In 2011, the senior authors were contacted by Ron Gardiner of Questa, and Village of Questa Mayor Esther Garcia, to discuss the existing and future groundwater supply for the Village of Questa. This meeting led to the development of a plan in 2013 to perform an integrated geologic, geophysical, and hydrogeologic investigation of the Questa area by the New Mexico Bureau of Geology & Mineral Resources (NMBG), the U.S. Geological Survey (USGS), and New Mexico Tech (NMT).
The NMBG was responsible for the geologic map and geologic cross sections. The USGS was responsible for a detailed geophysical model to be incorporated into the NMBG products. NMT was responsible for providing a graduate student to develop a geochemical and groundwater flow model. This report represents the final products of the geologic and geophysical investigations conducted by the NMBG and USGS. The USGS final products have been incorporated directly into the geologic cross sections.
The objective of the study was to characterize and interpret the shallow (to a depth of approximately 5,000 ft) three-dimensional geology and preliminary hydrogeology of the Questa area. The focus of this report is to compile existing geologic and geophysical data, integrate new geophysical data, and interpret these data to construct three, detailed geologic cross sections across the Questa area. These cross sections can be used by the Village of Questa to make decisions about municipal water-well development, and can be used in the future to help in the development of a conceptual model of groundwater flow for the Questa area. Attached to this report are a location map, a preliminary geologic map and unit descriptions, tables of water wells and springs used in the study, and three detailed hydrogeologic cross sections shown at two different vertical scales. The locations of the cross sections are shown on the index map of the cross section sheet.
","language":"English","publisher":"New Mexico Bureau of Geology and Mineral Resources","usgsCitation":"Bauer, P.W., Grauch, V.J., Johnson, P.S., Thompson, R.A., Drenth, B.J., and Kelson, K., 2015, Geologic cross sections and preliminary geologic map of the Questa Area, Taos County, New Mexico: Open-File Report 578, 16 p.","productDescription":"16 p.","ipdsId":"IP-069393","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":340204,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58ff0ea0e4b006455f2d61d2","contributors":{"authors":[{"text":"Bauer, Paul W.","contributorId":145562,"corporation":false,"usgs":false,"family":"Bauer","given":"Paul","email":"","middleInitial":"W.","affiliations":[{"id":16150,"text":"New Mexico Bureau of Geology and Mineral Resources","active":true,"usgs":false}],"preferred":false,"id":588672,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grauch, V. J. S. 0000-0002-0761-3489 tien@usgs.gov","orcid":"https://orcid.org/0000-0002-0761-3489","contributorId":886,"corporation":false,"usgs":true,"family":"Grauch","given":"V.","email":"tien@usgs.gov","middleInitial":"J. S.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":588673,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Peggy S.","contributorId":85689,"corporation":false,"usgs":true,"family":"Johnson","given":"Peggy","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":588674,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, Ren A. 0000-0002-3044-3043 rathomps@usgs.gov","orcid":"https://orcid.org/0000-0002-3044-3043","contributorId":1265,"corporation":false,"usgs":true,"family":"Thompson","given":"Ren","email":"rathomps@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":588671,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Drenth, Benjamin J. 0000-0002-3954-8124 bdrenth@usgs.gov","orcid":"https://orcid.org/0000-0002-3954-8124","contributorId":1315,"corporation":false,"usgs":true,"family":"Drenth","given":"Benjamin","email":"bdrenth@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":588675,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kelson, Keith I.","contributorId":75851,"corporation":false,"usgs":true,"family":"Kelson","given":"Keith I.","affiliations":[],"preferred":false,"id":588676,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70164520,"text":"70164520 - 2015 - Interpretation of S waves generated by near-surface chemical explosions at SAFOD","interactions":[],"lastModifiedDate":"2016-02-09T12:57:30","indexId":"70164520","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Interpretation of S waves generated by near-surface chemical explosions at SAFOD","docAbstract":"A series of near-surface chemical explosions conducted at the San Andreas Fault Observatory at Depth (SAFOD) were recorded by high-frequency downhole receiver arrays in separate experiments in November 2003 and May 2005. The 2003 experiment involved ∼100 kg shots detonated along a 46-km-long line (Hole–Ryberg line) centered on SAFOD and recorded by 32 three-component geophones in the pilot hole between 0.8 and 2.0 km depth. The 2005 experiment involved ∼36 kg shots detonated at Parkfield Area Seismic Observatory (PASO) stations (at ∼1–8 km offset) recorded by 80 three-component geophones in the main hole between the surface and 2.4 km depth. These data sample the downgoing seismic wavefield and constrain the shallow velocity and attenuation structure, as well as the first-order characteristics of the source. Using forward modeling on a velocity structure designed for the near field, both observed P- and S-wave energy for the PASO shots are identified with the travel times expected for direct and/or reflected phases. Larger-offset recordings from shots along the Hole–Ryberg line reveal substantial SV and SH energy, especially southwest of SAFOD from the source as indicated by P-to-S amplitude ratios. The generated SV energy is interpreted to arise chiefly from P-to-S conversions at subhorizontal discontinuities. This provides a simple mechanism for often-observed low P-to-S amplitude ratios from nuclear explosions in the far field, as originating from strong near-field wave conversions.
","language":"English","publisher":"Seismological Society of Amercia","doi":"10.1785/0120140242","usgsCitation":"Pollitz, F., Ellsworth, W.L., and Rubinstein, J.L., 2015, Interpretation of S waves generated by near-surface chemical explosions at SAFOD: Bulletin of the Seismological Society of America, v. 105, no. 6, p. 2835-2851, https://doi.org/10.1785/0120140242.","productDescription":"17 p.","startPage":"2835","endPage":"2851","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057606","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":316740,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"105","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-30","publicationStatus":"PW","scienceBaseUri":"56bb1bc5e4b08d617f654e1f","contributors":{"authors":[{"text":"Pollitz, Fred F. fpollitz@usgs.gov","contributorId":2408,"corporation":false,"usgs":true,"family":"Pollitz","given":"Fred F.","email":"fpollitz@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":597718,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ellsworth, William L. ellsworth@usgs.gov","contributorId":787,"corporation":false,"usgs":true,"family":"Ellsworth","given":"William","email":"ellsworth@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":597719,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rubinstein, Justin L. 0000-0003-1274-6785 jrubinstein@usgs.gov","orcid":"https://orcid.org/0000-0003-1274-6785","contributorId":2404,"corporation":false,"usgs":true,"family":"Rubinstein","given":"Justin","email":"jrubinstein@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":597720,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196071,"text":"70196071 - 2015 - Sources and transport of phosphorus to rivers in California and adjacent states, U.S., as determined by SPARROW modeling","interactions":[],"lastModifiedDate":"2018-09-13T16:50:34","indexId":"70196071","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Sources and transport of phosphorus to rivers in California and adjacent states, U.S., as determined by SPARROW modeling","docAbstract":"The SPARROW (SPAtially Referenced Regression on Watershed attributes) model was used to simulate annual phosphorus loads and concentrations in unmonitored stream reaches in California, U.S., and portions of Nevada and Oregon. The model was calibrated using de-trended streamflow and phosphorus concentration data at 80 locations. The model explained 91% of the variability in loads and 51% of the variability in yields for a base year of 2002. Point sources, geological background, and cultivated land were significant sources. Variables used to explain delivery of phosphorus from land to water were precipitation and soil clay content. Aquatic loss of phosphorus was significant in streams of all sizes, with the greatest decay predicted in small- and intermediate-sized streams. Geological sources, including volcanic rocks and shales, were the principal control on concentrations and loads in many regions. Some localized formations such as the Monterey shale of southern California are important sources of phosphorus and may contribute to elevated stream concentrations. Many of the larger point source facilities were located in downstream areas, near the ocean, and do not affect inland streams except for a few locations. Large areas of cultivated land result in phosphorus load increases, but do not necessarily increase the loads above those of geological background in some cases because of local hydrology, which limits the potential of phosphorus transport from land to streams.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12326","usgsCitation":"Domagalski, J.L., and Saleh, D., 2015, Sources and transport of phosphorus to rivers in California and adjacent states, U.S., as determined by SPARROW modeling: Journal of the American Water Resources Association, v. 51, no. 6, p. 1463-1486, https://doi.org/10.1111/1752-1688.12326.","productDescription":"24 p.","startPage":"1463","endPage":"1486","ipdsId":"IP-052538","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":352579,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"6","noUsgsAuthors":false,"publicationDate":"2015-07-14","publicationStatus":"PW","scienceBaseUri":"5afeeb20e4b0da30c1bfc64a","contributors":{"authors":[{"text":"Domagalski, Joseph L. 0000-0002-6032-757X joed@usgs.gov","orcid":"https://orcid.org/0000-0002-6032-757X","contributorId":1330,"corporation":false,"usgs":true,"family":"Domagalski","given":"Joseph","email":"joed@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731207,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Saleh, Dina 0000-0002-1406-9303 dsaleh@usgs.gov","orcid":"https://orcid.org/0000-0002-1406-9303","contributorId":939,"corporation":false,"usgs":true,"family":"Saleh","given":"Dina","email":"dsaleh@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731208,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70160784,"text":"70160784 - 2015 - Large-scale control site selection for population monitoring: an example assessing Sage-grouse trends","interactions":[],"lastModifiedDate":"2015-12-31T13:03:13","indexId":"70160784","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Large-scale control site selection for population monitoring: an example assessing Sage-grouse trends","docAbstract":"Human impacts on wildlife populations are widespread and prolific and understanding wildlife responses to human impacts is a fundamental component of wildlife management. The first step to understanding wildlife responses is the documentation of changes in wildlife population parameters, such as population size. Meaningful assessment of population changes in potentially impacted sites requires the establishment of monitoring at similar, nonimpacted, control sites. However, it is often difficult to identify appropriate control sites in wildlife populations. We demonstrated use of Geographic Information System (GIS) data across large spatial scales to select biologically relevant control sites for population monitoring. Greater sage-grouse (Centrocercus urophasianus; hearafter, sage-grouse) are negatively affected by energy development, and monitoring of sage-grouse population within energy development areas is necessary to detect population-level responses. Weused population data (1995–2012) from an energy development area in Wyoming, USA, the Atlantic Rim Project Area (ARPA), and GIS data to identify control sites that were not impacted by energy development for population monitoring. Control sites were surrounded by similar habitat and were within similar climate areas to the ARPA. We developed nonlinear trend models for both the ARPA and control sites and compared long-term trends from the 2 areas. We found little difference between the ARPA and control sites trends over time. This research demonstrated an approach for control site selection across large landscapes and can be used as a template for similar impact-monitoring studies. It is important to note that identification of changes in population parameters between control and treatment sites is only the first step in understanding the mechanisms that underlie those changes. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.
","language":"English","publisher":"Wiley","doi":"10.1002/wsb.601","usgsCitation":"Fedy, B.C., O’Donnell, M.S., and Bowen, Z.H., 2015, Large-scale control site selection for population monitoring: an example assessing Sage-grouse trends: Wildlife Society Bulletin, v. 39, no. 4, p. 700-712, https://doi.org/10.1002/wsb.601.","productDescription":"13 p.","startPage":"700","endPage":"712","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053414","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":499960,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/1512b0d458ea4c8ab77bd670ee6a3220","text":"External Repository"},{"id":313148,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"South-Central","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.226806640625,\n 42.99259451971113\n ],\n [\n -109.21508789062499,\n 42.97250158602597\n ],\n [\n -109.97863769531249,\n 43.11702412135048\n ],\n [\n -110.841064453125,\n 43.56845179881218\n ],\n [\n -110.841064453125,\n 43.28920196020127\n ],\n [\n -110.9124755859375,\n 42.601619944327965\n ],\n [\n -111.05529785156249,\n 42.589488572714245\n ],\n [\n -111.03881835937499,\n 41.000629848685385\n ],\n [\n -108.2208251953125,\n 41.01721057822846\n ],\n [\n -108.1109619140625,\n 41.27367811566259\n ],\n [\n -107.0562744140625,\n 41.611335399441735\n ],\n [\n -106.3421630859375,\n 41.693424216151314\n ],\n [\n -106.226806640625,\n 42.99259451971113\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"39","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-13","publicationStatus":"PW","scienceBaseUri":"56865fc8e4b0e7594ee74ccf","contributors":{"authors":[{"text":"Fedy, Bradley C.","contributorId":64080,"corporation":false,"usgs":true,"family":"Fedy","given":"Bradley","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":583891,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Donnell, Michael S. 0000-0002-3488-003X odonnellm@usgs.gov","orcid":"https://orcid.org/0000-0002-3488-003X","contributorId":140876,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Michael","email":"odonnellm@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":583890,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bowen, Zachary H. 0000-0002-8656-1831 bowenz@usgs.gov","orcid":"https://orcid.org/0000-0002-8656-1831","contributorId":821,"corporation":false,"usgs":true,"family":"Bowen","given":"Zachary","email":"bowenz@usgs.gov","middleInitial":"H.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":583892,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70159816,"text":"70159816 - 2015 - Evaluating potential conservation conflicts between two listed species: Sea otters and black abalone","interactions":[],"lastModifiedDate":"2015-11-30T11:51:28","indexId":"70159816","displayToPublicDate":"2015-11-30T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3835,"text":"Ecology, Evolution, and Systematics","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating potential conservation conflicts between two listed species: Sea otters and black abalone","docAbstract":"Population consequences of endangered species interacting as predators and prey have been considered theoretically and legally, but rarely investigated in the field. We examined relationships between spatially variable populations of a predator, the California sea otter, Enhydra lutris nereis, and a prey species, the black abalone, Haliotis cracherodii. Both species are federally listed under the Endangered Species Act and co-occur along the coast of California. We compared the local abundance and habitat distribution of black abalone at 12 sites with varying densities of sea otters. All of the populations of abalone we examined were in the geographic area currently unaffected by withering disease, which has decimated populations south of the study area. Surprisingly, our findings indicate that sea otter density is positively associated with increased black abalone density. The presence of sea otters also correlated with a shift in black abalone to habitat conferring greater refuge, which could decrease illegal human harvest. These results highlight the need for a multi-species approach to conservation management of the two species, and demonstrate the importance of using field-collected data rather than simple trophic assumptions to understand relationships between jointly vulnerable predator and prey populations.
Many arid and semiarid ecosystems have soils covered with well-developed biological soil crust communities (biocrusts) made up of mosses, lichens, cyanobacteria, and heterotrophs living at the soil surface. These communities are a fundamental component of dryland ecosystems, and are critical to dryland carbon (C) cycling. To examine the effects of warming temperatures on soil C balance in a dryland ecosystem, we used infrared heaters to warm biocrust-dominated soils to 2 °C above control conditions at a field site on the Colorado Plateau, USA. We monitored net soil exchange (NSE) of CO2 every hour for 21 months using automated flux chambers (5 control and 5 warmed chambers), which included the CO2 fluxes of the biocrusts and the soil beneath them. We observed measurable photosynthesis in biocrust soils on 12 % of measurement days, which correlated well with precipitation events and soil wet-up. These days included several snow events, providing what we believe to be the first evidence of substantial photosynthesis underneath snow by biocrust organisms in drylands. Overall, biocrust soils in both control and warmed plots were net CO2 sources to the atmosphere, with control plots losing 62 ± 8 g C m−2 (mean ± SE) over the first year of measurement and warmed plots losing 74 ± 9 g C m−2. Between control and warmed plots, the difference in soil C loss was uncertain over the course of the entire year due to large and variable rates in spring, but on days during which soils were wet and crusts were actively photosynthesizing, biocrusts that were warmed by 2 °C had a substantially more negative C balance (i.e., biocrust soils took up less C and/or lost more C in warmed plots). Taken together, our data suggest a substantial risk of increased C loss from biocrust soils with higher future temperatures, and highlight a robust capacity to predict CO2 exchange in biocrust soils using easily measured environmental parameters.
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- 2015 - A broader definition of occupancy: A reply to Hayes and Monofils","interactions":[],"lastModifiedDate":"2016-02-16T14:09:30","indexId":"70168478","displayToPublicDate":"2015-11-26T00:00:00","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":"A broader definition of occupancy: A reply to Hayes and Monofils","docAbstract":"Occupancy models are widely used to analyze presence–absence data for a variety of taxa while accounting for observation error (MacKenzie et al. 2002, 2006; Tyre et al. 2003; Royle and Dorazio 2008). Hayes and Monfils (2015) question their use for analyzing avian point count data based on purported violations of model assumptions incurred by avian mobility. Animal mobility is an important consideration, not just for occupancy models, but for a variety of population and habitat models (Boyce 2006, Royle et al. 2009, Manning and Goldberg 2010, Dormann et al. 2013, Renner et al. 2015). Nevertheless, we believe the ultimate conclusions of Hayes and Monfils are shortsighted mainly due to a narrow interpretation of occupancy. Rather than turn away from the use of occupancy models, we believe they remain an appropriate method for analyzing many data sets collected from avian point count surveys. Further, we suggest that there is value in having a broader and more nuanced interpretation of occupancy that incorporates the potential for animal movement.
\nThe critical role of rare earth elements (REEs), particularly heavy REEs (HREEs), in high-tech industries has created a surge in demand that is quickly outstripping known global supply and has triggered a worldwide scramble to discover new sources. The chemical analysis of 23 sedimentary phosphate deposits (phosphorites) in the United States demonstrates that they are significantly enriched in REEs. Leaching experiments using dilute H2SO4 and HCl, extracted nearly 100% of their total REE content and show that the extraction of REEs from phosphorites is not subject to the many technological and environmental challenges that vex the exploitation of many identified REE deposits. Our data suggest that phosphate rock currently mined in the United States has the potential to produce a significant proportion of the world's REE demand as a byproduct. Importantly, the size and concentration of HREEs in some unmined phosphorites dwarf the world's richest REE deposits. Secular variation in phosphate REE contents identifies geologic time periods favorable for the formation of currently unrecognized high-REE phosphates. The extraordinary endowment, combined with the ease of REE extraction, indicates that such phosphorites might be considered as a primary source of REEs with the potential to resolve the global REE (particularly for HREE) supply shortage.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gr.2014.10.008","usgsCitation":"Emsbo, P., McLaughlin, P.I., Breit, G.N., du Bray, E.A., and Koenig, A.E., 2015, Rare earth elements in sedimentary phosphate deposits: Solution to the global REE crisis?: Gondwana Research, v. 27, no. 2, p. 776-785, https://doi.org/10.1016/j.gr.2014.10.008.","productDescription":"10 p.","startPage":"776","endPage":"785","ipdsId":"IP-053368","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":471624,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gr.2014.10.008","text":"Publisher Index Page"},{"id":342853,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59521d20e4b062508e3c3676","contributors":{"authors":[{"text":"Emsbo, Poul 0000-0001-9421-201X pemsbo@usgs.gov","orcid":"https://orcid.org/0000-0001-9421-201X","contributorId":997,"corporation":false,"usgs":true,"family":"Emsbo","given":"Poul","email":"pemsbo@usgs.gov","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":700467,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McLaughlin, Patrick I.","contributorId":105165,"corporation":false,"usgs":true,"family":"McLaughlin","given":"Patrick","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":700473,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Breit, George N. 0000-0003-2188-6798 gbreit@usgs.gov","orcid":"https://orcid.org/0000-0003-2188-6798","contributorId":1480,"corporation":false,"usgs":true,"family":"Breit","given":"George","email":"gbreit@usgs.gov","middleInitial":"N.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":700474,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"du Bray, Edward A. 0000-0002-4383-8394 edubray@usgs.gov","orcid":"https://orcid.org/0000-0002-4383-8394","contributorId":755,"corporation":false,"usgs":true,"family":"du Bray","given":"Edward","email":"edubray@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":700475,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Koenig, Alan E. 0000-0002-5230-0924 akoenig@usgs.gov","orcid":"https://orcid.org/0000-0002-5230-0924","contributorId":1564,"corporation":false,"usgs":true,"family":"Koenig","given":"Alan","email":"akoenig@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":700476,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70134260,"text":"70134260 - 2015 - Remote sensing systems – Platforms and sensors: Aerial, satellites, UAVs, optical, radar, and LiDAR","interactions":[],"lastModifiedDate":"2023-01-02T14:52:45.247243","indexId":"70134260","displayToPublicDate":"2015-11-26T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"1","title":"Remote sensing systems – Platforms and sensors: Aerial, satellites, UAVs, optical, radar, and LiDAR","docAbstract":"The American Society of Photogrammetry and Remote Sensing defined remote sensing as the measurement or acquisition of information of some property of an object or phenomenon, by a recording device that is not in physical or intimate contact with the object or phenomenon under study (Colwell et al., 1983). Environmental Systems Research Institute (ESRI) in its geographic information system (GIS) dictionary defines remote sensing as “collecting and interpreting information about the environment and the surface of the earth from a distance, primarily by sensing radiation that is naturally emitted or reflected by the earth’s surface or from the atmosphere, or by sending signals transmitted from a device and reflected back to it (ESRI, 2014).” The usual source of passive remote sensing data is the measurement of reflected or transmitted electromagnetic radiation (EMR) from the sun across the electromagnetic spectrum (EMS); this can also include acoustic or sound energy, gravity, or the magnetic field from or of the objects under consideration. In this context, the simple act of reading this text is considered remote sensing. In this case, the eye acts as a sensor and senses the light reflected from the object to obtain information about the object. It is the same technology used by a handheld camera to take a photograph of a person or a distant scenic view. Active remote sensing, however, involves sending a pulse of energy and then measuring the returned energy through a sensor (e.g., Radio Detection and Ranging [RADAR], Light Detection and Ranging [LiDAR]). Thermal sensors measure emitted energy by different objects. Thus, in general, passive remote sensing involves the measurement of solar energy reflected from the Earth’s surface, while active remote sensing involves synthetic (man-made) energy pulsed at the environment and the return signals are measured and recorded.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Remotely sensed data characterization, classification, and accuracies","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"CRC Press","publisherLocation":"Boca Raton, FL","usgsCitation":"Panda, S.S., Rao, M.N., Thenkabail, P.S., and Fitzerald, J.E., 2015, Remote sensing systems – Platforms and sensors: Aerial, satellites, UAVs, optical, radar, and LiDAR, chap. 1 of Remotely sensed data characterization, classification, and accuracies, p. 3-57.","productDescription":"55 p.","startPage":"3","endPage":"57","ipdsId":"IP-060641","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":342120,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":411272,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.taylorfrancis.com/chapters/edit/10.1201/b19294-8/remote-sensing-systems%E2%80%94platforms-sensors-aerial-satellite-uav-optical-radar-lidar-sudhanshu-panda-mahesh-rao-prasad-%C2%82enkabail-james-fitzerald?context=ubx&refId=44b9585a-fc6b-4fa8-9f55-6c56552074ed"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59366da9e4b0f6c2d0d7d62c","contributors":{"authors":[{"text":"Panda, Sudhanshu S.","contributorId":127587,"corporation":false,"usgs":false,"family":"Panda","given":"Sudhanshu","email":"","middleInitial":"S.","affiliations":[{"id":7066,"text":"University of North Georgia","active":true,"usgs":false}],"preferred":false,"id":697141,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rao, Mahesh N.","contributorId":127588,"corporation":false,"usgs":false,"family":"Rao","given":"Mahesh","email":"","middleInitial":"N.","affiliations":[{"id":7067,"text":"Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":525767,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thenkabail, Prasad S. 0000-0002-2182-8822 pthenkabail@usgs.gov","orcid":"https://orcid.org/0000-0002-2182-8822","contributorId":570,"corporation":false,"usgs":true,"family":"Thenkabail","given":"Prasad","email":"pthenkabail@usgs.gov","middleInitial":"S.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":525765,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fitzerald, James E.","contributorId":127589,"corporation":false,"usgs":false,"family":"Fitzerald","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":7068,"text":"Cobb County Government, GA","active":true,"usgs":false}],"preferred":false,"id":697142,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159774,"text":"fs20153081 - 2015 - Landsat—Earth observation satellites","interactions":[{"subject":{"id":70038609,"text":"fs20123072 - 2012 - Landsat: A global land-imaging mission","indexId":"fs20123072","publicationYear":"2012","noYear":false,"title":"Landsat: A global land-imaging mission"},"predicate":"SUPERSEDED_BY","object":{"id":70159774,"text":"fs20153081 - 2015 - Landsat—Earth observation satellites","indexId":"fs20153081","publicationYear":"2015","noYear":false,"title":"Landsat—Earth observation satellites"},"id":1},{"subject":{"id":70047982,"text":"fs20133060 - 2013 - Landsat 8","indexId":"fs20133060","publicationYear":"2013","noYear":false,"title":"Landsat 8"},"predicate":"SUPERSEDED_BY","object":{"id":70159774,"text":"fs20153081 - 2015 - Landsat—Earth observation satellites","indexId":"fs20153081","publicationYear":"2015","noYear":false,"title":"Landsat—Earth observation satellites"},"id":2}],"lastModifiedDate":"2022-08-24T16:34:32.839169","indexId":"fs20153081","displayToPublicDate":"2015-11-25T11:00:00","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":"2015-3081","displayTitle":"Landsat—Earth Observation Satellites","title":"Landsat—Earth observation satellites","docAbstract":"Since 1972, Landsat satellites have continuously acquired space-based images of the Earth’s land surface, providing data that serve as valuable resources for land use/land change research. The data are useful to a number of applications including forestry, agriculture, geology, regional planning, and education. Landsat is a joint effort of the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). NASA develops remote sensing instruments and the spacecraft, then launches and validates the performance of the instruments and satellites. The USGS then assumes ownership and operation of the satellites, in addition to managing all ground reception, data archiving, product generation, and data distribution. The result of this program is an unprecedented continuing record of natural and human-induced changes on the global landscape.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153081","usgsCitation":"U.S. Geological Survey, 2015, Landsat—Earth observation satellites (ver. 1.4, August 2022): U.S. Geological Survey Fact Sheet 2015–3081, 4 p., https://doi.org/10.3133/fs20153081.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068422","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":311694,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2015/3081/coverthb5.jpg"},{"id":405531,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3081/fs20153081.pdf","text":"Report","size":"4.58 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2015–3081"},{"id":405532,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/fs/2015/3081/versionHist.txt","text":"Version History","size":"13.9 kB","linkFileType":{"id":2,"text":"txt"},"description":"FS 2015–3081 Version History"}],"edition":"Version 1.0: November 25, 2015; Version 1.1: August 22, 2016; Version 1.2: April 8, 2020; Version 1.3: August 3, 2022; Version 1.4: August 24, 2022","contact":"Earth Resources Observation and Science (EROS) Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2015-11-25","revisedDate":"2022-08-24","noUsgsAuthors":false,"publicationDate":"2015-11-25","publicationStatus":"PW","scienceBaseUri":"5656dbabe4b071e7ea53eeb5","contributors":{"authors":[{"text":"U.S. Geological Survey","contributorId":128240,"corporation":true,"usgs":false,"organization":"U.S. Geological Survey","id":580391,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70159804,"text":"70159804 - 2015 - Changes in seasonality and timing of peak streamflow in snow and semi-arid climates of the north-central United States, 1910–2012","interactions":[],"lastModifiedDate":"2017-10-12T20:00:47","indexId":"70159804","displayToPublicDate":"2015-11-24T16:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Changes in seasonality and timing of peak streamflow in snow and semi-arid climates of the north-central United States, 1910–2012","docAbstract":"
Changes in the seasonality and timing of annual peak streamflow in the north-central USA are likely because of changes in precipitation and temperature regimes. A source of long-term information about flood events across the study area is the U.S. Geological Survey peak streamflow database. However, one challenge of answering climate-related questions with this dataset is that even in snowmelt-dominated areas, it is a mixed population of snowmelt/spring rain generated peaks and summer/fall rain generated peaks. Therefore, a process was developed to divide the annual peaks into two populations, or seasons, snowmelt/spring, and summer/fall. The two series were then tested for the hypotheses that because of changes in precipitation regimes, the odds of summer/fall peaks have increased and, because of temperature changes, snowmelt/spring peaks happen earlier. Over climatologically and geographically similar regions in the north-central USA, logistic regression was used to model the odds of getting a summer/fall peak. When controlling for antecedent wet and dry conditions and geographical differences, the odds of summer/fall peaks occurring have increased across the study area. With respect to timing within the seasons, trend analysis showed that in northern portions of the study region, snowmelt/spring peaks are occurring earlier. The timing of snowmelt/spring peaks in three regions in the northern part of the study area is earlier by 8.7– 14.3 days. These changes have implications for water interests, such as potential changes in lead-time for flood forecasting or changes in the operation of flood-control dams.
","language":"English","publisher":"John Wiley & Sons","doi":"10.1002/hyp.10693","usgsCitation":"Ryberg, K.R., Akyuz, F.A., Wiche, G.J., and Lin, W., 2015, Changes in seasonality and timing of peak streamflow in snow and semi-arid climates of the north-central United States, 1910–2012: Hydrological Processes, v. 30, no. 8, p. 1208-1218, https://doi.org/10.1002/hyp.10693.","productDescription":"11 p.","startPage":"1208","endPage":"1218","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"1910-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-059283","costCenters":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":311699,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Iowa, Kansas, Minnesota, Missouri, Montana, Nebraska, North Dakota, South Dakota, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.7353515625,\n 48.574789910928864\n ],\n [\n -91.23046875,\n 43.45291889355465\n ],\n [\n -90.263671875,\n 42.00032514831621\n ],\n [\n -91.4501953125,\n 40.38002840251183\n ],\n [\n -90.8349609375,\n 39.13006024213511\n ],\n [\n -102.1728515625,\n 38.61687046392973\n ],\n [\n -105.77636718749999,\n 38.92522904714054\n ],\n [\n -109.4677734375,\n 45.01141864227728\n ],\n [\n -113.09326171875,\n 48.99463598353408\n ],\n [\n -95.20751953125,\n 49.009050809382046\n ],\n [\n -93.7353515625,\n 48.574789910928864\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"8","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-11","publicationStatus":"PW","scienceBaseUri":"56558a32e4b071e7ea53dedf","chorus":{"doi":"10.1002/hyp.10693","url":"http://dx.doi.org/10.1002/hyp.10693","publisher":"Wiley-Blackwell","authors":"Ryberg Karen R., Akyüz F. Adnan, Wiche Gregg J., Lin Wei","journalName":"Hydrological Processes","publicationDate":"11/11/2015","auditedOn":"4/11/2016"},"contributors":{"authors":[{"text":"Ryberg, Karen R. 0000-0002-9834-2046 kryberg@usgs.gov","orcid":"https://orcid.org/0000-0002-9834-2046","contributorId":1172,"corporation":false,"usgs":true,"family":"Ryberg","given":"Karen","email":"kryberg@usgs.gov","middleInitial":"R.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":580536,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Akyuz, F. Adnan","contributorId":140760,"corporation":false,"usgs":false,"family":"Akyuz","given":"F.","email":"","middleInitial":"Adnan","affiliations":[{"id":13555,"text":"North Dakota Climate Office","active":true,"usgs":false}],"preferred":false,"id":580538,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wiche, Gregg J. gjwiche@usgs.gov","contributorId":1675,"corporation":false,"usgs":true,"family":"Wiche","given":"Gregg","email":"gjwiche@usgs.gov","middleInitial":"J.","affiliations":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":580539,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lin, Wei","contributorId":93805,"corporation":false,"usgs":true,"family":"Lin","given":"Wei","email":"","affiliations":[],"preferred":false,"id":580537,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70158680,"text":"sir20155131 - 2015 - Aquifer geometry, lithology, and water levels in the Anza–Terwilliger area—2013, Riverside and San Diego Counties, California","interactions":[],"lastModifiedDate":"2015-11-25T08:14:40","indexId":"sir20155131","displayToPublicDate":"2015-11-24T16:00:00","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":"2015-5131","title":"Aquifer geometry, lithology, and water levels in the Anza–Terwilliger area—2013, Riverside and San Diego Counties, California","docAbstract":"The population of the Anza–Terwilliger area relies solely on groundwater pumped from the alluvial deposits and surrounding bedrock formations for water supply. The size, characteristics, and current conditions of the aquifer system in the Anza–Terwilliger area are poorly understood, however. In response to these concerns, the U.S. Geological Survey, in cooperation with the High Country Conservancy and Rancho California Water District, undertook a study to (1) improve mapping of groundwater basin geometry and lithology and (2) to resume groundwater-level monitoring last done during 2004–07 in the Anza–Terwilliger area.
\nInversion of gravity data, including new data collected for this study, was done to estimate the thickness of the alluvial deposits that form the Cahuilla and Terwilliger groundwater basins and to understand the geometry of the underlying basement complex. After processing of the gravity data, the thickness of the alluvial aquifer materials was modeled by using all available lithology, density, and geophysical data.
\nThe thickest alluvial deposits (greater than 500 feet) are in the northern part of the study area along the south side of the San Jacinto fault zone, in the southern part of the Cahuilla groundwater basin, and in the western part of the Terwilliger groundwater basin. Through most of the area of alluvial materials, the thickness of the alluvium estimated from gravity data is less than 400 feet.
\nAnalysis of more than 900 drillers’ logs indicated that in areas having relatively thick alluvium, particularly along the San Jacinto fault zone and in the Terwilliger Valley, the alluvium is predominantly composed of sands and gravels. Fine-textured sediments appeared to be discontinuous rather than forming laterally extensive, low-permeability layers. More than 500 drillers’ logs indicated only bedrock is present, indicating that the fractured bedrock is an important source of groundwater, primarily for domestic use, in the study area. The depths of the holes drilled into the bedrock indicated that fractures potentially supplying water to wells persist in the upper few hundred feet and that the permeable zone of the fractured bedrock extends to depths greater than weathered zones in the upper part of the basement complex.
\nWater-level data were collected from 59 wells during fall 2013. These data indicated that hydraulic head did not vary substantially with well depth and that the measured water levels in bedrock and alluvium were similar. Large offsets in groundwater altitude across the San Jacinto fault zone indicated that the fault zone is a barrier to groundwater flow in the northeastern part of the Anza Valley.
\nOn the basis of data from 33 wells, water levels mostly declined between the fall of 2006 and the fall of 2013; the median decline was 5.1 feet during this period, for a median rate of decline of about 0.7 feet/year. Based on data from 40 wells, water-level changes between fall 2004 and fall 2013 were variable in magnitude and trend, but had a median decline of 2.4 feet and a median rate of decline of about 0.3 feet/ year. These differences in apparent rates of groundwater-level change highlight the value of ongoing water-level measurements to distinguish decadal, or longer term, trends in groundwater storage often associated with climatic variability and trends. Fifty-four long-term hydrographs indicated the sensitivity of groundwater levels to climatic conditions; they also showed a general decline in water levels across the study area since 1986 and, in some cases, dating back to the 1950s.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155131","collaboration":"Prepared in cooperation with the High Country Conservancy and Rancho California Water District","usgsCitation":"Landon, M.K., Morita, A.Y., Nawikas, J.M., Christensen, A.H., Faunt, C.C., and Langenheim, V.E., 2015, Aquifer geometry, lithology, and water levels in the Anza–Terwilliger Area—2013, Riverside and San Diego Counties, California: U.S. Geological Survey Scientific Investigations Report 2015–5131, 30 p.\nhttps://dx.doi.org/10.3133/sir20155131.","productDescription":"Report: iv, 30 p.; Appendixes: 1-4","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2013-01-01","temporalEnd":"2013-12-31","ipdsId":"IP-057158","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":311697,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5131/sir20155131.pdf","text":"Report","size":"2.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5131"},{"id":311696,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5131/coverthb.jpg"},{"id":311698,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5131/sir20155131_appendixes.xlsx","text":"Appendixes 1–4","size":"422 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5131 Appendixes 1-4"}],"country":"United States","state":"California","county":"Riverside County, San Diego County","otherGeospatial":"Anza–Terwilliger Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.82174682617188,\n 33.426856918285004\n ],\n [\n -116.82174682617188,\n 33.59803478218408\n ],\n [\n -116.51481628417967,\n 33.59803478218408\n ],\n [\n -116.51481628417967,\n 33.426856918285004\n ],\n [\n -116.82174682617188,\n 33.426856918285004\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, CA 95819
http://ca.water.usgs.gov
Wildlife managers need reliable methods to estimate large carnivore densities and population trends; yet large carnivores are elusive, difficult to detect, and occur at low densities making traditional approaches intractable. Recent advances in spatial capture-recapture (SCR) models have provided new approaches for monitoring trends in wildlife abundance and these methods are particularly applicable to large carnivores. We applied SCR models in a Bayesian framework to estimate mountain lion densities in the Bitterroot Mountains of west central Montana. We incorporate an existing resource selection function (RSF) as a density covariate to account for heterogeneity in habitat use across the study area and include data collected from harvested lions. We identify individuals through DNA samples collected by (1) biopsy darting mountain lions detected in systematic surveys of the study area, (2) opportunistically collecting hair and scat samples, and (3) sampling all harvested mountain lions. We included 80 DNA samples collected from 62 individuals in the analysis. Including information on predicted habitat use as a covariate on the distribution of activity centers reduced the median estimated density by 44%, the standard deviation by 7%, and the width of 95% credible intervals by 10% as compared to standard SCR models. Within the two management units of interest, we estimated a median mountain lion density of 4.5 mountain lions/100 km2 (95% CI = 2.9, 7.7) and 5.2 mountain lions/100 km2 (95% CI = 3.4, 9.1). Including harvested individuals (dead recovery) did not create a significant bias in the detection process by introducing individuals that could not be detected after removal. However, the dead recovery component of the model did have a substantial effect on results by increasing sample size. The ability to account for heterogeneity in habitat use provides a useful extension to SCR models, and will enhance the ability of wildlife managers to reliably and economically estimate density of wildlife populations, particularly large carnivores.
The Borrego Valley is a small valley (110 square miles) in the northeastern part of San Diego County, California. Although the valley is about 60 miles northeast of city of San Diego, it is separated from the Pacific Ocean coast by the mountains to the west and is mostly within the boundaries of Anza-Borrego Desert State Park. From the time the basin was first settled, groundwater has been the only source of water to the valley. Groundwater is used for agricultural, recreational, and municipal purposes. Over time, groundwater withdrawal through pumping has exceeded the amount of water that has been replenished, causing groundwater-level declines of more than 100 feet in some parts of the basin. Continued pumping has resulted in an increase in pumping lifts, reduced well efficiency, dry wells, changes in water quality, and loss of natural groundwater discharge. As a result, the U.S. Geological Survey began a cooperative study of the Borrego Valley with the Borrego Water District (BWD) in 2009. The purpose of the study was to develop a greater understanding of the hydrogeology of the Borrego Valley Groundwater Basin (BVGB) and to provide tools to help evaluate the potential hydrologic effects of future development. The objectives of the study were to (1) improve the understanding of groundwater conditions and land subsidence, (2) incorporate this improved understanding into a model that would assist in the management of the groundwater resources in the Borrego Valley, and (3) use this model to test several management scenarios. This model provides the capability for the BWD and regional stakeholders to quantify the relative benefits of various options for increasing groundwater storage. The study focuses on the period 1945–2010, with scenarios 50 years into the future.
\nThis report documents and presents (1) an analysis of the conceptual model, (2) a description of the hydrologic features, (3) a compilation and analysis of water-quality data, (4) the measurement and analysis of land subsidence by using geophysical and remote sensing techniques, (5) the development and calibration of a two-dimensional borehole-groundwater-flow model to estimate aquifer hydraulic conductivities, (6) the development and calibration of a three-dimensional (3-D) integrated hydrologic flow model, (7) a water-availability analysis with respect to current climate variability and land use, and (8) potential future management scenarios. The integrated hydrologic model, referred to here as the “Borrego Valley Hydrologic Model” (BVHM), is a tool that can provide results with the accuracy needed for making water-management decisions, although potential future refinements and enhancements could further improve the level of spatial and temporal resolution and model accuracy. Because the model incorporates time-varying inflows and outflows, this tool can be used to evaluate the effects of temporal changes in recharge and pumping and to compare the relative effects of different water-management scenarios on the aquifer system. Overall, the development of the hydrogeologic and hydrologic models, data networks, and hydrologic analysis provides a basis for assessing surface and groundwater availability and potential water-resource management guidelines.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155150","collaboration":"Prepared in cooperation with the Borrego Water District","usgsCitation":"Faunt, C.C., Stamos, C.L., Flint, L.E., Wright, M.T., Burgess, M.K., Sneed, Michelle, Brandt, Justin, Martin, Peter, and Coes, A.L., 2015, Hydrogeology, hydrologic effects of development, and simulation of groundwater flow in the Borrego Valley, San Diego County, California: U.S. Geological Survey Scientific Investigations Report 2015–5150, 135 p., https://dx.doi.org/10.3133/sir20155150.","productDescription":"xiv, 135 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-024573","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":311633,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5150/sir20155150.pdf","text":"Report","size":"21.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5150"},{"id":311632,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5150/coverthb.jpg"},{"id":311671,"rank":3,"type":{"id":18,"text":"Project Site"},"url":"https://dx.doi.org/10.5066/F7S180J9","text":"Borrego Valley Groundwater Conditions"},{"id":314004,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2015/5150/sir20155150_input.zip","text":"Model Input","size":"420 KB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2015-5150 Model Input files"},{"id":314005,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2015/5150/sir20155150_output.zip","text":"Model Output","size":"45 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2015-5150 Model Output files"}],"country":"United States","state":"California","otherGeospatial":"Borrego Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.54708862304686,\n 32.89342578969234\n ],\n [\n -116.54708862304686,\n 33.34659043589842\n ],\n [\n -115.73272705078124,\n 33.34659043589842\n ],\n [\n -115.73272705078124,\n 32.89342578969234\n ],\n [\n -116.54708862304686,\n 32.89342578969234\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, CA 95819
http://ca.water.usgs.gov
The Northern Range (NR) of Yellowstone National Park (YNP) hosts a higher prey biomass density in the form of elk (Cervus elaphus L., 1758) than any other system of gray wolves (Canis lupus L., 1758) and prey reported. Therefore, it is important to determine whether that wolf–prey system fits a long-standing model relating wolf density to prey biomass. Using data from 2005 to 2012 after elk population fluctuations dampened 10 years subsequent to wolf reintroduction, we found that NR prey biomass predicted wolf density. This finding and the trajectory of the regression extend the validity of the model to prey densities 19% higher than previous data and suggest that the model would apply to wolf–prey systems of even higher prey biomass.
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dioxide-enriched water. Concentrations of uranium, collected from ten depth intervals, ranged from 5 to 1920 ppm. A composite sample contained 750 ppm uranium with an average oxidation state of 54% U(VI) and 46% U(IV). Scanning electron microscopy (SEM) indicated rare high uranium (∼1000 ppm U) in spatial association with P/Ca and Si/O attributed to relict uranium minerals, possibly coffinite, uraninite, and autunite, trapped within low permeability layers bypassed during ISR mining. Fission track analysis revealed lower but still elevated concentrations of U in the clay/silica matrix and organic matter (several 10 s ppm) and yet higher concentrations associated with Fe-rich/S-poor sites, likely iron oxides, on altered chlorite or euhedral pyrite surfaces (but not on framboidal pyrite). Organic C (<1.62%), total S (<0.31%), and P (<0.03%) were in low abundance relative to the overall bulk composition. Microbial community analysis showed a diverse group of bacteria present with a wide range of putative metabolisms, and provides evidence for a variety of redox microenvironments co-existing in core samples. Although the uranium minerals persisting in low permeability areas in association with organic carbon were less affected by oxidizing solutions during mining, the likely sequestration of uranium within labile iron oxides following mining and sensitivity to changes in redox conditions requires careful attention during groundwater restoration.
\n\n
A groundwater-flow model was developed for the Bad River Watershed and surrounding area by using the U.S. Geological Survey (USGS) finite-difference code MODFLOW-NWT. The model simulates steady-state groundwater-flow and base flow in streams by using the streamflow routing (SFR) package. The objectives of this study were to: (1) develop an improved understanding of the groundwater-flow system in the Bad River Watershed at the regional scale, including the sources of water to the Bad River Band of Lake Superior Chippewa Reservation (Reservation) and groundwater/surface-water interactions; (2) provide a quantitative platform for evaluating future impacts to the watershed, which can be used as a starting point for more detailed investigations at the local scale; and (3) identify areas where more data are needed. This report describes the construction and calibration of the groundwater-flow model that was subsequently used for analyzing potential locations for the collection of additional field data, including new observations of water-table elevation for refining the conceptualization and corresponding numerical model of the hydrogeologic system.
\nThe study area can be conceptually divided into three primary hydrogeologic environments. The first encompasses the southern uplands with relatively low topographic relief, where groundwater-flow is unconfined and occurs primarily in sandy till and glacial outwash overlying Archean-aged crystalline bedrock. The second includes a transitional area of higher topographic relief and shallow depth to bedrock, in the vicinity of ridges formed by steeply dipping, early-Proterozoic aged metasedimentary units of the Marquette Range Supergroup (including the Ironwood Formation), and late-Proterozoic igneous units associated with the Midcontinent Rift System (MRS). Groundwater-flow in this area likely occurs primarily through connected networks of bedrock fractures that are not well characterized, and also in isolated pockets of Quaternary deposits. The third and last hydrogeologic environment includes lowlands along Lake Superior where a deep sandstone aquifer is confined by thick deposits of clay-rich till.
\nModel input was compiled by using both published and unpublished data. Constant flux boundary conditions for the model perimeter were developed from a regional analytic element model described in appendix 1 of this report. Pumping from 26 high-capacity wells within the model area was included. The SFR stream network was developed from the National Hydrography Dataset (NHDPlus Version 2) and hydrography from the Wisconsin Department of Natural Resources (WDNR). Hydraulic conductivity values were determined for each model cell by interpolation from a network of pilot points, within zones representing major hydrogeologic units.
\nRecharge to the groundwater system was estimated on a cell-by-cell basis by using the Soil Water Balance code (SWB), with gridded daily temperature and precipitation data for the period 1980–2011, and GIS coverages of soil and land-surface conditions. Estimated recharge varies considerably, following spatial patterns in the precipitation and soil hydrologic group inputs. The lowest recharge values occur in the Superior lowlands, whereas the highest values occur in the upland areas, especially those underlain by sandy soils, and in the vicinity of bedrock hills.
\nThe model was calibrated to groundwater-levels and base flows obtained from the USGS National Water Information System (NWIS) database, and groundwater-levels obtained from the WDNR and Band River Band well-construction databases. Calibration was performed via nonlinear regression by using the parameter-estimation software suite PEST. Groundwater levels and base-flow observations in the calibration dataset were well simulated by the calibrated model, with reasonable values of hydraulic conductivity. The pilot-point parameters that were most constrained by observations during model calibration coincided with the locations containing the most wells (head observations)—especially the population centers of Ashland, Mellen, and other communities along the major highway corridors.
\nResults from the calibrated model illustrate differences in the nature of groundwater-flow within the watershed. In the southern part of the watershed, where bedrock is shallow, groundwater flow paths are relatively short, extending from local recharge areas to adjacent first and second-order streams. In contrast, laterally continuous deposits of clay-rich till covering the Superior Lowlands isolate most smaller streams from the sandstone aquifer, allowing for longer flow paths toward larger streams such as the Bad, Marengo, and White Rivers. Approximately three-quarters of all first-order stream cells were dry in the Superior Lowlands, compared to only half of first-order stream cells in the southern bedrock uplands.
\nThe model was used to delineate the groundwatershed for the Bad and Kakagon Rivers. “Groundwatershed” is defined as the area contributing groundwater discharge to one of these streams and their tributaries. The groundwatershed was found to align closely with the surface-watershed, with the most notable exception occurring along the southwestern half of Birch Hill, where surface water drains southwest towards the Potato River, and groundwater flows north and east towards Lake Superior. Similarly, the contributing area of groundwater-flow to the Reservation was delineated. Results indicate the off-Reservation groundwater contributing area to be limited in comparison to the extent of the watershed, extending southward into the highlands underlain by MRS igneous rock units, but not further into the area underlain by the Marquette Range Supergroup.
\nStable isotope samples were collected from 54 wells within the watershed, to investigate sources of groundwater. Oxygen-18 (δ 18O) values lower than -13.0 per mil were documented in the sampling, and likely indicate the presence of recharge water from the last glacial period (>9,500 years old) beneath the northern portion of the Reservation, in the vicinity of Odanah, Wisconsin.
\nFinally, a new data-worth analysis of potential new monitoring-well locations was performed by using the model. The relative worth of new measurements was evaluated based on their ability to increase confidence in model predictions of groundwater levels and base flows at 35 locations, under the condition of a proposed open-pit iron mine. Results of the new data-worth analysis, and other inputs and outputs from the Bad River model, are available through an online dynamic web mapping service at (http://wim.usgs.gov/badriver/).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155162","collaboration":"Prepared in cooperation with the Bad River Band of Lake Superior Chippewa; U.S. Bureau of Indian Affairs","usgsCitation":"Leaf, A.T., Fienen, M.N., Hunt, R.J., and Buchwald, C.A., 2015, Groundwater/Surface-Water Interactions in the Bad\n River Watershed, Wisconsin: U.S. Geological Survey Scientific Investigations Report 2015–5162, 110 p., https://dx.doi.org/10.3133/sir20155162.","productDescription":"viii, 110 p.","numberOfPages":"122","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-061535","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":311584,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5162/coverthb.jpg"},{"id":311585,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5162/sir20155162.pdf","text":"Report","size":"24.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015=5162"},{"id":332726,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7Z0368H","text":"MODFLOW-NWT model used to evaluate groundwater/surface-water interactions in the Bad River Watershed, Wisconsin"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Bad River Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.06842041015625,\n 46.36777895261494\n ],\n [\n -91.06842041015625,\n 46.76996843356982\n ],\n [\n -90.43121337890625,\n 46.76996843356982\n ],\n [\n -90.43121337890625,\n 46.36777895261494\n ],\n [\n -91.06842041015625,\n 46.36777895261494\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wisconsin Water Science Center
U.S. Geological Survey
8505 Research W
Middleton, WI USA 53562
http://wi.water.usgs.gov/
In 2006, the U.S. Geological Survey, in cooperation with the Town of Danby and the Tompkins County Planning Department, began a study of the stratified-drift aquifers in the upper Buttermilk Creek and Danby Creek valleys in the Town of Danby, Tompkins County, New York. In the northern part of the north-draining upper Buttermilk Creek valley, there is only one sand and gravel aquifer, a confined basal unit that overlies bedrock. In the southern part of upper Buttermilk Creek valley, there are as many as four sand and gravel aquifers, two are unconfined and two are confined. In the south-draining Danby Creek valley, there is an unconfined aquifer consisting of outwash and kame sand and gravel (deposited by glacial meltwaters during the late Pleistocene Epoch) and alluvial silt, sand, and gravel (deposited by streams during the Holocene Epoch). In addition, throughout the study area, there are several small local unconfined aquifers where large tributaries deposited alluvial fans in the valley.
\nThe principal sources of recharge to the unconfined aquifers in the study area include direct infiltration of precipitation (rain and snowmelt) at land surface, unchanneled surface runoff from adjacent hillsides that seeps into the aquifer along the edges of the valley, groundwater inflow from adjacent till and bedrock that enters the aquifer along the sides of the valley, and seepage loss from upland-tributary streams where they flow over their alluvial fans in the valley. The percentages of all sources of recharge to the contiguous unconfined aquifer in Danby Creek valley include 16 percent from precipitation that falls directly over the aquifer, 55 percent from unchanneled surface runoff and groundwater inflow from hillsides, and 29 percent from losing tributary streams that cross the aquifer. The total annual recharge to the contiguous unconfined aquifer is 2.56 cubic feet per second (604 million gallons per year).
\nThe principal sources of recharge to the confined aquifers include precipitation that falls directly on the surficial confining unit, which then slowly flows vertically downward through the fine-grained sediments and enters the confined aquifer, and groundwater inflow from till and bedrock that borders the aquifer along adjacent hillsides and at the bottom of the valley. In addition, there is substantial amounts of recharge to the confined aquifers where the confining units are locally absent (forming windows) and where parts of the confining units consist of sediments of low to moderate permeability (forming a semiconfining layer).
\nIn the northern part of the study area (upper Buttermilk Creek valley), groundwater in the stratified-drift aquifers discharges to (1) domestic and commercial wells; (2) Buttermilk Creek in the area near the northern town border, and (3) and a small unnamed stream in a ravine in Buttermilk State Park just north of the town border. In the southern part of the study area (Danby Creek valley), groundwater discharges (1) to domestic, commercial, and farm wells; (2) to Danby Creek; (3) to a large wetland in the central parts of Danby Creek valley; and (4) as losses because of plant uptake and evaporation. About 300 people depend on groundwater from the upper Buttermilk Creek and Danby Creek stratified-drift aquifer system.
\nAn unconfined surficial aquifer about 8,000 feet (ft) long and as much as 800 ft wide, with a saturated thickness of about 20 ft, occupies the lower (southeastern most) 8,000 ft of Danby Creek valley within the Town of Danby. However, because the aquifer is thin, the volume of water stored in the aquifer is small and the potential for induced recharge from Danby Creek during summer periods of low flow is also small, an array of wells would probably be needed to provide sustainable continuous amount of water to large water users such as municipalities and industries. Additional data and a groundwater flow model would be required to estimate sustainable withdrawal from the confined aquifers in upper Buttermilk Creek valley. Well data from water-well drillers through 2012 indicate that the confined aquifers in upper Buttermilk Creek valley are thin (typically about 10 feet thick) and the reported well-yield data suggest these aquifers may not be capable of supplying sufficient water to meet the needs of municipalities and industries. However, additional geohydrologic data leading to calibration of a groundwater flow model would be needed to properly evaluate the long-term (multiple years) potential yield of the confined aquifer system in upper Buttermilk Creek valley and of the unconfined aquifer in Danby Creek valley.
\nDuring 2007–10, groundwater samples were collected from 13 wells including 7 wells that are completed in the confined sand and gravel aquifers, 1 well that is completed in the unconfined aquifer, and 5 wells that are completed in the bedrock aquifers. Calcium dominates the cation composition and bicarbonate dominates the anion composition in most groundwater. Water quality in the study area generally meets state and Federal drinking-water standards but concentrations of some constituents exceeded the standards. The standards that were exceeded include sodium (3 samples), dissolved solids (1 sample), iron (3 samples), manganese (8 samples), and arsenic (1 sample).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155138","collaboration":"Prepared in cooperation with the Town of Danby and the Tompkins County Planning Department","usgsCitation":"Miller, T.S., 2015, Geohydrology and water quality of the stratified-drift aquifers in upper Buttermilk Creek and Danby Creek valleys, Town of Danby, Tompkins County, New York: U.S. Geological Survey Scientific Investigations Report 2015–5138, 66 p., https://dx.doi.org/10.3133/sir20155138.","productDescription":"viii, 66 p.","numberOfPages":"78","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-055138","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":311559,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5138/coverthb.jpg"},{"id":311560,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5138/sir20155138.pdf","text":"Report","size":"6.42 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5138"}],"country":"United States","state":"New York","county":"Tompkins County","city":"Danby","otherGeospatial":"Danby Creek, Upper Buttermilk Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.51290893554688,\n 42.357782825014176\n ],\n [\n -76.51290893554688,\n 42.428524987525385\n ],\n [\n -76.43051147460938,\n 42.428524987525385\n ],\n [\n -76.43051147460938,\n 42.357782825014176\n ],\n [\n -76.51290893554688,\n 42.357782825014176\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
30 Brown Road
Ithaca, NY 14850
http://ny.water.usgs.gov
Information requests:
(518) 285-5602
Next-Generation Radar (NEXRAD) has become an integral component in the estimation of precipitation (Kitzmiller and others, 2013). The high spatial and temporal resolution of NEXRAD has revolutionized the ability to estimate precipitation across vast regions, which is especially beneficial in areas without a dense rain-gage network. With the improved precipitation estimates, hydrologic models can produce reliable streamflow forecasts for areas across the United States. NEXRAD data from the National Weather Service (NWS) has been an invaluable tool used by the U.S. Geological Survey (USGS) for numerous projects and studies; NEXRAD data processing techniques similar to those discussed in this Fact Sheet have been developed within the USGS, including the NWS Quantitative Precipitation Estimates archive developed by Blodgett (2013).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153076","collaboration":"Prepared in cooperation with the DuPage County Stormwater Management Department","usgsCitation":"Ortel, T.W., and Spies, R.R., 2015, NEXRAD Quantitative precipitation estimates, data acquisition, and processing for the DuPage County, Illinois, streamflow-simulation modeling system: U.S. Geological Survey Fact Sheet 2015–3076, 2 p., https://dx.doi.org/10.3133/fs20153076.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-057259","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":311538,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2015/3076/coverthb.jpg"},{"id":311539,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3076/fs20153076.pdf","text":"Report","size":"1.18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2015-3076"}],"country":"United States","state":"Illinois","county":"DuPage County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.49212646484374,\n 41.281934557995356\n ],\n [\n -88.49212646484374,\n 42.04929263868686\n ],\n [\n -87.6104736328125,\n 42.04929263868686\n ],\n [\n -87.6104736328125,\n 41.281934557995356\n ],\n [\n -88.49212646484374,\n 41.281934557995356\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Illinois Water Science Center
U.S. Geological Survey
405 North Goodwin Avenue
Urbana, IL 61801–2347
Phone: (217) 328–USGS (8747)
http://il.water.usgs.gov/
The horseshoe crab fishery on the US Atlantic coast represents a compelling fishery management story for many reasons, including ecological complexity, health and human safety ramifications, and socio-economic conflicts. Knowledge of stock status and assessment and monitoring capabilities for the species have increased greatly in the last 15 years and permitted managers to make more informed harvest recommendations. Incorporating the bioenergetics needs of migratory shorebirds, which feed on horseshoe crab eggs, into the management framework for horseshoe crabs was identified as a goal, particularly in the Delaware Bay region where the birds and horseshoe crabs exhibit an important ecological interaction. In response, significant effort was invested in studying the population dynamics, migration ecology, and the ecologic relationship of a key migratory shorebird, the Red Knot, to horseshoe crabs. A suite of models was developed that linked Red Knot populations to horseshoe crab populations through a mass gain function where female spawning crab abundance determined what proportion of the migrating Red Knot population reached a critical body mass threshold. These models were incorporated in an adaptive management framework wherein optimal harvest decisions for horseshoe crab are recommended based on several resource-based and value-based variables and thresholds. The current adaptive framework represents a true multispecies management effort where additional data over time are employed to improve the predictive models and reduce parametric uncertainty. The possibility of increasing phenologic asynchrony between the two taxa in response to climate change presents a potential challenge to their ecologic interaction in Delaware Bay.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Changing Global Perspectives on Horseshoe Crab Biology, Conservation and Management","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","publisherLocation":"Cham","doi":"10.1007/978-3-319-19542-1_24","usgsCitation":"Millard, M.J., Sweka, J.A., McGowan, C., and Smith, D., 2015, Assessment and Mmanagement of North American horseshoe crab populations, with emphasis on a multispecies framework for Delaware Bay, U.S.A. populations: Chapter 24, chap. of Changing Global Perspectives on Horseshoe Crab Biology, Conservation and Management, p. 407-431, https://doi.org/10.1007/978-3-319-19542-1_24.","startPage":"407","endPage":"431","numberOfPages":"25","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059817","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":326655,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57b58abee4b03bcb0104bb5e","contributors":{"authors":[{"text":"Millard, Michael J.","contributorId":23411,"corporation":false,"usgs":false,"family":"Millard","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":645754,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sweka, John A.","contributorId":80945,"corporation":false,"usgs":true,"family":"Sweka","given":"John","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":645755,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGowan, Conor P. cmcgowan@usgs.gov","contributorId":145496,"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":564308,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, David R.","contributorId":173756,"corporation":false,"usgs":false,"family":"Smith","given":"David R.","affiliations":[],"preferred":false,"id":645756,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159728,"text":"70159728 - 2015 - Biofilm formation of Francisella noatunensis subsp. orientalis","interactions":[],"lastModifiedDate":"2016-12-19T11:59:44","indexId":"70159728","displayToPublicDate":"2015-11-19T12:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3685,"text":"Veterinary Microbiology","active":true,"publicationSubtype":{"id":10}},"title":"Biofilm formation of Francisella noatunensis subsp. orientalis","docAbstract":"Francisella noatunensis subsp. orientalis (Fno) is an emergent fish pathogen in both marine and fresh water environments. The bacterium is suspected to persist in the environment even without the presence of a suitable fish host. In the present study, the influence of different abiotic factors such as salinity and temperature were used to study the biofilm formation of different isolates of Fno including intracellular growth loci C (iglC)and pathogenicity determinant protein A (pdpA) knockout strains. Finally, we compared the susceptibility of planktonic and biofilm to three disinfectants used in the aquaculture and ornamental fish industry, namely Virkon®, bleach and hydrogen peroxide. The data indicates that Fno is capable of producing biofilms within 24 h where both salinity as well as temperature plays a role in the growth and biofilm formation of Fno. Mutations in theiglC or pdpA, both known virulence factors, do not appear to affect the capacity of Fno to produce biofilms, and the minimum inhibitory concentration, and minimum biocidal concentration for the three disinfectants were lower than the minimum biofilm eradication concentration values. This information needs to be taken into account if trying to eradicate the pathogen from aquaculture facilities or aquariums.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.vetmic.2015.10.007","usgsCitation":"Soto, E., Halliday-Wimmonds, I., Francis, S., Kearney, M.T., and Hansen, J.D., 2015, Biofilm formation of Francisella noatunensis subsp. orientalis: Veterinary Microbiology, v. 181, no. 3-4, p. 313-317, https://doi.org/10.1016/j.vetmic.2015.10.007.","productDescription":"5 p.","startPage":"313","endPage":"317","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061353","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":311568,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"181","issue":"3-4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"564ef2b5e4b064dd1d095552","contributors":{"authors":[{"text":"Soto, Esteban","contributorId":64142,"corporation":false,"usgs":true,"family":"Soto","given":"Esteban","email":"","affiliations":[],"preferred":false,"id":580224,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Halliday-Wimmonds, Iona","contributorId":149970,"corporation":false,"usgs":false,"family":"Halliday-Wimmonds","given":"Iona","email":"","affiliations":[{"id":17866,"text":"Department of Biomedical Sciences, Ross University School of Veterinary Medicine, PO Box 334, Basseterre, St. Kitts, West Indies","active":true,"usgs":false}],"preferred":false,"id":580225,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Francis, Stewart","contributorId":177541,"corporation":false,"usgs":false,"family":"Francis","given":"Stewart","email":"","affiliations":[],"preferred":false,"id":656130,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kearney, Michael T.","contributorId":149971,"corporation":false,"usgs":false,"family":"Kearney","given":"Michael","email":"","middleInitial":"T.","affiliations":[{"id":17867,"text":"Department of Pathobiological Sciences, School of Veterinary Medicine, Louisiana State University, Baton Rouge, Louisiana, USA 70803","active":true,"usgs":false}],"preferred":false,"id":580226,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hansen, John D. 0000-0002-3006-2734 jhansen@usgs.gov","orcid":"https://orcid.org/0000-0002-3006-2734","contributorId":3440,"corporation":false,"usgs":true,"family":"Hansen","given":"John","email":"jhansen@usgs.gov","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":580223,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70159742,"text":"70159742 - 2015 - Evidence of population resistance to extreme low flows in a fluvial-dependent fish species","interactions":[],"lastModifiedDate":"2015-11-19T09:34:11","indexId":"70159742","displayToPublicDate":"2015-11-19T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Evidence of population resistance to extreme low flows in a fluvial-dependent fish species","docAbstract":"Extreme low streamflows are natural disturbances to aquatic populations. Species in naturally intermittent streams display adaptations that enhance persistence during extreme events; however, the fate of populations in perennial streams during unprecedented low-flow periods is not well-understood. Biota requiring swift-flowing habitats may be especially vulnerable to flow reductions. We estimated the abundance and local survival of a native fluvial-dependent fish species (Etheostoma inscriptum) across 5 years encompassing historic low flows in a sixth-order southeastern USA perennial river. Based on capturemark-recapture data, the study shoal may have acted as a refuge during severe drought, with increased young-of-the-year (YOY) recruitment and occasionally high adult immigration. Contrary to expectations, summer and autumn survival rates (30 days) were not strongly depressed during low-flow periods, despite 25%-80% reductions in monthly discharge. Instead, YOY survival increased with lower minimum discharge and in response to small rain events that increased low-flow variability. Age-1+ fish showed the opposite pattern, with survival decreasing in response to increasing low-flow variability. Results from this population dynamics study of a small fish in a perennial river suggest that fluvial-dependent species can be resistant to extreme flow reductions through enhanced YOY recruitment and high survival
","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2015-0173","usgsCitation":"Katz, R.A., and Freeman, M., 2015, Evidence of population resistance to extreme low flows in a fluvial-dependent fish species: Canadian Journal of Fisheries and Aquatic Sciences, v. 11, no. 29, p. 1776-1787, https://doi.org/10.1139/cjfas-2015-0173.","productDescription":"12 p.","startPage":"1776","endPage":"1787","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065219","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":311557,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"11","issue":"29","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"564ef2b9e4b064dd1d09555c","contributors":{"authors":[{"text":"Katz, Rachel A.","contributorId":149995,"corporation":false,"usgs":false,"family":"Katz","given":"Rachel","email":"","middleInitial":"A.","affiliations":[{"id":17882,"text":"Odum School of Ecology, University of Georgia","active":true,"usgs":false}],"preferred":false,"id":580305,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":580304,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70159743,"text":"70159743 - 2015 - Estimating occupancy dynamics for large-scale monitoring networks: amphibian breeding occupancy across protected areas in the northeast United States","interactions":[],"lastModifiedDate":"2015-11-19T09:30:04","indexId":"70159743","displayToPublicDate":"2015-11-19T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Estimating occupancy dynamics for large-scale monitoring networks: amphibian breeding occupancy across protected areas in the northeast United States","docAbstract":"Regional monitoring strategies frequently employ a nested sampling design where a finite set of study areas from throughout a region are selected within which intensive sub-sampling occurs. This sampling protocol naturally lends itself to a hierarchical analysis to account for dependence among sub-samples. Implementing such an analysis within a classic likelihood framework is computationally prohibitive with species occurrence data when accounting for detection probabilities. Bayesian methods offer an alternative framework to make this analysis feasible. We demonstrate a general approach for estimating occupancy when data come from a nested sampling design. Using data from a regional monitoring program of wood frogs (Lithobates sylvaticus) and spotted salamanders (Ambystoma maculatum) in vernal pools, we analyzed data using static and dynamic occupancy frameworks. We analyzed observations from 2004-2013collected within 14 protected areas located throughout the northeast United States . We use the data set to estimate trends in occupancy at both the regional and individual protected area level. We show that occupancy at the regional level was relatively stable for both species. Much more variation occurred within individual study areas, with some populations declining and some increasing for both species. We found some evidence for a latitudinal gradient in trends among protected areas. However, support for this pattern is overestimated when the hierarchical nature of the data collection is not controlled for in the analysis. For both species, occupancy appeared to be declining in the most southern areas, while occupancy was stable or increasing in more northern areas. These results shed light on the range-level population status of these pond-breeding amphibians and our approach provides a framework that can be used to examine drivers of change including among-year and among-site variation in occurrence dynamics, while properly accounting for nested structure of data collection.
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