Medicine Lake volcano is among the very best places in the United States to see and walk on a variety of well-exposed young lava flows that range in composition from basalt to rhyolite. This field-trip guide to the volcano and to Lava Beds National Monument, which occupies part of the north flank, directs visitors to a wide range of lava flow compositions and volcanic phenomena, many of them well exposed and Holocene in age. The writing of the guide was prompted by a field trip to the California Cascades Arc organized in conjunction with the International Association of Volcanology and Chemistry of the Earth’s Interior (IAVCEI) quadrennial meeting in Portland, Oregon, in August of 2017. This report is one of a group of three guides describing the three major volcanic centers of the southern Cascades Volcanic Arc. The guides describing the Mount Shasta and Lassen Volcanic Center parts of the trip share an introduction, written as an overview to the IAVCEI field trip. However, this guide to Medicine Lake volcano has descriptions of many more stops than are included in the 2017 field trip. The 23 stops described here feature a range of compositions and volcanic phenomena. Many other stops are possible and some have been previously described, but these 23 have been selected to highlight the variety of volcanic phenomena at this rear-arc center, the range of compositions, and for the practical reason that they are readily accessible. Open ground cracks, various vent features, tuffs, lava-tube caves, evidence for glaciation, and lava flows that contain inclusions and show visible evidence of compositional zonation are described and visited along the route.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175022K1","usgsCitation":"Donnelly-Nolan, J.M., and Grove, T.L., 2017, Geologic field-trip guide to Medicine Lake Volcano, northern California, including Lava Beds National Monument: U.S. Geological Survey Scientific Investigations Report 2017–5022–K1, 53 p., https://doi.org/10.3133/sir20175022K1.","productDescription":"Report: ix, 53 p.; 3 Related Works","numberOfPages":"68","onlineOnly":"Y","ipdsId":"IP-089118","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":344930,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175022K","text":"Scientific Investigations Report 2017-5022-K","description":"SIR 2017-5022-K","linkHelpText":" - Chapter K: Overview for geologic field-trip guides to volcanoes of the Cascades Arc in northern California"},{"id":344914,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5022/k1/sir20175022k1.pdf","text":"Report","size":"41 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5022-K1"},{"id":344913,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5022/k1/coverthb.jpg"},{"id":362962,"rank":6,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5022/k1/sir20175022k1_medlake_geopdf.pdf","text":"Map of field-trip stops near Medicine Lake ","size":"11 MB GeoPDF","description":"SIR-20175022-K1","linkHelpText":" - To use the map, users need to download and install a mapping application for smartphone or tablet such as Avenza or Terra Go Toolbar."},{"id":344939,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175022K2","text":"Scientific Investigations Report 2017-5022-K2","description":"SIR 2017-5022-K2","linkHelpText":" - Chapter K2: Geologic Field-Trip Guide to the Lassen Segment of the Cascades Arc, Northern California"},{"id":362963,"rank":7,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5022/k1/sir20175022k1_lavabeds_geopdf.pdf","text":"Map of field-trip stops in Lava Beds National Monument","size":"6 MB GeoPDF","description":"SIR-20175022-K1","linkHelpText":" - To use the map, users need to download and install a mapping application for smartphone or tablet such as Avenza or Terra Go Toolbar."},{"id":344954,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175022K3","text":"Scientific Investigations Report 2017-5022-K3","description":"SIR 2017-5022-K3","linkHelpText":" - Chapter K3: Geologic Field-Trip Guide to Mount Shasta Volcano, Northern California"}],"country":"United States","state":"California","otherGeospatial":"Medicine Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.7401885986328,\n 41.43140151372244\n ],\n [\n -121.41815185546875,\n 41.43140151372244\n ],\n [\n -121.41815185546875,\n 41.68163038712496\n ],\n [\n -121.7401885986328,\n 41.68163038712496\n ],\n [\n -121.7401885986328,\n 41.43140151372244\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Volcano Science Center - Menlo Park
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We examined the relationship between local- (wetland) and landscape-level factors and breeding bird abundances on 1,190 depressional wetlands in the Prairie Pothole Region of North and South Dakota during the breeding seasons in 1995–97. The surveyed wetlands were selected from five wetland classes (alkali, permanent, semipermanent, seasonal, or temporary), two wetland types (natural or restored), and two landowner groups (private or Federal). We recorded 133 species of birds in the surveyed wetlands during the 3 years. We analyzed the nine most common (or focal) species (that is, species that were present in 25 percent or more of the 1,190 wetlands): the Red-winged Blackbird (Agelaius phoeniceus), Blue-winged Teal (Anas discors), Mallard (Anas platyrhynchos), American Coot (Fulica americana), Gadwall (Anas strepera), Common Yellowthroat (Geothlypis trichas), Yellow-headed Blackbird (Xanthocephalus xanthocephalus), Northern Shoveler (Anas clypeata), and Savannah Sparrow (Passerculus sandwichensis). Our results emphasize the ecological value of all wetland classes, natural and restored wetlands, and publicly and privately owned wetlands in this region, including wetlands that are generally smaller and shallower (that is, temporary and seasonal wetlands) and thus most vulnerable to drainage. Blue-winged Teal, Northern Shoveler, Gadwall, Common Yellowthroat, and Red-winged Blackbird had higher abundances on Federal than on private wetlands. Abundances differed among wetland classes for seven of the nine focal species: Blue-winged Teal, Northern Shoveler, Mallard, American Coot, Common Yellowthroat, Yellow-headed Blackbird, Red-winged Blackbird. American Coot had higher abundances on restored wetlands than on natural wetlands overall, and Gadwall and Common Yellowthroat had higher abundances on private restored wetlands than on private natural wetlands. The Common Yellowthroat was the only species that had higher abundances on restored private wetlands than on restored Federal wetlands. After adjusting for wetland size and the date and location of the surveys, our results demonstrated that incorporating wetland- and landscape-level factors in models can improve our ability to predict abundances of wetland birds in this region. The top model for eight of the nine focal species included wetland- and landscape-level factors, whereas the best model for Blue-winged Teal included only wetland-level attributes. Although local factors (for example, percent open water or emergent vegetation) in individual wetlands are important factors for some wetland breeding birds, it is important that natural resource managers consider landscape-level factors beyond the local factors in their conservation plans for wetland birds.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171096","usgsCitation":"Igl, L.D., Shaffer, J.A., Johnson, D.H., and Buhl, D.A., 2017, The influence of local- and landscape-level factors on wetland breeding birds in the Prairie Pothole Region of North and South Dakota: U.S. Geological Survey Open-File Report 2017–1096, 65 p., https://doi.org/10.3133/ofr20171096.","productDescription":"Report: vii, 65 p.; Data Release","numberOfPages":"72","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-086062","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":344903,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7FX77XM","text":"USGS Data Release","linkHelpText":"The influence of local- and landscape-level factors on wetland breeding birds in the Prairie Pothole Region of North and South Dakota 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U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
Solar photovoltaic (PV) and wind turbine technologies are projected to make up an increasing proportion of electricity generation capacity in the United States in the coming decades. By 2050, they will account for 36 percent (or 566 gigawatts) of capacity compared with about 11 percent (or 118 gigawatts) in 2016 (fig. 1; EIA, 2017).
There are several different types of commercial solar PV and wind turbine technologies, and each type makes use of different minor metals. “Minor metal” is the term used for metals for which world production is small compared with the more widely produced base metals, and they are often produced as byproducts of the mining or processing of base metals. Minor metals used in renewable energy technologies often have complex supply chains, are often produced primarily outside of the United States, and are also used in many other applications. A larger amount of minor metals will be needed in the future to support the projected increases in solar PV and wind energy production capacity (Nassar and others, 2016).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173061","usgsCitation":"Singerling, S.A., and Nassar, N.T., 2017, Minor metals and renewable energy—Diversifying America’s energy sources: U.S. Geological Survey Fact Sheet 2017–3061, 2 p., https://doi.org/10.3133/fs20173061.","productDescription":"2 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-086064","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":344580,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3061/coverthb2.jpg"},{"id":344585,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3061/fs20173061.pdf","text":"Report","size":"453 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017-3061"}],"country":"United States","contact":"Director, National Minerals Information Center
U.S. Geological Survey
12201 Sunrise Valley Drive
988 National Center
Reston, VA 20192
Email: nmicrecordsmgt@usgs.gov
An accurate inventory of irrigated crop acreage is not available at the level of resolution needed to better estimate agricultural water use or to project future water demands in many Florida counties. A detailed digital map and summary of irrigated acreage was developed for Polk County, Florida, during the 2016 growing season. This cooperative project between the U.S. Geological Survey and the Office of Agricultural Water Policy of the Florida Department of Agriculture and Consumer Services is part of an effort to improve estimates of water use and projections of future demands across all counties in the State. The irrigated areas were delineated by using land-use data provided by the Florida Department of Agriculture and Consumer Services, along with information obtained from the South and Southwest Florida Water Management Districts consumptive water-use permits. Delineations were field verified between April and December 2016. Attribute data such as crop type, primary water source, and type of irrigation system were assigned to the irrigated areas.
The results of this inventory and field verification indicate that during the 2016 growing seasons (spring, summer, fall, and winter), an estimated 88,652 acres were irrigated within Polk County. Of the total field-verified crops, 83,995 acres were in citrus; 2,893 acres were in other non-citrus fruit crops (blueberries, grapes, peaches, and strawberries); 621 acres were in row crops (primarily beans and watermelons); 1,117 acres were in nursery (container and tree farms) and sod production; and 26 acres were in field crops including hay and pasture. Of the total inventoried irrigated acreage within Polk County, 98 percent (86,566 acres) was in the Southwest Florida Water Management District, and the remaining 2 percent (2,086 acres) was in the South Florida Water Management District.
About 85,788 acres (96.8 percent of the acreage inventoried) were irrigated by a microirrigation system, including drip, bubblers, and spray emitters. The remaining 3.2 percent of the irrigated acreage was irrigated by a sprinkler system (2,360 acres) or subsurface flood systems (504 acres). Groundwater was the primary source of water used on irrigated acreage (88 percent, or 78,050 acres); the remaining 10,602 acres (12 percent) used groundwater combined with surface water as the irrigation source.
The irrigated acreage estimated by the U.S. Geological Survey (USGS) for this 2016 inventory (88,652 acres) is about 11 percent higher than the 79,869 acres estimated by the U.S. Department of Agriculture (USDA) for 2012. Citrus and pasture in Polk County show the biggest difference in irrigated acreage between the USGS and USDA totals. Irrigated citrus acreage inventoried in 2016 by the USGS totaled 83,996 acres, whereas the USDA reported 78,305 acres of citrus in 2012. The USGS identified 6 acres of irrigated pasture and 20 acres of hay, whereas the USDA reported 6,631 acres of irrigated pasture and 1,349 acres of hay for 2012. In general, differences between the 2016 USGS field-verified acreage totals and acreage published by the USDA for 2012 could be due to (1) irrigated acreage for some specific crops increased or decreased substantially during the 4-year interval between 2012 and 2016 because of production or economic changes, (2) the assumption that if an irrigation system was present, it was used in 2016, when in fact some landowners may not have used their irrigation systems during this growing period even if they had a crop in the field, or (3) the amount of irrigated acreage published by the USDA for selected crops may be underestimated as a result of how information is obtained and formulated by the agency during census compilations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171082","collaboration":"Prepared in cooperation with the Florida Department of Agriculture and Consumer Services Office of Agricultural Water Policy","usgsCitation":"Marella, R.L., Berry, D.R., and Dixon, J.F., 2017, Agricultural irrigated land-use inventory for Polk County, Florida, 2016: U.S. Geological Survey Open-File Report 2017–1082, 14 p., https://doi.org/10.3133/ofr20171082.","productDescription":"14 p.","numberOfPages":"15","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-080915","costCenters":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"links":[{"id":344885,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1082/coverthb.jpg"},{"id":344888,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F76W98BN","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"GIS data and tables associated with irrigated agricultural land use survey in Polk County, Florida, 2016"},{"id":344886,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1082/ofr20171082.pdf","text":"Report","size":"823 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1082"},{"id":344887,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2017/1082/ofr20171082_Appendix01.pdf","text":"Appendix 1","size":"1.17 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1082 Appendix 1"}],"country":"United 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Caribbean-Florida Science Center
U.S. Geological Survey
12703 Research Parkway
Orlando, Florida 32826
Human perceptions of the landscape can influence land-use and land-management decisions. Recognizing the diversity of landscape perceptions across space and time is essential to understanding land change processes and emergent landscape patterns. We summarize the role of landscape perceptions in the land change process, demonstrate advances in quantifying and mapping landscape perceptions, and describe how these spatially explicit techniques have and may benefit land change research.
Mapping landscape perceptions is becoming increasingly common, particularly in research focused on quantifying ecosystem services provision. Spatial representations of landscape perceptions, often measured in terms of landscape values and functions, provide an avenue for matching social and environmental data in land change studies. Integrating these data can provide new insights into land change processes, contribute to landscape planning strategies, and guide the design and implementation of land change models.
Challenges remain in creating spatial representations of human perceptions. Maps must be accompanied by descriptions of whose perceptions are being represented and the validity and uncertainty of those representations across space. With these considerations, rapid advancements in mapping landscape perceptions hold great promise for improving representation of human dimensions in landscape ecology and land change research.
Historical data for six selected U.S. Geological Survey streamgages along Soldier Creek in northeast Kansas were used in an assessment of streamflow characteristics and trends. This information is required by the Prairie Band Potawatomi Nation for the effective management of tribal water resources, including drought contingency planning. Streamflow data for the period of record at each streamgage were used to assess annual mean streamflow, annual mean base flow, mean monthly flow, annual peak flow, and annual minimum flow.
Annual mean streamflows along Soldier Creek were characterized by substantial year-to-year variability with no pronounced long-term trends. On average, annual mean base flow accounted for about 20 percent of annual mean streamflow. Mean monthly flows followed a general seasonal pattern that included peak values in spring and low values in winter. Annual peak flows, which were characterized by considerable year-to-year variability, were most likely to occur in May and June and least likely to occur during November through February. With the exception of a weak yet statistically significant increasing trend at the Soldier Creek near Topeka, Kansas, streamgage, there were no pronounced long-term trends in annual peak flows. Annual 1-day, 30-day, and 90-day mean minimum flows were characterized by considerable year-to-year variability with no pronounced long-term trend. During an extreme drought, as was the case in the mid-1950s, there may be zero flow in Soldier Creek continuously for a period of one to several months.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175061","collaboration":"Prepared in cooperation with the Prairie Band Potawatomi Nation","usgsCitation":"Juracek, K.E., 2017, Streamflow characteristics and trends along Soldier Creek, northeast Kansas: U.S. Geological Survey Scientific Investigations Report 2017–5061, 30 p., https://doi.org/10.3133/sir20175061.","productDescription":"v, 30 p.","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-084908","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":344845,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5061/coverthb.jpg"},{"id":344846,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5061/sir20175061.pdf","text":"Report","size":"5.57 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5061"}],"country":"United States","state":"Kansas","otherGeospatial":"Soldier Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.2896728515625,\n 38.94018471320357\n ],\n [\n -95.2734375,\n 38.94018471320357\n ],\n [\n -95.2734375,\n 39.8928799002948\n ],\n [\n -96.2896728515625,\n 39.8928799002948\n ],\n [\n -96.2896728515625,\n 38.94018471320357\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
4821 Quail Crest Place
Lawrence, KS 66049
The Cascade Range in central Oregon has been shaped by tectonics, volcanism, and hydrology, as well as geomorphic forces that include glaciations. As a result of the rich interplay between these forces, mafic volcanism here can have surprising manifestations, which include relatively large tephra footprints and extensive lava flows, as well as water shortages, transportation and agricultural disruption, and forest fires. Although the focus of this multidisciplinary field trip will be on mafic volcanism, we will also look at the hydrology, geomorphology, and ecology of the area, and we will examine how these elements both influence and are influenced by mafic volcanism. We will see mafic volcanic rocks at the Sand Mountain volcanic field and in the Santiam Pass area, at McKenzie Pass, and in the southern Bend region. In addition, this field trip will occur during a total solar eclipse, the first one visible in the United States in more than 25 years (and the first seen in the conterminous United States in more than 37 years).
The Cascade Range is the result of subduction of the Juan de Fuca plate underneath the North American plate. This north-south-trending volcanic mountain range is immediately downwind of the Pacific Ocean, a huge source of moisture. As moisture is blown eastward from the Pacific on prevailing winds, it encounters the Cascade Range in Oregon, and the resulting orographic lift and corresponding rain shadow is one of the strongest precipitation gradients in the conterminous United States. We will see how the products of the volcanoes in the central Oregon Cascades have had a profound influence on groundwater flow and, thus, on the distribution of Pacific moisture. We will also see the influence that mafic volcanism has had on landscape evolution, vegetation development, and general hydrology.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Field-trip guides to selected volcanoes and volcanic landscapes of the western United States (Scientific Investigations Report 2017-5022)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175022H","usgsCitation":"Deligne, N.I., Mckay, D., Conrey, R.M., Grant, G.E., Johnson, E.R., O’Connor, J., and Sweeney, K., 2017, Field-trip guide to mafic volcanism of the Cascade Range in central Oregon—A volcanic, tectonic, hydrologic, and geomorphic journey: U.S. Geological Survey Scientific Investigations Report 2017–5022–H, 94 p., https://doi.org/10.3133/sir20175022H.","productDescription":"xii, 94 p.","numberOfPages":"110","onlineOnly":"Y","ipdsId":"IP-076209","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":344876,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5022/h/sir20175022h.pdf","text":"Report","size":"34 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5022-H"},{"id":344875,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5022/h/coverthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Cascade Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.1787109375,\n 43.61619382369185\n ],\n [\n -121.0089111328125,\n 43.61619382369185\n ],\n [\n -121.0089111328125,\n 45.57944511437787\n ],\n [\n -123.1787109375,\n 45.57944511437787\n ],\n [\n -123.1787109375,\n 43.61619382369185\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Volcano Science Center - Menlo Park
U.S. Geological Survey
345 Middlefield Road, MS 910
Menlo Park, CA 94025
Most of the land-surface subsidence in the Houston-Galveston region, Texas, has occurred as a direct result of groundwater withdrawals for municipal supply, commercial and industrial use, and irrigation that depressured and dewatered the Chicot and Evangeline aquifers, thereby causing compaction of the aquifer sediments, mostly in the fine-grained silt and clay layers. This report, prepared by the U.S. Geological Survey in cooperation with the Harris-Galveston Subsidence District, City of Houston, Fort Bend Subsidence District, Lone Star Groundwater Conservation District, and Brazoria County Groundwater Conservation District, is one in an annual series of reports depicting water-level altitudes and water-level changes in the Chicot, Evangeline, and Jasper aquifers and measured cumulative compaction of subsurface sediments in the Chicot and Evangeline aquifers in the Houston-Galveston region. This report contains regional-scale maps depicting approximate 2017 water-level altitudes (represented by measurements made during December 2016 through March 2017) and long-term water-level changes for the Chicot, Evangeline, and Jasper aquifers; a map depicting locations of borehole-extensometer (hereinafter referred to as “extensometer”) sites; and graphs depicting measured long-term cumulative compaction of subsurface sediments at the extensometers during 1973–2016.
In 2017, water-level-altitude contours for the Chicot aquifer ranged from 200 feet (ft) below the North American Vertical Datum of 1988 (hereinafter referred to as “datum”) in two localized areas in southwestern and northwestern Harris County to 200 ft above datum in west-central Montgomery County. The largest water-level-altitude decline (120 ft) depicted by the 1977–2017 water-level-change contours for the Chicot aquifer was in northwestern Harris County. A broad area where water-level altitudes declined in the Chicot aquifer extends from northwestern, north-central, and southwestern Harris County across parts of north-central, eastern, and south-central Fort Bend County into southeastern Waller County. Adjacent to the areas where water levels declined was a broad area where water levels rose in central, eastern, and southeastern Harris County, most of Galveston County, eastern and northernmost Brazoria County, and northeastern Fort Bend County. The largest rise (200 ft) in water-level altitudes in the Chicot aquifer from 1977 to 2017 was in southeastern Harris County.
The water-level-altitude contours for the Evangeline aquifer in 2017 indicated two areas where the water-level altitudes were 250 ft below datum—one area extending from south-central Montgomery County into north-central Harris County and another area in western Harris County. Water-level altitudes in the Evangeline aquifer ranged from 50 to 200 ft below datum throughout most of Harris County in 2017. In Montgomery County, water-level altitudes in the Evangeline aquifer in 2017 ranged from the aforementioned area where they were 250 ft below datum to an area where they were 200 ft above datum in the northwestern part of the county. The 1977–2017 water-level-change contours for the Evangeline aquifer depict a broad area where water-level altitudes declined in north-central Harris and south-central Montgomery Counties, extending through north-central, northwestern, and southwestern Harris County into western Liberty, southeastern and northeastern Waller, and northeastern and east-central Fort Bend Counties. The largest water-level-altitude decline (280 ft) was in north-central Harris and south-central Montgomery Counties. Water-level altitudes rose in a broad area from central, east-central, and southern Harris County extending into the northernmost part of Brazoria County, the northernmost part of Galveston County, and the southwestern area of Liberty County. The largest rise in water-level altitudes in the Evangeline aquifer from 1977 to 2017 (240 ft) was in southeastern Harris County.
Water-level-altitude contours for the Jasper aquifer in 2017 ranged from 200 ft below datum in three isolated areas of south-central Montgomery County (the westernmost of these areas extended slightly into north-central Harris County) to 250 ft above datum in extreme northwestern Montgomery County, northeastern Grimes County, and southwestern Walker County. The 2000–17 water-level-change contours for the Jasper aquifer depict water-level declines in a broad area throughout most of Montgomery County and in parts of Waller, Grimes, and Harris Counties, with the largest decline (220 ft) in an isolated area in south-central Montgomery County.
Compaction of subsurface sediments (mostly in the fine-grained silt and clay layers) in the Chicot and Evangeline aquifers was recorded continuously by using 13 extensometers at 11 sites that were either activated or installed between 1973 and 1980. During the period of record beginning in 1973 (or later depending on activation or installation date) and ending in late November or December 2016, measured cumulative compaction at the 13 extensometers ranged from 0.096 ft at the Texas City-Moses Lake extensometer to 3.700 ft at the Addicks extensometer. From January through late November or December 2016, the Addicks, Lake Houston, Southwest, and Northeast extensometers recorded net decreases in land-surface elevation, but the Baytown C–1 (shallow), Baytown C–2 (deep), Clear Lake (shallow), Clear Lake (deep), East End, Johnson Space Center, Pasadena, Seabrook, and Texas City-Moses Lake extensometers recorded net increases in land-surface elevation.
The rate of compaction varies from site to site because of differences in rates of groundwater withdrawal in the areas adjacent to each extensometer site; differences among sites in the ratios of sand, silt, and clay and their corresponding compressibilities; and previously established preconsolidation heads. It is not appropriate, therefore, to extrapolate or infer a rate of compaction for an adjacent area on the basis of the rate of compaction recorded by proximal extensometers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175080","collaboration":"Prepared in cooperation with the Harris-Galveston Subsidence District, City of Houston, Fort Bend Subsidence District, Lone Star Groundwater Conservation District, and Brazoria County Groundwater Conservation District","usgsCitation":"Kasmarek, M.C., and Ramage, J.K., 2017, Water-level altitudes 2017 and water-level changes in the Chicot, Evangeline, and Jasper aquifers and compaction 1973–2016 in the Chicot and Evangeline aquifers, Houston-Galveston region, Texas: U.S. Geological Survey Scientific Investigations Report 2017–5080, 32 p., https://doi.org/10.3133/sir20175080. ","productDescription":"Report: vii, 32 p.; Data Releases","numberOfPages":"44","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-083843","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":344822,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77S7M18","text":"USGS - Data Release","description":"USGS Data Release","linkHelpText":"Water-level measurement data, water-level altitude and long-term water-level altitude change contours (2017) in the Chicot, Evangeline, and Jasper aquifers, Houston-Galveston region, Texas"},{"id":344820,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5080/coverthb.jpg"},{"id":344823,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7PC30KC","text":"USGS - Data Release","description":"USGS Data Release","linkHelpText":"Cumulative compaction of subsurface sediments (2016) in 13 extensometers completed in the Chicot and Evangeline aquifers in the Houston-Galveston region, Texas"},{"id":344821,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5080/sir20175080.pdf","text":"Report","size":"16.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5080"}],"country":"United States","state":"Texas","city":"Galveston, Houston","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.339111328125,\n 28.372068829631633\n ],\n [\n -96.21826171874999,\n 28.44937385955666\n ],\n [\n -95.965576171875,\n 28.58452171937042\n ],\n [\n -95.77880859375,\n 28.65203063036226\n ],\n [\n -95.592041015625,\n 28.719496107557465\n ],\n [\n -95.4052734375,\n 28.825425374477224\n ],\n [\n -95.185546875,\n 28.950475674848008\n ],\n [\n -95.00976562499999,\n 29.094577077511826\n ],\n [\n -94.833984375,\n 29.23847708592805\n ],\n [\n -94.68017578125,\n 29.401319510041485\n ],\n [\n -94.482421875,\n 29.477861195816843\n ],\n [\n -94.19677734375,\n 29.611670115197377\n ],\n [\n -93.966064453125,\n 29.6594160549124\n ],\n [\n -93.80126953124999,\n 29.707139348134145\n ],\n [\n -93.900146484375,\n 29.850173125689896\n ],\n [\n -93.89465332031249,\n 29.888280933159265\n ],\n [\n -93.88916015625,\n 29.92637417863576\n ],\n [\n -93.768310546875,\n 29.964452850852005\n ],\n [\n -93.75732421875,\n 30.021543509740027\n ],\n [\n -93.74633789062499,\n 30.088107753367257\n ],\n [\n -93.724365234375,\n 30.287531589298727\n ],\n [\n -93.74633789062499,\n 30.391830328088137\n ],\n [\n -93.75732421875,\n 30.56226095049944\n ],\n [\n -93.66943359374999,\n 30.675715404167743\n ],\n [\n -93.592529296875,\n 30.826780904779774\n ],\n [\n -93.53759765625,\n 31.015278981711266\n ],\n [\n -93.53759765625,\n 31.147006308556566\n ],\n [\n -93.62548828125,\n 31.27855085894653\n ],\n [\n -93.7353515625,\n 31.512995857454676\n ],\n [\n -93.779296875,\n 31.606609719226917\n ],\n [\n -93.812255859375,\n 31.774877618507386\n ],\n [\n -93.900146484375,\n 31.87755764334002\n ],\n [\n -93.98803710937499,\n 31.952162238024975\n ],\n [\n -94.053955078125,\n 31.99875937194732\n ],\n [\n -94.053955078125,\n 32.32427558887655\n ],\n [\n -95.416259765625,\n 32.16631295696736\n ],\n [\n -96.580810546875,\n 32.03602003973755\n ],\n [\n -96.96533203125,\n 31.970803930433096\n ],\n [\n -96.339111328125,\n 28.372068829631633\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, Texas 78754–4501
These field-trip guides were written for the occasion of the International Association of Volcanology and Chemistry of the Earth’s Interior (IAVCEI) quadrennial scientific assembly in Portland, Oregon, in August 2017. The guide to Mount Mazama and Crater Lake caldera is an updated and expanded version of the guide (Bacon, 1989) for part of an earlier IAVCEI trip to the southern Cascade Range. The guide to Newberry Volcano describes the stops included in the 2017 field trip. Crater Lake and Newberry are the two best-preserved and most recent calderas in the Cascades Volcanic Arc. Although located in different settings in the arc, with Crater Lake on the arc axis and Newberry in the rear-arc, both volcanoes are located at the intersection of the arc and the northwest corner region of the extensional Basin and Range Province.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175022J","usgsCitation":"Bacon, C.R., Donnelly-Nolan, J.M., Jensen, R.A., and Wright, H.M., 2017, Overview for Geologic Field-Trip Guides to Mount Mazama, Crater Lake Caldera, and Newberry Volcano, Oregon: U.S. Geological Survey Scientific Investigations Report 2017–5022–J, 3 p., https://doi.org/10.3133/sir20175022J.","productDescription":"vii, 3 p.","numberOfPages":"5","onlineOnly":"Y","ipdsId":"IP-089109","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":344907,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5022/j/sir2017-5022j.pdf","text":"Report","size":"5.25 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5022-J"},{"id":344906,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5022/j/coverthb.jpg"},{"id":344956,"rank":3,"type":{"id":6,"text":"Chapter"},"url":"https://doi.org/10.3133/sir20175022J1","text":"Scientific Investigations Report 2017-5022-J1","description":"SIR 2017-5022-J1","linkHelpText":" - Chapter J1: Geologic field trip guide to Mount Mazama and Crater Lake Caldera, Oregon"},{"id":344957,"rank":4,"type":{"id":6,"text":"Chapter"},"url":"https://doi.org/10.3133/sir20175022J2","text":"Scientific Investigations Report 2017-5022-J2","description":"SIR 2017-5022-J2","linkHelpText":" - Chapter J2: Field-trip guide to the geologic highlights of Newberry Volcano, Oregon"}],"country":"United States","state":"Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.21716308593749,\n 42.23665188032057\n ],\n [\n -120.08056640625,\n 42.25291778330197\n ],\n [\n -120.047607421875,\n 44.82860426955568\n ],\n [\n -123.21716308593749,\n 44.83249999349062\n ],\n [\n -123.21716308593749,\n 42.23665188032057\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Volcano Science Center - Menlo Park
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345 Middlefield Road, MS 910
Menlo Park, CA 94025
We report the development and validation of two quantitative PCR (qPCR) assays to detect Nanophyetus salmincola DNA in water samples and in fish and snail tissues. Analytical and diagnostic validation demonstrated good sensitivity, specificity, and repeatability of both qPCR assays. The N. salmincola DNA copy number in kidney tissue was significantly correlated with metacercaria counts based on microscopy. Extraction methods were optimized for the sensitive qPCR detection of N. salmincola DNA in settled water samples. Artificially spiked samples suggested that the 1-cercaria/L threshold corresponded to an estimated log10 copies per liter ≥ 6.0. Significant correlation of DNA copy number per liter and microscopic counts indicated that the estimated qPCR copy number was a good predictor of the number of waterborne cercariae. However, the detection of real-world samples below the estimated 1-cercaria/L threshold suggests that the assays may also detect other N. salmincola life stages, nonintact cercariae, or free DNA that settles with the debris. In summary, the qPCR assays reported here are suitable for identifying and quantifying all life stages of N. salmincola that occur in fish tissues, snail tissues, and water.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/08997659.2017.1365780","usgsCitation":"Purcell, M., Powers, R., Besijn, B., and Hershberger, P., 2017, Detection of Nanophyetus salmincola in water, snails, and fish tissues by quantitative polymerase chain reaction: Journal of Aquatic Animal Health, v. 29, no. 4, p. 189-198, https://doi.org/10.1080/08997659.2017.1365780.","productDescription":"10 p.","startPage":"189","endPage":"198","ipdsId":"IP-086638","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":438246,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7FN14QN","text":"USGS data release","linkHelpText":"Purcell_Nanophyetus_Data_Release_2017"},{"id":346361,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-14","publicationStatus":"PW","scienceBaseUri":"59d4a1a7e4b05fe04cc4e0f3","contributors":{"authors":[{"text":"Purcell, Maureen K. mpurcell@usgs.gov","contributorId":3061,"corporation":false,"usgs":true,"family":"Purcell","given":"Maureen K.","email":"mpurcell@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":711860,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Powers, Rachel L. 0000-0001-6901-4361","orcid":"https://orcid.org/0000-0001-6901-4361","contributorId":190182,"corporation":false,"usgs":true,"family":"Powers","given":"Rachel L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":711861,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Besijn, Bonnie 0000-0001-9939-9768 bbesijn@usgs.gov","orcid":"https://orcid.org/0000-0001-9939-9768","contributorId":196890,"corporation":false,"usgs":true,"family":"Besijn","given":"Bonnie","email":"bbesijn@usgs.gov","affiliations":[],"preferred":true,"id":711862,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hershberger, Paul K. phershberger@usgs.gov","contributorId":1945,"corporation":false,"usgs":true,"family":"Hershberger","given":"Paul K.","email":"phershberger@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":711863,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70193719,"text":"70193719 - 2017 - Surface morphology of caldera-forming eruption deposits revealed by lidar mapping of Crater Lake National Park, Oregon- Implications for emplacement and surface modification","interactions":[],"lastModifiedDate":"2017-11-06T14:50:52","indexId":"70193719","displayToPublicDate":"2017-08-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Surface morphology of caldera-forming eruption deposits revealed by lidar mapping of Crater Lake National Park, Oregon- Implications for emplacement and surface modification","docAbstract":"Large explosive eruptions of silicic magma can produce widespread pumice fall, extensive ignimbrite sheets, and collapse calderas. The surfaces of voluminous ignimbrites are rarely preserved or documented because most terrestrial examples are heavily vegetated, or severely modified by post-depositional processes. Much research addresses the internal sedimentary characteristics, flow processes, and depositional mechanisms of ignimbrites, however, surface features of ignimbrites are less well documented and understood, except for comparatively small-volume deposits of historical eruptions. The ~7,700 calendar year B.P. climactic eruption of Mount Mazama, USA vented ~50 km3 of magma, deposited first as rhyodacite pumice fall and then as a zoned rhyodacite-to-andesite ignimbrite as Crater Lake caldera collapsed. Lidar collected during summer 2010 reveals the remarkably well-preserved surface of the Mazama ignimbrite and related deposits surrounding Crater Lake caldera in unprecedented detail despite forest cover. The ±1 m lateral and ±4 cm vertical resolution lidar allows surface morphologies to be classified. Surface morphologies are created by internal depositional processes and can point to the processes at work when pyroclastic flows come to rest. We describe nine surface features including furrow-ridge sets and wedge-shaped mounds in pumice fall eroded by high-energy pyroclastic surges, flow- parallel ridges that record the passage of multiple pyroclastic flows, perched benches of marginal deposits stranded by more-mobile pyroclastic-flow cores, hummocks of dense clasts interpreted as lag deposit, transverse ridges that mark the compression and imbrication of flows as they came to rest, scarps indicating ignimbrite remobilization, fields of pit craters caused by phreatic explosions, fractures and cracks caused by extensional processes resulting from ignimbrite volume loss, and stream channels eroded in the newly formed surface. The nine morphologies presented here illustrate a dynamic depositional environment that varied spatially and with time during the eruption, and show that multiple processes modified the ignimbrite after deposition, both during and after the eruption.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2017.02.012","usgsCitation":"Robinson, J., Bacon, C.R., Major, J.J., Wright, H.M., and Vallance, J.W., 2017, Surface morphology of caldera-forming eruption deposits revealed by lidar mapping of Crater Lake National Park, Oregon- Implications for emplacement and surface modification: Journal of Volcanology and Geothermal Research, v. 342, p. 61-78, https://doi.org/10.1016/j.jvolgeores.2017.02.012.","productDescription":"18 p.","startPage":"61","endPage":"78","numberOfPages":"18","ipdsId":"IP-065541","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":461430,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2017.02.012","text":"Publisher Index Page"},{"id":348294,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Crater Lake, Crater Lake National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.19131469726561,\n 42.8\n ],\n [\n -122.03887939453125,\n 42.8\n ],\n [\n -122.03887939453125,\n 43.1\n ],\n [\n -122.19131469726561,\n 43.1\n ],\n [\n -122.19131469726561,\n 42.8\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"342","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a07e896e4b09af898c8cb89","contributors":{"authors":[{"text":"Robinson, Joel E. 0000-0002-5193-3666 jrobins@usgs.gov","orcid":"https://orcid.org/0000-0002-5193-3666","contributorId":2757,"corporation":false,"usgs":true,"family":"Robinson","given":"Joel E.","email":"jrobins@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":720043,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bacon, Charles R. 0000-0002-2165-5618 cbacon@usgs.gov","orcid":"https://orcid.org/0000-0002-2165-5618","contributorId":2909,"corporation":false,"usgs":true,"family":"Bacon","given":"Charles","email":"cbacon@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":720044,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Major, Jon J. 0000-0003-2449-4466 jjmajor@usgs.gov","orcid":"https://orcid.org/0000-0003-2449-4466","contributorId":439,"corporation":false,"usgs":true,"family":"Major","given":"Jon","email":"jjmajor@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":720046,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wright, Heather M. 0000-0001-9013-507X hwright@usgs.gov","orcid":"https://orcid.org/0000-0001-9013-507X","contributorId":3949,"corporation":false,"usgs":true,"family":"Wright","given":"Heather","email":"hwright@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":720045,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vallance, James W. 0000-0002-3083-5469 jvallance@usgs.gov","orcid":"https://orcid.org/0000-0002-3083-5469","contributorId":547,"corporation":false,"usgs":true,"family":"Vallance","given":"James","email":"jvallance@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":720047,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70190170,"text":"70190170 - 2017 - Evidence of compounded disturbance effects on vegetation recovery following high-severity wildfire and spruce beetle outbreak","interactions":[],"lastModifiedDate":"2017-08-15T17:45:02","indexId":"70190170","displayToPublicDate":"2017-08-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Evidence of compounded disturbance effects on vegetation recovery following high-severity wildfire and spruce beetle outbreak","docAbstract":"Spruce beetle (Dendroctonus rufipennis) outbreaks are rapidly spreading throughout subalpine forests of the Rocky Mountains, raising concerns that altered fuel structures may increase the ecological severity of wildfires. Although many recent studies have found no conclusive link between beetle outbreaks and increased fire size or canopy mortality, few studies have addressed whether these combined disturbances produce compounded effects on short-term vegetation recovery. We tested for an effect of spruce beetle outbreak severity on vegetation recovery in the West Fork Complex fire in southwestern Colorado, USA, where much of the burn area had been affected by severe spruce beetle outbreaks in the decade prior to the fire. Vegetation recovery was assessed using the Landsat-derived Normalized Difference Vegetation Index (NDVI) two years after the fire, which occurred in 2013. Beetle outbreak severity, defined as the basal area of beetle-killed trees within Landsat pixels, was estimated using vegetation index differences (dVIs) derived from pre-outbreak and post-outbreak Landsat images. Of the seven dVIs tested, the change in Normalized Difference Moisture Index (dNDMI) was most strongly correlated with field measurements of beetle-killed basal area (R2 = 0.66). dNDMI was included as an explanatory variable in sequential autoregressive (SAR) models of NDVI2015. Models also included pre-disturbance NDVI, topography, and weather conditions at the time of burning as covariates. SAR results showed a significant correlation between NDVI2015 and dNDMI, with more severe spruce beetle outbreaks corresponding to reduced post-fire vegetation cover. The correlation was stronger for models which were limited to locations in the red stage of outbreak (outbreak ≤ 5 years old at the time of fire) than for models of gray-stage locations (outbreak > 5 years old at the time of fire). These results indicate that vegetation recovery processes may be negatively impacted by severe spruce beetle outbreaks occurring within a decade of stand-replacing wildfire.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0181778","usgsCitation":"Carlson, A., Sibold, J.S., Assal, T.J., and Negron, J.F., 2017, Evidence of compounded disturbance effects on vegetation recovery following high-severity wildfire and spruce beetle outbreak: PLoS ONE, v. 12, no. 8, Article e0181778: 24 p., https://doi.org/10.1371/journal.pone.0181778.","productDescription":"Article e0181778: 24 p.","ipdsId":"IP-083553","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":469607,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0181778","text":"Publisher Index Page"},{"id":344878,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"West Fork Complex","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.03955078125,\n 37.09023980307208\n ],\n [\n -106.3037109375,\n 37.09023980307208\n ],\n [\n -106.3037109375,\n 38.238180119798635\n ],\n [\n -108.03955078125,\n 38.238180119798635\n ],\n [\n -108.03955078125,\n 37.09023980307208\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-04","publicationStatus":"PW","scienceBaseUri":"59940845e4b0fe2b9fe8af8d","contributors":{"authors":[{"text":"Carlson, Amanda R. 0000-0002-0450-2636","orcid":"https://orcid.org/0000-0002-0450-2636","contributorId":195661,"corporation":false,"usgs":false,"family":"Carlson","given":"Amanda R.","affiliations":[],"preferred":false,"id":707799,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sibold, Jason S.","contributorId":195662,"corporation":false,"usgs":false,"family":"Sibold","given":"Jason","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":707800,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Assal, Timothy J. 0000-0001-6342-2954 assalt@usgs.gov","orcid":"https://orcid.org/0000-0001-6342-2954","contributorId":2203,"corporation":false,"usgs":true,"family":"Assal","given":"Timothy","email":"assalt@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":707798,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Negron, Jose F.","contributorId":10734,"corporation":false,"usgs":true,"family":"Negron","given":"Jose","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":707801,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70190165,"text":"70190165 - 2017 - Centennial-scale reductions in nitrogen availability in temperate forests of the United States","interactions":[],"lastModifiedDate":"2017-11-22T17:00:21","indexId":"70190165","displayToPublicDate":"2017-08-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Centennial-scale reductions in nitrogen availability in temperate forests of the United States","docAbstract":"Forests cover 30% of the terrestrial Earth surface and are a major component of the global carbon (C) cycle. Humans have doubled the amount of global reactive nitrogen (N), increasing deposition of N onto forests worldwide. However, other global changes—especially climate change and elevated atmospheric carbon dioxide concentrations—are increasing demand for N, the element limiting primary productivity in temperate forests, which could be reducing N availability. To determine the long-term, integrated effects of global changes on forest N cycling, we measured stable N isotopes in wood, a proxy for N supply relative to demand, on large spatial and temporal scales across the continental U.S.A. Here, we show that forest N availability has generally declined across much of the U.S. since at least 1850 C.E. with cool, wet forests demonstrating the greatest declines. Across sites, recent trajectories of N availability were independent of recent atmospheric N deposition rates, implying a minor role for modern N deposition on the trajectory of N status of North American forests. Our results demonstrate that current trends of global changes are likely to be consistent with forest oligotrophication into the foreseeable future, further constraining forest C fixation and potentially storage.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-017-08170-z","usgsCitation":"McLauchlan, K.K., Gerhart, L.M., Battles, J.J., Craine, J.M., Elmore, A.J., Higuera, P., Mack, M.M., McNeil, B.E., Nelson, D.M., Pederson, N., and Perakis, S.S., 2017, Centennial-scale reductions in nitrogen availability in temperate forests of the United States: Scientific Reports, v. 7, Article 7856: 7 p., https://doi.org/10.1038/s41598-017-08170-z.","productDescription":"Article 7856: 7 p.","ipdsId":"IP-088632","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":469606,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-017-08170-z","text":"Publisher Index Page"},{"id":344879,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-10","publicationStatus":"PW","scienceBaseUri":"59940846e4b0fe2b9fe8af93","contributors":{"authors":[{"text":"McLauchlan, Kendra K.","contributorId":7994,"corporation":false,"usgs":true,"family":"McLauchlan","given":"Kendra","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":707778,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gerhart, Laci M.","contributorId":150048,"corporation":false,"usgs":false,"family":"Gerhart","given":"Laci","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":707779,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Battles, John J.","contributorId":102006,"corporation":false,"usgs":false,"family":"Battles","given":"John","email":"","middleInitial":"J.","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":707780,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Craine, Joseph M.","contributorId":139154,"corporation":false,"usgs":false,"family":"Craine","given":"Joseph","email":"","middleInitial":"M.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":707781,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Elmore, Andrew J.","contributorId":29702,"corporation":false,"usgs":true,"family":"Elmore","given":"Andrew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":707782,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Higuera, Phil E.","contributorId":16736,"corporation":false,"usgs":true,"family":"Higuera","given":"Phil E.","affiliations":[],"preferred":false,"id":707783,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mack, Michelle M","contributorId":195657,"corporation":false,"usgs":false,"family":"Mack","given":"Michelle","email":"","middleInitial":"M","affiliations":[],"preferred":false,"id":707784,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McNeil, Brendan E.","contributorId":195658,"corporation":false,"usgs":false,"family":"McNeil","given":"Brendan","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":707785,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Nelson, David M.","contributorId":175098,"corporation":false,"usgs":false,"family":"Nelson","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":13479,"text":"University of Maryland Center for Environmental Science, Appalachian Laboratory, 301 Braddock Road, Frostburg, Maryland","active":true,"usgs":false}],"preferred":false,"id":707786,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Pederson, Neil","contributorId":149422,"corporation":false,"usgs":false,"family":"Pederson","given":"Neil","email":"","affiliations":[{"id":17731,"text":"Research Scientist, Tree Ring Laboratory, Lamont-Doherty Earth Observatory","active":true,"usgs":false}],"preferred":false,"id":707787,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Perakis, Steven S. 0000-0003-0703-9314 sperakis@usgs.gov","orcid":"https://orcid.org/0000-0003-0703-9314","contributorId":145528,"corporation":false,"usgs":true,"family":"Perakis","given":"Steven","email":"sperakis@usgs.gov","middleInitial":"S.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":707777,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70190171,"text":"70190171 - 2017 - Plasticity in skeletal characteristics of nursery-raised staghorn coral, Acropora cervicornis","interactions":[],"lastModifiedDate":"2017-08-15T17:38:59","indexId":"70190171","displayToPublicDate":"2017-08-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1338,"text":"Coral Reefs","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Plasticity in skeletal characteristics of nursery-raised staghorn coral, Acropora cervicornis","title":"Plasticity in skeletal characteristics of nursery-raised staghorn coral, Acropora cervicornis","docAbstract":"Staghorn coral, Acropora cervicornis, is a threatened species and the primary focus of western Atlantic reef restoration efforts to date. We compared linear extension, calcification rate, and skeletal density of nursery-raised A. cervicornis branches reared for 6 months either on blocks attached to substratum or hanging from PVC trees in the water column. We demonstrate that branches grown on the substratum had significantly higher skeletal density, measured using computerized tomography, and lower linear extension rates compared to water-column fragments. Calcification rates determined with buoyant weighing were not statistically different between the two grow-out methods, but did vary among coral genotypes. Whereas skeletal density and extension rates were plastic traits that depended on grow-out method, calcification rate was conserved. Our results show that the two rearing methods generate the same amount of calcium carbonate skeleton but produce colonies with different skeletal characteristics and suggest that there is genetically based variability in coral calcification performance.
We determine Modified Mercalli (Seismic) Intensities (MMI) for nine onshore earthquakes of magnitude 4.5 and larger that occurred in central and western Washington between 1989 and 1999, on the basis of effects reported in postal questionnaires, the press, and professional collaborators. The earthquakes studied include four earthquakes of M5 and larger: the M5.0 Deming earthquake of April 13, 1990, the M5.0 Point Robinson earthquake of January 29, 1995, the M5.4 Duvall earthquake of May 3, 1996, and the M5.8 Satsop earthquake of July 3, 1999. The MMI are assigned using data and procedures that evolved at the U.S. Geological Survey (USGS) and its Department of Commerce predecessors and that were used to assign MMI to felt earthquakes occurring in the United States between 1931 and 1986. We refer to the MMI assigned in this report as traditional MMI, because they are based on responses to postal questionnaires and on newspaper reports, and to distinguish them from MMI calculated from data contributed by the public by way of the internet. Maximum traditional MMI documented for the M5 and larger earthquakes are VII for the 1990 Deming earthquake, V for the 1995 Point Robinson earthquake, VI for the 1996 Duvall earthquake, and VII for the 1999 Satsop earthquake; the five other earthquakes were variously assigned maximum intensities of IV, V, or VI. Starting in 1995, the Pacific Northwest Seismic Network (PNSN) published MMI maps for four of the studied earthquakes, based on macroseismic observations submitted by the public by way of the internet. With the availability now of the traditional USGS MMI interpreted for all the sites from which USGS postal questionnaires were returned, the four Washington earthquakes join a rather small group of earthquakes for which both traditional USGS MMI and some type of internet-based MMI have been assigned. The values and distributions of the traditional MMI are broadly similar to the internet-based PNSN intensities; we discuss some differences in detail that reflect differences in data-sampling procedure, differences in the procedure used to assign intensity numbers from macroseismic observations, and differences in how intensities are mapped.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171104","usgsCitation":"Brocher, T.M., Dewey, J.W., and Cassidy, J.F., 2017, Modified Mercalli Intensities for nine earthquakes in central and western Washington between 1989 and 1999: U.S. Geological Survey Open-File Report 2017–1104, 82 p., https://doi.org/10.3133/ofr20171104.","productDescription":"v, 82 p.","numberOfPages":"87","onlineOnly":"Y","ipdsId":"IP-080341","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":344861,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1104/ofr2017.1104.pdf","text":"Report","size":"4.25 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1104"},{"id":344860,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1104/coverthb.jpg"}],"country":"United States","state":"Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -126.925048828125,\n 44.12702800650004\n ],\n [\n -116.90551757812499,\n 44.12702800650004\n ],\n [\n -116.90551757812499,\n 49.78835749241399\n ],\n [\n -126.925048828125,\n 49.78835749241399\n ],\n [\n -126.925048828125,\n 44.12702800650004\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"USGS Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road
Mail Stop 977
Menlo Park, CA 94025
The California Cascades field trip is a loop beginning and ending in Portland, Oregon. The route of day 1 goes eastward across the Cascades just south of Mount Hood, travels south along the east side of the Cascades for an overview of the central Oregon volcanoes (including Three Sisters and Newberry Volcano), and ends at Klamath Falls, Oregon. Day 2 and much of day 3 focus on Medicine Lake Volcano. The latter part of day 3 consists of a drive south across the Pit River into the Hat Creek Valley and then clockwise around Lassen Volcanic Center to the town of Chester, California. Day 4 goes from south to north across Lassen Volcanic Center, ending at Burney, California. Day 5 and the first part of day 6 follow a clockwise route around Mount Shasta. The trip returns to Portland on the latter part of day 6, west of the Cascades through the Klamath Mountains and the Willamette Valley.
Each of the three sections of this guidebook addresses one of the major volcanic regions: Lassen Volcanic Center (a volcanic field that spans the volcanic arc), Mount Shasta (a fore-arc stratocone), and Medicine Lake Volcano (a rear-arc, shield-shaped edifice). Each section of the guide provides (1) an overview of the extensive field and laboratory studies, (2) an introduction to the literature, and (3) directions to the most important and accessible field localities. The field-trip sections contain far more stops than can possibly be visited in the actual 6-day 2017 IAVCEI excursion from Portland. We have included extra stops in order to provide a field-trip guide that will have lasting utility for those who may have more time or may want to emphasize one particular volcanic area.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Field-trip guides to selected volcanoes and volcanic landscapes of the western United States (Scientific Investigation Report 2017–5022)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175022K","usgsCitation":"Muffler, L.J.P., Donnelly-Nolan, J.M., Grove, T.L., Clynne, M.A., Christiansen, R.L., Calvert, A.T., and Ryan-Davis, J., 2017, Overview for geologic field-trip guides to volcanoes of the Cascades Arc in Northern California: U.S. Geological Survey Scientific Investigations Report 2017–5022–K, 6 p., https://doi.org/10.3133/sir20175022K.","productDescription":"viii, 6 p.","startPage":"1","endPage":"6","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-077694","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":344874,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5022/k/sir20175022k_.pdf","text":"Report","size":"5.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5022-K"},{"id":344938,"rank":4,"type":{"id":6,"text":"Chapter"},"url":"https://doi.org/10.3133/sir20175022K2","text":"Scientific Investigations Report 2017-5022-K2","description":"SIR 2017-5022-K2","linkHelpText":" - Chapter K2: Geologic Field-Trip Guide to the Lassen Segment of the Cascades Arc, Northern California"},{"id":344873,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5022/k/coverthb.jpg"},{"id":344937,"rank":3,"type":{"id":6,"text":"Chapter"},"url":"https://doi.org/10.3133/sir20175022K1","text":"Scientific Investigations Report 2017-5022-K1","description":"SIR 2017-5022-K1","linkHelpText":" - Chapter K1: Geologic Field-Trip Guide to Medicine Lake Volcano, Northern California, Including Lava Beds National Monument"},{"id":344953,"rank":5,"type":{"id":6,"text":"Chapter"},"url":"https://doi.org/10.3133/sir20175022K3","text":"Scientific Investigations Report 2017-5022-K3","description":"SIR 2017-5022-K3","linkHelpText":" - Chapter K3: Geologic Field-Trip Guide to Mount Shasta Volcano, Northern California"}],"country":"United States","state":"California","otherGeospatial":"Cascades Volcanic Arc","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.64038085937499,\n 40.06125658140474\n ],\n [\n -119.981689453125,\n 40.06125658140474\n ],\n [\n -119.981689453125,\n 42.66628070564928\n ],\n [\n -122.64038085937499,\n 42.66628070564928\n ],\n [\n -122.64038085937499,\n 40.06125658140474\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Volcano Science Center - Menlo Park
U.S. Geological Survey
345 Middlefield Road, MS 910
Menlo Park, CA 94025
No abstract available.
Potential contamination bias was estimated for 8 nutrient analytes and 40 pesticides in stream water collected by the U.S. Geological Survey at 147 stream sites from across the United States, and representing a variety of hydrologic conditions and site types, for water years 2002–12. This study updates previous U.S. Geological Survey evaluations of potential contamination bias for nutrients and pesticides. Contamination is potentially introduced to water samples by exposure to airborne gases and particulates, from inadequate cleaning of sampling or analytic equipment, and from inadvertent sources during sample collection, field processing, shipment, and laboratory analysis. Potential contamination bias, based on frequency and magnitude of detections in field blanks, is used to determine whether or under what conditions environmental data might need to be qualified for the interpretation of results in the context of comparisons with background levels, drinking-water standards, aquatic-life criteria or benchmarks, or human-health benchmarks. Environmental samples for which contamination bias as determined in this report applies are those from historical U.S. Geological Survey water-quality networks or programs that were collected during the same time frame and according to the same protocols and that were analyzed in the same laboratory as field blanks described in this report.
Results from field blanks for ammonia, nitrite, nitrite plus nitrate, orthophosphate, and total phosphorus were partitioned by analytical method; results from the most commonly used analytical method for total phosphorus were further partitioned by date. Depending on the analytical method, 3.8, 9.2, or 26.9 percent of environmental samples, the last of these percentages pertaining to all results from 2007 through 2012, were potentially affected by ammonia contamination. Nitrite contamination potentially affected up to 2.6 percent of environmental samples collected between 2002 and 2006 and affected about 3.3 percent of samples collected between 2007 and 2012. The percentages of environmental samples collected between 2002 and 2011 that were potentially affected by nitrite plus nitrate contamination were 7.3 for samples analyzed with the low-level method and 0.4 for samples analyzed with the standard-level method. These percentages increased to 14.8 and 2.2 for samples collected in 2012 and analyzed using replacement low- and standard-level methods, respectively. The maximum potentially affected concentrations for nitrite and for nitrite plus nitrate were much less than their respective maximum contamination levels for drinking-water standards. Although contamination from particulate nitrogen can potentially affect up to 21.2 percent and that from total Kjeldahl nitrogen can affect up to 16.5 percent of environmental samples, there are no critical or background levels for these substances.
For total nitrogen, orthophosphate, and total phosphorus, contamination in a small percentage of environmental samples might be consequential for comparisons relative to impairment risks or background levels. At the low ends of the respective ranges of impairment risk for these nutrients, contamination in up to 5 percent of stream samples could account for at least 23 percent of measured concentrations of total nitrogen, for at least 40 or 90 percent of concentrations of orthophosphate, depending on the analytical method, and for 31 to 76 percent of concentrations of total phosphorus, depending on the time period.
Twenty-six pesticides had no detections in field blanks. Atrazine with 12 and metolachlor with 11 had the highest number of detections, mostly occurring in spring or early summer. At a 99-percent level of confidence, contamination was estimated to be no greater than the detection limit in at least 98 percent of all samples for 38 of 40 pesticides. For metolachlor and atrazine, potential contamination was no greater than 0.0053 and 0.0093 micrograms per liter in 98 percent of samples. For 11 of 14 pesticides with at least one detection, the maximum potentially affected concentration of the environmental sample was less than their respective human-health or aquatic-life benchmarks. Small percentages of environmental samples had concentrations high enough that atrazine contamination potentially could account for the entire aquatic-life benchmark for acute effects on nonvascular plants, that dieldrin contamination could account for up to 100 percent of the cancer health-based screening level, or that chlorpyrifos contamination could account for 13 or 12 percent of the concentrations in the aquatic-life benchmarks for chronic effects on invertebrates or the criterion continuous concentration for chronic effects on aquatic life.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165129","usgsCitation":"Medalie, Laura, and Martin, J.D., 2017, Nutrient and pesticide contamination bias estimated from field blanks collected at surface-water sites in U.S. Geological Survey water-quality networks, 2002–12: U.S. Geological Survey Scientific Investigations Report 2016–5129, 40 p., https://doi.org/10.3133/sir20165129.","productDescription":"Report: vi, 40 p.; Appendixes 1-2","numberOfPages":"50","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-070500","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":344595,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5129/attachments/sir20165129_appendix2_metadata.txt","text":"Appendix 2","size":"1.43 KB","linkFileType":{"id":2,"text":"txt"},"linkHelpText":"- Metadata, pesticide field-blank data from surface-water 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U.S. Geological Survey
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In 2005, the U.S. Geological Survey began a cooperative study with New York City Department of Environmental Protection to characterize the local groundwater-flow system and identify potential sources of seeps on the southern embankment at the Hillview Reservoir in southern Westchester County, New York. Monthly site inspections at the reservoir indicated an approximately 90-square-foot depression in the land surface directly upslope from a seep that has episodically flowed since 2007. In July 2008, the U.S. Geological Survey surveyed the topography of land surface in this depression area by collecting high-accuracy (resolution less than 1 inch) measurements. A point of origin was established for the topographic survey by using differentially corrected positional data collected by a global navigation satellite system. Eleven points were surveyed along the edge of the depression area and at arbitrary locations within the depression area by using robotic land-surveying techniques. The points were surveyed again in March 2012 to evaluate temporal changes in land-surface altitude. Survey measurements of the depression area indicated that the land-surface altitude at 8 of the 11 points decreased beyond the accepted measurement uncertainty during the 44 months from July 2008 to March 2012. Two additional control points were established at stable locations along Hillview Avenue, which runs parallel to the embankment. These points were measured during the July 2008 survey and measured again during the March 2012 survey to evaluate the relative accuracy of the altitude measurements. The relative horizontal and vertical (altitude) accuracies of the 11 topographic measurements collected in March 2012 were ±0.098 and ±0.060 feet (ft), respectively. Changes in topography at 8 of the 11 points ranged from 0.09 to 0.63 ft and topography remained constant, or within the measurement uncertainty, for 3 of the 11 points.
Two cross sections were constructed through the depression area by using land-surface altitude data that were interpolated from positional data collected during the two topographic surveys. Cross section A–A′ was approximately 8.5 ft long and consisted of three surveyed points that trended north to south across the depression. Land-surface altitude change decreased along the entire north-south trending cross section during the 44 months, and ranged from 0.2 to more than 0.6 ft. In general, greater land-surface altitude change was measured north of the midpoint as compared to south of the midpoint of the cross section. Cross section B–B′ was 18 ft long and consisted of six surveyed points that trended east to west across the depression. Land-surface altitude change generally decreased or remained constant along the east-west trending cross section during the 44 months and ranged from 0.0 to 0.3 ft. Volume change of the depression area was calculated by using a three-dimensional geographic information system utility that subtracts interpolated surfaces. The results indicated a net volume loss of approximately 38 ±5 cubic feet of material from the depression area during the 44 months.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171028","collaboration":"Prepared in cooperation with the New York City Department of Environmental Protection","usgsCitation":"Noll, M.L., and Chu, Anthony, 2017, Detecting temporal change in land-surface altitude using robotic land-surveying techniques and geographic information system applications at an earthen dam site in southern Westchester County, New York: U.S. Geological Survey Open-File Report 2017–1028, 15 p., https://doi.org/10.3133/ofr20171028.","productDescription":"vi, 15 p.","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-077425","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":344641,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1028/ofr20171028.pdf","text":"Report","size":"1.03 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1028"},{"id":344640,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1028/coverthb.jpg"}],"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 -73.88648986816406,\n 40.894180824484465\n ],\n [\n -73.85250091552734,\n 40.894180824484465\n ],\n [\n -73.85250091552734,\n 40.92726192578736\n ],\n [\n -73.88648986816406,\n 40.92726192578736\n ],\n [\n -73.88648986816406,\n 40.894180824484465\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
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A study was done by the U.S. Geological Survey in cooperation with the Kansas Department of Transportation and the Federal Emergency Management Agency to develop regression models to estimate peak streamflows of annual exceedance probabilities of 50, 20, 10, 4, 2, 1, 0.5, and 0.2 percent at ungaged locations in Kansas. Peak streamflow frequency statistics from selected streamgages were related to contributing drainage area and average precipitation using generalized least-squares regression analysis. The peak streamflow statistics were derived from 151 streamgages with at least 25 years of streamflow data through 2015. The developed equations can be used to predict peak streamflow magnitude and frequency within two hydrologic regions that were defined based on the effects of irrigation. The equations developed in this report are applicable to streams in Kansas that are not substantially affected by regulation, surface-water diversions, or urbanization. The equations are intended for use for streams with contributing drainage areas ranging from 0.17 to 14,901 square miles in the nonirrigation effects region and, 1.02 to 3,555 square miles in the irrigation-affected region, corresponding to the range of drainage areas of the streamgages used in the development of the regional equations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175063","collaboration":"Prepared in cooperation with the Kansas Department of Transportation and Federal Emergency Management Agency","usgsCitation":"Painter, C.C., Heimann, D.C., and Lanning-Rush, J.L., 2017, Methods for estimating annual exceedance-probability streamflows for streams in Kansas based on data through water year 2015 (ver. 1.1, September 2017): U.S. Geological Survey Scientific Investigations Report 2017–5063, 20 p., https://doi.org/10.3133/sir20175063.","productDescription":"Report: vi, 20 p.; 4 Tables","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-087048","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":345864,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2017/5063/versionHist.txt","size":"1 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2017–5063 Version History"},{"id":344871,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5063/sir20175063_table5.xlsx","text":"Table 5","size":"47 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017–5063 Table 5"},{"id":344870,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5063/sir20175063_table4.xlsx","text":"Table 4","size":"23 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017–5063 Table 4"},{"id":344868,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5063/sir20175063_table2.xlsx","text":"Table 2","size":"42 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017–5063 Table 2"},{"id":344869,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5063/sir20175063_table3.xlsx","text":"Table 3","size":"60 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017–5063 Table 3"},{"id":344698,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5063/coverthb2.jpg"},{"id":344699,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5063/sir20175063.pdf","text":"Report","size":"1.52 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5063"}],"country":"United States","state":"Colorado, Kansas, Missouri, Nebraska, Oklahoma","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -102.48046875,\n 36.38591277287651\n ],\n [\n -93.93310546875,\n 36.38591277287651\n ],\n [\n -93.93310546875,\n 40.713955826286046\n ],\n [\n -102.48046875,\n 40.713955826286046\n ],\n [\n -102.48046875,\n 36.38591277287651\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally posted August 14, 2017; Version 1.1: September 18, 2017","contact":"Director, Kansas Water Science Center
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4821 Quail Crest Place
Lawrence, KS 66049
Genetic differentiation among Spotted Owl (Strix occidentalis) subspecies has been established in prior studies. These investigations also provided evidence for introgression and hybridization among taxa but were limited by a lack of samples from geographic regions where subspecies came into close contact. We analyzed new sets of samples from Northern Spotted Owls (NSO: S. o. caurina) and California Spotted Owls (CSO: S. o. occidentalis) in northern California using mitochondrial DNA sequences (mtDNA) and 10 nuclear microsatellite loci to obtain a clearer depiction of genetic differentiation and hybridization in the region. Our analyses revealed that a NSO population close to the northern edge of the CSO range in northern California (the NSO Contact Zone population) is highly differentiated relative to other NSO populations throughout the remainder of their range. Phylogenetic analyses identified a unique lineage of mtDNA in the NSO Contact Zone, and Bayesian clustering analyses of the microsatellite data identified the Contact Zone as a third distinct population that is differentiated from CSO and NSO found in the remainder of the subspecies' range. Hybridization between NSO and CSO was readily detected in the NSO Contact Zone, with over 50% of individuals showing evidence of hybrid ancestry. Hybridization was also identified among 14% of CSO samples, which were dispersed across the subspecies' range in the Sierra Nevada Mountains. The asymmetry of hybridization suggested that the hybrid zone may be dynamic and moving. Although evidence of hybridization existed, we identified no F1 generation hybrid individuals. We instead found evidence for F2 or backcrossed individuals among our samples. The absence of F1 hybrids may indicate that (1) our 10 microsatellites were unable to distinguish hybrid types, (2) primary interactions between subspecies are occurring elsewhere on the landscape, or (3) dispersal between the subspecies' ranges is reduced relative to historical levels, potentially as a consequence of recent regional fires.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.3260","usgsCitation":"Miller, M.P., Mullins, T.D., Forsman, E.D., and Haig, S.M., 2017, Genetic differentiation and inferred dynamics of a hybrid zone between Northern Spotted Owls (Strix occidentalis caurina) and California Spotted Owls (S. o. occidentalis) in northern California: Ecology and Evolution, v. 7, no. 17, p. 6871-6883, https://doi.org/10.1002/ece3.3260.","productDescription":"13 p.","startPage":"6871","endPage":"6883","ipdsId":"IP-085456","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":469608,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.3260","text":"Publisher Index Page"},{"id":344850,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.76074218749999,\n 37.49229399862877\n ],\n [\n -119.02587890624999,\n 37.49229399862877\n ],\n [\n -119.02587890624999,\n 42.58544425738491\n ],\n [\n -124.76074218749999,\n 42.58544425738491\n ],\n [\n -124.76074218749999,\n 37.49229399862877\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"17","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-27","publicationStatus":"PW","scienceBaseUri":"59b76ec2e4b08b1644ddfac6","contributors":{"authors":[{"text":"Miller, Mark P. 0000-0003-1045-1772 mpmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-1045-1772","contributorId":1967,"corporation":false,"usgs":true,"family":"Miller","given":"Mark","email":"mpmiller@usgs.gov","middleInitial":"P.","affiliations":[{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"preferred":true,"id":707746,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mullins, Thomas D. 0000-0001-8948-9604 tom_mullins@usgs.gov","orcid":"https://orcid.org/0000-0001-8948-9604","contributorId":149824,"corporation":false,"usgs":true,"family":"Mullins","given":"Thomas","email":"tom_mullins@usgs.gov","middleInitial":"D.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":707747,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Forsman, Eric D.","contributorId":96792,"corporation":false,"usgs":false,"family":"Forsman","given":"Eric","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":707748,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haig, Susan M. 0000-0002-6616-7589 susan_haig@usgs.gov","orcid":"https://orcid.org/0000-0002-6616-7589","contributorId":719,"corporation":false,"usgs":true,"family":"Haig","given":"Susan","email":"susan_haig@usgs.gov","middleInitial":"M.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":707749,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70190155,"text":"70190155 - 2017 - Seasonal trends in eDNA detection and occupancy of bigheaded carps","interactions":[],"lastModifiedDate":"2017-08-14T17:39:33","indexId":"70190155","displayToPublicDate":"2017-08-14T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal trends in eDNA detection and occupancy of bigheaded carps","docAbstract":"Bigheaded carps, which include silver and bighead carp, are threatening to invade the Great Lakes. These species vary seasonally in distribution and abundance due to environmental conditions such as precipitation and temperature. Monitoring this seasonal movement is important for management to control the population size and spread of the species. We examined if environmental DNA (eDNA) approaches could detect seasonal changes of these species. To do this, we developed a novel genetic marker that was able to both detect and differentiate bighead and silver carp DNA. We used the marker, combined with a novel occupancy model, to study the occurrence of bigheaded carps at 3 sites on the Wabash River over the course of a year. We studied the Wabash River because of concerns that carps may be able to use the system to invade the Great Lakes via a now closed (ca. 2017) connection at Eagle Marsh between the Wabash River's watershed and the Great Lakes' watershed. We found seasonal trends in the probability of detection and occupancy that varied across sites. These findings demonstrate that eDNA methods can detect seasonal changes in bigheaded carps densities and suggest that the amount of eDNA present changes seasonally. The site that was farthest upstream and had the lowest carp densities exhibited the strongest seasonal trends for both detection probabilities and sample occupancy probabilities. Furthermore, other observations suggest that carps seasonally leave this site, and we were able to detect this with our eDNA approach.
","language":"English","publisher":"International Association for Great Lakes Research","doi":"10.1016/j.jglr.2017.06.003","usgsCitation":"Erickson, R.A., Merkes, C.M., Jackson, C., Goforth, R., and Amberg, J., 2017, Seasonal trends in eDNA detection and occupancy of bigheaded carps: Journal of Great Lakes Research, v. 43, no. 4, p. 762-770, https://doi.org/10.1016/j.jglr.2017.06.003.","productDescription":"9 p.","startPage":"762","endPage":"770","ipdsId":"IP-074701","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":469610,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2017.06.003","text":"Publisher Index Page"},{"id":344854,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59b76ec2e4b08b1644ddfac8","contributors":{"authors":[{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":707727,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Merkes, Christopher M. 0000-0001-8191-627X cmerkes@usgs.gov","orcid":"https://orcid.org/0000-0001-8191-627X","contributorId":139516,"corporation":false,"usgs":true,"family":"Merkes","given":"Christopher","email":"cmerkes@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":707728,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jackson, Craig 0000-0003-4023-0276 cjackson@usgs.gov","orcid":"https://orcid.org/0000-0003-4023-0276","contributorId":192276,"corporation":false,"usgs":true,"family":"Jackson","given":"Craig","email":"cjackson@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":707729,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goforth, Reuben","contributorId":192277,"corporation":false,"usgs":false,"family":"Goforth","given":"Reuben","affiliations":[],"preferred":false,"id":707730,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Amberg, Jon 0000-0002-8351-4861 jamberg@usgs.gov","orcid":"https://orcid.org/0000-0002-8351-4861","contributorId":149785,"corporation":false,"usgs":true,"family":"Amberg","given":"Jon","email":"jamberg@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":707731,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}