Continuous slope-area (CSA) streamgages have been developed and implemented by the U.S. Geological Survey (USGS) to enable the recording of discharge hydrographs in areas where direct discharge measurements cannot be made. The flashy nature of streamflow in parts of the arid Southwest and remote location of many sites make discharge measurements difficult or impossible to obtain. Consequently, available discharge measurements may be insufficient to develop accurate rating curves, which relate discharge to continuously recorded stage measured at standard streamgages. Nine CSA streamgages have been installed in Maricopa County, Arizona, since 2004 in cooperation with the Flood Control District of Maricopa County. This report presents the data and analysis of computed discharges from those streamgages, along with descriptions of the streamgage site and stream properties.
\nAnalyses of sources of errors and the impact stage data errors have on calculated discharge time series are considered, along with issues in data reduction. Steeper, longer stream reaches are generally less sensitive to measurement error. Other issues considered are pressure transducer drawdown, capture of flood peaks with discrete stage data, selection of stage record for development of rating curves, and minimum stages for the calculation of discharge.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155172","collaboration":"Prepared in cooperation with the Flood Control District of Maricopa County","usgsCitation":"Wiele, S.M., Heaton, J.W., Bunch, C.E., Gardner, D.E., and Smith, C.F., 2015, Continuous slope-area discharge records in Maricopa County, Arizona, 2004–2012: U.S. Geological Survey Scientific Investigations Report 2015–5172, 28 p., https://dx.doi.org/10.3133/sir20155172.","productDescription":"vii, 28 p.","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-046154","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":321784,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5172/sir20155172_appendixes1-9.zip","text":"Appendixes 1-9","size":"967 KB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2015-5172 Appendixes 1-9"},{"id":311902,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5172/coverthb.jpg"},{"id":311903,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5172/sir20155172.pdf","text":"Report","size":"19 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5172"}],"country":"United States","state":"Arizona","county":"Maricopa County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.79638671875,\n 32.96258644191747\n ],\n [\n -113.79638671875,\n 34.32529192442733\n ],\n [\n -111.5716552734375,\n 34.32529192442733\n ],\n [\n -111.5716552734375,\n 32.96258644191747\n ],\n [\n -113.79638671875,\n 32.96258644191747\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
http://az.water.usgs.gov/
Asian carp eggs are semi-buoyant and must remain suspended in the water to survive, supported by the turbulence of the flow, until they hatch and develop the ability to swim. Analysis of the transport and dispersal patterns of Asian carp eggs will facilitate the development and implementation of control strategies to target the early life stages. Experimenting with Asian carp eggs is complicated due to practical issues of obtaining eggs in close proximity to experimental facilities and extensive handling of eggs tends to damage them. Herein, we describe laboratory experiments using styrene beads (4.85 mm diameter) as synthetic surrogate eggs to mimic the physical properties of water-hardened silver carp eggs. The first set of experiments was completed in a rectangular vertical column filled with salt water. The salinity of the water was adjusted in an iterative fashion to obtain a close approximation of the fall velocity of the styrene beads to the mean fall velocity of silver carp water-hardened eggs. The terminal fall velocity of synthetic eggs was measured using an image processing method. The second set of experiments was performed in a temperature-controlled recirculatory flume with a sediment bed. The flume was filled with salt water, and synthetic eggs were allowed to drift under different flow conditions. Drifting behavior, suspension conditions, and settling characteristics of synthetic eggs were observed. At high velocities, eggs were suspended and distributed through the water column. Eggs that touched the sediment bed were re-entrained by the flow. Eggs saltated when they touched the bed, especially at moderate velocities and with a relatively flat bed. At lower velocities, some settling of the eggs was observed. With lower velocities and a flat bed, eggs were trapped near the walls of the flume. When bedforms were present, eggs were trapped in the lee of the bedforms in addition to being trapped near the flume walls. Results of this research study provide insights about transport, suspension, and dispersion of silver carp eggs. The knowledge gained from this study is useful to characterize the critical hydrodynamic conditions of the flow at which surrogates for silver carp water-hardened eggs settle out of suspension, and provides insight into how eggs may interact with riverbed sediments and morphology.
","language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco","doi":"10.1371/journal.pone.0145775","collaboration":"Great Lakes Restoration Initiative \nUniversity of Illinois","usgsCitation":"Garcia, T., Zuniga Zamalloa, C., Jackson, P., Murphy, E., and Garcia, M., 2015, A laboratory investigation of the suspension, transport, and settling of silver carp eggs using synthetic surrogates: PLoS ONE, p. 1-19, https://doi.org/10.1371/journal.pone.0145775.","productDescription":"19 p.","startPage":"1","endPage":"19","numberOfPages":"19","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-064982","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":471554,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0145775","text":"Publisher Index Page"},{"id":313936,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-29","publicationStatus":"PW","scienceBaseUri":"568e48cee4b0e7a44bc41839","contributors":{"authors":[{"text":"Garcia, Tatiana 0000-0002-1979-7246 tgarcia@usgs.gov","orcid":"https://orcid.org/0000-0002-1979-7246","contributorId":140327,"corporation":false,"usgs":true,"family":"Garcia","given":"Tatiana","email":"tgarcia@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":573635,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zuniga Zamalloa, Carlo","contributorId":148037,"corporation":false,"usgs":false,"family":"Zuniga Zamalloa","given":"Carlo","email":"","affiliations":[{"id":16984,"text":"University of Illinois at Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":573636,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jackson, P. Ryan pjackson@usgs.gov","contributorId":2960,"corporation":false,"usgs":true,"family":"Jackson","given":"P. Ryan","email":"pjackson@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":573637,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Murphy, Elizabeth A. emurphy@usgs.gov","contributorId":140328,"corporation":false,"usgs":true,"family":"Murphy","given":"Elizabeth A.","email":"emurphy@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":573638,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Garcia, Marcelo H.","contributorId":74236,"corporation":false,"usgs":false,"family":"Garcia","given":"Marcelo H.","affiliations":[{"id":33106,"text":"University of Illinois at Urbana Champaign","active":true,"usgs":false}],"preferred":false,"id":573639,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70159829,"text":"sir20155173 - 2015 - Preliminary assessment of aggradation potential in the North Fork Stillaguamish River downstream of the State Route 530 landslide near Oso, Washington","interactions":[],"lastModifiedDate":"2016-01-04T18:19:31","indexId":"sir20155173","displayToPublicDate":"2015-12-28T16:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5173","title":"Preliminary assessment of aggradation potential in the North Fork Stillaguamish River downstream of the State Route 530 landslide near Oso, Washington","docAbstract":"On March 22, 2014, the State Route 530 Landslide near Oso, Washington, traveled almost 2 kilometers (km), destroyed more than 40 structures, and impounded the North Fork Stillaguamish River to a depth of 8 meters (m) and volume of 3.3×106 cubic meters (m3). The landslide killed 43 people. After overtopping and establishing a new channel through the landslide, the river incised into the landslide deposit over the course of 10 weeks draining the impoundment lake and mobilizing an estimated 280,000±56,000 m3 of predominantly sand-sized and finer sediment. During the first 4 weeks after the landslide, this eroded sediment caused downstream riverbed aggradation of 1–2 m within 1 km of the landslide and 0.4 m aggradation at Whitman Road Bridge, 3.5 km downstream. Winter high flows in 2014–15 were anticipated to mobilize an additional 220,000±44,000 m3 of sediment, potentially causing additional aggradation and exacerbating flood risk downstream of the landslide. Analysis of unit stream power and bed-material transport capacity along 35 km of the river corridor indicated that most fine-grained sediment will transport out of the North Fork Stillaguamish River, although some localized additional aggradation was possible. This new aggradation was not likely to exceed 0.1 m except in reaches within a few kilometers downstream of the landslide, where additional aggradation of up to 0.5 m is possible. Alternative river response scenarios, including continued mass wasting from the landslide scarp, major channel migration or avulsion, or the formation of large downstream wood jams, although unlikely, could result in reaches of significant local aggradation or channel change.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155173","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency and Snohomish County Department of Public Works","usgsCitation":"Magirl, C.S., Keith, M.K., Anderson, S.W., O’Connor, J.E., Aldrich, Robert, and Mastin, M.C., 2015, Preliminary assessment of aggradation potential in the North Fork Stillaguamish River downstream of the State Route 530 landslide near Oso, Washington: U.S. Geological Survey Scientific Investigations Report 2015–5173, 20 p., https://dx.doi.org/10.3133/sir20155173.","productDescription":"v, 20 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-060502","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":312938,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5173/sir20155173.pdf","text":"Report","size":"1.3 MB","description":"SIR 2015-5173 Report PDF"},{"id":312937,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5173/cover.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"North Fork Stillaguamish River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.5,\n 48.5\n ],\n [\n -122.5,\n 48\n ],\n [\n -121.5,\n 48\n ],\n [\n -121.5,\n 48.5\n ],\n [\n -122.5,\n 48.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
http://wa.water.usgs.gov
We present ∼1300 new isotopic measurements (δ18O and δ2H) from a network of snowpack sites in the Rocky Mountains that have been sampled since 1993. The network includes 177 locations where depth-integrated snow samples are collected each spring near peak accumulation. At 57 of these locations snowpack samples were obtained for 10–21 years and their isotopic measurements provide unprecedented spatial and temporal documentation of snowpack isotope values at mid-latitudes. For environments where snowfall accounts for the majority of annual precipitation, snowmelt is likely to have the strongest influence on isotope values retained in proxy archives. In this first presentation of the dataset we (1) describe the basic features of the isotope values in relation to the Global Meteoric Water Line (GMWL), (2) evaluate space for time substitutions traditionally used to establish δ18O-temperature relations, (3) evaluate site-to-site similarities across the network and identify those that are the most regionally representative, (4) examine atmospheric circulation patterns for several years with spatially coherent isotope patterns, and (5) provide examples of the implications this new dataset has for interpreting paleoclimate records (Bison Lake, Colorado and Minnetonka Cave, Idaho). Results indicate that snowpack δ18O is rarely a simple proxy of temperature. Instead, it exhibits a high degree of spatial heterogeneity and temporal variance that reflect additional processes such as vapor transport and post-depositional modification. Despite these complexities we identify consistent climate-isotope patterns and regionally representative locations that serve to better define Holocene hydroclimate estimates and their uncertainty. Climate change has and will affect western U.S. snowpack and we suggest these changes can be better understood and anticipated by oxygen and hydrogen isotope-based reconstructions of Holocene hydroclimate using a process-based understanding of the controls on snowpack isotope ratios.
","language":"English","publisher":"Elseiver Ltd.","doi":"10.1016/j.quascirev.2015.03.023","usgsCitation":"Anderson, L., Berkelhammer, M., and Mast, M.A., 2015, Isotopes in North American Rocky Mountain snowpack 1993–2014: Quaternary Science Reviews, v. 131, p. 262-273, https://doi.org/10.1016/j.quascirev.2015.03.023.","productDescription":"12 p.","startPage":"262","endPage":"273","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061199","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":312939,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Idaho, Montana, New Mexico, Wyoming","otherGeospatial":"Bison Lake, Minnetonka Cave, Rocky Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.8515625,\n 49.03786794532644\n ],\n [\n -111.796875,\n 47.96050238891509\n ],\n [\n -110.830078125,\n 46.86019101567027\n ],\n [\n -109.51171875,\n 46.437856895024204\n ],\n [\n -108.5009765625,\n 45.583289756006316\n ],\n [\n -108.06152343749999,\n 43.83452678223682\n ],\n [\n -107.0068359375,\n 42.293564192170095\n ],\n [\n -104.9853515625,\n 41.07935114946899\n ],\n [\n -103.88671875,\n 38.06539235133249\n ],\n [\n -104.32617187499999,\n 35.88905007936091\n ],\n [\n -105.29296874999999,\n 34.161818161230386\n ],\n [\n -107.70996093749999,\n 34.161818161230386\n ],\n [\n -110.302734375,\n 35.53222622770337\n ],\n [\n -112.8955078125,\n 41.27780646738183\n ],\n [\n -116.806640625,\n 43.51668853502909\n ],\n [\n -117.90527343750001,\n 46.49839225859763\n ],\n [\n -118.125,\n 48.922499263758255\n ],\n [\n -117.90527343750001,\n 49.095452162534826\n ],\n [\n -112.8515625,\n 49.03786794532644\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"131","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56825d29e4b0a04ef4925af5","contributors":{"authors":[{"text":"Anderson, Lesleigh 0000-0002-5264-089X land@usgs.gov","orcid":"https://orcid.org/0000-0002-5264-089X","contributorId":436,"corporation":false,"usgs":true,"family":"Anderson","given":"Lesleigh","email":"land@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":583487,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Berkelhammer, Max ","contributorId":150891,"corporation":false,"usgs":false,"family":"Berkelhammer","given":"Max ","affiliations":[{"id":18133,"text":"University of Illinois Chicago","active":true,"usgs":false}],"preferred":false,"id":583488,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mast, M. Alisa 0000-0001-6253-8162 mamast@usgs.gov","orcid":"https://orcid.org/0000-0001-6253-8162","contributorId":827,"corporation":false,"usgs":true,"family":"Mast","given":"M.","email":"mamast@usgs.gov","middleInitial":"Alisa","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":583489,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70160649,"text":"70160649 - 2015 - Rangeland monitoring reveals long-term plant responses to precipitation and grazing at the landscape scale","interactions":[],"lastModifiedDate":"2015-12-28T14:18:59","indexId":"70160649","displayToPublicDate":"2015-12-28T13:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"Rangeland monitoring reveals long-term plant responses to precipitation and grazing at the landscape scale","docAbstract":"Managers of rangeland ecosystems require methods to track the condition of natural resources over large areas and long periods of time as they confront climate change and land use intensification. We demonstrate how rangeland monitoring results can be synthesized using ecological site concepts to understand how climate, site factors, and management actions affect long-term vegetation dynamics at the landscape-scale. Forty-six years of rangeland monitoring conducted by the Bureau of Land Management (BLM) on the Colorado Plateau reveals variable responses of plant species cover to cool-season precipitation, land type (ecological site groups), and grazing intensity. Dominant C3 perennial grasses (Achnatherum hymenoides, Hesperostipa comata), which are essential to support wildlife and livestock on the Colorado Plateau, had responses to cool-season precipitation that were at least twice as large as the dominant C4 perennial grass (Pleuraphis jamesii) and woody vegetation. However, these C3 perennial grass responses to precipitation were reduced by nearly one-third on grassland ecological sites with fine- rather than coarse-textured soils, and there were no detectable C3 perennial grass responses to precipitation on ecological sites dominated by a dense-growing shrub, Coleogyne ramosissima. Heavy grazing intensity further reduced the responses of C3 perennial grasses to cool-season precipitation on ecological sites with coarse-textured soils and surprisingly reduced the responses of shrubs as well. By using ecological site groups to assess rangeland condition, we were able to improve our understanding of the long-term relationships between vegetation change and climate, land use, and site characteristics, which has important implications for developing landscape-scale monitoring strategies.
","language":"English","publisher":"Society for Range Management","publisherLocation":"Lakewood, CO","doi":"10.1016/j.rama.2015.09.004","usgsCitation":"Munson, S.M., Duniway, M.C., and Johanson, J.K., 2015, Rangeland monitoring reveals long-term plant responses to precipitation and grazing at the landscape scale: Rangeland Ecology and Management, v. 69, no. 1, p. 76-83, https://doi.org/10.1016/j.rama.2015.09.004.","productDescription":"8 p.","startPage":"76","endPage":"83","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060797","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":438658,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75D8PZ5","text":"USGS data release","linkHelpText":"Rangeland Ecology Monitoring Data, Utah, 1967-2013"},{"id":312935,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah","otherGeospatial":"Colorado Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.56689453125,\n 40.896905775860006\n ],\n [\n -107.81982421874999,\n 40.06125658140471\n ],\n [\n -107.6220703125,\n 38.856820134743636\n ],\n [\n -107.8857421875,\n 38.013476231041935\n ],\n [\n -107.4462890625,\n 37.28279464911045\n ],\n [\n -106.5673828125,\n 36.50963615733049\n ],\n [\n -106.32568359375,\n 35.44277092585766\n ],\n [\n -106.63330078125,\n 34.488447837809304\n ],\n [\n -107.75390625,\n 34.252676117101515\n ],\n [\n -110.58837890625,\n 34.288991865037524\n ],\n [\n -111.64306640625,\n 34.72355492704221\n ],\n [\n -112.65380859375,\n 35.90684930677121\n ],\n [\n -113.44482421875,\n 36.54494944148322\n ],\n [\n -113.64257812499999,\n 37.33522435930639\n ],\n [\n -113.40087890624999,\n 38.013476231041935\n ],\n [\n -112.65380859375,\n 38.71980474264239\n ],\n [\n -111.90673828125,\n 40.12849105685408\n ],\n [\n -111.55517578125,\n 40.88029480552824\n ],\n [\n -110.41259765625,\n 40.88029480552824\n ],\n [\n -108.56689453125,\n 40.896905775860006\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"69","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56825d29e4b0a04ef4925afd","contributors":{"authors":[{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":583462,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":583463,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johanson, Jamin K.","contributorId":150880,"corporation":false,"usgs":false,"family":"Johanson","given":"Jamin","email":"","middleInitial":"K.","affiliations":[{"id":18131,"text":"National Resources Conservation Service, Richfield, UT 84701 USA","active":true,"usgs":false}],"preferred":false,"id":583464,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70160614,"text":"70160614 - 2015 - Organic amendments for risk mitigation of organochlorine pesticide residues in old orchard soils","interactions":[],"lastModifiedDate":"2018-08-09T12:21:06","indexId":"70160614","displayToPublicDate":"2015-12-28T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1555,"text":"Environmental Pollution","active":true,"publicationSubtype":{"id":10}},"title":"Organic amendments for risk mitigation of organochlorine pesticide residues in old orchard soils","docAbstract":"Performance of compost and biochar amendments for in situ risk mitigation of aged DDT, DDE and dieldrin residues in an old orchard soil was examined. The change in bioavailability of pesticide residues to Lumbricus terrestris L. relative to the unamended control soil was assessed using 4-L soil microcosms with and without plant cover in a 48-day experiment. The use of aged dairy manure compost and biosolids compost was found to be effective, especially in the planted treatments, at lowering the bioavailability factor (BAF) by 18–39%; however, BAF results for DDT in the unplanted soil treatments were unaffected or increased. The pine chip biochar utilized in this experiment was ineffective at lower the BAF of pesticides in the soil. The US EPA Soil Screening Level approach was used with our measured values. Addition of 10% of the aged dairy manure compost reduced the average hazard quotient values to below 1.0 for DDT + DDE and dieldrin. Results indicate this sustainable approach is appropriate to minimize risks to wildlife in areas of marginal organochlorine pesticide contamination. Application of this remediation approach has potential for use internationally in areas where historical pesticide contamination of soils remains a threat to wildlife populations.
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GIWs constitute most of the wetlands in many North American landscapes, provide a disproportionately large fraction of wetland edges where many functions are enhanced, and form complexes with other water bodies to create spatial and temporal heterogeneity in the timing, flow paths, and magnitude of network connectivity. These attributes signal a critical role for GIWs in sustaining a portfolio of landscape functions, but legal protections remain weak despite preferential loss from many landscapes. GIWs lack persistent surface water connections, but this condition does not imply the absence of hydrological, biogeochemical, and biological exchanges with nearby and downstream waters. Although hydrological and biogeochemical connectivity is often episodic or slow (e.g., via groundwater), hydrologic continuity and limited evaporative solute enrichment suggest both flow generation and solute and sediment retention. 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We surveyed four altitudinal sites ranging from 1,200 to 2,200 m asl in the Kahuku Unit of Hawai‘i Volcanoes National Park (Kahuku) and three altitudinal sites ranging from 1,200 to 1,500 m asl in the Ka‘u Forest Reserve (Ka‘u) for the prevalence of avian disease and presence of mosquitoes. We collected blood samples from native and non-native forest birds and screened for avian malaria (Plasmodium relictum) using PCR diagnostics. We examined birds for signs of avian pox (Avipoxvirus sp.), knemidokoptic mange (Knemidokoptes jamaicensis) and feather ectoparasites. We also trapped adult mosquitoes (Culex quinquefasciatus and Aedes japonicus japonicus) and surveyed for available larval habitat. Between September, 2012 and October, 2014, we completed 3,219 hours of mist-netting in Kahuku capturing 515 forest birds and 3,103 hours of mist-netting in Ka‘u capturing 270 forest birds. We screened 750 blood samples for avian malaria. Prevalence of avian malaria in all species was higher in Ka‘u than Kahuku when all sites were combined for each tract. Prevalence of avian malaria in resident Hawai‘i ‘amakihi (Chlorodrepanis virens) was greatest at the lowest elevation sites in Kahuku (26%; 1,201 m asl) and Ka‘u (42%; 1,178 m asl) and in general, prevalence decreased with increasing elevation and geographically from east to west. Significantly higher prevalence was seen in Ka‘u at comparable low and mid elevation sites but not at comparable high elevation sites. The overall presumptive pox prevalence was 1.7% (13/785) for both tracts, and it was higher in native birds than non-native birds, but it was not significant. Presumptive knemidokoptic mange was detected at two sites in lower elevation Kahuku, with prevalence ranging from 2‒4%. The overall prevalence of ectoparasites (Analges and Proctophyllodes spp.) was 6.7% (53/785). The site with the highest prevalence was Lower Glover in Kahuku (7.2%; 10/138) and Maka‘alia in Ka‘u. In general, mosquito larval habitat was more prevalent at lower elevation sites than higher elevation sites within the Kahuku—Ka‘u landscape, and more prevalent in Ka‘u than Kahuku. We observed significantly more available larval mosquito habitat in total belt transect plots in Ka‘u than Kahuku for both hapu‘u cavities (Χ2 = 47.06, df = 1, p < 0.01) and other habitat types combined (i.e., ground pools, rock holes, tree holes) (Χ2 = 104.35, df = 1, p < 0.01). Mosquitoes were most abundant at low elevation Kahuku, but were captured at all sites up to 1,532 m asl in Kahuku. The malarial infection rate of live mosquitoes was 21% (39/186) at Kahuku and 25% (2/8) at Ka‘u. There were 19 times more larval habitats available in Ka‘u than Kahuku on survey transects, yet we captured 53 times more C. quinquefasciatus mosquitoes in Kahuku. We captured very few adult A. j. japonicus across the landscape (Ntotal = 6) and no Aedes albopictus were detected in this study. Larval surveys along ranch roads and infrastructure revealed that ground pools along rutted, overgrown ranch roads were the likely source of Kahuku mosquitoes. We did not find mosquito larvae associated with ranching infrastructure. Unlike the low elevation forests on windward Hawai‘i Island, avian malaria prevalence, mosquito abundance, and the density of available larval habitat in Kahuku and Ka‘u were relatively low. Although altitudinal variations in climate appear to be the primary factors limiting the distribution of avian disease, habitat type, avian movements, human activity, and feral pig (Sus scrofa) management all may play important roles in determining the prevalence of avian malaria across the Kahuku—Ka‘u landscape.
","language":"English","publisher":"University of Hawaii at Hilo","publisherLocation":"Hilo, HI","usgsCitation":"Gaudioso, J., Lapointe, D., Atkinson, C.T., and Egan, A.N., 2015, Avian disease and mosquito vectors in the Kahuku unit of Hawai`i Volcanoes National Park and Ka`u Forest Reserve: Technical Report HCSU-070, Report: iv, 41 p.","productDescription":"Report: iv, 41 p.","startPage":"1","endPage":"41","numberOfPages":"45","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071145","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":326259,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57a9ad38e4b05e859bdfb845","contributors":{"authors":[{"text":"Gaudioso, Jacqueline jgaudioso@usgs.gov","contributorId":5637,"corporation":false,"usgs":true,"family":"Gaudioso","given":"Jacqueline","email":"jgaudioso@usgs.gov","affiliations":[{"id":524,"text":"Pacific Islands Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":583758,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LaPointe, Dennis A. 0000-0002-6323-263X dlapointe@usgs.gov","orcid":"https://orcid.org/0000-0002-6323-263X","contributorId":150365,"corporation":false,"usgs":true,"family":"LaPointe","given":"Dennis","email":"dlapointe@usgs.gov","middleInitial":"A.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":583759,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Atkinson, Carter T. 0000-0002-4232-5335 catkinson@usgs.gov","orcid":"https://orcid.org/0000-0002-4232-5335","contributorId":1124,"corporation":false,"usgs":true,"family":"Atkinson","given":"Carter","email":"catkinson@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":583760,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Egan, Ariel N.","contributorId":150954,"corporation":false,"usgs":false,"family":"Egan","given":"Ariel","email":"","middleInitial":"N.","affiliations":[{"id":13351,"text":"University of Hawaii Cooperative Studies Unit","active":true,"usgs":false}],"preferred":false,"id":583761,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159764,"text":"ofr20151223 - 2015 - Water-quality, bed-sediment, and biological data (October 2013 through September 2014) and statistical summaries of data for streams in the Clark Fork Basin, Montana","interactions":[],"lastModifiedDate":"2015-12-28T10:21:29","indexId":"ofr20151223","displayToPublicDate":"2015-12-24T10:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1223","title":"Water-quality, bed-sediment, and biological data (October 2013 through September 2014) and statistical summaries of data for streams in the Clark Fork Basin, Montana","docAbstract":"Water, bed sediment, and biota were sampled in streams from Butte to near Missoula, Montana, as part of a monitoring program in the upper Clark Fork Basin of western Montana. The sampling program was led by the U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency, to characterize aquatic resources in the Clark Fork Basin, with emphasis on trace elements associated with historic mining and smelting activities. Sampling sites were located on the Clark Fork and selected tributaries. Water samples were collected periodically at 20 sites from October 2013 through September 2014. Bed-sediment and biota samples were collected once at 14 sites during August 2014.
\nThis report presents the analytical results and qualityassurance data for water-quality, bed-sediment, and biota samples collected at sites from October 2013 through September 2014. Water-quality data include concentrations of selected major ions, trace elements, and suspended sediment. At 12 sites, dissolved organic carbon and turbidity samples were collected. In addition, nitrogen (nitrate plus nitrite) samples were collected at two sites. Daily values of mean suspended-sediment concentration and suspended-sediment discharge were determined for four sites. Seasonal daily values of turbidity were determined for four sites. Bed-sediment data include trace-element concentrations in the fine-grained fraction. Biological data include trace-element concentrations in wholebody tissue of aquatic benthic insects. Statistical summaries of water-quality, bed-sediment, and biological data for sites in the upper Clark Fork Basin are provided for the period of record.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151223","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Dodge, K.A., and Hornberger, M.I., 2015, Water-quality, bed-sediment, and biological data (October 2013 through September\n2014) and statistical summaries of data for streams in the Clark Fork Basin, Montana: U.S. Geological Survey Open-File Report 2015–1223, 125 p., https://dx.doi.org/10.3133/ofr20151223.","productDescription":"vi, 125 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068852","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":312826,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1223/ofr20151223.pdf","text":"Report","size":"2.04 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1223"},{"id":312825,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1223/coverthb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Clark Fork Basin, Silver Bow Creek, Warm Springs Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.0655517578125,\n 46.97275640318636\n ],\n [\n -113.0712890625,\n 46.81133924039194\n ],\n [\n -112.30224609374999,\n 46.3810438458062\n ],\n [\n -112.0550537109375,\n 46.02366774426006\n ],\n [\n -111.91223144531249,\n 45.75602615586017\n ],\n [\n -111.917724609375,\n 45.3868773482704\n ],\n [\n -112.071533203125,\n 45.182036837015886\n ],\n [\n -113.4283447265625,\n 45.90147732739488\n ],\n [\n -114.2962646484375,\n 46.543749602738565\n ],\n [\n -114.32922363281249,\n 46.991494313050424\n ],\n [\n -114.0655517578125,\n 46.97275640318636\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Ave.
Helena, MT 59601
http://wy-mt.water.usgs.gov/
Knowledge of the magnitude and frequency of low flows in streams, which are flows in a stream during prolonged dry weather, is fundamental for water-supply planning and design; waste-load allocation; reservoir storage design; and maintenance of water quality and quantity for irrigation, recreation, and wildlife conservation. This report presents the results of a statewide study for which regional regression equations were developed for estimating 13 flow-duration curve statistics and 10 low-flow frequency statistics at ungaged stream locations in Minnesota. The 13 flow-duration curve statistics estimated by regression equations include the 0.0001, 0.001, 0.02, 0.05, 0.1, 0.25, 0.50, 0.75, 0.9, 0.95, 0.99, 0.999, and 0.9999 exceedance-probability quantiles. The low-flow frequency statistics include annual and seasonal (spring, summer, fall, winter) 7-day mean low flows, seasonal 30-day mean low flows, and summer 122-day mean low flows for a recurrence interval of 10 years. Estimates of the 13 flow-duration curve statistics and the 10 low-flow frequency statistics are provided for 196 U.S. Geological Survey continuous-record streamgages using streamflow data collected through September 30, 2012.
\nThe study area includes 196 streamgages located within Minnesota and 50 miles beyond the State’s borders in North Dakota, South Dakota, Iowa, and Wisconsin. The study area was divided into five regions that were developed in a previous study using the concept of hydrologic landscape units. Geographic information system software was used to calculate 18 characteristics investigated as potential explanatory variables in regression analyses for each streamgage drainage basin. Trend analyses indicated statistically significant trends in summer 7-day low flows that were not related to precipitation patterns for 19 streamgages. For 16 of these streamgages, the streamflow record was subset using structural change analysis to identify the most recent period of record without a significant trend. The three remaining streamgages with significant trends were excluded from the final analysis because the effective period of record without a significant trend was less than 10 years.
\nBecause several streams in this study have zero flow as their minimum reported flow, weighted left-censored regression was used to analyze the flow data in an unbiased manner, with weights based on the number of years of record. A total of 115 regression equations were developed in this study to calculate flow-duration curve and low-flow frequency statistics for ungaged locations in the study area. In addition, data from 25 pairs of streamgages were used to develop drainage-area ratio equations that can be used to estimate streamflow statistics at ungaged locations on streams that have a streamgage in another location. Streamflow statistics estimated using regional regression and drainage-area ratio equations were compared among regions. For regions A, D, and E, drainagearea ratio equations were more accurate than regional regression equations for flows, but regional regression equations were more accurate for high flows. For region F, regional regression equations were consistently more accurate than drainage-area ratio equations. For region BC, the pattern in accuracies of regional regression and drainage-area ratio equations between low flows and high flows was not consistent.
\nEquations developed in this study apply only to stream locations where flows are not substantially affected by regulation, diversion, or urbanization. All equations presented in this study will be incorporated into StreamStats, a web-based geographic information system tool developed by the U.S. Geological Survey. StreamStats allows users to obtain streamflow statistics, basin characteristics, and other information for user-selected locations on streams through an interactive map.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155170","collaboration":"Prepared in cooperation with the Minnesota Pollution Control Agency","usgsCitation":"Ziegeweid, J.R., Lorenz, D.L., Sanocki, C.A., and Czuba, C.R., 2015, Methods for estimating flow-duration curve and\nlow-flow frequency statistics for ungaged locations on small streams in Minnesota: U.S. Geological Survey Scientific\nInvestigations Report 2015–5170, 23 p., https://dx.doi.org/10.3133/sir20155170.","productDescription":"Report: vi, 23 p.; Appendix","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-046283","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":312848,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5170/coverthb.jpg"},{"id":312849,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5170/sir20155170.pdf","text":"Report","size":"2.13 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5170"},{"id":312850,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5170/downloads/sir20155170_table1-1.xlsx","text":"Table 1-1","size":"89.1 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5170 Appendix 1"}],"country":"United States","state":"Iowa, Minnesota, North Dakota, South Dakota, Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.27294921875,\n 49.023461463214126\n ],\n [\n -95.16357421875,\n 49.023461463214126\n ],\n [\n -95.16357421875,\n 49.439556958940855\n ],\n [\n -94.68017578125,\n 49.38237278700955\n ],\n [\n -94.54833984375,\n 49.081062364320736\n ],\n [\n -94.59228515625,\n 48.80686346108517\n ],\n [\n -94.28466796874999,\n 48.76343113791796\n ],\n [\n -93.8232421875,\n 48.69096039092549\n ],\n [\n -93.62548828125,\n 48.60385760823255\n ],\n [\n -93.3837890625,\n 48.67645370777654\n ],\n [\n -92.900390625,\n 48.73445537176822\n ],\n [\n -92.548828125,\n 48.61838518688487\n ],\n [\n -92.46093749999999,\n 48.472921272487824\n ],\n [\n -92.21923828124999,\n 48.4146186174932\n ],\n [\n -91.86767578124999,\n 48.31242790407178\n ],\n [\n -91.51611328125,\n 48.151428143221224\n ],\n [\n -91.14257812499999,\n 48.22467264956519\n ],\n [\n -90.76904296874999,\n 48.31242790407178\n ],\n [\n -90.63720703125,\n 48.22467264956519\n ],\n [\n -90.439453125,\n 48.180738507303836\n ],\n [\n -90.087890625,\n 48.19538740833338\n ],\n [\n -89.82421875,\n 48.09275716032736\n ],\n [\n -89.56054687499999,\n 48.019324184801185\n ],\n [\n -89.93408203124999,\n 47.84265762816538\n ],\n [\n -90.63720703125,\n 47.60616304386874\n ],\n [\n -91.12060546875,\n 47.32393057095941\n ],\n [\n -91.47216796875,\n 47.12995075666307\n ],\n [\n -91.845703125,\n 46.86019101567027\n ],\n [\n -91.82373046875,\n 46.800059446787316\n ],\n [\n -91.3623046875,\n 46.875213396722685\n ],\n [\n -90.72509765625,\n 47.14489748555398\n ],\n [\n -90.1318359375,\n 47.12995075666307\n ],\n [\n -89.8681640625,\n 47.040182144806664\n ],\n [\n -89.67041015625,\n 46.694667307773095\n ],\n [\n -89.8681640625,\n 46.27103747280261\n ],\n [\n -90.32958984375,\n 46.07323062540838\n ],\n [\n -90.90087890624999,\n 45.69083283645816\n ],\n [\n -91.14257812499999,\n 45.13555516012536\n ],\n [\n -91.1865234375,\n 44.54350521320822\n ],\n [\n -90.966796875,\n 44.008620115415354\n ],\n [\n -90.59326171875,\n 43.37311218382002\n ],\n [\n -90.46142578125,\n 42.98857645832184\n ],\n [\n -90.04394531249999,\n 42.68243539838623\n ],\n [\n -89.84619140625,\n 42.24478535602799\n ],\n [\n -90.68115234375,\n 42.04929263868686\n ],\n [\n -91.69189453125,\n 42.58544425738491\n ],\n [\n -92.04345703125,\n 43.197167282501276\n ],\n [\n -93.40576171875,\n 43.11702412135048\n ],\n [\n -95.361328125,\n 42.98857645832184\n ],\n [\n -96.39404296875,\n 42.87596410238254\n ],\n [\n -96.5478515625,\n 42.68243539838623\n ],\n [\n -97.03125,\n 42.956422511073335\n ],\n [\n -97.18505859374999,\n 43.992814500489914\n ],\n [\n -97.8662109375,\n 45.460130637921004\n ],\n [\n -97.88818359375,\n 46.36209301204985\n ],\n [\n -98.10791015625,\n 47.517200697839414\n ],\n [\n -98.15185546874999,\n 48.73445537176822\n ],\n [\n -97.80029296875,\n 48.936934954094035\n ],\n [\n -97.27294921875,\n 49.023461463214126\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Minnesota Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, Minnesota 55112
http://mn.water.usgs.gov/
Assessing the physical change to shorelines and wetlands is critical for determining the resiliency of wetland systems that protect adjacent habitat and communities. The wetland and back-barrier shorelines of the New Jersey barrier islands were changed by wave action and storm surge from Hurricane Sandy in 2012. The U.S. Geological Survey Coastal and Marine Geology Program is assessing the impact of Hurricane Sandy to understand its historical context and the vulnerability of wetland systems. These assessments require data that document physical changes over time, such as maps, aerial photographs, satellite imagery, and lidar elevation data.
\nThis Data Series Report includes open-ocean shorelines, back-island shorelines, back-island shoreline points, sand polygons, and sand lines for the undeveloped areas of New Jersey barrier islands. These data were extracted from orthoimagery (aerial photography) taken between March 9, 1991, and July 30, 2013. The images used were 0.3–1-meter (m)-resolution U.S. Geological Survey Digital Orthophoto Quarter Quads (DOQQ), U.S. Department of Agriculture National Agriculture Imagery Program (NAIP) images, National Oceanic and Atmospheric Administration images, and New Jersey Geographic Information Network images. The back-island shorelines were hand-digitized at the intersects of the apparent back-island shoreline and transects spaced at 20-m intervals. The open-ocean shorelines were hand-digitized at the approximate still-water level, such as tide level, which was fit through the average position of waves and swash apparent on the beach. Hand-digitizing was done at a scale of approximately 1:2,000. The sand polygons were derived by an image-processing unsupervised classification technique that separates images into classes. The classes were then visually categorized as either sand or not sand. Sand lines were taken from the sand polygons. Also included in this report are 20-m-spaced transect lines and the transect base lines.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds960","usgsCitation":"Guy, K.K., 2015, Back-Island and Open-Ocean Shorelines, and Sand Areas of the Undeveloped Areas of New Jersey Barrier Islands, March 9, 1991, to July 30, 2013. U.S. Geological Survey Data Series","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-065228","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":311110,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0960/coverthb.jpg"},{"id":311111,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0960","text":"Report (HTML)","description":"Data Series 960"}],"country":"United States","state":"New Jersey","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.04510498046875,\n 40.48455955508278\n ],\n [\n -73.99566650390625,\n 40.49709237269567\n ],\n [\n -73.95172119140624,\n 40.40931350359072\n ],\n [\n -74.00115966796875,\n 40.40303919701655\n ],\n [\n -74.04510498046875,\n 40.48455955508278\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.11651611328125,\n 39.926588421909436\n ],\n [\n -74.03961181640625,\n 39.920269337634004\n ],\n [\n -74.0753173828125,\n 39.75154536393759\n ],\n [\n -74.1632080078125,\n 39.76632525654491\n ],\n [\n -74.11651611328125,\n 39.926588421909436\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.22637939453125,\n 39.5146359327835\n ],\n [\n -74.29229736328125,\n 39.552765371831015\n ],\n [\n -74.41864013671875,\n 39.444677580473424\n ],\n [\n -74.31976318359375,\n 39.39375459224348\n ],\n [\n -74.22637939453125,\n 39.5146359327835\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.69879150390625,\n 39.172658670429946\n ],\n [\n -74.66033935546875,\n 39.15136267949032\n ],\n [\n -74.59716796875,\n 39.24288969082635\n ],\n [\n -74.62738037109375,\n 39.264157950942185\n ],\n [\n -74.69879150390625,\n 39.172658670429946\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.8114013671875,\n 39.031986028740086\n ],\n [\n -74.783935546875,\n 39.01064750994083\n ],\n [\n -74.7564697265625,\n 39.036252959636606\n ],\n [\n -74.77844238281249,\n 39.0533181067413\n ],\n [\n -74.8114013671875,\n 39.031986028740086\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.915771484375,\n 38.94659331893374\n ],\n [\n -74.90478515625,\n 38.91881851059804\n ],\n [\n -74.81689453125,\n 38.950865400919994\n ],\n [\n -74.83612060546875,\n 38.97862765746913\n ],\n [\n -74.915771484375,\n 38.94659331893374\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"St. Petersburg Coastal and Marine Science Center
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Identifying plant taxa that honey bees (Apis mellifera) forage upon is of great apicultural interest, but traditional methods are labor intensive and may lack resolution. Here we evaluate a high-throughput genetic barcoding approach to characterize trap-collected pollen from multiple North Dakota apiaries across multiple years. We used the Illumina MiSeq platform to generate sequence scaffolds from non-overlapping 300-bp paired-end sequencing reads of the ribosomal internal transcribed spacers (ITS). Full-length sequence scaffolds represented ~530 bp of ITS sequence after adapter trimming, drawn from the 5’ of ITS1 and the 3’ of ITS2, while skipping the uninformative 5.8S region. Operational taxonomic units (OTUs) were picked from scaffolds clustered at 97% identity, searched by BLAST against the nt database, and given taxonomic assignments using the paired-read lowest common ancestor approach. Taxonomic assignments and quantitative patterns were consistent with known plant distributions, phenology, and observational reports of pollen foraging, but revealed an unexpected contribution from non-crop graminoids and wetland plants. The mean number of plant species assignments per sample was 23.0 (+/- 5.5) and the mean species diversity (effective number of equally abundant species) was 3.3 (+/- 1.2). Bray-Curtis similarities showed good agreement among samples from the same apiary and sampling date. Rarefaction plots indicated that fewer than 50,000 reads are typically needed to characterize pollen samples of this complexity. Our results show that a pre-compiled, curated reference database is not essential for genus-level assignments, but species-level assignments are hindered by database gaps, reference length variation, and probable errors in the taxonomic assignment, requiring post-hoc evaluation. Although the effective per-sample yield achieved using custom MiSeq amplicon primers was less than the machine maximum, primarily due to lower “read2” quality, further protocol optimization and/or a modest reduction in multiplex scale should offset this difficulty. As small quantities of pollen are sufficient for amplification, our approach might be extendable to other questions or species for which large pollen samples are not available.
","language":"English","publisher":"PLoS","publisherLocation":"San Francisco","doi":"10.1371/journal.pone.0145365","usgsCitation":"Cornman, R.S., Otto, C., Iwanowicz, D.D., and Pettis, J.S., 2015, Taxonomic characterization of honey bee (Apis mellifera) pollen foraging based on non-overlapping paired-end sequencing of nuclear ribosomal loci: PLoS ONE, v. 10, no. 12, p. 1-26, https://doi.org/10.1371/journal.pone.0145365.","productDescription":"26 p.","startPage":"1","endPage":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-067288","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":471557,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0145365","text":"Publisher Index Page"},{"id":313041,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.96484375,\n 46.84704298339389\n ],\n [\n -98.96484375,\n 47.44852243794931\n ],\n [\n -97.83599853515625,\n 47.44852243794931\n ],\n [\n -97.83599853515625,\n 46.84704298339389\n ],\n [\n -98.96484375,\n 46.84704298339389\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"12","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-23","publicationStatus":"PW","scienceBaseUri":"56850061e4b0a04ef4933751","contributors":{"authors":[{"text":"Cornman, Robert S. 0000-0001-9511-2192 rcornman@usgs.gov","orcid":"https://orcid.org/0000-0001-9511-2192","contributorId":5356,"corporation":false,"usgs":true,"family":"Cornman","given":"Robert","email":"rcornman@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":583636,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Otto, Clint 0000-0002-7582-3525 cotto@usgs.gov","orcid":"https://orcid.org/0000-0002-7582-3525","contributorId":5426,"corporation":false,"usgs":true,"family":"Otto","given":"Clint","email":"cotto@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":583637,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Iwanowicz, Deborah D. 0000-0002-9613-8594 diwanowicz@usgs.gov","orcid":"https://orcid.org/0000-0002-9613-8594","contributorId":2253,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Deborah","email":"diwanowicz@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":583638,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pettis, Jeffery S","contributorId":150913,"corporation":false,"usgs":false,"family":"Pettis","given":"Jeffery","email":"","middleInitial":"S","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":583639,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70174979,"text":"70174979 - 2015 - An apparatus reconstruction of the conodont Caenodontus serrulatus Behnken 1975","interactions":[],"lastModifiedDate":"2016-07-27T12:30:35","indexId":"70174979","displayToPublicDate":"2015-12-23T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2735,"text":"Micropaleontology","active":true,"publicationSubtype":{"id":10}},"title":"An apparatus reconstruction of the conodont Caenodontus serrulatus Behnken 1975","docAbstract":"The conodont species Caenodontus serrulatus Behnken is a rare coniform element first described in 1975 from Guadalupian strata exposed in the Guadalupe and Delaware Mountains of West Texas. Because it is rare, coniform, and occurs long after most coniform elements supposedly disappeared, it has been hauntingly mysterious. Based on new material containing a varied assemblage of coniform elements recovered from an outcrop of the Hegler Limestone (Guadalupian) in the Patterson Hills, West Texas, it is proposed that Caenodontusis comprised of a 6-7 membrate coniform apparatus and that this apparatus is very similar to the one proposed for the genus Ansella from the Ordovician.
","language":"English","publisher":"Micropaleontology Press","usgsCitation":"Nestell, M.K., and Wardlaw, B.R., 2015, An apparatus reconstruction of the conodont Caenodontus serrulatus Behnken 1975: Micropaleontology, v. v. 61, no. no 4 - 5, p. 293-300.","productDescription":"7 p.","startPage":"293","endPage":"300","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071098","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":325706,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":325705,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.micropress.org.ezproxy.library.wisc.edu/microaccess/micropaleontology"}],"country":"United States","state":"Texas","otherGeospatial":"Guadalupe Mountains National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.95582580566406,\n 31.997012406423654\n ],\n [\n -104.95719909667969,\n 31.98187064456415\n ],\n [\n -104.95719909667969,\n 31.974881296156596\n ],\n [\n -104.95994567871094,\n 31.970803930433096\n ],\n [\n -104.96131896972656,\n 31.959153316146658\n ],\n [\n -105.00251770019531,\n 31.956240431596452\n ],\n [\n -105.01350402832031,\n 31.955657843600374\n ],\n [\n -105.01350402832031,\n 31.946918580249633\n ],\n [\n -105.02792358398436,\n 31.944587969619008\n ],\n [\n -105.03067016601562,\n 31.893299584369487\n ],\n [\n -105.02792358398436,\n 31.875808372704054\n ],\n [\n -105.00595092773438,\n 31.868227816180674\n ],\n [\n -104.99977111816406,\n 31.87056036152958\n ],\n [\n -104.9908447265625,\n 31.85598098460412\n ],\n [\n -104.95788574218749,\n 31.853648070322752\n ],\n [\n -104.95101928710938,\n 31.87172661206501\n ],\n [\n -104.93453979492186,\n 31.868810958052563\n ],\n [\n -104.92973327636719,\n 31.85073184447357\n ],\n [\n -104.92218017578125,\n 31.828565514766165\n ],\n [\n -104.92424011230469,\n 31.808144448024276\n ],\n [\n -104.87136840820312,\n 31.798807599289702\n ],\n [\n -104.83360290527342,\n 31.81572994283835\n ],\n [\n -104.8370361328125,\n 31.85073184447357\n ],\n [\n -104.82536315917967,\n 31.86064663609563\n ],\n [\n -104.80957031249999,\n 31.876974556818304\n ],\n [\n -104.79583740234375,\n 31.88105608497267\n ],\n [\n -104.77935791015625,\n 31.886886525780806\n ],\n [\n -104.75875854492188,\n 31.904375633517787\n ],\n [\n -104.76493835449219,\n 31.92885480180959\n ],\n [\n -104.76356506347655,\n 31.943422642136195\n ],\n [\n -104.73541259765625,\n 31.951579624162896\n ],\n [\n -104.72442626953124,\n 31.974298826428072\n ],\n [\n -104.72511291503906,\n 31.992353668990656\n ],\n [\n -104.72648620605469,\n 31.99992399713997\n ],\n [\n -104.95582580566406,\n 31.997012406423654\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"v. 61","issue":"no 4 - 5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5799db32e4b0589fa1c7e693","contributors":{"authors":[{"text":"Nestell, Merlynd K.","contributorId":68603,"corporation":false,"usgs":false,"family":"Nestell","given":"Merlynd","email":"","middleInitial":"K.","affiliations":[{"id":12734,"text":"University of Texas at Arlington","active":true,"usgs":false}],"preferred":false,"id":643492,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wardlaw, Bruce R. bwardlaw@usgs.gov","contributorId":266,"corporation":false,"usgs":true,"family":"Wardlaw","given":"Bruce","email":"bwardlaw@usgs.gov","middleInitial":"R.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":643491,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70159801,"text":"ds973 - 2015 - Chemical concentrations and instantaneous loads, Green River to the Lower Duwamish Waterway near Seattle, Washington, 2013–15","interactions":[],"lastModifiedDate":"2015-12-28T12:34:29","indexId":"ds973","displayToPublicDate":"2015-12-23T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"973","title":"Chemical concentrations and instantaneous loads, Green River to the Lower Duwamish Waterway near Seattle, Washington, 2013–15","docAbstract":"In November 2013, U.S. Geological Survey streamgaging equipment was installed at a historical water-quality station on the Duwamish River, Washington, within the tidal influence at river kilometer 16.7 (U.S. Geological Survey site 12113390; Duwamish River at Golf Course at Tukwila, WA). Publicly available, real-time continuous data includes river streamflow, stream velocity, and turbidity. Between November 2013 and March 2015, the U.S. Geological Survey collected representative samples of water, suspended sediment, or bed sediment from the streamgaging station during 28 periods of differing flow conditions. Samples were analyzed by Washington-State-accredited laboratories for a large suite of compounds, including metals, dioxins/furans, semivolatile compounds including polycyclic aromatic hydrocarbons, pesticides, butytins, polychlorinated biphenyl (PCB) Aroclors and the 209 PCB congeners, volatile organic compounds, hexavalent chromium, and total and dissolved organic carbon. Metals, PCB congeners, and dioxins/furans were frequently detected in unfiltered-water samples, and concentrations typically increased with increasing suspended-sediment concentrations. Chemical concentrations in suspendedsediment samples were variable between sampling periods. The highest concentrations of many chemicals in suspended sediment were measured during summer and early autumn storm periods.
\nMedian chemical concentrations in suspended-sediment samples were greater than median chemical concentrations in fine bed sediment (less than 62.5 µm) samples, which were greater than median chemical concentrations in paired bulk bed sediment (less than 2 mm) samples. Suspended-sediment concentration, sediment particle-size distribution, and general water-quality parameters were measured concurrent with the chemistry sampling. From this discrete data, combined with the continuous streamflow record, estimates of instantaneous sediment and chemical loads from the Green River to the Lower Duwamish Waterway were calculated. For most compounds, loads were higher during storms than during baseline conditions because of high streamflow and high chemical concentrations. The highest loads occurred during dam releases (periods when stored runoff from a prior storm is released from the Howard Hanson Dam into the upper Green River) because of the high river streamflow and high suspended-sediment concentration, even when chemical concentrations were lower than concentrations measured during storm events.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds973","collaboration":"Prepared in cooperation with the Washington State Department of Ecology","usgsCitation":"Conn, K.E., Black, R.W., Vanderpool-Kimura, A.M., Foreman, J.R., Peterson, N.T., Senter, C.A., and Sissel, S.K., 2015, Chemical concentrations and instantaneous loads, Green River to the Lower Duwamish Waterway near Seattle, Washington, 2013–15: U.S. Geological Survey Data Series 973, 46 p., https://dx.doi.org/10.3133/ds973.","productDescription":"Report: vii, 46 p.; Appendix","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-065963","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":312810,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0973/ds973.pdf","text":"Report","size":"2.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 973 PDF"},{"id":312811,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0973/coverthb.jpg"},{"id":312812,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0973/ds973_appendixa.xlsx","text":"Appendix A","size":"846 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 973 Appendix A XLSX"}],"country":"United States","state":"Washington","otherGeospatial":"Green River, Lower Duwamish Waterway","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.4,\n 47.4\n ],\n [\n -122.4,\n 47.6\n ],\n [\n -122.2,\n 47.6\n ],\n [\n -122.2,\n 47.4\n ],\n [\n -122.4,\n 47.4\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
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http://wa.water.usgs.gov
The hydrogeology of the Owego-Apalachin Elementary School geothermal fields, which penetrate saline water and methane in fractured upper Devonian age bedrock in the Owego Creek valley, south-central New York, was characterized through the analysis of drilling and geophysical logs, water-level monitoring data, and specific-depth water samples. Hydrogeologic insights gained during the study proved beneficial for the design of the geothermal drilling program and protection of the overlying aquifer during construction, and may be useful for the development of future geothermal fields and other energy-related activities, such as drilling for oil and natural gas in similar fractured-bedrock settings.
\nThe southwest geothermal field consists of 204 closed-loop wells that penetrate a major saline water-bearing zone associated with bedding-plane fractures near the middle of an interbedded sandstone and shale interval at depths of 238 to 263 feet below land surface (ft bls). The northeast geothermal field consists of 80 closed-loop wells that penetrate a major saline water-bearing zone associated with bedding-plane fractures near the base of the interbedded sandstone and shale interval at depths of 303 to 323 ft bls.
\nTransmissivity estimates for the major saline water-bearing fractured zones range from 735 to 3,400 feet squared per day. The saline water-bearing zone in the southwest field is hydraulically connected over a horizontal distance of at least 350 feet. The hydraulic connection between subhorizontal, stacked bedding-plane fractures is limited by the number and transmissivity of interspersed higher angle fractures; locally, greater stratigraphic separation results in reduced connectivity to a greater degree than does horizontal distance.
\nThe specific conductance of the saline water from the shallower fractured zone in the southwest field was about 16,000 microsiemens per centimeter at 25 degrees Celsius (μS/cm at 25°C), and that from the fractured zone in the northeast field was about 65,000 μS/cm at 25°C. The saline waters were characterized by a chemical composition similar to that of deep formation brines collected from oil and gas wells in the Appalachian Basin. About 40 percent of the geothermal wells discharged methane gas to land surface during and (or) following drilling. Sandstone beds at depths of 348 to 378 ft bls are the likely source of the methane gas, which was determined to be early thermogenic in origin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155155","usgsCitation":"Williams, J.H., and Kappel, W.M., 2015, Hydrogeology of the Owego-Apalachin Elementary School geothermal fields, Tioga County, New York: U.S. Geological Survey Scientific Investigations Report 2015–5155, 29 p., https://dx.doi.org/10.3133/sir20155155.","productDescription":"Report: vii, 29 p.; 4 Appendixes","numberOfPages":"29","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066669","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":312655,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5155/sir20155155_appendix02.xlsx","text":"Appendix 2","size":"23 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5155","linkHelpText":"Location, construction, and hydrogeologic information for selected boreholes and wells"},{"id":312729,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5155/sir20155155_appendix01.m4v","text":"Appendix 1 (Low Resolution)","size":"5.12 MB","description":"SIR 2015-5155","linkHelpText":"Video of local news report about methane fire during drilling of borehole A9"},{"id":312730,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5155/sir20155155_appendix04.m4v","text":"Appendix 4 (Low Resolution)","size":"35.6 MB","description":"SIR 2015-5155","linkHelpText":"Video of unloading of methane gas and water from borehole A12"},{"id":312654,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5155/sir20155155_appendix01.mp4","text":"Appendix 1 (High Resolution)","size":"10.2 MB","description":"SIR 2015-5155","linkHelpText":"Video of local news report about methane fire during drilling of borehole A9"},{"id":312657,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5155/sir20155155_appendix04.mp4","text":"Appendix 4 (High Resolution)","size":"49.8 MB","description":"SIR 2015-5155","linkHelpText":"Video of unloading of methane gas and water from borehole A12"},{"id":312652,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5155/sir20155155.pdf","text":"Report","size":"7.60 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5155"},{"id":312651,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5155/images/coverthb.jpg"},{"id":312656,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5155/sir20155155_appendix03.xlsx","text":"Appendix 3","size":"15 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5155","linkHelpText":"Field and laboratory chemical analyses from boreholes A9 and Q1"}],"country":"United States","state":"New York","county":"Tioga County","city":"Owego","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-76.1258,42.4107],[-76.123,42.3825],[-76.1267,42.382],[-76.1247,42.3652],[-76.1173,42.3653],[-76.1172,42.3576],[-76.1129,42.3571],[-76.1122,42.348],[-76.1084,42.3476],[-76.1071,42.3376],[-76.1195,42.3375],[-76.1194,42.3275],[-76.1139,42.3276],[-76.1144,42.3185],[-76.1069,42.3181],[-76.1069,42.3094],[-76.1025,42.309],[-76.1031,42.3026],[-76.0981,42.3022],[-76.0993,42.2927],[-76.1073,42.2931],[-76.1079,42.2876],[-76.1017,42.2877],[-76.1023,42.2808],[-76.088,42.2804],[-76.0892,42.275],[-76.0842,42.2746],[-76.0842,42.2664],[-76.0798,42.2659],[-76.0791,42.2587],[-76.0965,42.2595],[-76.0964,42.25],[-76.0909,42.25],[-76.0921,42.2459],[-76.0859,42.2459],[-76.0858,42.2414],[-76.092,42.2414],[-76.0913,42.2337],[-76.0845,42.2341],[-76.0857,42.2282],[-76.082,42.2273],[-76.0801,42.2183],[-76.0862,42.2178],[-76.085,42.2119],[-76.0912,42.2123],[-76.0899,42.2064],[-76.083,42.2069],[-76.0823,42.1928],[-76.0885,42.1928],[-76.0885,42.1869],[-76.1151,42.1858],[-76.1123,42.1509],[-76.106,41.9991],[-76.1165,41.9992],[-76.1467,41.9991],[-76.3826,41.9989],[-76.466,41.9999],[-76.5229,42.0005],[-76.5531,42.0008],[-76.5618,42.0009],[-76.5675,42.0121],[-76.5632,42.0153],[-76.544,42.0536],[-76.5538,42.0885],[-76.5581,42.1239],[-76.5594,42.1312],[-76.5539,42.1312],[-76.5597,42.1507],[-76.5598,42.1557],[-76.5344,42.1568],[-76.5377,42.2504],[-76.5382,42.2817],[-76.4731,42.2808],[-76.4734,42.2631],[-76.417,42.2631],[-76.4153,42.3194],[-76.3507,42.3181],[-76.35,42.3085],[-76.2898,42.308],[-76.2891,42.2962],[-76.25,42.2964],[-76.2514,42.3073],[-76.2497,42.3241],[-76.2473,42.336],[-76.2425,42.3446],[-76.2382,42.3542],[-76.2402,42.3624],[-76.2433,42.3664],[-76.2764,42.3794],[-76.2944,42.3816],[-76.2957,42.3866],[-76.2947,42.4075],[-76.2549,42.4082],[-76.1258,42.4107]]]},\"properties\":{\"name\":\"Tioga\",\"state\":\"NY\"}}]}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180-8349
Federal agencies that oversee land management for much of the Snake Range in eastern Nevada, including the management of Great Basin National Park by the National Park Service, need to understand the potential extent of adverse effects to federally managed lands from nearby groundwater development. As a result, this study was developed (1) to attain a better understanding of aquifers controlling groundwater flow on the eastern side of the southern part of the Snake Range and their connection with aquifers in the valleys, (2) to evaluate the relation between surface water and groundwater along the piedmont slopes, (3) to evaluate sources for Big Springs and Rowland Spring, and (4) to assess groundwater flow from southern Spring Valley into northern Hamlin Valley. The study focused on two areas—the first, a northern area along the east side of Great Basin National Park that included Baker, Lehman, and Snake Creeks, and a second southern area that is the potential source area for Big Springs. Data collected specifically for this study included the following: (1) geologic field mapping; (2) drilling, testing, and water quality sampling from 7 test wells; (3) measuring discharge and water chemistry of selected creeks and springs; (4) measuring streambed hydraulic gradients and seepage rates from 18 shallow piezometers installed into the creeks; and (5) monitoring stream temperature along selected reaches to identify places of groundwater inflow.
\nThe Snake Range was formed by a generally normal-faulted uplift, where late Proterozoic and Cambrian siliciclastic rocks and metamorphic rocks are present at the highest altitudes and younger Paleozoic carbonate rocks are exposed along the flanks. The consolidated rocks are intruded by Jurassic to Tertiary age plutons, which are most common between the Lehman and Snake Creek drainage basins. Older Cenozoic rocks, including Oligocene volcanic rocks and Miocene sedimentary rocks, crop out locally and fill the basins that underlie Snake, Spring, and Hamlin Valleys. Younger Tertiary and Quaternary sedimentary (basin-fill) deposits overlie the older Cenozoic rocks.
\nThe rocks and deposits can be divided into three distinct aquifers. These aquifers include (1) basin-fill aquifers that consist of the permeable parts of the Cenozoic basin fill and some fractured or jointed Cenozoic volcanic rocks, (2) an upper carbonate-rock aquifer that consists of upper Paleozoic carbonate rocks overlying a regionally extensive middle Paleozoic siliciclastic confining unit, and (3) a lower carbonate-rock aquifer that consists of lower Paleozoic carbonate rocks. Secondary openings created by faults, shear zones, fractures, and, in the carbonate rocks, karst solution features, largely determine the water-transmitting properties of the volcanic- and carbonate-rock aquifers. The basin-fill aquifers are composed of a wide variety of rock types and have highly variable hydraulic properties. The three aquifers are stratigraphically and structurally heterogeneous, causing large variations in the ability to store and transmit water. The aquifers are separated by confining units in some areas and are in contact with each other in other areas, yet function as a single, composite aquifer system. Basin-fill aquifers most often overlie or adjoin the lower and upper carbonate-rock aquifers.
\nBaker, Lehman and Snake Creek drainage basins were divided into five hydrologic zones on the basis of climate, geology, and topography. The five zones, from highest to lowest altitudes, are the mountain-upland, karst-limestone, upper-piedmont, lower-piedmont, and valley-lowland zones. The primary hydrologic connection between the mountain-upland and the valley-lowland zones is streamflow. Much of the streamflow from the mountain-upland zone is generated above tree line.
\nGroundwater flow increases in the karst-limestone zone because of increased permeability caused by dissolution, which results in increased streamflow losses. Most of the increased groundwater flow is to springs near faults that form the boundary with the upper-piedmont zone. Thus, groundwater flow from the karst-limestone zone to the upper-piedmont zone was only 10 percent of the combined flow of streams and springs that exit the karst-limestone zone. About 60 percent of the water flowing from Rowland Spring in the Lehman Creek drainage basin was from streamflow losses along Baker Creek. The remaining flow from Rowland Spring comes from local recharge in the karst-limestone zone.
\nIn the upper-piedmont zone, the water table by Baker, Lehman and Snake Creeks was near the water level in the creeks for several hundred feet downstream from the karst-limestone zone. Water levels in piezometers along Snake Creek downstream from its confluence with Spring Creek were far below the streambed, indicating gravity drainage beneath this section of the creek. Estimated vertical hydraulic conductivity along a 3-mile reach of Snake Creek downstream of this confluence was 0.5 foot per day, which was an order of magnitude less than that estimated for Baker and Lehman Creeks. The low vertical hydraulic conductivity in the streambed along the lower reaches of Snake Creek results from chemical precipitation of calcite caused by off-gassing of carbon dioxide derived from springs at the end of the karst-limestone zone.
\nThe younger alluvial deposits thicken rapidly across faults that form the upper boundary of the lower-piedmont zone. The absence of springs or groundwater flow to the creeks upstream of these faults indicates they are not a complete barrier to groundwater flow. The water table was shallow in the valley-lowland zone in the Baker and Lehman Creek drainage basins, whereas the water table was more than 50 feet below land surface in the Snake Creek drainage basin. In contrast to thick basin fill in the valley-lowland zone in the Baker and Lehman Creek drainage basins, fractured and karst limestone underlie basin fill at relatively shallow depths in Snake Creek drainage basin. The underlying limestone acts as a drain for groundwater in the basin fill beneath Snake Creek.
\nA groundwater divide in southern Spring Valley south of Baking Powder Flat separates groundwater flow to the flat from southeastward flow into northern Hamlin Valley. Groundwater flow from southern Spring Valley south of the groundwater divide into northern Hamlin Valley was estimated to range from 6,000 to 11,000 acre-feet per year. This groundwater does not flow to Big Springs in southern Snake Valley; rather, the source of water to Big Springs is groundwater recharge in the Big Spring Wash drainage basin and in nearby smaller drainage basins at the south end of the Snake Range.
\nGroundwater flow from southern Spring Valley continues through the western side of Hamlin Valley before being directed northeast toward the south end of Snake Valley. This flow is constrained by southward-flowing groundwater from Big Spring Wash and northward-flowing groundwater beneath central Hamlin Valley. The redirection to the northeast corresponds to a narrowing of the width of flow in southern Snake Valley caused by a constriction formed by a steeply dipping middle Paleozoic siliciclastic confining unit exposed in the flanks of the mountains and hills on the east side of southern Snake Valley and shallowly buried beneath basin fill in the valley. The narrowing of groundwater flow could be responsible for the large area where groundwater flows to springs or is lost to evapotranspiration between Big Springs in Nevada and Pruess Lake in Utah.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1819","collaboration":"Prepared in cooperation with the National Park Service, Bureau of Land Management, U.S. Fish and Wildlife Service, and U.S. Forest Service","usgsCitation":"Prudic, D.E, Sweetkind, D.S., Jackson, T.R., Dotson, K.E., Plume, R.W., Hatch, C.E., and Halford, K.J. 2015, Evaluating connection of aquifers to springs and streams, Great Basin National Park and vicinity, Nevada: U.S. Geological Survey Professional Paper 1819, 188 p., https://dx.doi.org/10.3133/pp1819.","productDescription":"Report: xxii, 187 p.; Appendixes 1-16","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-034324","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":312322,"rank":16,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1819/pp1819_appendix14.zip","text":"Appendix 14","size":"4.3 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11"},{"id":312321,"rank":15,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1819/pp1819_appendix13.zip","text":"Appendix 13","size":"481 KB","linkFileType":{"id":6,"text":"zip"},"description":"PP 1819 Appendix 13"},{"id":312313,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1819/pp1819_appendix5.zip","text":"Appendix 5","size":"216 KB","linkFileType":{"id":6,"text":"zip"},"description":"PP 1819 Appendix 5"},{"id":312314,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1819/pp1819_appendix6.zip","text":"Appendix 6","size":"29 KB","linkFileType":{"id":6,"text":"zip"},"description":"PP 1819 Appendix 6"}],"country":"United States","state":"Nevada","county":"Lincoln County, White Pine County","otherGeospatial":"Baker Creek, Big Springs, Great Basin National Park, Hamlin Valley, Lehman Creek, Rowland Spring, Snake Range, Spring Valley, Snake 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Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Rd.
Carson City, NV 89701
http://nevada.usgs.gov/water/
Benthic invertebrate communities are monitored because the composition of those communities can effect and be affected by the water quality of an aquatic system. Benthic communities use and sometimes regulate the cycling of essential elements (for example, carbon). Benthic invertebrate taxa may also indicate acutely and chronically stressful environments because they are mostly sessile, accumulate contaminants, and sometimes respond dramatically to oligotrophic as well as eutrophic conditions. Benthic communities can in turn affect water quality by grazing pelagic food resources and increasing the rate of nutrient regeneration through feeding and bioturbating the sediment.
South San Francisco Bay is a system dependent on phytoplankton as the base to the food web. Despite abundant nutrients, south San Francisco Bay has had limited phytoplankton production in the last several decades owning to poor light conditions and high grazing losses from the water column by benthic invertebrates. The south San Francisco Bay achieves a balance of biogeochemical conditions in most springs to accommodate a short phytoplankton bloom. This balance has maintained the phytoplankton in south San Francisco Bay at low biomass levels relative to other high-nutrient urban estuaries. The role that benthic invertebrates play in this balance, in these episodic spring events, and in other seasons within the estuary remains of great interest to water-quality and biological resource managers.
Our primary objective in this study is to quantify current (2014) benthic-community structure and function in the south San Francisco Bay sloughs and to compare those communities temporally over decadal time scales with a unique long-term dataset. The study area (fig. 1) is inclusive of the area south of the Dumbarton Bridge (DB) including Alviso and Guadalupe Sloughs and Coyote Creek.
The following are results highlighted in this report:
NRP staff, National Research Program
U.S. Geological Survey
345 Middlefield Road, MS-435
Menlo Park, CA 94025
http://water.usgs.gov/nrp/
Georges Bank is a shallow submarine bank that lies south of Nova Scotia and east of Cape Cod and bounds the seaward side of the Gulf of Maine. The international boundary between Canada and the United States transects the bank, and the eastern part of the bank (~7500 square kilometres) lies in Canadian territory. This map shows the surficial geology of a part of Georges Bank at a scale of 1:50 000. This map has companion topographic and backscatter strength maps. These companion maps provide a basis for interpreting the origin of seafloor features and the nature of materials that form the seafloor. The maps are based on multibeam-sonar surveys conducted in 1999 and 2000 to map 11,965 square kilometres of the seafloor.
","largerWorkTitle":"Geological Survey of Canada Open File series","language":"English","publisher":"Natural Resources Canada","doi":"10.4095/296975","usgsCitation":"Todd, B., and Valentine, P.C., 2015, Surficial geology and shaded seafloor relief of Georges Bank, Fundian Channel and Northeast Channel, Gulf of Maine, https://doi.org/10.4095/296975.","ipdsId":"IP-065278","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":471558,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.4095/296975","text":"Publisher Index Page"},{"id":337559,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":328897,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.4095/296975"}],"publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58c90127e4b0849ce97abcef","contributors":{"authors":[{"text":"Todd, B.J.","contributorId":120970,"corporation":false,"usgs":false,"family":"Todd","given":"B.J.","email":"","affiliations":[],"preferred":false,"id":649436,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Valentine, Page C. 0000-0002-0485-6266 pvalentine@usgs.gov","orcid":"https://orcid.org/0000-0002-0485-6266","contributorId":1947,"corporation":false,"usgs":true,"family":"Valentine","given":"Page","email":"pvalentine@usgs.gov","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":649435,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70159884,"text":"sir20155122 - 2015 - Estimating natural recharge in San Gorgonio Pass watersheds, California, 1913–2012","interactions":[],"lastModifiedDate":"2019-12-30T14:34:52","indexId":"sir20155122","displayToPublicDate":"2015-12-21T19:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5122","title":"Estimating natural recharge in San Gorgonio Pass watersheds, California, 1913–2012","docAbstract":"A daily precipitation-runoff model was developed to estimate spatially and temporally distributed recharge for groundwater basins in the San Gorgonio Pass area, southern California. The recharge estimates are needed to define transient boundary conditions for a groundwater-flow model being developed to evaluate the effects of pumping and climate on the long-term availability of groundwater. The area defined for estimating recharge is referred to as the San Gorgonio Pass watershed model (SGPWM) and includes three watersheds: San Timoteo Creek, Potrero Creek, and San Gorgonio River. The SGPWM was developed by using the U.S. Geological Survey INFILtration version 3.0 (INFILv3) model code used in previous studies of recharge in the southern California region, including the San Gorgonio Pass area. The SGPWM uses a 150-meter gridded discretization of the area of interest in order to account for spatial variability in climate and watershed characteristics. The high degree of spatial variability in climate and watershed characteristics in the San Gorgonio Pass area is caused, in part, by the high relief and rugged topography of the area.
\nDaily climate data developed from a network of monitoring sites and published average monthly precipitation maps were used to develop the climate inputs for the SGPWM. Geographic Information System (GIS) data defining land surface altitude, vegetation, soils, surficial geology, and land cover were used to define input parameters representing the physical characteristics of the land surface, root zone, and shallow subsurface underlying the root zone. Model parameterization was based on a previous INFILv3 model developed for an area including the upper parts of the San Timoteo Creek and Potrero Creek drainages and the western part of the San Gorgonio River watershed. The previous INFILv3 model was calibrated by using available streamflow records from the model area. The SGPWM uses an updated INFILv3 version to represent shallow groundwater flow better beneath the root zone that contributes to lateral, downslope seepage rather than deep recharge. The SGPWM calibration was tested by using available streamflow records in the San Gorgonio Pass region.
\nThe SGPWM was used to simulate a 100-year water budget, including recharge and runoff, for water years 1913 through 2012. Results indicated that most recharge came from episodic infiltration of surface-water runoff in the larger stream channels. Results also indicated periods of great variability in recharge and runoff in response to variability in precipitation. More recharge was simulated for the area of the groundwater basin underlying the more permeable alluvial fill of the valley floor compared to recharge in the neighboring upland areas of the less permeable mountain blocks. The greater recharge was in response to the episodic streamflow that discharged from the mountain block areas and quickly infiltrated the permeable alluvial fill of the groundwater basin. Although precipitation at the higher altitudes of the mountain block was more than double precipitation at the lower altitudes of the valley floor, recharge for inter-channel areas of the mountain block was limited by the lower permeability bedrock underlying the thin soil cover, and most of the recharge in the mountain block was limited to the main stream channels underlain by alluvial fill.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155122","collaboration":"Prepared in cooperation with the San Gorgonio Pass Water Agency","usgsCitation":"Hevesi, J.A., and Christensen, A.H., 2015, Estimating natural recharge in San Gorgonio Pass watersheds, California, 1913–2012: U.S. Geological Survey Scientific Investigations Report 2015–5122, 74 p. https://dx.doi.org/10.3133/ SIR20155122.","productDescription":"xii, 74 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-054946","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":312622,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5122/sir20155122.pdf","text":"Report","size":"29.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5122"},{"id":312621,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5122/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Gorgonio Pass","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.301025390625,\n 33.43831750748322\n ],\n [\n -116.05682373046875,\n 33.43831750748322\n ],\n [\n -116.05682373046875,\n 34.19135773925218\n ],\n [\n -117.301025390625,\n 34.19135773925218\n ],\n [\n -117.301025390625,\n 33.43831750748322\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, CA 95819
http://ca.water.usgs.gov
Bat mortality rates from white-nose syndrome and wind power development are unprecedented. Cryptic and wide-ranging behaviours of bats make them difficult to survey, and population estimation is often intractable. We advance a model-based framework for making spatially explicit predictions about summertime distributions of bats from capture and acoustic surveys. Motivated by species-energy and life-history theory, our models describe hypotheses about spatio-temporal variation in bat distributions along environmental gradients and life-history attributes, providing a statistical basis for conservation decision-making.
\nOregon and Washington, USA.
\nWe developed Bayesian hierarchical models for 14 bat species from an 8-year monitoring dataset across a ~430,000 km2 study area. Models accounted for imperfect detection and were temporally dynamic. We mapped predicted occurrence probabilities and prediction uncertainties as baselines for assessing future declines.
\nForest cover, snag abundance and cliffs were important predictors for most species. Species occurrence patterns varied along elevation and precipitation gradients, suggesting a potential hump-shaped diversity–productivity relationship. Annual turnover in occurrence was generally low, and occurrence probabilities were stable among most species. We found modest evidence that turnover covaried with the relative riskiness of bat roosting and migration. The fringed myotis (Myotis thysanodes), canyon bat (Parastrellus hesperus) and pallid bat (Antrozous pallidus) were rare; fringed myotis occurrence probabilities declined over the study period. We simulated anticipated declines to demonstrate that mapped occurrence probabilities, updated over time, provide an intuitive way to assess bat conservation status for a broad audience.
\nLandscape keystone structures associated with roosting habitat emerged as regionally important predictors of bat distributions. The challenges of bat monitoring have constrained previous species distribution modelling efforts to temporally static presence-only approaches. Our approach extends to broader spatial and temporal scales than has been possible in the past for bats, making a substantial increase in capacity for bat conservation.
","language":"English","publisher":"Blackwell Science","publisherLocation":"Oxford","doi":"10.1111/ddi.12372","usgsCitation":"Rodhouse, T., Ormsbee, P., Irvine, K.M., Vierling, L.A., Szewczak, J.M., and Vierling, K.T., 2015, Establishing conservation baselines with dynamic distribution models for bat populations facing imminent decline: Diversity and Distributions, v. 21, no. 12, p. 1401-1413, https://doi.org/10.1111/ddi.12372.","startPage":"1401","endPage":"1413","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063534","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":471560,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.12372","text":"Publisher Index Page"},{"id":325981,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","volume":"21","issue":"12","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-21","publicationStatus":"PW","scienceBaseUri":"57a1c42fe4b006cb45552c10","contributors":{"authors":[{"text":"Rodhouse, Thomas J.","contributorId":127378,"corporation":false,"usgs":false,"family":"Rodhouse","given":"Thomas J.","affiliations":[{"id":6924,"text":"National Park Service, Upper Columbia Basin Network","active":true,"usgs":false}],"preferred":false,"id":644350,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ormsbee, Patricia C.","contributorId":127379,"corporation":false,"usgs":false,"family":"Ormsbee","given":"Patricia C.","affiliations":[{"id":6925,"text":"US Forest Service, retired","active":true,"usgs":false}],"preferred":false,"id":644351,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Irvine, Kathryn M. 0000-0002-6426-940X kirvine@usgs.gov","orcid":"https://orcid.org/0000-0002-6426-940X","contributorId":2218,"corporation":false,"usgs":true,"family":"Irvine","given":"Kathryn","email":"kirvine@usgs.gov","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":644349,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vierling, Lee A.","contributorId":169443,"corporation":false,"usgs":false,"family":"Vierling","given":"Lee","email":"","middleInitial":"A.","affiliations":[{"id":6711,"text":"University of Idaho, Moscow ID","active":true,"usgs":false}],"preferred":false,"id":644352,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Szewczak, Joseph M.","contributorId":30127,"corporation":false,"usgs":false,"family":"Szewczak","given":"Joseph","email":"","middleInitial":"M.","affiliations":[{"id":6958,"text":"Department of Biological Sciences, Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":644353,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vierling, Kerri T.","contributorId":140099,"corporation":false,"usgs":false,"family":"Vierling","given":"Kerri","email":"","middleInitial":"T.","affiliations":[{"id":13384,"text":"Department of Fish and Wildlife Sciences, University of Idaho,","active":true,"usgs":false}],"preferred":false,"id":644354,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70159986,"text":"ds975 - 2015 - The U.S. Geological Survey coal quality (COALQUAL) database version 3.0","interactions":[],"lastModifiedDate":"2015-12-21T14:50:46","indexId":"ds975","displayToPublicDate":"2015-12-21T15:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"975","title":"The U.S. Geological Survey coal quality (COALQUAL) database version 3.0","docAbstract":"Since the mid-1970s, the U.S. Geological Survey (USGS) has maintained a coal quality database of national scope named USCHEM, which currently contains data for over 13,000 samples. A subset of the USCHEM database called COALQUAL Version 1.3 was initially published in 1994 and was followed by Version 2.0 in 1997. Version 3.0 of the COALQUAL database represents a major editing effort to resolve some of the DOS software limitations used by earlier versions of the database.
\nBecause of database size limits during the development of COALQUAL Version 1.3, many analyses of individual bench samples were merged into whole coal bed averages. The methodology for making these composite intervals was not consistent. Size limits also restricted the amount of georeferencing information and forced removal of qualifier notations such as \"less than detection limit\" (<) information, which can cause problems when using the data. A review of the original data sheets revealed that COALQUAL Version 2.0 was missing information that was needed for a complete understanding of a coal section. Another important database issue to resolve was the USGS \"remnant moisture\" problem. Prior to 1998, tests for remnant moisture (as-determined moisture in the sample at the time of analysis) were not performed on any USGS major, minor, or trace element coal analyses. Without the remnant moisture, it is impossible to convert the analyses to a usable basis (as-received, dry, etc.). Based on remnant moisture analyses of hundreds of samples of different ranks (and known residual moisture) reported after 1998, it was possible to develop a method to provide reasonable estimates of remnant moisture for older data to make it more useful in COALQUAL Version 3.0. In addition, COALQUAL Version 3.0 is improved by (1) adding qualifiers, including statistical programming to deal with the qualifiers; (2) clarifying the sample compositing problems; and (3) adding associated samples. Version 3.0 of COALQUAL also represents the first attempt to incorporate data verification by mathematically crosschecking certain analytical parameters. Finally, a new database system was designed and implemented to replace the outdated DOS program used in earlier versions of the database.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds975","usgsCitation":"Palmer, C.A., Oman, C.L., Park, A.J., and Luppens, J.A., 2015, The U.S. Geological Survey coal quality (COALQUAL) database version 3.0: U.S. Geological Survey Data Series 975, 43 p. with appendixes, https://dx.doi.org/10.3133/ds975.","productDescription":"Report: v, 50 p.; Database","numberOfPages":"57","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-038492","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":312552,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0975/ds975.pdf","size":"5.95 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 975"},{"id":312553,"rank":3,"type":{"id":9,"text":"Database"},"url":"https://ncrdspublic.er.usgs.gov/coalqual/","text":"COALQUAL Database","description":"DS 975"},{"id":312551,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0975/coverthb.jpg"}],"contact":"Eastern Energy Resources Science Center
U.S. Geological Survey
Mail Stop 913 National Center
12201 Sunrise Valley Drive
Reston, Virginia 20192
Or visit the USGS Eastern Energy Resources Science Center Web site at:
http://energy.usgs.gov/GeneralInfo/
ScienceCenters/Eastern.aspx
Water use, such as withdrawals, wastewater return flows, and interbasin transfers, can alter streamflow regimes, water quality, and the integrity of aquatic habitat and affect the availability of water for human and ecosystem needs. To provide the information needed to determine alteration of streamflows and pond water levels in southeastern Massachusetts, existing groundwater models of the Plymouth-Carver region and western (Sagamore flow lens) and eastern (Monomoy flow lens) Cape Cod were used to delineate subbasins and simulate long-term average and average monthly streamflows and pond levels for a series of water-use conditions. Model simulations were used to determine the extent to which streamflows and pond levels were altered by comparing simulated streamflows and pond levels under predevelopment conditions with streamflows and pond levels under pumping only and pumping with wastewater return flow conditions. The pumping and wastewater return flow rates used in this study are the same as those used in previously published U.S. Geological Survey studies in southeastern Massachusetts and represent the period from 2000 to 2005. Streamflow alteration for the nontidal portions of streams in southeastern Massachusetts was evaluated within and at the downstream outlets of 78 groundwater subbasins delineated for this study. Evaluation of streamflow alteration at subbasin outlets is consistent with the approach used by the U.S. Geological Survey for the topographically derived subbasins in the rest of Massachusetts.
\nThe net effect of pumping and wastewater return flows on streamflows and pond levels varied by location and included no change in areas minimally affected by water use, decreases in areas affected more by pumping than by wastewater return flows, or increases in areas affected more by wastewater return flows than by pumping. Simulated alterations to long-term average streamflows at subbasin outlets in response to pumping with wastewater return flows were within about 10 percent of predevelopment streamflows for most of the subbasins in the study area. Alterations ranged from a decrease (depletion) of 43.9 percent at an unnamed tributary to Salt Pond in the Plymouth-Carver region to an increase (surcharge) of 18.2 percent at an unnamed tributary to the Centerville River on western Cape Cod. In general, the relative effects of pumping and wastewater return flows typically were larger in the subbasins with low streamflows than in the subbasins with high streamflows, and there were more depleted streamflows than surcharged streamflows. Increases in streamflows in response to wastewater return flows were generally largest in subbasins with a high density of septic systems or a centralized wastewater treatment facility. For average monthly conditions, streamflow alteration results were similar spatially to results for long-term average conditions. However, differences in the extent of alteration by month were observed; percentage streamflow depletions in most subbasins typically were greatest during the low-streamflow months of August and October.
\nThe percentages of the total number of ponds affected by pumping with wastewater return flows under long-term average conditions in the modeled areas were 28 percent for the Plymouth-Carver region, 67 percent for western Cape Cod, and 75 percent for eastern Cape Cod. Pond-level alterations ranged from a decrease of 4.6 feet at Great South Pond in the Plymouth Carver region to an increase of 0.9 feet at Wequaquet Lake in western Cape Cod. The magnitudes of monthly alterations to pond water levels were fairly consistent throughout the year.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155168","collaboration":"Prepared in cooperation with the Massachusetts Department of Environmental Protection","usgsCitation":"Carlson, C.S., Walter, D.A., and Barbaro, J.R., 2015, Simulated responses of streams and ponds to groundwater withdrawals and wastewater return flows in southeastern Massachusetts: U.S. Geological Survey Scientific Investigations Report 2015–5168, 60 p., https://dx.doi.org/10.3133/sir20155168.","productDescription":"Report: vii, 60 p.; 2 Tables; 2 Appendixes","numberOfPages":"72","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-065841","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":312500,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5168/sir20155168_appendix2_gis.zip","text":"Appendix 2 - Shapefiles and spreadsheet files","size":"15.8 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2015-5168"},{"id":312497,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5168/coverthb2.jpg"},{"id":312501,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5168/sir20155168_appendix3_gis.zip","text":"Appendix 3 - Shapefiles and spreadsheet files","size":"3.3 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2015-5168"},{"id":312498,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5168/sir20155168.pdf","text":"Report","size":"8.41 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5168"},{"id":312499,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2015/5168/sir20155168_tables3-4.xlsx","text":"Tables 3-4","size":"52 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5168","linkHelpText":"Table 3. Stream identification, landscape characteristics, and Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Or visit our Web site at:
http://newengland.water.usgs.gov
The Ozark aquifer, within the Ozark Plateaus aquifer system (herein referred to as the “Ozark system”), is the primary groundwater source in the Ozark Plateaus physiographic province (herein referred to as the “Ozark Plateaus”) of Arkansas, Kansas, Missouri, and Oklahoma. Groundwater from the Ozark system has historically been an important part of the water resource base, and groundwater availability is a concern in some areas; dependency on the Ozark aquifer as a water supply has caused evolving, localized issues. The construction of a regional potentiometric-surface map of the Ozark aquifer is needed to aid assessment of current and future groundwater use and availability. The regional potentiometric-surface mapping is part of the U.S. Geological Survey (USGS) Groundwater Resources Program initiative (http://water.usgs.gov/ogw/gwrp/activities/regional.html) and the Ozark system groundwater availability project (http://ar.water.usgs.gov/ozarks), which seeks to quantify current groundwater resources, evaluate changes in these resources over time, and provide the information needed to simulate system response to future human-related and environmental stresses.
The Ozark groundwater availability project objectives include assessing (1) growing demands for groundwater and associated declines in groundwater levels as agricultural, industrial, and public supply pumping increases to address needs; (2) regional climate variability and pumping effects on groundwater and surface-water flow paths; (3) effects of a gradual shift to a greater surface-water dependence in some areas; and (4) shale-gas production requiring groundwater and surface water for hydraulic fracturing. Data compiled and used to construct the regional Ozark aquifer potentiometric surface will aid in the assessment of those objectives.
Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
401 Hardin Road
Little Rock, Arkansas 72211–3528
http://ar.water.usgs.gov/
The U.S. Geological Survey estimated volumes of potential additions to oil and gas reserves for the United States by reserve growth in discovered accumulations. These volumes were derived by using a new methodology developed by the U.S. Geological Survey and reviewed by the American Association of Petroleum Geologists Committee on Resource Evaluation. This methodology was used to assess reserve growth in individual accumulations (reservoirs, groups of reservoirs, or fields). Selected, large, well-studied, conventional accumulations in the United States that are estimated to contribute most to reserve growth were assessed using analysis of geology and engineering practices. Potential additions to oil and gas reserves for large, discovered, conventional accumulations outside of the United States due to reserve growth were assessed using the U.S. accumulations as analogs. Potential oil and gas volumes were assumed to be added to proven plus probable reserves.
\nThe U.S. Geological Survey estimated volumes of technically recoverable, conventional petroleum resources resulting from reserve growth for discovered fields outside the United States that have reported in-place oil and gas volumes of 500 million barrels of oil equivalent or greater. The mean volumes of reserve growth were estimated at 665 billion barrels of crude oil; 1,429 trillion cubic feet of natural gas; and 16 billion barrels of natural gas liquids. These volumes constitute a significant portion of the world’s oil and gas resources and represent the potential future growth of current global reserves over time based on better assessment methodology, new technologies, and greater understanding of reservoirs.
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U.S. Geological Survey
Box 25046, MS-939
Denver Federal Center
Denver, CO 80225-0046
http://energy.usgs.gov/