The U.S. Geological Survey, in cooperation with the Alabama Department of Agriculture and Industries, sampled a network of 15 wells for up to 167 pesticides and pesticide degradates from 2009 through 2013 in three areas of high-density row-crop agriculture in Alabama. Eighteen herbicides, 2 fungicides, and 9 degradates were detected in water from the sampled wells. The highest concentration of a detected pesticide was 4.49 micrograms per liter of bentazon in Baldwin County, Alabama, which was well below the lifetime health advisory level of 200 micrograms per liter. None of the measured pesticide concentrations exceeded a human-health benchmark. Insecticides were not detected.
\nRelatively flat land and permeable soils prevalent in each of the three areas facilitate the transport of pesticides through the unsaturated zone into the underlying aquifers. Pesticides and the degradate, deethylatrazine, were more frequently detected in groundwater from wells located in northern Alabama than in southeastern Alabama and Baldwin County, Alabama. Greater amounts of pesticide usage and shallow well depths in northern Alabama likely explain the detection of pesticides in that area. Pesticides were detected in two of the shallowest sampled wells in southeastern Alabama, and the detected pesticides have been extensively used on the crops grown in this area. Total pesticide use among the three areas was lowest in Baldwin County; however, fungicides were detected more often in Baldwin County, which is indicative of peanut crops planted in that area.
\nConcentrations of metolachlor and atrazine have substantially decreased in the northern Alabama wells since 2000. A decline in use of metolachlor and atrazine from a high in the late-1990s and a high in 2004, respectively, in northern Alabama could account for the lower concentrations. Fluometuron use has also declined since 1998, but the relation between time and concentrations differed in the five northern Alabama wells. Fluometuron concentrations in three of the five wells have been decreasing over time, while concentrations in the remaining two wells have been increasing.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155014","collaboration":"Prepared in cooperation with the Alabama Department of Agriculture and Industries","usgsCitation":"Welch, H.L., 2015, Occurrence of pesticides in groundwater underlying areas of high-density row-crop production in Alabama, 2009-2013: U.S. Geological Survey Scientific Investigations Report 2015-5014, Report: iv, 35 p.; 2 Appendices, https://doi.org/10.3133/sir20155014.","productDescription":"Report: iv, 35 p.; 2 Appendices","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2009-01-01","ipdsId":"IP-060255","costCenters":[{"id":105,"text":"Alabama Water Science Center","active":true,"usgs":true}],"links":[{"id":299398,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155014.jpg"},{"id":299395,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5014/"},{"id":299396,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5014/pdf/sir2015-5014.pdf","text":"Report","size":"888 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":299397,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5014/download","text":"Appendix 2","size":"167 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix 2","linkHelpText":"Concentrations of detected compounds in groundwater samples from wells located in areas of high-density row-crop production in Alabama, 2000-2013."}],"country":"United States","state":"Alabama","county":"Baldwin County, Colbert County, Geneva County, Henry County, Houston County, Lauderdale County, Limestone County, Madison County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.53700256347656,\n 30.40471180080158\n ],\n [\n -87.76771545410156,\n 30.39656853856939\n ],\n [\n -87.90435791015625,\n 30.53860787885458\n ],\n [\n -87.89920806884764,\n 30.55132212123368\n ],\n [\n -87.81543731689453,\n 30.593592390615303\n ],\n [\n -87.77938842773438,\n 30.584430469735068\n ],\n [\n -87.73441314697266,\n 30.427065265208352\n ],\n [\n -87.53734588623047,\n 30.42144037217422\n ],\n [\n -87.53700256347656,\n 30.40471180080158\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.63107299804688,\n 34.728069689872285\n ],\n [\n -87.6324462890625,\n 34.69307382947489\n ],\n [\n -87.57888793945312,\n 34.6704879985043\n ],\n [\n -86.8414306640625,\n 34.65919277297455\n ],\n [\n -86.48574829101562,\n 34.820567967282706\n ],\n [\n -86.396484375,\n 34.99062863827382\n ],\n [\n -86.50772094726562,\n 34.99287873327227\n ],\n [\n -86.572265625,\n 34.82282272723702\n ],\n [\n -86.82083129882812,\n 34.728069689872285\n ],\n [\n -87.63107299804688,\n 34.728069689872285\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.37200927734375,\n 31.007628489931207\n ],\n [\n -85.68511962890624,\n 31.065286288898164\n ],\n [\n -85.72288513183594,\n 31.19107061829726\n ],\n [\n -85.39192199707031,\n 31.36946776371185\n ],\n [\n -85.28205871582031,\n 31.371812843961937\n ],\n [\n -85.37200927734375,\n 31.007628489931207\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5523a017e4b027f0aee3d115","contributors":{"authors":[{"text":"Welch, Heather L. 0000-0001-8370-7711 hllott@usgs.gov","orcid":"https://orcid.org/0000-0001-8370-7711","contributorId":552,"corporation":false,"usgs":true,"family":"Welch","given":"Heather","email":"hllott@usgs.gov","middleInitial":"L.","affiliations":[{"id":105,"text":"Alabama Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539455,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70144431,"text":"sir20155038 - 2015 - Potential groundwater recharge for the State of Minnesota using the Soil-Water-Balance model, 1996-2010","interactions":[],"lastModifiedDate":"2015-04-06T15:06:47","indexId":"sir20155038","displayToPublicDate":"2015-04-06T15:00:00","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":"2015-5038","title":"Potential groundwater recharge for the State of Minnesota using the Soil-Water-Balance model, 1996-2010","docAbstract":"Groundwater recharge is one of the most difficult components of a water budget to ascertain, yet is an important boundary condition necessary for the quantification of water resources. In Minnesota, improved estimates of recharge are necessary because approximately 75 percent of drinking water and 90 percent of agricultural irrigation water in Minnesota are supplied from groundwater. The water that is withdrawn must be supplied by some combination of (1) increased recharge, (2) decreased discharge to streams, lakes, and other surface-water bodies, and (3) removal of water that was stored in the system. Recent pressure on groundwater resources has highlighted the need to provide more accurate recharge estimates for various tools that can assess the sustainability of long-term water use. As part of this effort, the U.S. Geological Survey, in cooperation with the Minnesota Pollution Control Agency, used the Soil-Water-Balance model to calculate gridded estimates of potential groundwater recharge across Minnesota for 1996‒2010 at a 1-kilometer (0.621-mile) resolution. The potential groundwater recharge estimates calculated for Minnesota from the Soil-Water Balance model included gridded values (1-kilometer resolution) of annual mean estimates (that is, the means for individual years from 1996 through 2010) and mean annual estimates (that is, the mean for the 15-year period 1996−2010).
\nThe Soil-Water-Balance model uses a modified Thornthwaite-Mather soil-water-balance approach, with components of the soil-water balance calculated on a daily basis. A key advantage of this approach includes the use of commonly available geographic information system data layers that incorporate land cover, soil properties, and daily meteorological data to produce temporally and spatially variable gridded estimates of potential recharge. The Soil-Water-Balance model was calibrated by using a combination of parameter estimation techniques, making manual adjustments of model parameters, and using parameter values from previously published Soil-Water-Balance models. Each calibration simulation compared the potential recharge estimate from the model against base-flow estimates derived from three separate hydrograph separation techniques. A total of 35 Minnesota watersheds were selected for the model calibration.
\nMeteorological data necessary for the model included daily precipitation, minimum daily temperature, and maximum daily temperature. All of the meteorological data were provided by the Daymet dataset, which included daily continuous surfaces of key climatological data. Land-cover data were provided by the 2001 and 2006 National Land Cover Database: the 2001 classification was used from 1994 through 2003, and the 2006 classification was used from 2004 through 2010. Soil data used in the model included hydrologic soils group and the available soil-water capacity. These soil data were obtained from the Natural Resources Conservation Service Soil Survey Geographic (SSURGO) database and the State Soil Geographic (STATSGO) database.
\nThe statewide mean annual potential recharge rate from 1996–2010 was 4.9 inches per year. Potential recharge estimates increased from west to east across Minnesota. The mean annual potential recharge estimates across Minnesota at a 1-km resolution for the overall simulation period (1996–2010) ranged from less than 0.1 to 17.8 inches per year. Some of the lowest potential recharge rates for the simulation period were in the Red River of the North Basin of northwestern Minnesota, and generally were between 1.0 and 1.5 inches per year. The highest potential recharge rates were in northeastern Minnesota and the Anoka Sand Plain in central Minnesota. Eighty-eight percent of the potential recharge rates (by grid cell) were between 2 and 8 inches per year from 1996–2010. Only about 3 percent of all the potential recharge estimates (by grid cell) were less than 2 inches per year, and 9 percent of estimates were greater than 8 inches per year.
\nOn an annual basis, however, potential recharge rates were as high as 27.2 inches per year. The highest annual mean recharge estimate across the State was for 2010, and the lowest mean recharge estimate was for 2003. Although precipitation variability partially explained the annual differences in potential recharge estimates, precipitation alone did not account for these differences, and other factors such as antecedent moisture conditions likely were important. Also, because precipitation gradients across the State can vary from year to year, the dominant land-cover class and hydrologic soil group combinations for a particular region had a large effect on the resulting potential recharge value. During 1996–2010, April had the greatest monthly mean potential recharge compared to all other months, accounting for a mean of 30 percent of annual potential recharge in this single month.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155038","collaboration":"Prepared in cooperation with the Minnesota Pollution Control Agency","usgsCitation":"Smith, E.A., and Westenbroek, S.M., 2015, Potential groundwater recharge for the State of Minnesota using the Soil-Water-Balance model, 1996-2010: U.S. Geological Survey Scientific Investigations Report 2015-5038, vii, 85 p., https://doi.org/10.3133/sir20155038.","productDescription":"vii, 85 p.","startPage":"85","numberOfPages":"98","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1996-01-01","temporalEnd":"2010-12-31","ipdsId":"IP-034584","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":299402,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155038.jpg"},{"id":299399,"type":{"id":15,"text":"Index 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,{"id":70143271,"text":"sim3322 - 2015 - Using satellite images to monitor glacial-lake outburst floods: Lago Cachet Dos drainage, Chile","interactions":[],"lastModifiedDate":"2015-04-06T13:00:00","indexId":"sim3322","displayToPublicDate":"2015-04-06T12:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3322","title":"Using satellite images to monitor glacial-lake outburst floods: Lago Cachet Dos drainage, Chile","docAbstract":"The U.S. Geological Survey (USGS) is monitoring and analyzing glacial-lake outburst floods (GLOFs) in the Colonia valley in the Patagonia region of southern Chile. A GLOF is a type of flood that occurs when water impounded by a glacier or a glacial moraine is released catastrophically. In the Colonia valley, GLOFs originating from Lago Cachet Dos, which is dammed by the Colonia Glacier, have recurred periodically since 2008. The water discharged during these GLOFs flows under or through the Colonia Glacier, into Lago Colonia and then the Río Colonia, and finally into the Río Baker—Chile's largest river in terms of volume of water.
\nThis report presents a GeoEye-1 image collected December 1, 2011 and a WorldView-2 image collected September 27, 2013. The 2011 image shows Lago Cachet Dos when the water level was near its maximum extent. The 2013 image shows the drained lake four days after a GLOF event. The images were used to delineate the differences in water surface area prior to, and immediately following, a GLOF event. The imagery shown here highlights the dramatic changes that typically occur during GLOFs from Lago Cachet Dos. The lake area decreased from 4.84 km2 in 2011 (pre-GLOF) to only 0.30 km2 in September 2013 (post-GLOF). The water surface lowered approximately 90 m between the pre- and post-GLOF satellite images, yielding a change in volume of approximately 217,000,000 m3; this value is similar to previous estimates (about 200 million m3) of the volume of flood water that flowed down the Río Colonia during some previous GLOFs.
\nDuring 2008–2013, 14 GLOFs were released from Lago Cachet Dos and created environmental and safety concerns for downstream residents and to infrastructure. If GLOFs and the consequent headward erosion continue, the moraine that creates Lago Cachet Uno could be destabilized and breached, and the two lakes could merge. If the two lakes become connected, the volume of future GLOFs likely would be greater and thus cause longer and (or) more extensive flooding downstream. Additional GLOFs from Lago Cachet Dos are expected in the future, and continued environmental monitoring could provide an early warning system as well as scientific information that could increase our understanding of GLOFs and their consequences. GLOFs occur in glaciated areas around the world and remote sensing technologies can allow researchers to better understand—and potentially predict—future GLOF events.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3322","usgsCitation":"Friesen, B.A., Cole, C.J., Nimick, D.A., Wilson, E.M., Fahey, M., McGrath, D.J., and Leidich, J., 2015, Using satellite images to monitor glacial-lake outburst floods: Lago Cachet Dos drainage, Chile: U.S. Geological Survey Scientific Investigations Map 3322, 44.17 x 41.0 inches, https://doi.org/10.3133/sim3322.","productDescription":"44.17 x 41.0 inches","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-053416","costCenters":[{"id":573,"text":"Special Applications Science Center","active":true,"usgs":true}],"links":[{"id":299392,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3322.jpg"},{"id":299390,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3322/"},{"id":299391,"rank":2,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3322/pdf/sim3322.pdf","text":"Map 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,{"id":70145260,"text":"70145260 - 2015 - Conceptual models of the formation of acid-rock drainage at road cuts in Tennessee","interactions":[],"lastModifiedDate":"2015-11-23T15:30:52","indexId":"70145260","displayToPublicDate":"2015-04-03T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":18,"text":"Abstract or summary"},"title":"Conceptual models of the formation of acid-rock drainage at road cuts in Tennessee","docAbstract":"Pyrite and other minerals containing sulfur and trace metals occur in several rock formations throughout Middle and East Tennessee. Pyrite (FeS2) weathers in the presence of oxygen and water to form iron hydroxides and sulfuric acid. The weathering and interaction of the acid on the rocks and other minerals at road cuts can result in drainage with low pH (< 4) and high concentrations of trace metals. Acid-rock drainage can cause environmental problems and damage transportation infrastructure. The formation and remediation of acid-drainage from roads cuts has not been researched as thoroughly as acid-mine drainage. The U.S Geological Survey, in cooperation with the Tennessee Department of Transportation, is conducting an investigation to better understand the geologic, hydrologic, and biogeochemical factors that control acid formation at road cuts. Road cuts with the potential for acid-rock drainage were identifed and evaluated in Middle and East Tennessee. The pyrite-bearing formations evaluated were the Chattanooga Shale (Devonian black shale), the Fentress Formation (coal-bearing), and the Precambrian Anakeesta Formation and similar Precambrian rocks. Conceptual models of the formation and transport of acid-rock drainage (ARD) from road cuts were developed based on the results of a literature review, site reconnaissance, and the initial rock and water sampling. The formation of ARD requires a combination of hydrologic, geochemical, and microbial interactions which affect drainage from the site, acidity of the water, and trace metal concentrations. The basic modes of ARD formation from road cuts are; 1 - seeps and springs from pyrite-bearing formations and 2 - runoff over the face of a road cut in a pyrite-bearing formation. Depending on site conditions at road cuts, the basic modes of ARD formation can be altered and the additional modes of ARD formation are; 3 - runoff over and through piles of pyrite-bearing material, either from construction or breakdown material weathered from shale, and 4 - the deposition of secondary-sulfate minerals can store trace metals and, during rainfall, result in increased acidity and higher concentrations of trace metals in storm runoff. Understanding the factors that control ARD formation and transport are key to addressing the problems associated with the movement of ARD from the road cuts to the environment. The investigation will provide the Tennessee Department of Transportation with a regional characterization of ARD and provide insights into the geochemical and biochemical attributes for the control and remediation of ARD from road cuts.
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Numerous changes to conservation actions (eg facilitated ecological transitions, managed relocations, or increased corridor development) have been recommended, but some institutional restructuring within organizations may also be needed. Here we discuss the capacity of conservation organizations to adapt to changing environmental conditions, focusing primarily on public agencies and nonprofits active in land protection and management in the US. After first reviewing how these organizations anticipate and detect impacts affecting target species and ecosystems, we then discuss whether they are sufficiently flexible to prepare and respond by reallocating funding, staff, or other resources. We raise new hypotheses about how the configuration of different organizations enables them to protect particular conservation targets and manage for particular biophysical changes that require coordinated management actions over different spatial and temporal scales. Finally, we provide a discussion resource to help conservation organizations assess their capacity to adapt.
","language":"English","publisher":"Ecological Society of America","publisherLocation":"Washington, D.C.","doi":"10.1890/130352","usgsCitation":"Armsworth, P.R., Larson, E.R., Jackson, S.T., Sax, D.F., Simonin, P.W., Blossey, B., Green, N., Lester, L., Klein, M.L., Ricketts, T.H., Runge, M.C., and Shaw, M.R., 2015, Are conservation organizations configured for effective adaptation to global change?: Frontiers in Ecology and the Environment, v. 13, no. 3, p. 163-169, https://doi.org/10.1890/130352.","startPage":"163","endPage":"169","numberOfPages":"7","ipdsId":"IP-057333","costCenters":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"links":[{"id":329514,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57ffdf00e4b0824b2d179cfc","contributors":{"authors":[{"text":"Armsworth, Paul R.","contributorId":175280,"corporation":false,"usgs":false,"family":"Armsworth","given":"Paul","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":650736,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Larson, Eric R.","contributorId":175281,"corporation":false,"usgs":false,"family":"Larson","given":"Eric","email":"","middleInitial":"R.","affiliations":[{"id":16989,"text":"University of Tennessee, Knoxville, TN","active":true,"usgs":false}],"preferred":false,"id":650737,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jackson, Stephen T. 0000-0002-1487-4652 stjackson@usgs.gov","orcid":"https://orcid.org/0000-0002-1487-4652","contributorId":344,"corporation":false,"usgs":true,"family":"Jackson","given":"Stephen","email":"stjackson@usgs.gov","middleInitial":"T.","affiliations":[{"id":560,"text":"South Central Climate Science Center","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":650670,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sax, Dov F.","contributorId":175300,"corporation":false,"usgs":false,"family":"Sax","given":"Dov","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":650738,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Simonin, Paul W.","contributorId":171499,"corporation":false,"usgs":false,"family":"Simonin","given":"Paul","email":"","middleInitial":"W.","affiliations":[{"id":18160,"text":"Rubenstein School of Environment and Natural Resources, University of Vermont","active":true,"usgs":false}],"preferred":false,"id":650739,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Blossey, Bernd","contributorId":175301,"corporation":false,"usgs":false,"family":"Blossey","given":"Bernd","email":"","affiliations":[],"preferred":false,"id":650740,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Green, Nancy","contributorId":147691,"corporation":false,"usgs":false,"family":"Green","given":"Nancy","email":"","affiliations":[{"id":16902,"text":"U.S. Fish and Wildlife Service, Ecological Services Program, Washington, D.C., 20240, USA","active":true,"usgs":false}],"preferred":false,"id":650741,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Klein, Mary L.","contributorId":175302,"corporation":false,"usgs":false,"family":"Klein","given":"Mary","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":650742,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lester, Liza","contributorId":175303,"corporation":false,"usgs":false,"family":"Lester","given":"Liza","email":"","affiliations":[],"preferred":false,"id":650743,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ricketts, Taylor H.","contributorId":175304,"corporation":false,"usgs":false,"family":"Ricketts","given":"Taylor","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":650744,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":650671,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Shaw, M. Rebecca","contributorId":175305,"corporation":false,"usgs":false,"family":"Shaw","given":"M.","email":"","middleInitial":"Rebecca","affiliations":[],"preferred":false,"id":650745,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70142541,"text":"sir20155042 - 2015 - Multilevel groundwater monitoring of hydraulic head and temperature in the eastern Snake River Plain aquifer, Idaho National Laboratory, Idaho, 2011-13","interactions":[],"lastModifiedDate":"2015-04-02T16:56:44","indexId":"sir20155042","displayToPublicDate":"2015-04-02T17:45:00","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":"2015-5042","title":"Multilevel groundwater monitoring of hydraulic head and temperature in the eastern Snake River Plain aquifer, Idaho National Laboratory, Idaho, 2011-13","docAbstract":"From 2011 to 2013, the U.S. Geological Survey’s Idaho National Laboratory (INL) Project Office, in cooperation with the U.S. Department of Energy, collected depth-discrete measurements of fluid pressure and temperature in 11 boreholes located in the eastern Snake River Plain aquifer. Each borehole was instrumented with a multilevel monitoring system (MLMS) consisting of a series of valved measurement ports, packer bladders, casing segments, and couplers.
\nMultilevel monitoring at the INL has been ongoing since 2006 and this report summarizes data collected from 2011 to 2013 in 11 multilevel monitoring wells. Hydraulic head (head) and groundwater temperature data were collected from 11 multilevel monitoring wells, including 177 hydraulically isolated depth intervals from 448.0 to 1,377.6 feet below land surface. One port (port 3) within borehole USGS 134 was not monitored because of a valve failure.
\nHead and temperature profiles reveal unique patterns for vertical examination of the aquifer’s complex basalt and sediment stratigraphy, proximity to aquifer recharge and discharge, and groundwater flow. These features contribute to some of the localized variability even though the general profile shape remained consistent over the period of record. Twenty-two major head inflections were described for 9 of 11 MLMS boreholes and almost always coincided with low‑permeability sediment layers and occasionally thick layers of dense basalt. However, the presence of a sediment layer or dense basalt layer was insufficient for identifying the location of a major head change within a borehole without knowing the true areal extent and relative transmissivity of the lithologic unit. Temperature profiles for boreholes completed within the Big Lost Trough indicate linear conductive trends; whereas, temperature profiles for boreholes completed within volcanic rift zones and near the southern boundary of the Idaho National Laboratory, indicate mostly convective heat transfer. Select boreholes along the southern boundary show a temperature reversal and cooler water deeper in the aquifer resulting from the vertical movement of groundwater.
\nVertical head and temperature change were quantified for each of the 11 multilevel monitoring systems. Vertical head gradients defined for the major inflections in the head profiles were as high as 2.9 feet per foot. In general, fractured basalt zones displayed relatively small vertical head differences and show a high occurrence within volcanic rift zones. Poor connectivity between fractures and higher vertical gradients were generally attributed to sediment layers and layers of dense basalt, or both. Groundwater temperatures in all boreholes ranged from 10.8 to 16.3 °C.
\nNormalized mean head values were analyzed for all 11 multilevel monitoring wells for the period of record (2007–13). The mean head values suggest a moderately positive correlation among all boreholes and generally reflect regional fluctuations in water levels in response to seasonal climatic changes. Boreholes within volcanic rift zones and near the southern boundary (USGS 103, USGS 105, USGS 108, USGS 132, USGS 135, USGS 137A) display a temporal correlation that is strongly positive. Boreholes in the Big Lost Trough display some variations in temporal correlations that may result from proximity to the mountain front to the northwest and episodic flow in the Big Lost River drainage system. For example, during June 2012, boreholes MIDDLE 2050A and MIDDLE 2051 showed head buildup within the upper zones when compared to the June 2010 profile event, which correlates to years when surface water was reported for the Big Lost River several months preceding the measurement period. With the exception of borehole USGS 134, temporal correlation between MLMS wells completed within the Big Lost Trough is generally positive. Temporal correlation for borehole USGS 134 shows the least agreement with other MLMS boreholes located within the Big Lost Trough; however, borehole USGS 134 is close to the mountain front where tributary valley subsurface inflow is suspected.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155042","collaboration":"Prepared in cooperation with the U.S. Department of Energy","usgsCitation":"Twining, B.V., and Fisher, J.C., 2015, Multilevel groundwater monitoring of hydraulic head and temperature in the eastern Snake River Plain aquifer, Idaho National Laboratory, Idaho, 2011-13: U.S. Geological Survey Scientific Investigations Report 2015-5042, Report: vii, 49 p.; 8 Appendices, https://doi.org/10.3133/sir20155042.","productDescription":"Report: vii, 49 p.; 8 Appendices","numberOfPages":"62","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2011-01-01","temporalEnd":"2013-12-31","ipdsId":"IP-056607","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":299324,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155042.jpg"},{"id":299323,"rank":10,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5042/pdf/sir20155042_AppH.pdf","text":"Appendix H","size":"161 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":299314,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5042/"},{"id":299315,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5042/pdf/sir2015-5042.pdf","size":"4.1 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":299316,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5042/pdf/sir20155042_AppA.pdf","text":"Appendix A","size":"98 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":299317,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5042/pdf/sir20155042_AppB.pdf","text":"Appendix B","size":"202 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":299318,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5042/pdf/sir20155042_AppC.pdf","text":"Appendix C","size":"125 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":299319,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5042/pdf/sir20155042_AppD.pdf","text":"Appendix D","size":"109 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":299320,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5042/pdf/sir20155042_AppE.pdf","text":"Appendix E","size":"592 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":299321,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5042/pdf/sir20155042_AppF.pdf","text":"Appendix F","size":"103 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":299322,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5042/pdf/sir20155042_AppG.pdf","text":"Appendix G","size":"148 KB","linkFileType":{"id":1,"text":"pdf"}}],"scale":"24000","projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1927","country":"United States","state":"Idaho","otherGeospatial":"Eastern Snake River Plain aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.104248046875,\n 43.52664646047308\n ],\n [\n -113.104248046875,\n 43.880077621969065\n ],\n [\n -112.61123657226562,\n 43.880077621969065\n ],\n [\n -112.61123657226562,\n 43.52664646047308\n ],\n [\n -113.104248046875,\n 43.52664646047308\n ]\n ]\n ]\n }\n }\n ]\n}","publicComments":"DOE/ID-22235","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"551e5a1fe4b027f0aee3b87d","contributors":{"authors":[{"text":"Twining, Brian V. 0000-0003-1321-4721 btwining@usgs.gov","orcid":"https://orcid.org/0000-0003-1321-4721","contributorId":2387,"corporation":false,"usgs":true,"family":"Twining","given":"Brian","email":"btwining@usgs.gov","middleInitial":"V.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":543938,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fisher, Jason C. 0000-0001-9032-8912 jfisher@usgs.gov","orcid":"https://orcid.org/0000-0001-9032-8912","contributorId":2523,"corporation":false,"usgs":true,"family":"Fisher","given":"Jason","email":"jfisher@usgs.gov","middleInitial":"C.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":543939,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70142609,"text":"ofr20151044 - 2015 - Mass-movement deposits in the lacustrine Eocene Green River Formation, Piceance Basin, western Colorado","interactions":[],"lastModifiedDate":"2015-04-02T11:21:47","indexId":"ofr20151044","displayToPublicDate":"2015-04-02T12:15:00","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":"2015-1044","title":"Mass-movement deposits in the lacustrine Eocene Green River Formation, Piceance Basin, western Colorado","docAbstract":"The Eocene Green River Formation was deposited in two large Eocene saline lakes, Lake Uinta in the Uinta and Piceance Basins and Lake Gosiute in the Greater Green River Basin. Here we will discuss mass-movement deposits in just the Piceance Basin part of Lake Uinta.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151044","usgsCitation":"Johnson, R.C., Birdwell, J.E., Brownfield, M.E., and Mercier, T.J., 2015, Mass-movement deposits in the lacustrine Eocene Green River Formation, Piceance Basin, western Colorado: U.S. Geological Survey Open-File Report 2015-1044, 42 p., https://doi.org/10.3133/ofr20151044.","productDescription":"42 p.","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059898","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":299310,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151044.jpg"},{"id":299308,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1044/"},{"id":299309,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1044/pdf/ofr2015-1044.pdf","size":"30.2 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Colorado","otherGeospatial":"Eocene Green River Formation, Piceance Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.819580078125,\n 39.2832938689385\n ],\n [\n -108.819580078125,\n 40.30466538259176\n ],\n [\n -107.720947265625,\n 40.30466538259176\n ],\n [\n -107.720947265625,\n 39.2832938689385\n ],\n [\n -108.819580078125,\n 39.2832938689385\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"551e5a1fe4b027f0aee3b87b","contributors":{"authors":[{"text":"Johnson, Ronald C. 0000-0002-6197-5165 rcjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-6197-5165","contributorId":1550,"corporation":false,"usgs":true,"family":"Johnson","given":"Ronald","email":"rcjohnson@usgs.gov","middleInitial":"C.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":543917,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":543918,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brownfield, Michael E. 0000-0003-3633-1138 mbrownfield@usgs.gov","orcid":"https://orcid.org/0000-0003-3633-1138","contributorId":1548,"corporation":false,"usgs":true,"family":"Brownfield","given":"Michael","email":"mbrownfield@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":543919,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mercier, Tracey J. 0000-0002-8232-525X tmercier@usgs.gov","orcid":"https://orcid.org/0000-0002-8232-525X","contributorId":2847,"corporation":false,"usgs":true,"family":"Mercier","given":"Tracey","email":"tmercier@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":543920,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70144294,"text":"ofr20151058 - 2015 - An evaluation of the accuracy of modeled and computed streamflow time-series data for the Ohio River at Hannibal Lock and Dam and at a location upstream from Sardis, Ohio","interactions":[],"lastModifiedDate":"2015-04-09T08:31:36","indexId":"ofr20151058","displayToPublicDate":"2015-04-02T11:00:00","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":"2015-1058","title":"An evaluation of the accuracy of modeled and computed streamflow time-series data for the Ohio River at Hannibal Lock and Dam and at a location upstream from Sardis, Ohio","docAbstract":"Between July 2013 and June 2014, the U.S. Geological Survey (USGS) made 10 streamflow measurements on the Ohio River about 1.5 miles (mi) downstream from the Hannibal Lock and Dam (near Hannibal, Ohio) and 11 streamflow measurements near the USGS Sardis gage (station number 03114306) located approximately 2.4 mi upstream from Sardis, Ohio. The measurement results were used to assess the accuracy of modeled or computed instantaneous streamflow time series created and supplied by the USGS, U.S. Army Corps of Engineers (USACE), and National Weather Service (NWS) for the Ohio River at Hannibal Lock and Dam and (or) at the USGS streamgage. Hydraulic or hydrologic models were used to create the modeled time series; index-velocity methods or gate-opening ratings coupled with hydropower operation data were used to create the computed time series. The time step of the various instantaneous streamflow time series ranged from 15 minutes to 24 hours (once-daily values at 12:00 Coordinated Universal Time [UTC]). The 15-minute time-series data, computed by the USGS for the Sardis gage, also were downsampled to 1-hour and 24-hour time steps to permit more direct comparisons with other streamflow time series.
\nTo facilitate comparisons between measurement results and time-series data, streamflows corresponding to the times of the streamflow measurements were computed from the time-series data by time-based linear interpolation. Prior to doing interpolations, measurement times for the Hannibal Lock and Dam location were adjusted for traveltime to account for the fact that the streamflow measurements were made about 1.5 mi downstream from the location corresponding to the modeled/computed time-series data. Measured and interpolated streamflows were tabulated along with residuals (the difference between measured and interpolated streamflows) and selected summary statistics.
\nOverall, streamflows interpolated from the USGS computed 15-minute time-series data (hereafter referred to as the USGS 15-minute time-series data) had the smallest root-mean-square error (RMSE) (3,939 cubic feet per second [ft3/s]) and the second smallest mean absolute residual (2,636 ft3/s), whereas streamflows interpolated from the USACE 12 UTC time series had the largest RMSE (14,590 ft3/s) and the largest mean absolute residual (10,800 ft3/s). The larger RMSEs for streamflows interpolated from the USACE 12 UTC time series likely resulted in part from the coarser time step of that time series. Streamflows interpolated from the USGS downsampled 1-hour time series had the second smallest RMSE (4,025 ft3/s) and the smallest mean absolute residual (2,600 ft3/s). Somewhat surprisingly, streamflows interpolated from the NWS 6-hour model time series had the third smallest RMSE (4,483 ft3/s) and mean absolute residual (4,050 ft3/s) in spite of being determined from a time series with a coarser time step than the USACE 1-hour modeled and computed time series.
\nMeasured streamflows at the Sardis gage and at the Hannibal Lock and Dam measurement location were plotted versus residuals (expressed as a percentage of the measured streamflows) of corresponding interpolated time-series streamflow values. Results for each of the time series exhibited some anomaly, possibly indicating the need and (or) potential for improvement in the streamflow computational/modeling processes.
\nStreamflow hydrographs were plotted for modeled/computed time series for the Ohio River near the USGS Sardis gage and the Ohio River at the Hannibal Lock and Dam. In general, the time series at these two locations compared well. Some notable differences include the exclusive presence of short periods of negative streamflows in the USGS 15-minute time-series data for the gage on the Ohio River above Sardis, Ohio, and the occurrence of several peak streamflows in the USACE gate/hydropower time series for the Hannibal Lock and Dam that were appreciably larger than corresponding peaks in the other time series, including those modeled/computed for the downstream Sardis gage
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151058","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Koltun, G., 2015, An evaluation of the accuracy of modeled and computed streamflow time-series data for the Ohio River at Hannibal Lock and Dam and at a location upstream from Sardis, Ohio: U.S. Geological Survey Open-File Report 2015-1058, viii, 23 p., https://doi.org/10.3133/ofr20151058.","productDescription":"viii, 23 p.","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-063449","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":299300,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151058.jpg"},{"id":299296,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1058/"},{"id":299297,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1058/pdf/ofr2015-1058.pdf","text":"Report","size":"1.20 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Ohio","otherGeospatial":"Ohio River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.96099853515624,\n 39.57817336212527\n ],\n [\n -80.96099853515624,\n 39.68182601089365\n ],\n [\n -80.82092285156249,\n 39.68182601089365\n ],\n [\n -80.82092285156249,\n 39.57817336212527\n ],\n [\n -80.96099853515624,\n 39.57817336212527\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"551e5a1be4b027f0aee3b86b","contributors":{"authors":[{"text":"Koltun, G. F. 0000-0003-0255-2960 gfkoltun@usgs.gov","orcid":"https://orcid.org/0000-0003-0255-2960","contributorId":1852,"corporation":false,"usgs":true,"family":"Koltun","given":"G. F.","email":"gfkoltun@usgs.gov","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":false,"id":543454,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70144432,"text":"70144432 - 2015 - Do management actions to restore rare habitat benefit native fish conservation? Distribution of juvenile native fish among shoreline habitats of the Colorado River","interactions":[],"lastModifiedDate":"2015-12-07T10:14:29","indexId":"70144432","displayToPublicDate":"2015-04-02T10:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Do management actions to restore rare habitat benefit native fish conservation? Distribution of juvenile native fish among shoreline habitats of the Colorado River","docAbstract":"Many management actions in aquatic ecosystems are directed at restoring or improving specific habitats to benefit fish populations. In the Grand Canyon reach of the Colorado River, experimental flow operations as part of the Glen Canyon Dam Adaptive Management Program have been designed to restore sandbars and associated backwater habitats. Backwaters can have warmer water temperatures than other habitats, and native fish, including the federally endangered humpback chub Gila cypha, are frequently observed in backwaters, leading to a common perception that this habitat is critical for juvenile native fish conservation. However, it is unknown how fish densities in backwaters compare with that in other habitats or what proportion of juvenile fish populations reside in backwaters. Here, we develop and fit multi-species hierarchical models to estimate habitat-specific abundances and densities of juvenile humpback chub, bluehead suckerCatostomus discobolus, flannelmouth sucker Catostomus latipinnis and speckled dace Rhinichthys osculus in a portion of the Colorado River. Densities of all four native fish were greatest in backwater habitats in 2009 and 2010. However, backwaters are rare and ephemeral habitats, so they contain only a small portion of the overall population. For example, the total abundance of juvenile humpback chub in this study was much higher in talus than in backwater habitats. Moreover, when we extrapolated relative densities based on estimates of backwater prevalence directly after a controlled flood, the majority of juvenile humpback chub were still found outside of backwaters. This suggests that the role of controlled floods in influencing native fish population trends may be limited in this section of the Colorado River.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.2842","usgsCitation":"Dodrill, M.J., Yackulic, C.B., Gerig, B., Pine, W.E., Korman, J., and Finch, C., 2015, Do management actions to restore rare habitat benefit native fish conservation? Distribution of juvenile native fish among shoreline habitats of the Colorado River: River Research and Applications, v. 31, no. 10, p. 1203-1217, https://doi.org/10.1002/rra.2842.","productDescription":"15 p.","startPage":"1203","endPage":"1217","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052358","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":299274,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.8902587890625,\n 36.097938036628065\n ],\n [\n -111.8902587890625,\n 36.289670126842225\n ],\n [\n -111.74057006835936,\n 36.289670126842225\n ],\n [\n -111.74057006835936,\n 36.097938036628065\n ],\n [\n -111.8902587890625,\n 36.097938036628065\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"31","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-10-08","publicationStatus":"PW","scienceBaseUri":"551e5a1ee4b027f0aee3b873","contributors":{"authors":[{"text":"Dodrill, Michael J. 0000-0002-7038-7170 mdodrill@usgs.gov","orcid":"https://orcid.org/0000-0002-7038-7170","contributorId":5468,"corporation":false,"usgs":true,"family":"Dodrill","given":"Michael","email":"mdodrill@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":543579,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":543580,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gerig, Brandon","contributorId":139958,"corporation":false,"usgs":false,"family":"Gerig","given":"Brandon","affiliations":[{"id":13331,"text":"University of Florida, Dept. of Wildlife Ecology and Conservation","active":true,"usgs":false}],"preferred":false,"id":543581,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pine, William E. III","contributorId":139959,"corporation":false,"usgs":false,"family":"Pine","given":"William","suffix":"III","email":"","middleInitial":"E.","affiliations":[{"id":13332,"text":"Uni. of Florida Department of Wildlife Ecology and Conservation","active":true,"usgs":false}],"preferred":false,"id":543582,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Korman, Josh","contributorId":139960,"corporation":false,"usgs":false,"family":"Korman","given":"Josh","email":"","affiliations":[{"id":13333,"text":"Ecometric Research Inc.","active":true,"usgs":false}],"preferred":false,"id":543583,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Finch, Colton","contributorId":139961,"corporation":false,"usgs":false,"family":"Finch","given":"Colton","affiliations":[{"id":13334,"text":"Uni. of Florida, Department of Wildlife Ecology and Conservation","active":true,"usgs":false}],"preferred":false,"id":543584,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70144936,"text":"70144936 - 2015 - Not putting all their eggs in one basket: bet-hedging despite extraordinary annual reproductive output of desert tortoises","interactions":[],"lastModifiedDate":"2015-04-27T13:40:37","indexId":"70144936","displayToPublicDate":"2015-04-02T10:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1019,"text":"Biological Journal of the Linnean Society","active":true,"publicationSubtype":{"id":10}},"title":"Not putting all their eggs in one basket: bet-hedging despite extraordinary annual reproductive output of desert tortoises","docAbstract":"Bet-hedging theory makes the counter-intuitive prediction that, if juvenile survival is low and unpredictable, organisms should consistently reduce short-term reproductive output to minimize the risk of reproductive failure in the long-term. We investigated the long-term reproductive output of an Agassiz's desert tortoise (Gopherus agassizii) population and conformance to a bet-hedging strategy of reproduction in an unpredictable but comparatively productive environment. Most females reproduced every year, even during periods of low precipitation and poor germination of food plants, and the mean percentage of reproducing females did not differ significantly on an annual basis. Although mean annual egg production (clutch size × clutch frequency) differed significantly among years, mean clutch size and mean clutch frequency remained relatively constant. During an El Niño year, mean annual egg production and mean annual clutch frequency were the highest ever reported for this species. Annual egg production was positively influenced by maternal body size but clutch size and clutch frequency were not. Our long-term results confirm earlier conclusions based on short-term research that desert tortoises have a bet-hedging strategy of producing small clutches almost every year. The risk of long-term reproductive failure is minimized in unpredictable environments, both through time by annually producing multiple small clutches over a long reproductive lifespan, even in years of low resource availability, and through space by depositing multiple annual clutches in different locations. The extraordinary annual reproductive output of this population appears to be the result of a typically high but unpredictable biomass of annual food plants at the site relative to tortoise habitat in dryer regions. Under the comparatively productive but unpredictable conditions, tortoises conform to predictions of a bet-hedging strategy of reproduction with relatively small but consistent clutch sizes.
","language":"English","publisher":"The Linnean Society of London","doi":"10.1111/bij.12505","usgsCitation":"Lovich, J.E., Ennen, J., Yackulic, C.B., Meyer-Wilkins, K., Agha, M., Loughran, C.L., Bjurlin, C., Austin, M., and Madrak, S.V., 2015, Not putting all their eggs in one basket: bet-hedging despite extraordinary annual reproductive output of desert tortoises: Biological Journal of the Linnean Society, v. 115, no. 2, p. 399-410, https://doi.org/10.1111/bij.12505.","productDescription":"12 p.","startPage":"399","endPage":"410","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059628","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":472160,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/bij.12505","text":"Publisher Index Page"},{"id":299271,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"115","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-19","publicationStatus":"PW","scienceBaseUri":"551e5a20e4b027f0aee3b87f","chorus":{"doi":"10.1111/bij.12505","url":"http://dx.doi.org/10.1111/bij.12505","publisher":"Oxford University Press (OUP)","authors":"Lovich Jeffrey E., Ennen Joshua R., Yackulic Charles B., Meyer-Wilkins Kathie, Agha Mickey, Loughran Caleb, Bjurlin Curtis, Austin Meaghan, Madrak Sheila","journalName":"Biological Journal of the Linnean Society","publicationDate":"3/19/2015","auditedOn":"7/24/2015"},"contributors":{"authors":[{"text":"Lovich, Jeffrey E. 0000-0002-7789-2831 jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":543848,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ennen, Joshua R.","contributorId":60368,"corporation":false,"usgs":false,"family":"Ennen","given":"Joshua R.","affiliations":[{"id":13216,"text":"Tennessee Aquarium Conservation Institute","active":true,"usgs":false}],"preferred":false,"id":543849,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":543856,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Meyer-Wilkins, Kathie","contributorId":8742,"corporation":false,"usgs":false,"family":"Meyer-Wilkins","given":"Kathie","affiliations":[],"preferred":false,"id":543850,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Agha, Mickey","contributorId":22235,"corporation":false,"usgs":false,"family":"Agha","given":"Mickey","email":"","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false},{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":543851,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Loughran, Caleb L.","contributorId":26599,"corporation":false,"usgs":true,"family":"Loughran","given":"Caleb","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":543852,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bjurlin, Curtis","contributorId":90183,"corporation":false,"usgs":false,"family":"Bjurlin","given":"Curtis","affiliations":[],"preferred":false,"id":543853,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Austin, Meaghan","contributorId":37244,"corporation":false,"usgs":true,"family":"Austin","given":"Meaghan","affiliations":[],"preferred":false,"id":543854,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Madrak, Sheila V.","contributorId":7403,"corporation":false,"usgs":true,"family":"Madrak","given":"Sheila","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":543855,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70144136,"text":"ofr20151051 - 2015 - Efficacy of Pseudomonas fluorescens strain CL145A spray dried powder for controlling zebra mussels adhering to native unionid mussels within field enclosures","interactions":[],"lastModifiedDate":"2015-04-02T08:37:22","indexId":"ofr20151051","displayToPublicDate":"2015-04-02T09:15:00","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":"2015-1051","title":"Efficacy of Pseudomonas fluorescens strain CL145A spray dried powder for controlling zebra mussels adhering to native unionid mussels within field enclosures","docAbstract":"The efficacy of a commercially prepared spray dried powder (SDP) formulation of Pseudomonas fluorescens (strain CL145A) was evaluated for removing zebra mussels (Dreissena polymorpha) adhering to a population of unionid mussels in Lake Darling (Alexandria, Minnesota). Two groups of unionid mussels were used in the study. Unionid mussels were collected near the test area, weighed, photographed, individually tagged, and randomly allocated to one of nine test enclosures in equal proportions and then divided into two groups. The first group of unionid mussels (Group 1, n = 5 per test enclosure) were indiscriminately selected from each test enclosure and used to estimate the number of zebra mussels adhering to unionid mussels prior to exposure. The second group of unionid mussels (Group 2, n = 22 per test enclosure) were used to evaluate the efficacy of SDP for removal of adhering zebra mussels. Both Group 1 and Group 2 mussels were used to evaluate the effects of SDP exposure on unionid mussel survival.
\nTreatment was assigned to each test enclosure by using a randomized block design. The three treatment groups were tested in triplicate and included an untreated control group and groups that received a single application of 50 or 100 milligrams per liter (mg/L) of SDP based on active ingredient. All treatment concentrations are reported as active ingredient of SDP. Test enclosures were removed at the 8-hour exposure termination. Both Group 1 and Group 2 mussels remained in their assigned exposure location during the postexposure holding period. The number of zebra mussels adhering to Group 2 mussels (live and dead) was assessed 18 to 20 days postexposure in addition to assessing the survival of Group 1 and Group 2 unionid mussels.
\nSDP, administered as a single treatment, significantly (p < 0.01) reduced the number of adhering zebra mussels when compared to the untreated controls. The number of zebra mussels adhering to unionid mussels (Group 2) was reduced 53 percent in the 50-mg/L treatment group and 68 percent in the 100-mg/L treatment group. The number of adhering zebra mussels did not differ (p = 0.79) between the 50- and 100-mg/L treatment groups after exposure. When standardized to the amount of SDP applied per square meter, each gram (g) of SDP applied in the 50-mg/L treatment reduced the number of adhering zebra mussel 59.8 percent more than the 100-mg/L treatment group.
\nGroup 1 mussel survival did not differ between treatment groups (p > 0.05); however, a difference was detected (p < 0.01) in the survival of Group 2 mussels. The survival of Group 2 mussels did not differ (p > 0.23) between control and treated groups. A difference in Group 2 mussel survival was detected (p = 0.03; odds ratio [OR] = 0.290) between the 50- and 100-mg/L treatment groups (that is, the survival was highest in the 50-mg/L treatment group and lowest in the 100-mg/L treatment group), however, the biological significance of the difference is indeterminate.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151051","usgsCitation":"Luoma, J.A., Weber, K.L., Severson, T.J., and Mayer, D., 2015, Efficacy of Pseudomonas fluorescens strain CL145A spray dried powder for controlling zebra mussels adhering to native unionid mussels within field enclosures: U.S. Geological Survey Open-File Report 2015-1051, viii, 302 p., https://doi.org/10.3133/ofr20151051.","productDescription":"viii, 302 p.","numberOfPages":"310","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-064301","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":299266,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151051.jpg"},{"id":299264,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1051/"},{"id":299265,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1051/pdf/ofr2015-1051.pdf","size":"8.11 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Minnesota","county":"Alexandria","otherGeospatial":"Lake Darling","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.38699150085449,\n 45.93131891375231\n ],\n [\n -95.38546800613403,\n 45.93160247365145\n ],\n [\n -95.38422346115112,\n 45.93169201858156\n ],\n [\n -95.38304328918457,\n 45.93152785276592\n ],\n [\n -95.3817343711853,\n 45.9312293682198\n ],\n [\n -95.38059711456299,\n 45.930647318734614\n ],\n [\n -95.37937402725218,\n 45.929975715584696\n ],\n [\n -95.37909507751465,\n 45.9295429003568\n ],\n [\n -95.37868738174438,\n 45.92870710966921\n ],\n [\n -95.37868738174438,\n 45.927617577899674\n ],\n [\n -95.37911653518677,\n 45.92700563971238\n ],\n [\n -95.38003921508788,\n 45.92630414129035\n ],\n [\n -95.38053274154663,\n 45.92611010824568\n ],\n [\n -95.3811764717102,\n 45.92576681735024\n ],\n [\n -95.38190603256226,\n 45.925602633997094\n ],\n [\n -95.38709878921509,\n 45.93133383799366\n ],\n [\n -95.38699150085449,\n 45.93131891375231\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"551e5a1ee4b027f0aee3b875","contributors":{"authors":[{"text":"Luoma, James A. 0000-0003-3556-0190 jluoma@usgs.gov","orcid":"https://orcid.org/0000-0003-3556-0190","contributorId":4449,"corporation":false,"usgs":true,"family":"Luoma","given":"James","email":"jluoma@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":543881,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weber, Kerry L. klweber@usgs.gov","contributorId":4750,"corporation":false,"usgs":true,"family":"Weber","given":"Kerry","email":"klweber@usgs.gov","middleInitial":"L.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":543882,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Severson, Todd J. 0000-0001-5282-3779 tseverson@usgs.gov","orcid":"https://orcid.org/0000-0001-5282-3779","contributorId":4749,"corporation":false,"usgs":true,"family":"Severson","given":"Todd","email":"tseverson@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":543883,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mayer, Denise A.","contributorId":98772,"corporation":false,"usgs":true,"family":"Mayer","given":"Denise A.","affiliations":[],"preferred":false,"id":543884,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70143552,"text":"fs20153020 - 2015 - The Pacific northwest stream quality assessment","interactions":[],"lastModifiedDate":"2015-04-03T12:40:17","indexId":"fs20153020","displayToPublicDate":"2015-04-02T07:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-3020","title":"The Pacific northwest stream quality assessment","docAbstract":"In 2015, the U.S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) program is assessing stream quality in the Pacific Northwest. The goals of the Pacific Northwest Stream Quality Assessment (Pacific Northwest study) are to assess the quality of streams in the region by characterizing multiple water-quality factors that are stressors to aquatic life and to evaluate the relation between these stressors and biological communities. The effects of urbanization and agriculture on stream quality for the Puget Lowlands and Willamette Valley are the focus of this regional study. Findings will provide the public and policymakers with information regarding which human and environmental factors are the most critical in affecting stream quality and, thus, provide insights about possible approaches to protect or improve the health of streams in the region.
\nThe Pacific Northwest study will be the third regional study by the NAWQA program, and it will be of similar design and scope as the first two—the Midwest in 2013 and the Southeast in 2014 (Van Metre and others, 2012, 2014).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153020","collaboration":"National Water-Quality Assessment Program","usgsCitation":"Van Metre, P., Morace, J.L., and Sheibley, R.W., 2015, The Pacific northwest stream quality assessment: U.S. Geological Survey Fact Sheet 2015-3020, 2 p., https://doi.org/10.3133/fs20153020.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063659","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":299263,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20153020.jpg"},{"id":299261,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2015/3020/"},{"id":299262,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3020/pdf/fs2015-3020.pdf","text":"Report","size":"448 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"projection":"Web Mercator Projection","datum":"World Geodetic System of 1984","country":"United States","state":"Oregon, Washington","otherGeospatial":"Pacific Northwest, Puget Lowlands, Willamette Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.12377929687499,\n 49.001843917978526\n ],\n [\n -122.1185302734375,\n 48.99824008113872\n ],\n [\n -122.25585937500001,\n 48.75618876280552\n ],\n [\n -121.47033691406249,\n 47.698671535297144\n ],\n [\n -122.464599609375,\n 46.46813299215554\n ],\n [\n -122.10205078125,\n 45.42158812329091\n ],\n [\n -122.464599609375,\n 45.06576154770312\n ],\n [\n -122.75024414062499,\n 43.937461690316646\n ],\n [\n -123.101806640625,\n 43.70759350405294\n ],\n [\n -123.49731445312499,\n 43.874138181474734\n ],\n [\n -123.662109375,\n 45.11230010229608\n ],\n [\n -123.26660156249999,\n 45.63708709571876\n ],\n [\n -123.01391601562499,\n 46.08085173686787\n ],\n [\n -123.12377929687499,\n 46.7549166192819\n ],\n [\n -123.71704101562499,\n 46.95776134668866\n ],\n [\n -123.85986328124999,\n 47.204642388766935\n ],\n [\n -123.02490234375,\n 47.66538735632654\n ],\n [\n -123.70605468750001,\n 48.11476663187632\n ],\n [\n -123.12377929687499,\n 49.001843917978526\n ]\n ]\n ]\n }\n }\n ]\n}","publicComments":"National Water-Quality Assessment Program","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"551e5a22e4b027f0aee3b88d","contributors":{"authors":[{"text":"Van Metre, Peter C. pcvanmet@usgs.gov","contributorId":486,"corporation":false,"usgs":true,"family":"Van Metre","given":"Peter C.","email":"pcvanmet@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":542801,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morace, Jennifer L. 0000-0002-8132-4044 jlmorace@usgs.gov","orcid":"https://orcid.org/0000-0002-8132-4044","contributorId":945,"corporation":false,"usgs":true,"family":"Morace","given":"Jennifer","email":"jlmorace@usgs.gov","middleInitial":"L.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":543952,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sheibley, Rich W. 0000-0003-1627-8536 sheibley@usgs.gov","orcid":"https://orcid.org/0000-0003-1627-8536","contributorId":3044,"corporation":false,"usgs":true,"family":"Sheibley","given":"Rich","email":"sheibley@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":543953,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70143862,"text":"ofr20151053 - 2015 - A method for determining average beach slope and beach slope variability for U.S. sandy coastlines","interactions":[],"lastModifiedDate":"2017-06-12T11:21:02","indexId":"ofr20151053","displayToPublicDate":"2015-04-02T07:30:00","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":"2015-1053","title":"A method for determining average beach slope and beach slope variability for U.S. sandy coastlines","docAbstract":"The U.S. Geological Survey (USGS) National Assessment of Hurricane-Induced Coastal Erosion Hazards compares measurements of beach morphology with storm-induced total water levels to produce forecasts of coastal change for storms impacting the Gulf of Mexico and Atlantic coastlines of the United States. The wave-induced water level component (wave setup and swash) is estimated by using modeled offshore wave height and period and measured beach slope (from dune toe to shoreline) through the empirical parameterization of Stockdon and others (2006). Spatial and temporal variability in beach slope leads to corresponding variability in predicted wave setup and swash. For instance, seasonal and storm-induced changes in beach slope can lead to differences on the order of 1 meter (m) in wave-induced water level elevation, making accurate specification of this parameter and its associated uncertainty essential to skillful forecasts of coastal change. A method for calculating spatially and temporally averaged beach slopes is presented here along with a method for determining total uncertainty for each 200-m alongshore section of coastline.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151053","usgsCitation":"Doran, K.S., Long, J.W., and Overbeck, J., 2015, A method for determining average beach slope and beach slope variability for U.S. sandy coastlines: U.S. Geological Survey Open-File Report 2015-1053, Report: iv, 5 p.; Data Releases, https://doi.org/10.3133/ofr20151053.","productDescription":"Report: iv, 5 p.; Data Releases","numberOfPages":"10","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-063337","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":438707,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F72805P1","text":"USGS data release","linkHelpText":"Beach Slopes of Florida: Miami to Jupiter"},{"id":299260,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151053.jpg"},{"id":342384,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.5066/F72805P1","text":"Beach slopes of Florida: Miami to Jupiter"},{"id":342385,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.5066/F7XK8CK2","text":"Beach slopes of Florida: Bradenton Beach to Clearwater Beach"},{"id":299257,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1053/"},{"id":299258,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1053/pdf/ofr2015-1053.pdf","text":"Report","size":"377 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":299259,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.5066/F7M906Q6","text":"Beach Slopes of North Carolina: Salvo to Duck","description":"Dataset website"}],"country":"United States","state":"North Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.84686279296874,\n 35.21420969483077\n ],\n [\n -75.84686279296874,\n 36.10015727402227\n ],\n [\n -75.21240234375,\n 36.10015727402227\n ],\n [\n -75.21240234375,\n 35.21420969483077\n ],\n [\n -75.84686279296874,\n 35.21420969483077\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"551e5a18e4b027f0aee3b869","contributors":{"authors":[{"text":"Doran, Kara S. 0000-0001-8050-5727 kdoran@usgs.gov","orcid":"https://orcid.org/0000-0001-8050-5727","contributorId":127855,"corporation":false,"usgs":true,"family":"Doran","given":"Kara","email":"kdoran@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":543875,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Long, Joseph W. 0000-0003-2912-1992 jwlong@usgs.gov","orcid":"https://orcid.org/0000-0003-2912-1992","contributorId":3303,"corporation":false,"usgs":true,"family":"Long","given":"Joseph","email":"jwlong@usgs.gov","middleInitial":"W.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":543876,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Overbeck, Jacquelyn R.","contributorId":140046,"corporation":false,"usgs":true,"family":"Overbeck","given":"Jacquelyn R.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":543877,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70146790,"text":"70146790 - 2015 - Managing habitat to slow or reverse population declines of the Columbia spotted frog in the Northern Great Basin","interactions":[],"lastModifiedDate":"2017-11-22T18:01:11","indexId":"70146790","displayToPublicDate":"2015-04-01T16:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Managing habitat to slow or reverse population declines of the Columbia spotted frog in the Northern Great Basin","docAbstract":"Evaluating the effectiveness of habitat management actions is critical to adaptive management strategies for conservation of imperiled species. We quantified the response of a Great Basin population of the Columbia spotted frog (Rana luteiventris) to multiple habitat improvement actions aimed to reduce threats and reverse population declines. We used mark-recapture data for 1,394 adult frogs that had been marked by state, federal, and university biologists in 9 ponds representing a single population over a 16-year period from 1997 to 2012. With the use of demographic models, we assessed population-level effects of 1) a grazing exclosure constructed around 6 stock ponds that had been used to water livestock for decades before being fully fenced in 2003, and 2) the construction of 3 new stock ponds in 2003 to provide alternative water sources for livestock and, secondarily, to provide additional frog habitat. These management actions were implemented in response to a decline of more than 80% in population size from 1997 to 2002. We found evidence that excluding cattle from ponds and surrounding riparian habitats resulted in higher levels of frog production (more egg masses), higher adult frog recruitment and survival, and higher population growth rate. We also found that frogs colonized the newly constructed stock ponds within 3 years and frogs began breeding in 2 of them after 5 years. The positive effects of the cattle exclosure and additional production from the new ponds, although notable, did not result in full recovery of the population even 9 years later. This slow recovery may be partly explained by the effects of weather on recruitment rates, particularly the negative effects of harsher winters with late springs and higher fall temperatures. Although our findings point to potential successes of habitat management aimed at slowing or reversing rapidly declining frog populations, our study also suggests that recovering from severe population declines can take many years because of demographic and environmental processes.
","language":"English","publisher":"Wildlife Society","doi":"10.1002/jwmg.868","usgsCitation":"Pilliod, D., and Scherer, R.D., 2015, Managing habitat to slow or reverse population declines of the Columbia spotted frog in the Northern Great Basin: Journal of Wildlife Management, v. 79, no. 4, p. 579-590, https://doi.org/10.1002/jwmg.868.","productDescription":"12 p.","startPage":"579","endPage":"590","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059456","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":299813,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","county":"Owyhee County","otherGeospatial":"Sam Noble Springs","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.02911376953124,\n 43.67979094030124\n ],\n [\n -116.97967529296874,\n 43.667871610117494\n ],\n [\n -116.95220947265624,\n 43.63806292753483\n ],\n [\n -116.91925048828124,\n 43.6102281417864\n ],\n [\n -116.86981201171875,\n 43.59431676355149\n ],\n [\n -116.817626953125,\n 43.5843700152048\n ],\n [\n -116.79290771484374,\n 43.538593801442374\n ],\n [\n -116.77093505859375,\n 43.48082639482503\n ],\n [\n -116.67205810546874,\n 43.389081939117496\n ],\n [\n -116.63635253906249,\n 43.37311218382002\n ],\n [\n -116.59240722656249,\n 43.31718491566708\n ],\n [\n -116.54296874999999,\n 43.29120116988416\n ],\n [\n -116.49627685546874,\n 43.28920196020127\n ],\n [\n -116.43035888671875,\n 43.28920196020127\n ],\n [\n -116.38641357421875,\n 43.23119629494612\n ],\n [\n -116.37542724609374,\n 43.193162620926074\n ],\n [\n -116.30950927734374,\n 43.153101551466385\n ],\n [\n -116.2847900390625,\n 43.111009147075116\n ],\n [\n -116.21887207031249,\n 43.09095496313368\n ],\n [\n -116.18316650390625,\n 43.06086137134326\n ],\n [\n -116.13922119140624,\n 43.04079076668198\n ],\n [\n -116.12823486328126,\n 43.01268088642034\n ],\n [\n -116.07330322265625,\n 42.98656732912335\n ],\n [\n -116.03759765625,\n 42.97049193148623\n ],\n [\n -115.97442626953125,\n 42.94637095514085\n ],\n [\n -115.97442626953125,\n 42.99259451971113\n ],\n [\n -115.94146728515625,\n 43.00866413845207\n ],\n [\n -115.9112548828125,\n 42.99058552185121\n ],\n [\n -115.8563232421875,\n 42.98656732912335\n ],\n [\n -115.81237792968749,\n 42.98053954751642\n ],\n [\n -115.77667236328125,\n 42.9524020856897\n ],\n [\n -115.69976806640625,\n 42.95039177450287\n ],\n [\n -115.65032958984375,\n 42.962452656668795\n ],\n [\n -115.6036376953125,\n 42.954412331213284\n ],\n [\n -115.55419921875,\n 42.9524020856897\n ],\n [\n -115.477294921875,\n 42.93229601903058\n ],\n [\n -115.43884277343749,\n 42.93430692117159\n ],\n [\n -115.4168701171875,\n 42.93430692117159\n ],\n [\n -115.3399658203125,\n 42.91620643817353\n ],\n [\n -115.3179931640625,\n 42.80144655484334\n ],\n [\n -115.01312255859375,\n 42.80144655484334\n ],\n [\n -114.95819091796876,\n 41.99828401778616\n ],\n [\n -115.037841796875,\n 41.99828401778616\n ],\n [\n -117.02911376953124,\n 41.99624282178583\n ],\n [\n -117.02911376953124,\n 43.67979094030124\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"79","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-24","publicationStatus":"PW","scienceBaseUri":"553774ade4b0b22a15808510","contributors":{"authors":[{"text":"Pilliod, David S. dpilliod@usgs.gov","contributorId":140097,"corporation":false,"usgs":true,"family":"Pilliod","given":"David S.","email":"dpilliod@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":545354,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scherer, Richard D.","contributorId":140359,"corporation":false,"usgs":false,"family":"Scherer","given":"Richard","email":"","middleInitial":"D.","affiliations":[{"id":13470,"text":"Conservation Science Partners","active":true,"usgs":false}],"preferred":false,"id":545355,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70146795,"text":"70146795 - 2015 - Desert tortoise use of burned habitat in the Eastern Mojave desert","interactions":[],"lastModifiedDate":"2016-04-13T13:08:25","indexId":"70146795","displayToPublicDate":"2015-04-01T16:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Desert tortoise use of burned habitat in the Eastern Mojave desert","docAbstract":"Wildfires burned 24,254 ha of critical habitat designated for the recovery of the threatened Mojave desert tortoise (Gopherus agassizii) in southern Nevada during 2005. The proliferation of non-native annual grasses has increased wildfire frequency and extent in recent decades and continues to accelerate the conversion of tortoise habitat across the Mojave Desert. Immediate changes to vegetation are expected to reduce quality of critical habitat, yet whether tortoises will use burned and recovering habitat differently from intact unburned habitat is unknown. We compared movement patterns, home-range size, behavior, microhabitat use, reproduction, and survival for adult desert tortoises located in, and adjacent to, burned habitat to understand how tortoises respond to recovering burned habitat. Approximately 45% of home ranges in the post-fire environment contained burned habitat, and numerous observations (n = 12,223) corroborated tortoise use of both habitat types (52% unburned, 48% burned). Tortoises moved progressively deeper into burned habitat during the first 5 years following the fire, frequently foraging in burned habitats that had abundant annual plants, and returning to adjacent unburned habitat for cover provided by intact perennial vegetation. However, by years 6 and 7, the live cover of the short-lived herbaceous perennial desert globemallow (Sphaeralcea ambigua) that typically re-colonizes burned areas declined, resulting in a contraction of tortoise movements from the burned areas. Health and egg production were similar between burned and unburned areas indicating that tortoises were able to acquire necessary resources using both areas. This study documents that adult Mojave desert tortoises continue to use habitat burned once by wildfire. Thus, continued management of this burned habitat may contribute toward the recovery of the species in the face of many sources of habitat loss.
","language":"English","publisher":"Wildlife Society","doi":"10.1002/jwmg.874","usgsCitation":"Drake, K.K., Esque, T., Nussear, K.E., DeFalco, L., Scoles-Sciulla, S.J., Modlin, A.T., and Medica, P.A., 2015, Desert tortoise use of burned habitat in the Eastern Mojave desert: Journal of Wildlife Management, v. 79, no. 4, p. 618-629, https://doi.org/10.1002/jwmg.874.","productDescription":"12 p.","startPage":"618","endPage":"629","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057109","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":299811,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","county":"Clark County","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.51025390625,\n 36.32397712011264\n ],\n [\n -115.323486328125,\n 36.32397712011264\n ],\n [\n -115.1312255859375,\n 36.33725319397006\n ],\n [\n -114.91149902343751,\n 36.348314860643015\n ],\n [\n -114.61212158203124,\n 36.361586786517776\n ],\n [\n -114.46380615234375,\n 36.38812384894608\n ],\n [\n -114.38690185546875,\n 36.41244153535644\n ],\n [\n -114.36767578124999,\n 36.4477991295848\n ],\n [\n -114.400634765625,\n 36.491973470593685\n ],\n [\n -114.4061279296875,\n 36.53832942872816\n ],\n [\n -114.36767578124999,\n 36.5978891330702\n ],\n [\n -114.36767578124999,\n 36.752089156946326\n ],\n [\n -114.3621826171875,\n 36.88621127842176\n ],\n [\n -115.95932006835938,\n 36.90213639045954\n ],\n [\n -115.93803405761717,\n 36.32729635065908\n ],\n [\n -115.51025390625,\n 36.32397712011264\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"79","issue":"4","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"553774aae4b0b22a1580850b","contributors":{"authors":[{"text":"Drake, K. Kristina 0000-0003-0711-7634 kdrake@usgs.gov","orcid":"https://orcid.org/0000-0003-0711-7634","contributorId":3799,"corporation":false,"usgs":true,"family":"Drake","given":"K.","email":"kdrake@usgs.gov","middleInitial":"Kristina","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":545361,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Esque, Todd C. tesque@usgs.gov","contributorId":140024,"corporation":false,"usgs":true,"family":"Esque","given":"Todd C.","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":545360,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nussear, Kenneth E. knussear@usgs.gov","contributorId":2695,"corporation":false,"usgs":true,"family":"Nussear","given":"Kenneth","email":"knussear@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":545362,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeFalco, Lesley ldefalco@usgs.gov","contributorId":139012,"corporation":false,"usgs":true,"family":"DeFalco","given":"Lesley","email":"ldefalco@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":545363,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Scoles-Sciulla, Sara J. 0000-0003-1693-5030 sscoles@usgs.gov","orcid":"https://orcid.org/0000-0003-1693-5030","contributorId":2614,"corporation":false,"usgs":true,"family":"Scoles-Sciulla","given":"Sara","email":"sscoles@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":545364,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Modlin, Andrew T. amodlin@usgs.gov","contributorId":5967,"corporation":false,"usgs":true,"family":"Modlin","given":"Andrew","email":"amodlin@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":545365,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Medica, Philip A.","contributorId":55780,"corporation":false,"usgs":true,"family":"Medica","given":"Philip","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":545366,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70144897,"text":"70144897 - 2015 - Can polar bears use terrestrial foods to offset lost ice-based hunting opportunities?","interactions":[],"lastModifiedDate":"2018-10-30T14:31:51","indexId":"70144897","displayToPublicDate":"2015-04-01T14:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1701,"text":"Frontiers in Ecology and the Environment","active":true,"publicationSubtype":{"id":10}},"title":"Can polar bears use terrestrial foods to offset lost ice-based hunting opportunities?","docAbstract":"Increased land use by polar bears (Ursus maritimus) due to climate-change-induced reduction of their sea-ice habitat illustrates the impact of climate change on species distributions and the difficulty of conserving a large, highly specialized carnivore in the face of this global threat. Some authors have suggested that terrestrial food consumption by polar bears will help them withstand sea-ice loss as they are forced to spend increasing amounts of time on land. Here, we evaluate the nutritional needs of polar bears as well as the physiological and environmental constraints that shape their use of terrestrial ecosystems. Only small numbers of polar bears have been documented consuming terrestrial foods even in modest quantities. Over much of the polar bear's range, limited terrestrial food availability supports only low densities of much smaller, resident brown bears (Ursus arctos), which use low-quality resources more efficiently and may compete with polar bears in these areas. Where consumption of terrestrial foods has been documented, polar bear body condition and survival rates have declined even as land use has increased. Thus far, observed consumption of terrestrial food by polar bears has been insufficient to offset lost ice-based hunting opportunities but can have ecological consequences for other species. Warming-induced loss of sea ice remains the primary threat faced by polar bears.
","language":"English","publisher":"Ecological Society of America","publisherLocation":"Washington, D.C.","doi":"10.1890/140202","usgsCitation":"Rode, K.D., Robbins, C.T., Nelson, L., and Amstrup, S.C., 2015, Can polar bears use terrestrial foods to offset lost ice-based hunting opportunities?: Frontiers in Ecology and the Environment, v. 13, no. 3, p. 138-145, https://doi.org/10.1890/140202.","productDescription":"8 p.","startPage":"138","endPage":"145","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057990","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":472161,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/140202","text":"Publisher Index Page"},{"id":299253,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Arctic","volume":"13","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"551d0899e4b0256c24f4214c","contributors":{"authors":[{"text":"Rode, Karyn D. 0000-0002-3328-8202 krode@usgs.gov","orcid":"https://orcid.org/0000-0002-3328-8202","contributorId":5053,"corporation":false,"usgs":true,"family":"Rode","given":"Karyn","email":"krode@usgs.gov","middleInitial":"D.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":543837,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robbins, Charles T.","contributorId":32436,"corporation":false,"usgs":false,"family":"Robbins","given":"Charles","email":"","middleInitial":"T.","affiliations":[{"id":5132,"text":"Washington State University, Pullman","active":true,"usgs":false}],"preferred":false,"id":543838,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nelson, Lynne","contributorId":140043,"corporation":false,"usgs":false,"family":"Nelson","given":"Lynne","email":"","affiliations":[],"preferred":false,"id":543839,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Amstrup, Steven C.","contributorId":67034,"corporation":false,"usgs":false,"family":"Amstrup","given":"Steven","email":"","middleInitial":"C.","affiliations":[{"id":13182,"text":"Polar Bears International","active":true,"usgs":false}],"preferred":false,"id":543840,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70188785,"text":"70188785 - 2015 - A sea-level database for the Pacific coast of central North America","interactions":[],"lastModifiedDate":"2018-08-07T14:38:07","indexId":"70188785","displayToPublicDate":"2015-04-01T14:37:58","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"A sea-level database for the Pacific coast of central North America","docAbstract":"A database of published and new relative sea-level (RSL) data for the past 16 ka constrains the sea-level histories of the Pacific coast of central North America (southern British Columbia to central California). Our reevaluation of the stratigraphic context and radiocarbon age of sea-level indicators from geological and archaeological investigations yields 600 sea-level index points and 241 sea-level limiting points. We subdivided the database into 12 regions based on the availability of data, tectonic setting, and distance from the former Cordilleran ice sheet. Most index (95%) and limiting points (54%) are <7 ka; older data come mainly from British Columbia and San Francisco Bay. The stratigraphic position of points was used as a first-order assessment of compaction. Formerly glaciated areas show variable RSL change; where data are present, highstands of RSL occur immediately post-deglaciation and in the mid to late Holocene. Sites at the periphery and distant to formerly glaciated areas demonstrate a continuous rise in RSL with a decreasing rate through time due to the collapse of the peripheral forebulge and the reduction in meltwater input during deglaciation. Late Holocene RSL change varies spatially from falling at 0.7 ± 0.8 mm a−1 in southern British Columbia to rising at 1.5 ± 0.3 mm a−1 in California. The different sea-level histories are an ongoing isostatic response to deglaciation of the Cordilleran and Laurentide Ice Sheets.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2014.12.001","usgsCitation":"Engelhart, S.E., Vacchi, M., Horton, B.P., Nelson, A.R., and Kopp, R.E., 2015, A sea-level database for the Pacific coast of central North America: Quaternary Science Reviews, v. 113, p. 78-92, https://doi.org/10.1016/j.quascirev.2014.12.001.","productDescription":"15 p.","startPage":"78","endPage":"92","ipdsId":"IP-061597","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":488783,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://durham-repository.worktribe.com/output/1290872","text":"External Repository"},{"id":356298,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"113","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fcc2de4b0f5d57878eccf","contributors":{"authors":[{"text":"Engelhart, Simon E.","contributorId":60104,"corporation":false,"usgs":false,"family":"Engelhart","given":"Simon","email":"","middleInitial":"E.","affiliations":[{"id":6923,"text":"University of Rhode Island, Kingston, RI","active":true,"usgs":false}],"preferred":false,"id":700351,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vacchi, Matteo","contributorId":193395,"corporation":false,"usgs":false,"family":"Vacchi","given":"Matteo","email":"","affiliations":[],"preferred":false,"id":700352,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Horton, Benjamin P.","contributorId":192807,"corporation":false,"usgs":false,"family":"Horton","given":"Benjamin","email":"","middleInitial":"P.","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false},{"id":5110,"text":"Earth Observatory of Singapore, Nanyang Technological University","active":true,"usgs":false}],"preferred":false,"id":700353,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nelson, Alan R. 0000-0001-7117-7098 anelson@usgs.gov","orcid":"https://orcid.org/0000-0001-7117-7098","contributorId":812,"corporation":false,"usgs":true,"family":"Nelson","given":"Alan","email":"anelson@usgs.gov","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":700354,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kopp, Robert E.","contributorId":193396,"corporation":false,"usgs":false,"family":"Kopp","given":"Robert","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":700355,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70145517,"text":"70145517 - 2015 - Sampling animal sign in heterogeneous environments: how much is enough?","interactions":[],"lastModifiedDate":"2018-09-04T15:30:57","indexId":"70145517","displayToPublicDate":"2015-04-01T14:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2183,"text":"Journal of Arid Environments","active":true,"publicationSubtype":{"id":10}},"title":"Sampling animal sign in heterogeneous environments: how much is enough?","docAbstract":"Animal ecologists often use animal sign as a surrogate for direct observation of organisms, especially when species are secretive or difficult to observe. Spatial heterogeneity in arid environments makes it challenging to consistently detect and precisely characterize animal sign, which can bias estimates of animal abundance or habitat use. Piute ground squirrels (Urocitellus mollis) and Owyhee harvester ants (Pogonomyrmex salinus) live in arid environments and are fossorial, which can make them difficult to observe directly. Their relative abundance can be assessed using sign (i.e., burrows and nests). We implemented an over-sampling framework (i.e., recorded an excessive amount of information) with two observers to 1) identify a sampling intensity that balanced precision with our resource constraints, and 2) assess classification and detection of squirrel burrows and ant nests across vegetation conditions. We sampled 20 1-ha plots for ground squirrel burrows and ant nests using six 4 m × 100 m belt transects. Analyses of precision and sampling effort indicated that three belt transects covering 1200 m2 per ha provided sufficient precision, while minimizing effort. Regardless of vegetation conditions, counts by two observers were strongly correlated for ground squirrel burrows (r = 0.99, P < 0.001, df = 18; slope = 0.92) and harvester ant nests (r = 0.99, P < 0.001, df = 18; slope = 1.01) indicating observer consistency and perhaps high detection probability. These findings illustrate an approach for evaluating sampling designs in many ecological contexts.
","language":"English","publisher":"Academic Press","publisherLocation":"London, England","doi":"10.1016/j.jaridenv.2015.03.013","usgsCitation":"Holbrook, J.D., Arkle, R., Rachlow, J.L., Vierling, K.T., and Pilliod, D., 2015, Sampling animal sign in heterogeneous environments: how much is enough?: Journal of Arid Environments, v. 119, p. 51-55, https://doi.org/10.1016/j.jaridenv.2015.03.013.","productDescription":"5 p.","startPage":"51","endPage":"55","numberOfPages":"5","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056543","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":299457,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"119","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5524ffb2e4b027f0aee3d485","contributors":{"authors":[{"text":"Holbrook, Joseph D.","contributorId":140098,"corporation":false,"usgs":false,"family":"Holbrook","given":"Joseph","email":"","middleInitial":"D.","affiliations":[{"id":13384,"text":"Department of Fish and Wildlife Sciences, University of Idaho,","active":true,"usgs":false}],"preferred":false,"id":544240,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arkle, Robert S. 0000-0003-3021-1389 rarkle@usgs.gov","orcid":"https://orcid.org/0000-0003-3021-1389","contributorId":3501,"corporation":false,"usgs":true,"family":"Arkle","given":"Robert S.","email":"rarkle@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":544241,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rachlow, Janet L.","contributorId":69298,"corporation":false,"usgs":true,"family":"Rachlow","given":"Janet","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":544242,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":544243,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pilliod, David S. dpilliod@usgs.gov","contributorId":140097,"corporation":false,"usgs":true,"family":"Pilliod","given":"David S.","email":"dpilliod@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":544239,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70147071,"text":"70147071 - 2015 - Targeting climate diversity in conservation planning to build resilience to climate change","interactions":[],"lastModifiedDate":"2018-09-18T10:34:24","indexId":"70147071","displayToPublicDate":"2015-04-01T13:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Targeting climate diversity in conservation planning to build resilience to climate change","docAbstract":"Climate change is raising challenging concerns for systematic conservation planning. Are methods based on the current spatial patterns of biodiversity effective given long-term climate change? Some conservation scientists argue that planning should focus on protecting the abiotic diversity in the landscape, which drives patterns of biological diversity, rather than focusing on the distribution of focal species, which shift in response to climate change. Climate is one important abiotic driver of biodiversity patterns, as different climates host different biological communities and genetic pools. We propose conservation networks that capture the full range of climatic diversity in a region will improve the resilience of biotic communities to climate change compared to networks that do not. In this study we used historical and future hydro-climate projections from the high resolution Basin Characterization Model to explore the utility of directly targeting climatic diversity in planning. Using the spatial planning tool, Marxan, we designed conservation networks to capture the diversity of climate types, at the regional and sub-regional scale, and compared them to networks we designed to capture the diversity of vegetation types. By focusing on the Conservation Lands Network (CLN) of the San Francisco Bay Area as a real-world case study, we compared the potential resilience of networks by examining two factors: the range of climate space captured, and climatic stability to 18 future climates, reflecting different emission scenarios and global climate models. We found that the climate-based network planned at the sub-regional scale captured a greater range of climate space and showed higher climatic stability than the vegetation and regional based-networks. At the same time, differences among network scenarios are small relative to the variance in climate stability across global climate models. Across different projected futures, topographically heterogeneous areas consistently show greater climate stability than homogenous areas. The analysis suggests that utilizing high-resolution climate and hydrological data in conservation planning improves the likely resilience of biodiversity to climate change. We used these analyses to suggest new conservation priorities for the San Francisco Bay Area.
","language":"English","publisher":"Ecological Society of America","publisherLocation":"Washington, D.C.","doi":"10.1890/ES14-00313.1","usgsCitation":"Heller, N.E., Kreitler, J.R., Ackerly, D., Weiss, S., Recinos, A., Branciforte, R., Flint, L.E., Flint, A.L., and Micheli, E., 2015, Targeting climate diversity in conservation planning to build resilience to climate change: Ecosphere, v. 6, no. 4, p. 1-20, https://doi.org/10.1890/ES14-00313.1.","productDescription":"20 p.","startPage":"1","endPage":"20","numberOfPages":"20","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058616","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":472162,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1890/es14-00313.1","text":"External Repository"},{"id":299894,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-04-24","publicationStatus":"PW","scienceBaseUri":"553f5dbbe4b0a658d7938cfc","contributors":{"authors":[{"text":"Heller, Nicole E.","contributorId":140429,"corporation":false,"usgs":false,"family":"Heller","given":"Nicole","email":"","middleInitial":"E.","affiliations":[{"id":13495,"text":"Dwight Center for Conservation Science at Pepperwood Preserve","active":true,"usgs":false}],"preferred":false,"id":545619,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kreitler, Jason R. 0000-0002-0243-5281 jkreitler@usgs.gov","orcid":"https://orcid.org/0000-0002-0243-5281","contributorId":4050,"corporation":false,"usgs":true,"family":"Kreitler","given":"Jason","email":"jkreitler@usgs.gov","middleInitial":"R.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":545618,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ackerly, David","contributorId":139541,"corporation":false,"usgs":false,"family":"Ackerly","given":"David","affiliations":[{"id":7102,"text":"University of California, Berkeley, Dept. of Civil & Envir. 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Here we synthesize observational studies of this event and compare findings to expected relationships with biotic and abiotic factors. Agreement exists on the occurrence of drought, presence of bark beetles and increased mortality of larger trees. However, studies disagree about the influences of stem density, elevation and other factors, perhaps related to study design, location and impact of extreme drought. Detailed information about bark beetles is seldom reported and their role is poorly understood. Our analysis reveals substantial limits to our knowledge regarding the processes that produce mortality patterns across space and time, indicating a poor ability to forecast mortality in response to expected increases in future droughts.
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SDM is a value-focused thinking approach that places paramount importance on first establishing clear management objectives that reflect core values of stakeholders. To be useful for management, objectives must be transparently stated in unambiguous and measurable terms. We used these concepts to develop consensus objectives for the multiple stakeholders of horseshoe crab harvest in Delaware Bay. Participating stakeholders first agreed on a qualitative statement of fundamental objectives, and then worked to convert those objectives to specific and measurable quantities, so that management decisions could be assessed. We used a constraint-based approach where the conservation objectives for Red Knots, a species of migratory shorebird that relies on horseshoe crab eggs as a food resource during migration, constrained the utility of crab harvest. 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","language":"English","publisher":"Springer-Verlag","publisherLocation":"New York, NY","doi":"10.1007/s00267-014-0422-8","usgsCitation":"McGowan, C., Lyons, J., and Smith, D., 2015, Developing objectives with multiple stakeholders: adaptive management of horseshoe crabs and Red Knots in the Delaware Bay: Environmental Management, v. 55, no. 4, p. 972-982, https://doi.org/10.1007/s00267-014-0422-8.","productDescription":"11 p.","startPage":"972","endPage":"982","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052744","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":305434,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"55","issue":"4","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2014-12-24","publicationStatus":"PW","scienceBaseUri":"55926c95e4b0b6d21dd6775f","contributors":{"authors":[{"text":"McGowan, Conor P. 0000-0002-7330-9581 cmcgowan@usgs.gov","orcid":"https://orcid.org/0000-0002-7330-9581","contributorId":3381,"corporation":false,"usgs":true,"family":"McGowan","given":"Conor P.","email":"cmcgowan@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":556713,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lyons, James E.","contributorId":35461,"corporation":false,"usgs":true,"family":"Lyons","given":"James E.","affiliations":[],"preferred":false,"id":563937,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, David 0000-0001-6074-9257","orcid":"https://orcid.org/0000-0001-6074-9257","contributorId":1989,"corporation":false,"usgs":false,"family":"Smith","given":"David","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":563938,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70160762,"text":"70160762 - 2015 - Summer diel diet and feeding periodicity of four species of cyprinids in the Salmon River, New York","interactions":[],"lastModifiedDate":"2015-12-30T11:50:25","indexId":"70160762","displayToPublicDate":"2015-04-01T12:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":737,"text":"American Midland Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Summer diel diet and feeding periodicity of four species of cyprinids in the Salmon River, New York","docAbstract":"The diel diet composition and feeding periodicity of Luxilus cornutus (common shiner), Exoglossum maxillingua (cutlip minnow), Semotilus corporalis (fallfish), and Notropis hudsonius (spottail shiner) were examined in the Salmon River, New York over a 24 h period during the summer. Chironomids were the major prey of common shiner (60.6%) and cutlip minnow (54.7%), whereas terrestrial invertebrates (30.0%) and amphipods (38.4%) were the primary food of fallfish and spottail shiner, respectively. Diet overlap was high between common shiner and cutlip minnow (Morisita's index = 0.88) and moderate between fallfish and common shiner (0.54) and fallfish and cutlip minnow (0.50). Diel temperal variation in diet composition was greatest (0.64) for spottail shiner. Three species exhibited diel variation in food consumption. Fallfish had a distinct feeding peak, whereas peak food consumption of common shiner and cutlip minnow occurred over a more extended period. Spottail shiner did not have a distinct feeding peak but food consumption was highest from 2400 to 0800 h. Each of the four species exhibited some degree of variation in their diel feeding ecology in regards to either diet composition or food consumption.
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