348008,"rank":7,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3382/sim3382_ReadMe.txt","text":"Read Me","size":"12.0 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3382 Read Me"},{"id":348002,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3382/sim3382_sheet1_hillshade.pdf","text":"Sheet 1, with hillshade—","size":"102 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3382 Sheet 1 with hillshade","linkHelpText":"Geologic map with shaded relief"},{"id":347996,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3382/sim3382_sheet1_georeferenced.pdf","text":"Sheet 1, georeferenced—","size":"335 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3382 Sheet 1 georeferenced","linkHelpText":"Georeferenced geologic map"},{"id":348005,"rank":6,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3382/sim3382_sheet2.pdf","text":"Sheet 2—","size":"1.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3382 Sheet 2","linkHelpText":" Correlation and description of map units"},{"id":348004,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3382/sim3382_sheet1_no_hillshade.pdf","text":"Sheet 1, without hillshade—","size":"50.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3382 Sheet 1 without hillshade","linkHelpText":"Geologic map without shaded relief"},{"id":347995,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3382/sim3382.pdf","text":"Report","size":"17.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3382 Report"},{"id":347994,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3382/coverthb2.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Upper Arkansas River Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.5,\n 38.5\n ],\n [\n -105.9,\n 38.5\n ],\n [\n -105.9,\n 39.5\n ],\n [\n -106.5,\n 39.5\n ],\n [\n -106.5,\n 38.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geosciences and Environmental Change Science Center
U.S. Geological Survey
Box 25046, MS-980
Denver, CO 80225-0046
Although the use of bird-borne data loggers has become widespread in avian field research, the effects of capture and transmitter attachment on behavior and demographic rates are not often measured. Tag- and capture-induced effects on individual behavior, survival and reproduction may limit extrapolation of transmitter data to wider populations. However, measuring individual responses to capture and tagging is a necessary step in developing research techniques that minimize negative effects. We measured the short-term behavioral effects of handling and GPS transmitter attachment on Brown Pelicans under both captive and field conditions, and followed tagged individuals through a full breeding season to assess whether capture and transmitter attachment increased rates of nest abandonment or breeding failure. We observed slight increases in preening among tagged individuals 0–2 h after capture relative to controls that had not been captured or tagged, with a corresponding reduction in time spent resting. One to three days post-capture, nesting behavior of tagged pelicans resembled that of neighbors that had not been captured or tagged. Eighty-eight percent of tagged breeders remained at the same nest location for more than 48 h after capture, attending nests and chicks for an average of 49 days, and 51% were assumed to successfully fledge young. Breeding success was driven primarily by variation in location; however, sex and handling time also influenced the probability of successful breeding in tagged pelicans, suggesting that individual characteristics and the capture process itself can confound the effects of capture and transmitter attachment. We conclude that pelicans fitted with GPS transmitters exhibit comparable behaviors to untagged individuals within a day of capture and that GPS tracking is a viable technique for studying behavior and demography in this species. We also identify measures to minimize post-capture nest abandonment rates in tracking studies, including minimizing handling time and covering nests during processing.
","language":"English","publisher":"Springer","doi":"10.1007/s10336-016-1418-3","usgsCitation":"Lamb, J.S., Satge, Y.G., Fiorello, C.V., and Jodice, P.G., 2017, Behavioral and reproductive effects of bird-borne data logger attachment on Brown Pelicans (Pelecanus occidentalis) on three temporal scales: Journal of Ornithology, v. 158, no. 2, p. 617-627, https://doi.org/10.1007/s10336-016-1418-3.","productDescription":"11 p.","startPage":"617","endPage":"627","ipdsId":"IP-073599","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":469218,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10336-016-1418-3","text":"Publisher Index Page"},{"id":354546,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.7783203125,\n 25\n ],\n [\n -82,\n 25\n ],\n [\n -82,\n 30.86451022625836\n ],\n [\n -97.7783203125,\n 30.86451022625836\n ],\n [\n -97.7783203125,\n 25\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"158","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-01","publicationStatus":"PW","scienceBaseUri":"5b155df4e4b092d9651e1b96","contributors":{"authors":[{"text":"Lamb, Juliet S. 0000-0003-0358-3240","orcid":"https://orcid.org/0000-0003-0358-3240","contributorId":198059,"corporation":false,"usgs":false,"family":"Lamb","given":"Juliet","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":736677,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Satge, Yvan G.","contributorId":200132,"corporation":false,"usgs":false,"family":"Satge","given":"Yvan","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":736678,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fiorello, Christine V.","contributorId":172678,"corporation":false,"usgs":false,"family":"Fiorello","given":"Christine","email":"","middleInitial":"V.","affiliations":[{"id":27076,"text":"Oiled Wildlife Care Network, UC Davis","active":true,"usgs":false}],"preferred":false,"id":736679,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X pjodice@usgs.gov","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":200009,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","email":"pjodice@usgs.gov","middleInitial":"G.R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":736617,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70194673,"text":"70194673 - 2017 - Element migration of pyrites during ductile deformation of the Yuleken porphyry Cu deposit (NW-China)","interactions":[],"lastModifiedDate":"2018-09-20T16:35:26","indexId":"70194673","displayToPublicDate":"2018-03-29T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2954,"text":"Ore Geology Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Element migration of pyrites during ductile deformation of the Yuleken porphyry Cu deposit (NW-China)","docAbstract":"The strongly deformed Yuleken porphyry Cu deposit (YPCD) occurs in the Kalaxiangar porphyry Cu belt (KPCB), which occupies the central area of the Central Asian Orogenic Belt (CAOB) between the Sawu’er island arc and the Altay Terrane in northern Xinjiang. The YPCD is one of several typical subduction-related deposits in the KPCB, which has undergone syn-collisional and post-collisional metallogenic overprinting. The YPCD is characterized by three pyrite-forming stages, namely a hydrothermal stage A (Py I), a syn-ductile deformation stage B (Py II) characterized by Cu-Au enrichment, and a fracture-filling stage C (Py III). In this study, we conducted systematic petrographic and geochemical studies of pyrites and coexist biotite, which formed during different stages, in order to constrain the physicochemical conditions of the ore formation. Euhedral, fragmented Py I has low Pb and high Te and Se concentration and Ni contents are low with Co/Ni ratios mostly between 1 and 10 (average 9.00). Py I is further characterized by enrichments of Bi, As, Ni, Cu, Te and Se in the core relative to the rim domains. Anhedral round Py II has moderate Co and Ni contents with high Co/Ni ratios >10 (average 95.2), and average contents of 46.5 ppm Pb and 5.80 ppm Te. Py II is further characterized by decreasing Bi, Cu, Pb, Zn, Ag, Te, Mo, Sb and Au contents from the rim to the core domains. Annealed Py III has the lowest Co content of all pyrite types with Co/Ni ratios mostly <0.1 (average 1.33). Furthermore, Py III has average contents of 3.31 ppm Pb, 1.33 ppm Te and 94.6 ppm Se. In addition, Fe does not correlate with Cu and S in the Py I and Py III, while Py II displays a negative correlation between Fe and Cu as well as a positive correlation between Fe and S. Therefore, pyrites which formed during different tectonic regimes also have different chemical compositions. Biotite geothermometer and oxygen fugacity estimates display increasing temperatures and oxygen fugacities from stage A to stage B, while temperature and oxygen fugacities decrease from stage B to stage C. The Co/Ni ratio of pyrite depends discriminates between the different mineralizing stages in the Yuleken porphyry copper deposit: Py II, associated with the deformation stage B and Cu-enrichment, shows higher Co/Ni ratios and enrichments of Pb, Zn, Mo, Te and Sb than the pyrites formed during the other two stages. The Co/Ni ratio of pyrite can not only apply to discriminate the submarine exhalative, magmatic or sedimentary origins for ore deposits but also can distinguish different ore-forming stages in a single porphyry Cu deposit. Thus, Co/Ni ratio of pyrites may act as an important exploration tool to distinguish pyrites from Cu-rich versus barren area. Furthermore, the distribution of Cu, Mo, Pb, Au, Bi, Sb and Zn in the variably deformed pyrite is proportional to the extent of deformation of the pyrites, indicating in accordance with variable physicochemical conditions different element migration behavior during the different stages of deformation and, thus, mineralisation.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.oregeorev.2017.10.019","usgsCitation":"Hong, T., Xu, X., Gao, J., Peters, S., Li, J., Cao, M., Xiang, P., Wu, C., and You, J., 2017, Element migration of pyrites during ductile deformation of the Yuleken porphyry Cu deposit (NW-China): Ore Geology Reviews, v. 100, p. 205-219, https://doi.org/10.1016/j.oregeorev.2017.10.019.","productDescription":"15 p.","startPage":"205","endPage":"219","ipdsId":"IP-092178","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":352972,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"100","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee788e4b0da30c1bfc2ba","contributors":{"authors":[{"text":"Hong, Tao","contributorId":201265,"corporation":false,"usgs":false,"family":"Hong","given":"Tao","email":"","affiliations":[],"preferred":false,"id":724856,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Xu, Xing-Wang","contributorId":201266,"corporation":false,"usgs":false,"family":"Xu","given":"Xing-Wang","email":"","affiliations":[],"preferred":false,"id":724857,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gao, Jungang","contributorId":201267,"corporation":false,"usgs":false,"family":"Gao","given":"Jungang","email":"","affiliations":[],"preferred":false,"id":724858,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peters, Stephen 0000-0002-4431-5675 speters@usgs.gov","orcid":"https://orcid.org/0000-0002-4431-5675","contributorId":167263,"corporation":false,"usgs":true,"family":"Peters","given":"Stephen","email":"speters@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":724855,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Li, Jilei","contributorId":201276,"corporation":false,"usgs":false,"family":"Li","given":"Jilei","email":"","affiliations":[],"preferred":false,"id":724859,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cao, Mingjian","contributorId":201277,"corporation":false,"usgs":false,"family":"Cao","given":"Mingjian","email":"","affiliations":[],"preferred":false,"id":724860,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Xiang, Peng","contributorId":201270,"corporation":false,"usgs":false,"family":"Xiang","given":"Peng","email":"","affiliations":[],"preferred":false,"id":724861,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wu, Chu","contributorId":201272,"corporation":false,"usgs":false,"family":"Wu","given":"Chu","email":"","affiliations":[],"preferred":false,"id":724862,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"You, Jun","contributorId":201273,"corporation":false,"usgs":false,"family":"You","given":"Jun","email":"","affiliations":[],"preferred":false,"id":724863,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70238847,"text":"70238847 - 2017 - Extending the habitat concept to the airspace","interactions":[],"lastModifiedDate":"2022-12-15T13:15:20.502484","indexId":"70238847","displayToPublicDate":"2018-03-24T09:29:00","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Extending the habitat concept to the airspace","docAbstract":"Habitat is one of the most familiar and fundamental concepts in the fields of ecology, animal behavior, and wildlife conservation and management. Humans interact with habitats through their senses and experiences and education to such a degree that their perceptions of habitat have become second nature. For this reason, it may be difficult at first to accept the airspace as habitat, an area that is invisible, untouchable, highly dynamic, and its occupants difficult to see. Nonetheless, the habitat concept, by definition and in practice, applies readily to the airspace. Some ecological and behavioral processes including habitat selection, foraging, and reproduction are operational in the airspace, while others, particularly those mediated by resource limitation such as territoriality, are likely uncommon if present at all. The behaviors of flying animals increasingly expose them to anthropogenic hazards as development of the airspace accelerates. This exacerbates the need to identify approaches for managing these human–wildlife conflicts in aerial habitats, especially where human safety or at-risk populations are concerned. The habitat concept has proven useful in shaping environmental law and policy to help mitigate these conflicts. It remains to be seen whether current law can bend to include a more expansive concept of habitat that includes the airspace.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Aeroecology","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-319-68576-2_3","usgsCitation":"Diehl, R.H., Peterson, A.C., Bolus, R.T., and Johnson, D., 2017, Extending the habitat concept to the airspace, chap. of Aeroecology, p. 47-69, https://doi.org/10.1007/978-3-319-68576-2_3.","productDescription":"23 p.","startPage":"47","endPage":"69","ipdsId":"IP-072820","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":410476,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2018-03-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Diehl, Robert H. 0000-0001-9141-1734 rhdiehl@usgs.gov","orcid":"https://orcid.org/0000-0001-9141-1734","contributorId":3396,"corporation":false,"usgs":true,"family":"Diehl","given":"Robert","email":"rhdiehl@usgs.gov","middleInitial":"H.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":858902,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peterson, Anna C.","contributorId":299880,"corporation":false,"usgs":false,"family":"Peterson","given":"Anna","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":858903,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bolus, Rachel T. rbolus@usgs.gov","contributorId":299881,"corporation":false,"usgs":false,"family":"Bolus","given":"Rachel","email":"rbolus@usgs.gov","middleInitial":"T.","affiliations":[{"id":32977,"text":"Southern Utah University","active":true,"usgs":false}],"preferred":false,"id":858904,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Douglas H. 0000-0002-7778-6641","orcid":"https://orcid.org/0000-0002-7778-6641","contributorId":220516,"corporation":false,"usgs":true,"family":"Johnson","given":"Douglas H.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":858905,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70185961,"text":"sim3378 - 2017 - Hydrogeologic characteristics and geospatial analysis of water-table changes in the alluvium of the lower Arkansas River Valley, southeastern Colorado, 2002, 2008, and 2015","interactions":[],"lastModifiedDate":"2018-03-08T14:30:44","indexId":"sim3378","displayToPublicDate":"2018-03-08T15:25:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3378","title":"Hydrogeologic characteristics and geospatial analysis of water-table changes in the alluvium of the lower Arkansas River Valley, southeastern Colorado, 2002, 2008, and 2015","docAbstract":"The U.S. Geological Survey in cooperation with the Lower Arkansas Valley Water Conservancy District measures groundwater levels periodically in about 100 wells completed in the alluvial material of the Arkansas River Valley in Pueblo, Crowley, Otero, Bent, and Prowers Counties in southeastern Colorado, of which 95 are used for the analysis in this report. The purpose of this report is to provide information to water-resource administrators, managers, planners, and users about groundwater characteristics in the alluvium of the lower Arkansas Valley extending roughly 150 miles between Pueblo Reservoir and the Colorado-Kansas State line. This report includes three map sheets showing (1) bedrock altitude at the base of the alluvium of the lower Arkansas Valley; (2) estimated spring-to-spring and fall-to-fall changes in water-table altitude between 2002, 2008, and 2015; and (3) estimated saturated thickness in the alluvium during spring and fall of 2002, 2008, and 2015, and thickness of the alluvium in the lower Arkansas Valley. Water-level changes were analyzed by geospatial interpolation methods.
Available data included all water-level measurements made between January 1, 2001, and December 31, 2015; however, only data from fall and spring of 2002, 2008, and 2015 are mapped in this report. To account for the effect of John Martin Reservoir in Bent County, Colorado, lake levels at the reservoir were assigned to points along the approximate shoreline and were included in the water-level dataset. After combining the water-level measurements and lake levels, inverse distance weighting was used to interpolate between points and calculate the altitude of the water table for fall and spring of each year for comparisons. Saturated thickness was calculated by subtracting the bedrock surface from the water-table surface. Thickness of the alluvium was calculated by subtracting the bedrock surface from land surface using a digital elevation model.
In order to analyze the response of the alluvium to varying environmental and anthropogenic conditions, the percentage of area of the lower Arkansas Valley showing an absolute change of 3 feet or less was calculated for each of the six water-table altitude change maps. For fall water-table altitude change maps, the periods between 2002 and 2008, 2008 and 2015, and 2002 and 2015 showed that 86.5 percent, 85.2 percent, and 66.3 percent of the study area, respectively, showed a net change of 3 feet or less. In the spring water-table altitude change maps these periods showed a net change of 3 feet or less in 94.4 percent, 96.1 percent, and 90.2 percent of the study area, respectively. While the estimated change in water-table altitude was slightly greater and more variable in fall-to-fall comparisons, these high percentages of area with relatively small net changes indicated that, at least in comparisons of the years presented, there was not a large amount of fluctuation in the altitude of the water table.
The saturated thickness in the lower Arkansas Valley was between 25 and 50 feet in 34.4 to 35.9 percent of the study area, depending on the season and year. Between 30.2 and 35.6 percent of the area showed saturated thicknesses between 0 and 25 feet. Less than 1 percent of the area showed a saturated thickness greater than 200 feet in all mapped seasons and years.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3378","collaboration":"Prepared in cooperation with the Lower Arkansas Valley Water Conservancy District","usgsCitation":"Holmberg, M.J., 2017, Hydrogeologic characteristics and geospatial analysis of water-table changes in the alluvium of the lower Arkansas River Valley, southeastern Colorado, 2002, 2008, and 2015: U.S. Geological Survey Scientific Investigations Map 3378, pamphlet 9 p., 3 sheets, scale 1:130,000 and 1:575, 000, https://doi.org/10.3133/sim3378.","productDescription":"Report: vi, 9 p.; 3 Sheets: 43.0 x 32.0 inches or smaller; 2 Appendixes; Data Release; Read Me","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-081751","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":341216,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3378/sim3378_sheet3.pdf","text":"Sheet 3","size":"17.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3378 Sheet 3","linkHelpText":" Estimated Saturated Thickness of the Alluvium, Spring 2002, 2008, and 2015; Fall, 2002, 2008, and 2015, and Estimated Thickness of the Alluvium in the Lower Arkansas River Valley, Southeast Colorado"},{"id":341219,"rank":8,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3378/sim3378Readme.txt","text":"Read Me","size":"12.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3378 Read Me"},{"id":341217,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sim/3378/sim3387_appendix1.xlsx","text":"Appendix 1","size":"36.0 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIM 3378 Appendix 1","linkHelpText":"Well Information and Measured Water Levels in the lower Arkansas Valley, Southeast Colorado, 2001–2015"},{"id":341213,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3378/coverthb.jpg"},{"id":341303,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71G0JF6","text":"USGS data release","description":"USGS data release","linkHelpText":"Hydrogeologic Characteristics and Geospatial Analysis of Water-Table Changes in the Alluvium of the Lower Arkansas River Valley, Southeastern Colorado, 2002, 2008, and 2015"},{"id":341215,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3378/sim3378_sheet2.pdf","text":"Sheet 2","size":"17.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3378 Sheet 2","linkHelpText":"Estimated Change in Water-Table Altitude, Spring-to-Spring, 2002–2008, 2018–2015, and 2002–2015; Fall-to-Fall, 2002–2008, 2018–2015, and 2002–2015; and Locations of Monitoring Wells in the Alluvium of the Lower Arkansas River Valley, Southeast Colorado"},{"id":341218,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sim/3378/sim3387_appendix2.pdf","text":"Appendix 2","size":"572 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3378 Appendix 2","linkHelpText":" Hydrographs Showing Water-Table Altitude in Select Monitoring Wells in the lower Arkansas Valley and Water-Surface Altitude in John Martin Reservoir, Southeast Colorado, 2001–2015"},{"id":341223,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3378/sim3378_sheet1.pdf","text":"Sheet 1","size":"8.02 MB ","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3378 Sheet 1","linkHelpText":" Bedrock Altitude at the Base of the Alluvium of the Lower Arkansas River Valley, Southeast Colorado"},{"id":341221,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3378/sim3378.pdf","text":"Report","size":"1.25 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3378 Report"}],"country":"United States","state":"Colorado","otherGeospatial":"Arkansas River Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.66125488281249,\n 37.93986540897977\n ],\n [\n -102.041015625,\n 37.93986540897977\n ],\n [\n -102.041015625,\n 38.29424797320529\n ],\n [\n -104.66125488281249,\n 38.29424797320529\n ],\n [\n -104.66125488281249,\n 37.93986540897977\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Colorado Water Science Center
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Monitoring and conserving waterbirds, including Sora (Porzana carolina), in Missouri, is constrained by the lack of information on migration phenology. We performed nocturnal distance sampling surveys by ATV across 11 state and federal managed wetlands in Missouri, USA from 2012–2015 to compare the timing of Sora' autumn migration among years. Migration of Sora in Missouri began in the first week of August, on average it peaked on 25 September, and continued through the last week of October. We detected migration of Sora earlier in autumn than did previous work. We found the start and end of migration did not vary annually in 3 of 4 years. With our results, wetland managers should be able to better time their management for rails in Missouri.
","language":"English","publisher":"The Wilson Ornithological Society","doi":"10.1676/16-108.1","usgsCitation":"Fournier, A., Mengel, D.C., Gbur, E.E., and Krementz, D.G., 2017, Timing of autumn migration of Sora (Porzana carolina) in Missouri: Wilson Journal of Ornithology, v. 129, no. 4, p. 765-770, https://doi.org/10.1676/16-108.1.","productDescription":"6 p.","startPage":"765","endPage":"770","ipdsId":"IP-071137","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":352872,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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