Recovering species are often limited to much smaller areas than they historically occupied. Conservation planning for the recovering species is often based on this limited range, which may simply be an artifact of where the surviving population persisted. Southern sea otters (Enhydra lutris nereis) were hunted nearly to extinction but recovered from a small remnant population on a remote stretch of the California outer coast, where most of their recovery has occurred. However, studies of recently-recolonized estuaries have revealed that estuaries can provide southern sea otters with high quality habitats featuring shallow waters, high production and ample food, limited predators, and protected haul-out opportunities. Moreover, sea otters can have strong effects on estuarine ecosystems, fostering seagrass resilience through their consumption of invertebrate prey. Using a combination of literature reviews, population modeling, and prey surveys we explored the former estuarine habitats outside the current southern sea otter range to determine if these estuarine habitats can support healthy sea otter populations. We found the majority of studies and conservation efforts have focused on populations in exposed, rocky coastal habitats. Yet historical evidence indicates that sea otters were also formerly ubiquitous in estuaries. Our habitat-specific population growth model for California’s largest estuary—San Francisco Bay—determined that it alone can support about 6,600 sea otters, more than double the 2018 California population. Prey surveys in estuaries currently with (Elkhorn Slough and Morro Bay) and without (San Francisco Bay and Drakes Estero) sea otters indicated that the availability of prey, especially crabs, is sufficient to support healthy sea otter populations. Combining historical evidence with our results, we show that conservation practitioners could consider former estuarine habitats as targets for sea otter and ecosystem restoration. This study reveals the importance of understanding how recovering species interact with all the ecosystems they historically occupied, both for improved conservation of the recovering species and for successful restoration of ecosystem functions and processes.
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2019 - Is the timing, pace and success of the monarch migration associated with sun angle?","interactions":[],"lastModifiedDate":"2019-12-10T17:09:34","indexId":"70207164","displayToPublicDate":"2019-12-10T17:06:18","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Is the timing, pace and success of the monarch migration associated with sun angle?","docAbstract":"A basic question concerning the monarch butterfly’s fall migration is which monarchs succeed in reaching overwintering sites in Mexico, which fail—and why. We document the timing and pace of the fall migration, ask whether the sun’s position in the sky is associated with the pace of the migration, and whether timing affects success in completing the migration. Using data from the Monarch Watch tagging program, we explore whether the fall monarch migration is associated with the daily maximum vertical angle of the sun above the horizon (Sun Angle at Solar Noon, SASN) or whether other processes are more likely to explain the pace of the migration. From 1998 to 2015, more than 1.38 million monarchs were tagged and 13,824 (1%) were recovered in Mexico. The pace of migration was relatively slow early in the migration but increased in late September and declined again later in October as the migrating monarchs approached lower latitudes. This slow-fast-slow pacing in the fall migration is consistent with monarchs reaching latitudes with the same SASN, day after day, as they move south to their overwintering sites. The observed pacing pattern and overall movement rates are also consistent with monarchs migrating at a pace determined by interactions among SASN, temperature, and daylength. The results suggest monarchs successfully reaching the Monarch Butterfly Biosphere Reserve (MBBR) migrate within a “migration window” with an SASN of about 57° at the leading edge of the migration and 46° at the trailing edge. Migrants reaching locations along the migration route with SASN outside this migration window may be considered early or late migrants. We noted several years with low overwintering abundance of monarchs, 2004 and 2011–2014, with high percentages of late migrants. This observation suggests a possible effect of migration timing on population size. The migration window defined by SASN might serve as a framework against which to establish the influence of environmental factors on the size, geographic distribution, and timing of past and future fall migrations.","language":"English","publisher":"Frontiers","doi":"10.3389/fevo.2019.00442","usgsCitation":"Taylor, O.R., Lovett, J., Gibo, D.L., Weiser, E.L., Thogmartin, W.E., Semmens, D.J., Diffendorfer, J., Pleasants, J.M., Pecoraro, S., and Grundel, R., 2019, Is the timing, pace and success of the monarch migration associated with sun angle?: Frontiers in Ecology and Evolution, v. 7, 442, https://doi.org/10.3389/fevo.2019.00442.","productDescription":"442","ipdsId":"IP-107707","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":458988,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2019.00442","text":"Publisher Index 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03354000), Indiana. Water-quality data used in the analyses were collected by several agencies between calendar years 1991 and 2017, and streamflow (discharge) data were collected by the USGS. For most of the water-quality constituents, there were suitable data to facilitate an analysis of the 26-year period extending from calendar years 1991 to 2017 (water years 1992 to 2017); however, shorter analytical periods were necessary for total Kjeldahl nitrogen for the study gages at Muncie and near Centerton and for total suspended solids for the study gage near Centerton.
Temporal trends in streamflows at the study gages for the period extending from water years 1978 to 2017 were assessed using Exploration and Graphics for RivEr Trends (EGRET) and Mann-Kendall and Pettitt tests. With just one exception, the annual maximum and mean daily streamflows and the annual minimum 7-day mean streamflows at the study gages demonstrated upward trends (increasing streamflows) in the EGRET analyses. The exception was the annual 7-day minimum streamflow at the study gage near Nora, which indicated no trend. Mann-Kendall tests also indicated that the average trend for the annual maximum daily, annual mean daily, and annual 7-day minimum streamflow statistics between water years 1978 and 2017 was upward at each of the study gages; however, only the trends in the annual mean daily streamflows at the study gage at Muncie and the annual maximum daily streamflows at the study gages near Nora and near Centerton were statistically significant at a 0.05 probability level. The Pettitt tests indicated that a statistically significant step trend (abrupt change) in annual mean daily streamflows occurred at each of the study gages around water year 2001.
The seasonal distributions of total suspended solids, total phosphorus, nitrate plus nitrite, and total Kjeldahl nitrogen concentrations at the study gages were evaluated to identify patterns and other distinguishing characteristics by examining boxplots of concentrations as a function of month of the year. Seasonal distributions of nitrate plus nitrite concentrations and total suspended solids concentrations differed from each other but were generally similar among the three study gages for a given constituent. Median concentrations of nitrate plus nitrite were highest during the January–June months, whereas median concentrations of total suspended solids were highest during June and July. Seasonal distributions of total phosphorus concentrations were similar at the study gages near Nora and near Centerton, but the seasonal distribution was noticeably different at the study gage at Muncie, which had monthly median concentrations that were substantially lower than at the two downstream study gages (near Nora and near Centerton). The seasonal distribution of total Kjeldahl nitrogen concentrations differed in pattern among the three study gages; however, in general, some of the higher monthly median total Kjeldahl nitrogen concentrations at each study gage were associated with the late spring and summer periods.
The Weighted Regressions on Time, Discharge, and Season (WRTDS) method implemented in EGRET was used to estimate water-year annual mean daily concentrations and flux of nutrients and total suspended solids, as well as estimates of concentrations and flux that were “normalized” to remove the effect of year-to-year variation in streamflow. The approximate coefficients of determination for the WRTDS regression models ranged from a high of 0.82 for total phosphorus for the study gage near Centerton to a low of 0.19 for nitrate plus nitrite for the study gage near Nora.
Loads and yields of total suspended solids, total phosphorus, nitrate plus nitrite, and total Kjeldahl nitrogen were estimated for analytical periods consisting of the longest periods of concurrent record at the three study gages. Loads of each of the constituents increased sequentially from the most upstream study gage to the most downstream study gage; however, the same was not true for yields. The highest yields of total suspended solids, total phosphorus, and total Kjeldahl nitrogen occurred at the most upstream study gage (at Muncie); however, the highest yield of nitrate plus nitrite occurred at the most downstream study gage (near Centerton).
WRTDS bootstrap tests were used to assess the magnitude, direction, and likelihood of changes in annual flow-normalized mean daily concentrations and flux of total suspended solids, total phosphorus, nitrate plus nitrite, and total Kjeldahl nitrogen at the study gages between water years 1997 and 2017. Changes in flow-normalized concentrations and flux of the constituents between water years 1997 and 2017 were mostly downward (decreasing). The exceptions were likely to highly likely upward (increasing) changes in (1) flow-normalized annual mean daily concentration and annual flux for total suspended solids and total phosphorus at the study gage at Muncie, (2) flow-normalized annual mean daily total phosphorus concentration at the study gage near Centerton, (3) flow-normalized annual flux of total phosphorus at the study gage near Centerton, and (4) flow-normalized annual mean daily nitrate plus nitrite concentration at the study gage near Centerton. Although an upward change in flow-normalized nitrate plus nitrite concentrations was likely at the study gage near Centerton, flow-normalized annual flux of nitrate plus nitrite at that study gage was determined to have a highly likely downward change.
EGRET and Exploration and Graphics for RivEr Trends Confidence Intervals (EGRETci) analyses can be used to improve our understanding of how concentrations and flux change as functions of time and streamflow, as well as provide information on how the relations between streamflow and constituent concentrations have changed within the calendar year between any 2 years included in the analyses. Examples of those uses, illustrating changes between calendar years 1992 and 2017, were given for total suspended solids concentrations at the study gage near Nora and for nitrate plus nitrite concentrations at the study gage near Centerton.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195119","collaboration":"Prepared in cooperation with The Nature Conservancy","usgsCitation":"Koltun, G.F., 2019, Trends in streamflow and concentrations and flux of nutrients and total suspended solids in the Upper White River at Muncie, near Nora, and near Centerton, Indiana: U.S. Geological Survey Scientific Investigations Report 2019–5119, 34 p., https://doi.org/10.3133/sir20195119.","productDescription":"Report: viii, 34 p.; Data Release","numberOfPages":"46","onlineOnly":"Y","ipdsId":"IP-109722","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":399602,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109513.htm"},{"id":370134,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VN5RKV","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Total suspended solids, total phosphorus, nitrate plus nitrite, and total Kjeldahl nitrogen concentration data for the White River at Muncie, near Nora, and near Centerton, Indiana, 1991–2017"},{"id":370133,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5119/sir20195119.pdf","text":"Report","size":"3.99 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5119"},{"id":370132,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5119/coverthb.jpg"}],"country":"United States","state":"Indiana","county":"Morgan County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.8311,\n 39.2633\n ],\n [\n -84.9667,\n 39.2633\n ],\n [\n -84.9667,\n 40.3608\n ],\n [\n -86.8311,\n 40.3608\n ],\n [\n -86.8311,\n 39.2633\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
6460 Busch Boulevard Ste 100
Columbus, OH 43229–1737
Volcanoes are the main pathway to the surface for volatiles that are stored within the Earth. Carbon dioxide (CO2) is of particular interest because of its potential for climate forcing. Understanding the balance of CO2 that is transferred from the Earth’s surface to the Earth’s interior, hinges on accurate quantification of the long-term emissions of volcanic CO2 to the atmosphere. Here we present an updated evaluation of the world’s volcanic CO2 emissions that takes advantage of recent improvements in satellite-based monitoring of sulfur dioxide, the establishment of ground-based networks for semi-continuous CO2-SO2 gas sensing and a new approach to estimate key volcanic gas parameters based on magma compositions. Our results reveal a global volcanic CO2 flux of 51.3 ± 5.7 Tg CO2/y (11.7 × 1011 mol CO2/y) for non-eruptive degassing and 1.8 ± 0.9 Tg/y for eruptive degassing during the period from 2005 to 2015. While lower than recent estimates, this global volcanic flux implies that a significant proportion of the surface-derived CO2 subducted into the Earth’s mantle is either stored below the arc crust, is efficiently consumed by microbial activity before entering the deeper parts of the subduction system, or becomes recycled into the deep mantle to potentially form diamonds.
","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/s41598-019-54682-1","usgsCitation":"Fischer, T.P., Arellano, S., Carn, S., Aiuppa, A., Bo Galle, Allard, P., Lopez, T., Shinohara, H., Kelly, P.J., Cynthia Werner, Cardelini, C., and Chiodini, G., 2019, The emissions of CO2 and other volatiles from the world’s subaerial volcanoes: Scientific Reports, v. 9, 18716, 11 p., https://doi.org/10.1038/s41598-019-54682-1.","productDescription":"18716, 11 p.","ipdsId":"IP-112914","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":458990,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-019-54682-1","text":"Publisher Index Page"},{"id":372915,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Fischer, Tobias P.","contributorId":223024,"corporation":false,"usgs":false,"family":"Fischer","given":"Tobias","email":"","middleInitial":"P.","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":783858,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arellano, Santiago","contributorId":223025,"corporation":false,"usgs":false,"family":"Arellano","given":"Santiago","email":"","affiliations":[{"id":40644,"text":"University of Chalmers","active":true,"usgs":false}],"preferred":false,"id":783859,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carn, Simon","contributorId":223026,"corporation":false,"usgs":false,"family":"Carn","given":"Simon","email":"","affiliations":[{"id":36614,"text":"Michigan Tech","active":true,"usgs":false}],"preferred":false,"id":783860,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aiuppa, Alessandro","contributorId":223027,"corporation":false,"usgs":false,"family":"Aiuppa","given":"Alessandro","email":"","affiliations":[{"id":25431,"text":"University of Palermo","active":true,"usgs":false}],"preferred":false,"id":783861,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bo Galle","contributorId":148064,"corporation":false,"usgs":false,"family":"Bo Galle","affiliations":[{"id":16988,"text":"Chalmers University of Technology, Sweden","active":true,"usgs":false}],"preferred":false,"id":783862,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Allard, Patrick","contributorId":223028,"corporation":false,"usgs":false,"family":"Allard","given":"Patrick","email":"","affiliations":[{"id":30776,"text":"Institut de Physique du Globe de Paris","active":true,"usgs":false}],"preferred":false,"id":783863,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lopez, Taryn","contributorId":199516,"corporation":false,"usgs":false,"family":"Lopez","given":"Taryn","email":"","affiliations":[],"preferred":false,"id":783864,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Shinohara, Hiroshi","contributorId":223029,"corporation":false,"usgs":false,"family":"Shinohara","given":"Hiroshi","email":"","affiliations":[{"id":27746,"text":"Geological Survey of Japan","active":true,"usgs":false}],"preferred":false,"id":783865,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kelly, Peter J. 0000-0002-3868-1046 pkelly@usgs.gov","orcid":"https://orcid.org/0000-0002-3868-1046","contributorId":5931,"corporation":false,"usgs":true,"family":"Kelly","given":"Peter","email":"pkelly@usgs.gov","middleInitial":"J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":783857,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cynthia Werner","contributorId":223030,"corporation":false,"usgs":false,"family":"Cynthia Werner","affiliations":[{"id":37768,"text":"USGS Contractor","active":true,"usgs":false}],"preferred":false,"id":783866,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Cardelini, Carlo","contributorId":223031,"corporation":false,"usgs":false,"family":"Cardelini","given":"Carlo","email":"","affiliations":[{"id":40645,"text":"Università di Perugia","active":true,"usgs":false}],"preferred":false,"id":783867,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Chiodini, Giovanni","contributorId":223032,"corporation":false,"usgs":false,"family":"Chiodini","given":"Giovanni","email":"","affiliations":[{"id":40646,"text":"INGV Bologna","active":true,"usgs":false}],"preferred":false,"id":783868,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70205085,"text":"sir20195086 - 2019 - Multi-resource analysis: A proof of concept study of natural resource tradeoffs in the Piceance Basin, Colorado, using the net resources assessment (NetRA) decision support tool","interactions":[],"lastModifiedDate":"2022-04-22T21:31:50.364127","indexId":"sir20195086","displayToPublicDate":"2019-12-10T14:25:00","publicationYear":"2019","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":"2019-5086","displayTitle":"Multi-Resource Analysis: A Proof of Concept Study of Natural Resource Tradeoffs in the Piceance Basin, Colorado, Using the Net Resources Assessment (NetRA) Decision Support Tool","title":"Multi-resource analysis: A proof of concept study of natural resource tradeoffs in the Piceance Basin, Colorado, using the net resources assessment (NetRA) decision support tool","docAbstract":"The U.S. Geological Survey (USGS) is developing a multi-resource analysis (MRA) line of products to inform land-use decision makers. Specifically, MRA products will integrate scientific information, include considerations for natural resource interrelations, and quantify the effects of resource management decisions in biophysical, economic, and societal terms. As part of the establishment of the MRA, the USGS, in collaboration with the University of New Mexico, has developed the Net Resources Assessment (NetRA) decision support tool. As a proof of concept analysis, the NetRA was applied to the Piceance basin in Colorado in a hypothetical example to illustrate how resource managers could use the NetRA to consider tradeoffs of natural resources among alternative development plans and land cover patterns within a geographic region.
The NetRA is a policy-relevant approach to assess the availability of multiple natural resources. It is an analytical toolset that may be used to examine the spatiotemporal relations between development of energy and mineral resources and delivery of biological natural resources. The NetRA operates at multiple map scales and contains a set of integrated, compatible submodels with specific data requirements for natural resource stocks, engineering economics, biophysical, and ecological data for ecosystem services stocks, market prices, regulations, and nonmarket values.
The NetRA includes an explicit process to consider the interdependence between development and conservation, which is a crucial consideration in land-management and land-use decisions. The NetRA is used to estimate an expected net resource value (NRV). The NRV is the expected, present value, economic benefit from the extraction of a resource (for example, natural gas) minus the total cost of production, which is the aggregation of the development, production, and social costs. Social costs include private costs plus any external costs. There can be external social benefits associated with natural gas production, such as increased demand for locally produced goods and increased employment in the local area through backward and forward linkages of natural gas production. The NRV is used to compare development outcomes (scenarios) from a range of exploration and development plans for cumulative energy production.
The Piceance basin application of the NetRA uses the NRV to assess the tradeoff between continuous natural gas extraction and the effects to the local populations of Odocoileus hemionus (mule deer) and aquatic species and to consumptive water uses for an area the size and resolution of a USGS energy resource assessment unit. In the proof of concept simulation, the 2.9-square-mile-area of USGS oil and gas assessment unit 50200263 (Piceance basin continuous gas unit of the Mesaverde Total Petroleum System) was gridded into 588 cells. From this area, seven clusters with potential for development and three that cannot be developed were identified; the three clusters that cannot be developed were identified as wilderness study areas, areas of critical environmental concern, and national forests. On the basis of these criteria, there are 118 cells unsuitable for development in the oil and gas assessment unit: 84 are in national forests, 23 are areas of critical environmental concern, and 11 are wilderness study areas. The remaining cells in the oil and gas assessment unit can be developed on both private and public lands.
Two scenarios were considered that are distinguished as plan 1 and plan 2. Plan 1 keeps the amount of land disturbance unchanged and limits the number of development locations to 140 grid cells for the production period, which constrains the amount of the energy resources available for development; the plan requires the usage of the Bureau of Land Management (BLM) unsuitability criteria. Plan 2 also limits the number of development locations to 140 grid cells for the production period but provides a constant volume of energy production by increasing the density of well pads within the cells. The effects of plan 2 to the NRV when there are five wells per pad and five pads per square mile happen mostly in the first 5 years of development, even though the effects on the population of mule deer continue in later years. This outcome is the result of the upfront development and investment costs and the initial effect to the ecosystem services.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195086","collaboration":"Prepared in cooperation with the University of New Mexico","usgsCitation":"Bernknopf, R., Broadbent, C., Adhikari, D., Mamun, S., Tidwell, V., Babis, C., and Pindilli, E., 2019, Multi-resource analysis—A proof of concept study of natural resource tradeoffs in the Piceance Basin, Colorado, using the net resources assessment (NetRA) decision support tool: U.S. Geological Survey Scientific Investigations Report 2019–5086, 40 p., https://doi.org/10.3133/sir20195086.","productDescription":"viii, 40 p.","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-088615","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":370122,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/cir1442","text":"Circular 1442","linkHelpText":"- Multi-Resource Analysis—Methodology and synthesis"},{"id":399539,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109512.htm"},{"id":370092,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5086/coverthb.jpg"},{"id":370099,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5086/sir20195086.pdf","text":"Report","size":"8.39 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5086"}],"country":"United States","state":"Colorado","otherGeospatial":"Piceance Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.22607421875,\n 40.463666324587685\n ],\n [\n -109.09423828125,\n 38.03078569382294\n ],\n [\n -108.12744140625,\n 37.43997405227057\n ],\n [\n -107.07275390625,\n 36.94989178681327\n ],\n [\n -106.2158203125,\n 36.84446074079564\n ],\n [\n -105.8203125,\n 37.142803443716836\n ],\n [\n -105.6884765625,\n 37.49229399862877\n ],\n [\n -105.0732421875,\n 37.125286284966805\n ],\n [\n -104.4580078125,\n 37.666429212090605\n ],\n [\n -104.4140625,\n 37.90953361677018\n ],\n [\n -104.8974609375,\n 38.77121637244273\n ],\n [\n -105.75439453125,\n 39.740986355883564\n ],\n [\n -105.18310546875,\n 40.17887331434696\n ],\n [\n -109.22607421875,\n 40.463666324587685\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Science and Decisions Center
U.S. Geological Survey
913 National Center
12201 Sunrise Valley Drive
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The New York-Pennsylvania area has a long history of hydrocarbon extraction, and the addition of shale gas extraction methods contributes to landscape disturbance borne by previously developed oil and non-shale gas resources. The main unconventional extraction method used to extract shale gas from the Marcellus Shale located in New York and Pennsylvania is hydraulic fracturing, or “fracking,” although other conventional methods are used extensively. All forms of hydrocarbon extraction disturb the surrounding landscape to some extent, primarily in the form of land clearance and degradation, road construction, and pipeline development, although the effects of these disturbances are not fully understood.
In this study, landscape-change metrics and indicators are used to analyze change in a 10-county region along the New York-Pennsylvania border—the New York counties of Allegany, Steuben, Chemung, Tioga, and Broome, and the Pennsylvania counties of McKean, Potter, Tioga, Bradford, and Susquehanna. This 10-county region was selected due to the differences in policies between the States of New York and Pennsylvania. While fracking occurred extensively in Pennsylvania over the past 10 years or more, the State of New York issued a temporary moratorium against hydraulic fracturing in 2010—citing repercussions that might affect air quality, water quality, and public health—and officially banned hydraulic fracturing in June 2015.
The quantification of landscape disturbance due to hydrocarbon extraction activities is presented in this report as land-use and land-cover (LULC) change between 2004 and 2013 and defined using specific disturbance categories (including well sites, roads, and pipelines) to compare the disturbances and changes, by county, on both sides of the New York-Pennsylvania border. The quantification was accomplished by gathering the signatures of disturbance from high-resolution aerial images, comparing the derived totals of disturbance, and then computing landscape metrics in a geographic information system (GIS) environment.
The collected data represent a summation of landscape disturbance from oil and gas development, as some of the data represented were established decades earlier. The Analytical Tools Interface for Landscape Assessments (ATtILA) software was used to calculate land-cover area and landscape metrics for each shale gas, non-shale gas, oil, and other infrastructure types associated with hydrocarbons across each county and both five-county regions in the study area. The three primary metrics used to describe changes in forest structure were (1)forest area, (2) interior forest area, and (3) forest edge area. The changes in metrics were subsequently evaluated using the Pearson correlation coefficient.
Overall, the disturbed-area footprint in the Pennsylvania region is considerably larger than the disturbed-area footprint in the New York region (13,687.9 hectares [ha] in Pennsylvania; 3,840.5 ha in New York). Disturbance per site is similar, with 1.2 disturbed ha per site in New York and 1.6 disturbed ha per site in Pennsylvania.
In the New York-Pennsylvania 10-county region, hydrocarbon-development and extraction disturbance strongly correlate with a reduction in the percentage of forest for the entire region. This observation also appears to be true in the New York five-county region for forest area. This form of disturbance in the New York five-county region shows significantly correlated changes in forest metrics (–0.4 percent total forest area), particularly in the percentage of interior forest (–1.2 percent total area) and forest edge (+0.7 percent total area). On the other hand, gas and hydrocarbon-development and extraction disturbance (1.0 percent total area) in the Pennsylvania five-county region strongly correlates with a total decline in forest area and agricultural land area (–0.8 percent combined total area) but not with either land-cover class separately.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195096","usgsCitation":"Roig-Silva, C.M., Milheim, L.E., Slonecker, E.T., Kalaly, S., and Chestnut, J., 2019, A comparison of hydrocarbon-related landscape disturbance patterns along the New York-Pennsylvania border, 2004–2013: U.S. Geological Survey Scientific Investigations Report 2019–5096, 23 p., https://doi.org/10.3133/sir20195096.","productDescription":"Report: v, 23 p.; Data Release","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-091180","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":399543,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109511.htm"},{"id":380624,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2019/5096/images/"},{"id":374941,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2019/5096/sir20195096.XML"},{"id":370125,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5096/sir20195096.pdf","text":"Report","size":"3.82 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5096"},{"id":370027,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5096/coverthb.jpg"},{"id":370021,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TT4Q67","text":"USGS data release","linkHelpText":"Natural gas and oil drilling disturbance in the Marcellus Shale region of the New York-Pennsylvania border"}],"country":"United States","state":"New York, Pennsylvania","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.9531,\n 41.4758\n ],\n [\n -75.6325,\n 41.4758\n ],\n [\n -75.6325,\n 42.5783\n ],\n [\n -78.9531,\n 42.5783\n ],\n [\n -78.9531,\n 41.4758\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Lower Mississippi-Gulf Water Science Center
Nashville, TN Office
U.S. Geological Survey
640 Grassmere Park Drive
Nashville, TN 37211
In 2005, the U.S. Geological Survey began a cooperative study with the New York City Department of Environmental Protection to characterize the local groundwater-flow system and identify potential sources of seeps on the southern embankment of the Hillview Reservoir in southern Westchester County, New York. The earthen embankment comprises low-permeability glacial clays that were excavated from the site and rest on a veneer of low-permeability glacial deposits that overlie crystalline bedrock. At least two groundwater-flow zones—one shallow and the other deep—overlie the bedrock at the reservoir. As part of the study, slug-test data from 38 screened wells were analyzed to determine the hydraulic conductivity of the sediments in the groundwater-flow zones. Slug-test data were collected from 12 wells at the Hillview Reservoir during August 2007 and from 25 wells at the reservoir and 1 monitoring well south of the reservoir in northern Bronx County in June 2012.
Hydraulic conductivity values at the reservoir ranged from 0.0012 to 2 feet per day. On the southern embankment, hydraulic conductivity ranged from 0.0026 to 1 foot per day for wells screened in the shallow saturated zone; 0.0012 to 2 feet per day for wells screened in the deep saturated zone; and 0.021 to 0.27 foot per day for wells screened in the toe of the southern embankment, where the deep and shallow saturated zones coalesce. A hydraulic conductivity of 0.016 foot per day was determined for a well partially screened in the crystalline-bedrock aquifer, which potentially indicates an interconnection of transmissive fractures near the bedrock surface. The results of four slug-out tests are also included in this report to quality assure the hydraulic conductivity estimates from the slug-in test analysis. The results of the four slug-out tests were within 8 percent of slug-in test results, with an average of less than 2 percent.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191102","collaboration":"Prepared in cooperation with the New York City Department of Environmental Protection","usgsCitation":"Noll, M.L., Chu, A., and Capurso, W.D., 2019, Slug-test analysis of selected wells at an earthen dam site in southern Westchester County, New York: U.S. Geological Survey Open-File Report 2019–1102, 14 p., https://doi.org/10.3133/ofr20191102.","productDescription":"Report: vi, 14 p.; Data Release","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-095039","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":399415,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109510.htm"},{"id":369616,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1102/coverthb.jpg"},{"id":369866,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1102/ofr20191102.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1102"},{"id":369619,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J404KW","text":"USGS data release","linkFileType":{"id":5,"text":"html"},"linkHelpText":"Data and analytical type-curve match for selected hydraulic tests in New York State"}],"country":"United States","state":"New York","county":"Westchester County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.87674808502196,\n 40.90551783054535\n ],\n [\n -73.86099815368652,\n 40.90551783054535\n ],\n [\n -73.86099815368652,\n 40.91821491609591\n ],\n [\n -73.87674808502196,\n 40.91821491609591\n ],\n [\n -73.87674808502196,\n 40.90551783054535\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
2045 Route 112, Building 4
Coram, NY 11727
Understanding the spatial ecology of sturgeon (Acipenseridae) has proven to be a challenge due to the life history characteristics of these fish, especially their long life span, intermittent spawning, and long‐distance migrations. Within the Huron‐Erie Corridor (HEC) of the Laurentian Great Lakes, habitat use of 247 lake sturgeon (Acipenser fulvescens ) was monitored over a three‐year period (2015–2017) with acoustic transmitters. Extensive spatial coverage of receivers throughout the St. Clair River, Lake St. Clair, and Detroit River between Lake Huron and Lake Erie (~150 km) allowed for continuous monitoring of the movements of acoustic‐tagged individuals. Sequence analysis of individual detection histories was used to describe lake sturgeon habitat use and to determine (1) whether distinct habitat‐use patterns occurred within the HEC; (2) whether the range of habitats occupied varied across seasons among sturgeon grouped by common patterns; and (3) whether variation identified was related to tagging sites in the two rivers or sex. Lake sturgeon were active throughout the HEC, but five distinct habitat‐use patterns were identified. River residents were not broadly distributed across entire rivers, but rather associated with particular segments (middle Detroit River, St. Clair River delta). Variations in habitat‐use sequences were in part related to three river tagging sites, but not sex, and did not produce groups with sequences that reflected all five habitat‐use patterns derived from cluster analysis. Lake sturgeon distribution was reduced to fewer habitat segments during winter and expanded to the maximum extent during the spring and summer. Conservation planning that incorporates behavioral diversity of habitat use is relatively rare due to a lack of observations on movements of individuals at biologically relevant spatial and temporal scales, but using telemetry and sequence analysis methods may promote the success of conservation and restoration efforts.
Larval fish ecology is poorly characterized because sampling is difficult and tools for phenotypically identifying larvae are poorly developed. While DNA barcoding can help address the latter problem, ‘universal’ primers do not work for all fish species. The Roanoke River in the southeastern United States includes seven darters (Family Percide: Tribe Etheostomatini). We made 393 collections of larval fishes in 2015 and 2018, examined darter larvae for morphometric and pigmentation traits, developed PCR primers amplifying darter DNA, and evaluated three gear types for collecting larval darters. Amplified DNA sequences for 1351 larvae matched archived mitochondrial cytochrome oxidase I sequences for darters occurring in the ecosystem. Larval darters were classified to genus with 100% accuracy using the ratio of pectoral fin length to body length; however, identification to species using morphometrics alone was subject to a misclassification rate of 11.8%, which can be resolved by considering pigmentation patterns. Gear-types varied considerably in their capture efficacy for larval darters; most Percina larvae were collected in drift nets. Larval Percina species appeared in the drift before Etheostoma species in both study years. Application of molecular genetic and phenotypic tools to larval fish identification can advance understanding of larval darter ecology.
","language":"English","publisher":"MDPI","doi":"10.3390/fishes4040059","usgsCitation":"Buckwalter, J., Angermeier, P.L., Argentina, J., Wolf, S., Floyd, S., and Hallerman, E., 2019, Drift of larval darters (Family Percidae) in the upper Roanoke River basin, USA, characterized using phenotypic and DNA barcoding markers: Fishes, v. 4, no. 4, 59, 16 p., https://doi.org/10.3390/fishes4040059.","productDescription":"59, 16 p.","ipdsId":"IP-113480","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":459002,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/fishes4040059","text":"Publisher Index Page"},{"id":396021,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina, Virginia","otherGeospatial":"Roanoke River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.2279052734375,\n 36.09349937380574\n ],\n [\n -77.1075439453125,\n 36.09349937380574\n ],\n [\n -77.1075439453125,\n 37.274052809979054\n ],\n [\n -79.2279052734375,\n 37.274052809979054\n ],\n [\n -79.2279052734375,\n 36.09349937380574\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"4","issue":"4","noUsgsAuthors":false,"publicationDate":"2019-12-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Buckwalter, Joseph","contributorId":279470,"corporation":false,"usgs":false,"family":"Buckwalter","given":"Joseph","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":834962,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Angermeier, Paul L. 0000-0003-2864-170X biota@usgs.gov","orcid":"https://orcid.org/0000-0003-2864-170X","contributorId":166679,"corporation":false,"usgs":true,"family":"Angermeier","given":"Paul","email":"biota@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":834961,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Argentina, Jane","contributorId":279471,"corporation":false,"usgs":false,"family":"Argentina","given":"Jane","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":834963,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wolf, Skylar","contributorId":279472,"corporation":false,"usgs":false,"family":"Wolf","given":"Skylar","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":834964,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Floyd, Stephen","contributorId":279473,"corporation":false,"usgs":false,"family":"Floyd","given":"Stephen","email":"","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":834965,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hallerman, Eric M.","contributorId":279474,"corporation":false,"usgs":false,"family":"Hallerman","given":"Eric M.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":834966,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70212557,"text":"70212557 - 2019 - Using incidental mark-encounter data to improve survival estimation","interactions":[],"lastModifiedDate":"2020-08-20T13:31:25.026173","indexId":"70212557","displayToPublicDate":"2019-12-08T08:26:08","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Using incidental mark-encounter data to improve survival estimation","docAbstract":"Currently, the volume of land ice on Earth is decreasing, driving consequential changes to global sea level and local stream habitat. Glacier retreat in Glacier National Park, Montana, U.S.A., is one example of land ice loss and glacier change. The U.S. Geological Survey Benchmark Glacier Project conducts glaciological research and collects field measurements across select North American glaciers, including Sperry Glacier located in Glacier National Park. These records provide direct evidence of glacier change. The amount and timing of Earth’s land ice that will be lost in the future depends on the future trajectory of greenhouse gas emissions. Ongoing glaciological research will enhance physical understanding and forecasting capabilities; however, the continued retreat and ice mass loss of small glaciers in Glacier National Park is certain.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193068","usgsCitation":"Florentine, C., 2019, Glacier retreat in Glacier National Park, Montana (ver. 1.1, December 2019): U.S. Geological Survey Fact Sheet 2019–3068, 2 p., https://doi.org/10.3133/fs20193068.","productDescription":"2 p.","onlineOnly":"N","ipdsId":"IP-110825","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":399143,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109486.htm"},{"id":370057,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/fs/2019/3068/versionHist.txt","text":"Version History","linkFileType":{"id":2,"text":"txt"},"description":"FS 2019-3068 Version History"},{"id":369842,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3068/coverthb2.jpg"},{"id":369843,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3068/fs20193068.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2019-3068"}],"country":"United States","state":"Montana","otherGeospatial":"Glacier National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.01586914062499,\n 48.070738264258296\n ],\n [\n -112.54394531249999,\n 48.070738264258296\n ],\n [\n -112.54394531249999,\n 48.97661158387714\n ],\n [\n -115.01586914062499,\n 48.97661158387714\n ],\n [\n -115.01586914062499,\n 48.070738264258296\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.1; December 6, 2019","contact":"Director, Northern Rocky Mountain Science Center
U.S. Geological Survey
2327 University Way, Suite 2
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The Arctic Alaska Province encompasses all lands and adjacent continental shelf areas north of the Brooks Range-Herald Arch tectonic belts and south of the northern (outboard) margin of the Alaska rift shoulder. Even though only a small part is thoroughly explored, it is one of the most prolific petroleum provinces in North America, with total known resources (cumulative production plus proved reserves) of about 28 billion barrels of oil equivalent.
For assessment purposes, the province is divided into a platform assessment unit, comprising the Alaska rift shoulder and its relatively undeformed flanks, and a fold-and-thrust belt assessment unit, comprising the deformed area north of the Brooks Range and Herald Arch tectonic belts. Mean estimates of undiscovered, technically recoverable resources include nearly 28 billion barrels of oil and 122 trillion cubic feet of nonassociated gas in the platform assessment unit and 2 billion barrels of oil and 59 trillion cubic feet of nonassociated gas in the fold-and-thrust belt assessment unit.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1824E","usgsCitation":"Houseknecht, D.W., Bird, K.J., and Garrity, C.P., 2019, Geology and assessment of undiscovered oil and gas resources of the Arctic Alaska Province, 2008, chap. E of Moore, T.E., and Gautier, D.L., eds., The 2008 Circum-Arctic Resource Appraisal: U.S. Geological Survey Professional Paper 1824, 25 p., https://doi.org/10.3133/pp1824E. [Supersedes USGS Scientific Investigations Report 2012–5147.]","productDescription":"Report: viii, 25 p.; 2 Appendixes","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-114210","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":370053,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/e/pp1824e_appendix1.xlsx","text":"Appendix 1","linkFileType":{"id":3,"text":"xlsx"},"description":"PP 1824 Chapter E Appendix 1"},{"id":370052,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1824/e/pp1824e.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1824 Chapter E"},{"id":370051,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1824/e/coverthb.jpg"},{"id":399506,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109507.htm"},{"id":370054,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/e/pp1824e_appendix2.xlsx","text":"Appendix 2","linkFileType":{"id":3,"text":"xlsx"},"description":"PP 1824 Chapter E Appendix 2"}],"country":"Canada, United States","state":"Alaska, Yukon","otherGeospatial":"Arctic Alaska Province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -136.0986328125,\n 68.89518688943544\n ],\n [\n -137.3291015625,\n 69.54987728327795\n ],\n [\n -156.7529296875,\n 71.37110941823617\n ],\n [\n -159.5654296875,\n 70.85908719717143\n ],\n [\n -161.015625,\n 70.27428967614655\n ],\n [\n -162.1142578125,\n 70.28911664330674\n ],\n [\n -164.3994140625,\n 68.98992503056704\n ],\n [\n -166.11328125,\n 68.942606818121\n ],\n [\n -166.5087890625,\n 68.38299634059615\n ],\n [\n -162.7294921875,\n 66.80922097449334\n ],\n [\n -161.19140625,\n 66.73990169639414\n ],\n [\n -154.599609375,\n 66.75724984139227\n ],\n [\n -149.4140625,\n 66.7745857647255\n ],\n [\n -143.61328125,\n 68.15520923883976\n ],\n [\n -141.1083984375,\n 68.13885164925573\n ],\n [\n -136.6259765625,\n 67.69277095059344\n ],\n [\n -135.3076171875,\n 68.15520923883976\n ],\n [\n -136.0986328125,\n 68.89518688943544\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Geology, Minerals, Energy, & Geophysics Science Center—Menlo Park
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
FAX 650-329-4936
Five integrator sites on streams draining mixed land-use watersheds were sampled monthly from July 2016 to June 2017. Two sites were sampled in the San Joaquin River watershed and one site was sampled in each of the Mokelumne River, Sacramento River, and Ulatis Creek watersheds.
A total of 53 out of 154 pesticides (18 herbicides, 14 insecticides, 13 fungicides, 7 breakdown products, and 1 synergist) were detected in surface-water samples and 95 percent of samples contained mixtures of 2 or more pesticides. The most frequently detected pesticides were the herbicides hexazinone, metolachlor, and diuron (present in 83 percent, 72 percent, and 67 percent of water samples, respectively), the insecticide methoxyfenozide (present in 83 percent of samples), and the fungicides boscalid and azoxystrobin (present in 67 percent and 58 percent of samples, respectively). Pesticide concentrations detected in water samples ranged from below method detection limits to 1,300 nanograms per liter (ng/L) for the insecticide chlorantraniliprole. A total of 4 pesticides (2 herbicides and 2 insecticides) were detected in suspended-sediment samples and 13 percent of suspended-sediment samples contained at least 1 pesticide. Pesticide concentrations detected in suspended-sediment samples ranged from 4.1 to 750 ng/L, both for the herbicide pendimethalin.
Six samples contained the insecticide imidacloprid at concentrations above the U.S. Environmental Protection Agency (EPA) Aquatic Life Benchmark (10 ng/L) for chronic toxicity to aquatic invertebrates. Three samples contained bifenthrin at concentrations above the EPA Aquatic Life Benchmark (1.3 ng/L) for chronic toxicity to invertebrates. One sample contained cyhalothrin at a concentration above the U.S. Aquatic Life Benchmark (3.5 ng/L) for acute toxicity to invertebrates.
Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
The largest earthquakes recorded in northern Alaska (Mw 6.4 and Mw 6.0) occurred ~6 hours apart on August 12, 2018 in the northeastern Brooks Range. The earthquakes were captured by Sentinel-1 InSAR satellites and Earthscope Transportable Array seismic data, giving insight into the little-known active tectonic processes of Arctic Alaska, obscured until recently by sparse data availability. In this study, InSAR modelling, teleseismic back projections, calibrated hypocentral relocations and regional moment tensor solutions resolve two previously unknown, SSW-dipping right-lateral fault segments. These are the first active faults identified as conjugate to the NE-trending sinistral Canning Displacement Zone directly to the west, which is therefore a more complex zone of diffuse faulting than previously thought. The northeastern Brooks Range has been characterized as an area of low to moderate seismic hazard, but these earthquakes illustrate the potential for larger, possibly destructive events in a region earmarked for rapid resource development.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019GL085651","usgsCitation":"Gaudreau, E., Nissen, E., Bergman, E.A., Benz, H.M., Tan, F., and Karasözen, E., 2019, The August 2018 Kaktovik earthquakes: Active tectonics in northeastern Alaska revealed With InSAR and seismology: Geophysical Research Letters, v. 46, no. 24, p. 14412-14420, https://doi.org/10.1029/2019GL085651.","productDescription":"9 p.","startPage":"14412","endPage":"14420","ipdsId":"IP-113641","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":370590,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -167.51953124999997,\n 64.92354174306496\n ],\n [\n -140.9765625,\n 64.92354174306496\n ],\n [\n -140.9765625,\n 71.35706654962706\n ],\n [\n -167.51953124999997,\n 71.35706654962706\n ],\n [\n -167.51953124999997,\n 64.92354174306496\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"46","issue":"24","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Gaudreau, E.","contributorId":221460,"corporation":false,"usgs":false,"family":"Gaudreau","given":"E.","email":"","affiliations":[{"id":16829,"text":"University of Victoria","active":true,"usgs":false}],"preferred":false,"id":778301,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nissen, E.K.","contributorId":221461,"corporation":false,"usgs":false,"family":"Nissen","given":"E.K.","email":"","affiliations":[{"id":16829,"text":"University of Victoria","active":true,"usgs":false}],"preferred":false,"id":778302,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bergman, Eric A. 0000-0002-7069-8286","orcid":"https://orcid.org/0000-0002-7069-8286","contributorId":84513,"corporation":false,"usgs":false,"family":"Bergman","given":"Eric","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":778303,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Benz, Harley M. 0000-0002-6860-2134 benz@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-2134","contributorId":794,"corporation":false,"usgs":true,"family":"Benz","given":"Harley","email":"benz@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":778304,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tan, F.","contributorId":221462,"corporation":false,"usgs":false,"family":"Tan","given":"F.","email":"","affiliations":[{"id":16829,"text":"University of Victoria","active":true,"usgs":false}],"preferred":false,"id":778305,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Karasözen, E.","contributorId":221463,"corporation":false,"usgs":false,"family":"Karasözen","given":"E.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":778306,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70206449,"text":"sir20195131 - 2019 - Flood-frequency comparison from 1995 to 2016 and trends in peak streamflow in Arkansas, water years 1930–2016","interactions":[],"lastModifiedDate":"2022-04-25T19:34:30.278239","indexId":"sir20195131","displayToPublicDate":"2019-12-05T14:04:12","publicationYear":"2019","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":"2019-5131","displayTitle":"Flood-Frequency Comparison from 1995 to 2016 and Trends in Peak Streamflow in Arkansas, Water Years 1930–2016","title":"Flood-frequency comparison from 1995 to 2016 and trends in peak streamflow in Arkansas, water years 1930–2016","docAbstract":"In 2016, the U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers and the Federal Emergency Management Agency, began a study in Arkansas to investigate possible increasing trends in annual peak streamflow data and the possible resulting increase in the annual exceedance probability flood (AEPF) predictions. Temporal trends of peak streamflow were investigated at 15 selected streamgages on unregulated streams in Arkansas having 30 or more years of peak streamflow data through the 2016 water year. For the period of record at each streamgage, the Mann-Kendall trend test indicated that 14 of the 15 streamgages had no statistically significant peak streamflow trends and 1 streamgage had a statistically significant decreasing peak streamflow trend. Visual examination of the locally estimated scatterplot smoothing technique trend lines of the peak streamflow data indicated a possible increasing peak streamflow trend at 8 of the 15 streamgages since the 1990s.
A sequential series analysis of the 1-percent AEPF at each of the 15 selected streamgages was completed by selecting an initial subset of the oldest peak streamflow data from each site to estimate the initial 1-percent AEPF. This initial peak streamflow data subset was subsequently appended with 10-year increments of additional peak streamflow data until the full period of peak streamflow data was analyzed. The maximum increase in the 1-percent AEPF was 113 percent, and the maximum decrease was 31.9 percent.
Percentage differences between the AEPFs derived from regional regression equations presented in the 1995 and 2016 Arkansas flood-frequency reports were compared. The average percentage differences for the 74 selected locations indicate that the 4-, 2-, 1-, and 0.2-percent AEPFs computed using the 2016 regional regression equations were higher by 3.52, 5.10, 8.59, and 13.31 percent, respectively (25-, 50-, 100-, and 500-year recurrence interval floods), than the same percentage AEPFs computed using the 1995 regional regression equations. The average percentage differences between the 1995 and 2016 AEPFs for the 10-percent AEPF (10-year recurrence interval flood) resulted in 2016 AEPF predictions being 0.41 percent higher. For the 50- and 20-percent AEPFs (2- and 5-year recurrence interval floods), the 2016 AEPFs were less than the 1995 AEPFs by 2.53 and 0.31 percent, respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195131","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers and Federal Emergency Management Agency","usgsCitation":"Ensminger, P.A., and Breaker, B.K., 2019, Flood-frequency comparison from 1995 to 2016 and trends in peak streamflow in Arkansas, water years 1930–2016: U.S. Geological Survey Scientific Investigations Report 2019–5131, 20 p., https://doi.org/10.3133/sir20195131.","productDescription":"vi, 20 p.","numberOfPages":"30","onlineOnly":"Y","ipdsId":"IP-087618","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":399610,"rank":3,"type":{"id":36,"text":"NGMDB Index 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U.S. Geological Survey
640 Grassmere Park, Ste 100
Nashville, TN 37211
The Yorktown-Eastover aquifer system of the Virginia Eastern Shore consists of upper, middle, and lower confined aquifers overlain by correspondingly named confining units and underlain by the Saint Marys confining unit. Miocene- to Pliocene-age marine-shelf sediments observed in 205 boreholes include medium- to coarse-grained sand and shells that compose the aquifers and fine-grained sand, silt, and clay that compose the confining units. The upper confining unit also includes fine-grained and organic-rich back-barrier and estuarine sediments of Pleistocene age. An overlying surficial aquifer is composed mostly of Pleistocene-age nearshore sand and gravel with smaller amounts of cobbles and boulders.
In addition, Pleistocene-age sediments that fill three buried paleochannels are for the first time explicitly delineated here as distinct hydrogeologic units. Two aquifers are composed of medium- to coarse-grained fluvial sand and gravel, and an intervening confining unit is composed of fine-grained estuarine sand, silt, clay, and organic material. Aquifer and confining-unit sediments are also mixed with reworked marine-shelf sediments eroded from the sides of the paleochannels.
Hydrogeologic units of the Yorktown-Eastover aquifer system generally dip eastward, are as much as several tens of feet thick, and have an undulating configuration possibly resulting from the underlying Chesapeake Bay impact crater. Aquifers and confining units are incised by the three paleochannels along an upward-widening and eastward-lengthening series of structural “windows.” Hydrogeologic units within mainstems and branching tributaries of the paleochannels dip southeastward parallel to slopes of the paleochannels, are as much as several tens of feet thick, and laterally abut the Yorktown-Eastover aquifer system along paleochannel sidewalls. The Yorktown-Eastover aquifer system is thereby hydraulically breached by the paleochannels to alternately create barriers to or conduits for groundwater flow.
Results of previously documented aquifer tests at 58 wells indicate that transmissivity is generally greatest in young, shallow, and coarse-grained nearshore and fluvial sediments of the surficial aquifer and paleochannels. Transmissivity progressively decreases with depth in older, deeper, and finer grained marine-shelf sediments of the Yorktown-Eastover aquifer system, probably because they have undergone compaction as a result of greater overburden pressure over longer periods of time.
Compiled chloride concentrations in samples from 330 wells generally increase downward, with most of the samples collected at altitudes above −300 feet and with most concentrations less than 250 milligrams per liter. The saltwater-transition zone has a broad trough-like shape aligned with the peninsula, being relatively shallow along the coastline and deeper along the central “spine.” Because movement of the saltwater is slow, the configuration largely reflects groundwater flow prior to widespread groundwater withdrawals. Fresh groundwater has leaked downward along deep parts of the saltwater-transition zone and leaked upward along shallower parts to discharge at the coast.
The saltwater-transition zone also exhibits an anomalous ridge across the center of the peninsula. Groundwater levels indicate that the saltwater ridge formed primarily by the Exmore paleochannel acting as a large lateral collector drain. Groundwater levels were lowered, and the position of saltwater-transition zone was elevated, by a flow conduit that intercepted groundwater that otherwise would have flowed toward and discharged along the coastline.
Nearly all freshwater on the Virginia Eastern Shore is supplied by groundwater withdrawals, which have lowered water levels, altered hydraulic gradients, and created a concern for saltwater intrusion. Previous characterizations of groundwater conditions that are relied on to manage groundwater development have been limited by a lack of hydrogeologic information, particularly data on buried paleochannels that are critical to safeguarding the groundwater supply. Using recently available expanded information, the U.S. Geological Survey undertook a study in cooperation with the Virginia Department of Environmental Quality during 2016–19 to develop an improved description of the groundwater system called a “hydrogeologic framework.”
The hydrogeologic framework can aid water-supply planning and development by providing information on broad trends in aquifer configurations, hydraulic properties, and proximity to saltwater to avoid chloride contamination. Digital models to evaluate effects of groundwater withdrawals can also be improved with expanded data and capabilities to evaluate paleochannel hydraulic connections and the potential for saltwater movement.
The hydrogeologic framework is limited by the nonuniform distribution of boreholes and the subjective delineation of aquifers and confining units, including those within paleochannels that are regarded as preliminary. The configuration of the saltwater-transition zone is also regarded as preliminary because of the nonuniform distribution of groundwater samples. Low well-sampling frequency precludes characterizing movement of the saltwater-transition zone. A monitoring strategy of sampling and possibly electromagnetic-induction well logging could be used to detect saltwater movement.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195093","collaboration":"Prepared in cooperation with the Virginia Department of Environmental Quality","usgsCitation":"McFarland, E.R., and Beach, T.A., 2019, Hydrogeologic framework of the Virginia Eastern Shore: U.S. Geological Survey Scientific Investigations Report 2019–5093, 26 p., 13 pl., https://doi.org/10.3133/sir20195093.","productDescription":"Report: viii, 26 p.; 13 Plates: 11.00 x 17.00 inches or smaller; Data Release","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-108409","costCenters":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"links":[{"id":369803,"rank":16,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5093/sir20195093.pdf","text":"Report","size":"3.47 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 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1730 East Parham Road
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