A daily precipitation-runoff model was developed to estimate spatially and temporally distributed recharge for groundwater basins in the San Gorgonio Pass area, southern California. The recharge estimates are needed to define transient boundary conditions for a groundwater-flow model being developed to evaluate the effects of pumping and climate on the long-term availability of groundwater. The area defined for estimating recharge is referred to as the San Gorgonio Pass watershed model (SGPWM) and includes three watersheds: San Timoteo Creek, Potrero Creek, and San Gorgonio River. The SGPWM was developed by using the U.S. Geological Survey INFILtration version 3.0 (INFILv3) model code used in previous studies of recharge in the southern California region, including the San Gorgonio Pass area. The SGPWM uses a 150-meter gridded discretization of the area of interest in order to account for spatial variability in climate and watershed characteristics. The high degree of spatial variability in climate and watershed characteristics in the San Gorgonio Pass area is caused, in part, by the high relief and rugged topography of the area.
\nDaily climate data developed from a network of monitoring sites and published average monthly precipitation maps were used to develop the climate inputs for the SGPWM. Geographic Information System (GIS) data defining land surface altitude, vegetation, soils, surficial geology, and land cover were used to define input parameters representing the physical characteristics of the land surface, root zone, and shallow subsurface underlying the root zone. Model parameterization was based on a previous INFILv3 model developed for an area including the upper parts of the San Timoteo Creek and Potrero Creek drainages and the western part of the San Gorgonio River watershed. The previous INFILv3 model was calibrated by using available streamflow records from the model area. The SGPWM uses an updated INFILv3 version to represent shallow groundwater flow better beneath the root zone that contributes to lateral, downslope seepage rather than deep recharge. The SGPWM calibration was tested by using available streamflow records in the San Gorgonio Pass region.
\nThe SGPWM was used to simulate a 100-year water budget, including recharge and runoff, for water years 1913 through 2012. Results indicated that most recharge came from episodic infiltration of surface-water runoff in the larger stream channels. Results also indicated periods of great variability in recharge and runoff in response to variability in precipitation. More recharge was simulated for the area of the groundwater basin underlying the more permeable alluvial fill of the valley floor compared to recharge in the neighboring upland areas of the less permeable mountain blocks. The greater recharge was in response to the episodic streamflow that discharged from the mountain block areas and quickly infiltrated the permeable alluvial fill of the groundwater basin. Although precipitation at the higher altitudes of the mountain block was more than double precipitation at the lower altitudes of the valley floor, recharge for inter-channel areas of the mountain block was limited by the lower permeability bedrock underlying the thin soil cover, and most of the recharge in the mountain block was limited to the main stream channels underlain by alluvial fill.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155122","collaboration":"Prepared in cooperation with the San Gorgonio Pass Water Agency","usgsCitation":"Hevesi, J.A., and Christensen, A.H., 2015, Estimating natural recharge in San Gorgonio Pass watersheds, California, 1913–2012: U.S. Geological Survey Scientific Investigations Report 2015–5122, 74 p. https://dx.doi.org/10.3133/ SIR20155122.","productDescription":"xii, 74 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-054946","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":312622,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5122/sir20155122.pdf","text":"Report","size":"29.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5122"},{"id":312621,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5122/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Gorgonio Pass","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.301025390625,\n 33.43831750748322\n ],\n [\n -116.05682373046875,\n 33.43831750748322\n ],\n [\n -116.05682373046875,\n 34.19135773925218\n ],\n [\n -117.301025390625,\n 34.19135773925218\n ],\n [\n -117.301025390625,\n 33.43831750748322\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, CA 95819
http://ca.water.usgs.gov
Bat mortality rates from white-nose syndrome and wind power development are unprecedented. Cryptic and wide-ranging behaviours of bats make them difficult to survey, and population estimation is often intractable. We advance a model-based framework for making spatially explicit predictions about summertime distributions of bats from capture and acoustic surveys. Motivated by species-energy and life-history theory, our models describe hypotheses about spatio-temporal variation in bat distributions along environmental gradients and life-history attributes, providing a statistical basis for conservation decision-making.
\nOregon and Washington, USA.
\nWe developed Bayesian hierarchical models for 14 bat species from an 8-year monitoring dataset across a ~430,000 km2 study area. Models accounted for imperfect detection and were temporally dynamic. We mapped predicted occurrence probabilities and prediction uncertainties as baselines for assessing future declines.
\nForest cover, snag abundance and cliffs were important predictors for most species. Species occurrence patterns varied along elevation and precipitation gradients, suggesting a potential hump-shaped diversity–productivity relationship. Annual turnover in occurrence was generally low, and occurrence probabilities were stable among most species. We found modest evidence that turnover covaried with the relative riskiness of bat roosting and migration. The fringed myotis (Myotis thysanodes), canyon bat (Parastrellus hesperus) and pallid bat (Antrozous pallidus) were rare; fringed myotis occurrence probabilities declined over the study period. We simulated anticipated declines to demonstrate that mapped occurrence probabilities, updated over time, provide an intuitive way to assess bat conservation status for a broad audience.
\nLandscape keystone structures associated with roosting habitat emerged as regionally important predictors of bat distributions. The challenges of bat monitoring have constrained previous species distribution modelling efforts to temporally static presence-only approaches. Our approach extends to broader spatial and temporal scales than has been possible in the past for bats, making a substantial increase in capacity for bat conservation.
","language":"English","publisher":"Blackwell Science","publisherLocation":"Oxford","doi":"10.1111/ddi.12372","usgsCitation":"Rodhouse, T., Ormsbee, P., Irvine, K.M., Vierling, L.A., Szewczak, J.M., and Vierling, K.T., 2015, Establishing conservation baselines with dynamic distribution models for bat populations facing imminent decline: Diversity and Distributions, v. 21, no. 12, p. 1401-1413, https://doi.org/10.1111/ddi.12372.","startPage":"1401","endPage":"1413","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063534","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":471560,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.12372","text":"Publisher Index Page"},{"id":325981,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","volume":"21","issue":"12","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-21","publicationStatus":"PW","scienceBaseUri":"57a1c42fe4b006cb45552c10","contributors":{"authors":[{"text":"Rodhouse, Thomas J.","contributorId":127378,"corporation":false,"usgs":false,"family":"Rodhouse","given":"Thomas J.","affiliations":[{"id":6924,"text":"National Park Service, Upper Columbia Basin Network","active":true,"usgs":false}],"preferred":false,"id":644350,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ormsbee, Patricia C.","contributorId":127379,"corporation":false,"usgs":false,"family":"Ormsbee","given":"Patricia C.","affiliations":[{"id":6925,"text":"US Forest Service, retired","active":true,"usgs":false}],"preferred":false,"id":644351,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Irvine, Kathryn M. 0000-0002-6426-940X kirvine@usgs.gov","orcid":"https://orcid.org/0000-0002-6426-940X","contributorId":2218,"corporation":false,"usgs":true,"family":"Irvine","given":"Kathryn","email":"kirvine@usgs.gov","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":644349,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vierling, Lee A.","contributorId":169443,"corporation":false,"usgs":false,"family":"Vierling","given":"Lee","email":"","middleInitial":"A.","affiliations":[{"id":6711,"text":"University of Idaho, Moscow ID","active":true,"usgs":false}],"preferred":false,"id":644352,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Szewczak, Joseph M.","contributorId":30127,"corporation":false,"usgs":false,"family":"Szewczak","given":"Joseph","email":"","middleInitial":"M.","affiliations":[{"id":6958,"text":"Department of Biological Sciences, Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":644353,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vierling, Kerri T.","contributorId":140099,"corporation":false,"usgs":false,"family":"Vierling","given":"Kerri","email":"","middleInitial":"T.","affiliations":[{"id":13384,"text":"Department of Fish and Wildlife Sciences, University of Idaho,","active":true,"usgs":false}],"preferred":false,"id":644354,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70159820,"text":"sir20155168 - 2015 - Simulated responses of streams and ponds to groundwater withdrawals and wastewater return flows in southeastern Massachusetts","interactions":[],"lastModifiedDate":"2015-12-21T14:01:13","indexId":"sir20155168","displayToPublicDate":"2015-12-21T14:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5168","title":"Simulated responses of streams and ponds to groundwater withdrawals and wastewater return flows in southeastern Massachusetts","docAbstract":"Water use, such as withdrawals, wastewater return flows, and interbasin transfers, can alter streamflow regimes, water quality, and the integrity of aquatic habitat and affect the availability of water for human and ecosystem needs. To provide the information needed to determine alteration of streamflows and pond water levels in southeastern Massachusetts, existing groundwater models of the Plymouth-Carver region and western (Sagamore flow lens) and eastern (Monomoy flow lens) Cape Cod were used to delineate subbasins and simulate long-term average and average monthly streamflows and pond levels for a series of water-use conditions. Model simulations were used to determine the extent to which streamflows and pond levels were altered by comparing simulated streamflows and pond levels under predevelopment conditions with streamflows and pond levels under pumping only and pumping with wastewater return flow conditions. The pumping and wastewater return flow rates used in this study are the same as those used in previously published U.S. Geological Survey studies in southeastern Massachusetts and represent the period from 2000 to 2005. Streamflow alteration for the nontidal portions of streams in southeastern Massachusetts was evaluated within and at the downstream outlets of 78 groundwater subbasins delineated for this study. Evaluation of streamflow alteration at subbasin outlets is consistent with the approach used by the U.S. Geological Survey for the topographically derived subbasins in the rest of Massachusetts.
\nThe net effect of pumping and wastewater return flows on streamflows and pond levels varied by location and included no change in areas minimally affected by water use, decreases in areas affected more by pumping than by wastewater return flows, or increases in areas affected more by wastewater return flows than by pumping. Simulated alterations to long-term average streamflows at subbasin outlets in response to pumping with wastewater return flows were within about 10 percent of predevelopment streamflows for most of the subbasins in the study area. Alterations ranged from a decrease (depletion) of 43.9 percent at an unnamed tributary to Salt Pond in the Plymouth-Carver region to an increase (surcharge) of 18.2 percent at an unnamed tributary to the Centerville River on western Cape Cod. In general, the relative effects of pumping and wastewater return flows typically were larger in the subbasins with low streamflows than in the subbasins with high streamflows, and there were more depleted streamflows than surcharged streamflows. Increases in streamflows in response to wastewater return flows were generally largest in subbasins with a high density of septic systems or a centralized wastewater treatment facility. For average monthly conditions, streamflow alteration results were similar spatially to results for long-term average conditions. However, differences in the extent of alteration by month were observed; percentage streamflow depletions in most subbasins typically were greatest during the low-streamflow months of August and October.
\nThe percentages of the total number of ponds affected by pumping with wastewater return flows under long-term average conditions in the modeled areas were 28 percent for the Plymouth-Carver region, 67 percent for western Cape Cod, and 75 percent for eastern Cape Cod. Pond-level alterations ranged from a decrease of 4.6 feet at Great South Pond in the Plymouth Carver region to an increase of 0.9 feet at Wequaquet Lake in western Cape Cod. The magnitudes of monthly alterations to pond water levels were fairly consistent throughout the year.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155168","collaboration":"Prepared in cooperation with the Massachusetts Department of Environmental Protection","usgsCitation":"Carlson, C.S., Walter, D.A., and Barbaro, J.R., 2015, Simulated responses of streams and ponds to groundwater withdrawals and wastewater return flows in southeastern Massachusetts: U.S. Geological Survey Scientific Investigations Report 2015–5168, 60 p., https://dx.doi.org/10.3133/sir20155168.","productDescription":"Report: vii, 60 p.; 2 Tables; 2 Appendixes","numberOfPages":"72","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-065841","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":312500,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5168/sir20155168_appendix2_gis.zip","text":"Appendix 2 - Shapefiles and spreadsheet files","size":"15.8 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2015-5168"},{"id":312497,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5168/coverthb2.jpg"},{"id":312501,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5168/sir20155168_appendix3_gis.zip","text":"Appendix 3 - Shapefiles and spreadsheet files","size":"3.3 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2015-5168"},{"id":312498,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5168/sir20155168.pdf","text":"Report","size":"8.41 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5168"},{"id":312499,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2015/5168/sir20155168_tables3-4.xlsx","text":"Tables 3-4","size":"52 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5168","linkHelpText":"Table 3. Stream identification, landscape characteristics, and Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Or visit our Web site at:
http://newengland.water.usgs.gov
Florida panthers are among the world’s most endangered — and elusive — animals. For approximately four decades, scientists have been researching this small population of panthers that inhabit the dense forests and swamps of south Florida. Because of their wide habitat range along with an absence of clear visual features, these animals are difficult to detect and identify. In 2013, however, researchers released a study that used camera trap images collected between 2005 and 2007 to generate the first statistically reliable density estimates for the remaining population of this subspecies.
\nCamera traps — remotely activated cameras with infrared sensors — first gained measurable popularity in wildlife conservation in the early 1990s. Today, they’re used for a variety of activities, from species-specific research to broad-scale inventory or monitoring programs that, in some cases, attempt to detect biodiversity across vast landscapes. As this modern tool continues to evolve, it’s worth examining its uses and benefits for wildlife management and conservation.
","language":"English","publisher":"Wildlife Society","publisherLocation":"Lawrence, KS","usgsCitation":"O’Connell, A.F., 2015, A hidden view of wildlife conservation: How camera traps aid science, research and management: The Wildlife Professional, v. 9, no. 3, p. 56-59.","productDescription":"4 p.","startPage":"56","endPage":"59","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063163","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":312707,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":390185,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://wildlife.org/"}],"volume":"9","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"567922a7e4b0da412f4fb507","contributors":{"authors":[{"text":"O’Connell, Allan F. 0000-0001-7032-7023 aoconnell@usgs.gov","orcid":"https://orcid.org/0000-0001-7032-7023","contributorId":471,"corporation":false,"usgs":true,"family":"O’Connell","given":"Allan","email":"aoconnell@usgs.gov","middleInitial":"F.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":571239,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70189904,"text":"70189904 - 2015 - Beyond annual streamflow reconstructions for the Upper Colorado River Basin: a paleo-water-balance approach","interactions":[],"lastModifiedDate":"2018-04-03T11:24:51","indexId":"70189904","displayToPublicDate":"2015-12-18T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Beyond annual streamflow reconstructions for the Upper Colorado River Basin: a paleo-water-balance approach","docAbstract":"In this paper, we present a methodology to use annual tree-ring chronologies and a monthly water balance model to generate annual reconstructions of water balance variables (e.g., potential evapotrans- piration (PET), actual evapotranspiration (AET), snow water equivalent (SWE), soil moisture storage (SMS), and runoff (R)). The method involves resampling monthly temperature and precipitation from the instrumental record directed by variability indicated by the paleoclimate record. The generated time series of monthly temperature and precipitation are subsequently used as inputs to a monthly water balance model. The methodology is applied to the Upper Colorado River Basin, and results indicate that the methodology reliably simulates water-year runoff, maximum snow water equivalent, and seasonal soil moisture storage for the instrumental period. As a final application, the methodology is used to produce time series of PET, AET, SWE, SMS, and R for the 1404–1905 period for the Upper Colorado River Basin.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015WR017283","usgsCitation":"Gangopadhyay, S., McCabe, G., and Woodhouse, C.A., 2015, Beyond annual streamflow reconstructions for the Upper Colorado River Basin: a paleo-water-balance approach: Water Resources Research, v. 51, no. 12, p. 9763-9774, https://doi.org/10.1002/2015WR017283.","productDescription":"12 p.","startPage":"9763","endPage":"9774","ipdsId":"IP-069011","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":344497,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.0390625,\n 43.14909399920127\n ],\n [\n -110.50048828124999,\n 42.45588764197166\n ],\n [\n -110.80810546875,\n 41.11246878918088\n ],\n [\n -111.0498046875,\n 40.17887331434696\n ],\n [\n -111.86279296875,\n 37.43997405227057\n ],\n [\n -111.6650390625,\n 36.686041276581925\n ],\n [\n -110.56640625,\n 36.421282443649496\n ],\n [\n -109.599609375,\n 36.33282808737917\n ],\n [\n -109.48974609375,\n 35.7286770448517\n ],\n [\n -108.56689453125,\n 35.7286770448517\n ],\n [\n -108.12744140625,\n 35.782170703266075\n ],\n [\n -107.3583984375,\n 36.54494944148322\n ],\n [\n -107.3583984375,\n 37.42252593456307\n ],\n [\n -107.77587890625,\n 37.70120736474139\n ],\n [\n -107.02880859375,\n 38.77121637244273\n ],\n [\n -106.962890625,\n 40.027614437486655\n ],\n [\n -107.46826171874999,\n 40.245991504199026\n ],\n [\n -107.68798828125,\n 40.96330795307353\n ],\n [\n -108.1494140625,\n 41.705728515237524\n ],\n [\n -107.57812499999999,\n 42.06560675405716\n ],\n [\n -108.984375,\n 42.50450285299051\n ],\n [\n -110.0390625,\n 43.14909399920127\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"51","issue":"12","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-18","publicationStatus":"PW","scienceBaseUri":"59819316e4b0e2f5d463b7a3","contributors":{"authors":[{"text":"Gangopadhyay, Subhrendu 0000-0003-3864-8251","orcid":"https://orcid.org/0000-0003-3864-8251","contributorId":173439,"corporation":false,"usgs":false,"family":"Gangopadhyay","given":"Subhrendu","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":706719,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":1453,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory J.","email":"gmccabe@usgs.gov","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"preferred":false,"id":706718,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woodhouse, Connie A.","contributorId":187601,"corporation":false,"usgs":false,"family":"Woodhouse","given":"Connie","email":"","middleInitial":"A.","affiliations":[{"id":32413,"text":"University of Arizona, Tucson, AZ, USA, 85721","active":true,"usgs":false}],"preferred":false,"id":706720,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70168799,"text":"70168799 - 2015 - Trans-Amazon Drilling Project (TADP): origins and evolution of the forests, climate, and hydrology of the South American tropics","interactions":[],"lastModifiedDate":"2016-03-04T13:51:18","indexId":"70168799","displayToPublicDate":"2015-12-17T14:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3356,"text":"Scientific Drilling","active":true,"publicationSubtype":{"id":10}},"title":"Trans-Amazon Drilling Project (TADP): origins and evolution of the forests, climate, and hydrology of the South American tropics","docAbstract":"This article presents the scientific rationale for an ambitious ICDP drilling project to continuously sample Late Cretaceous to modern sediment in four different sedimentary basins that transect the equatorial Amazon of Brazil, from the Andean foreland to the Atlantic Ocean. The goals of this project are to document the evolution of plant biodiversity in the Amazon forests and to relate biotic diversification to changes in the physical environment, including climate, tectonism, and the surface landscape. These goals require long sedimentary records from each of the major sedimentary basins across the heart of the Brazilian Amazon, which can only be obtained by drilling because of the scarcity of Cenozoic outcrops. The proposed drilling will provide the first long, nearly continuous regional records of the Cenozoic history of the forests, their plant diversity, and the associated changes in climate and environment. It also will address fundamental questions about landscape evolution, including the history of Andean uplift and erosion as recorded in Andean foreland basins and the development of west-to-east hydrologic continuity between the Andes, the Amazon lowlands, and the equatorial Atlantic. Because many modern rivers of the Amazon basin flow along the major axes of the old sedimentary basins, we plan to locate drill sites on the margin of large rivers and to access the targeted drill sites by navigation along these rivers.
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2130 SW 5th Avenue
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An understanding of the effects on human and ecological health brought by major coastal storms or flooding events is typically limited because of a lack of regionally consistent baseline and trends data in locations proximal to potential contaminant sources and mitigation activities, sensitive ecosystems, and recreational facilities where exposures are probable. In an attempt to close this gap, the U.S. Geological Survey (USGS) has implemented the Sediment-bound Contaminant Resiliency and Response (SCoRR) strategy pilot study to collect regional sediment-quality data prior to and in response to future coastal storms. The standard operating procedure (SOP) detailed in this document serves as the sample-collection protocol for the SCoRR strategy by providing step-by-step instructions for site preparation, sample collection and processing, and shipping of soil and surficial sediment (for example, bed sediment, marsh sediment, or beach material). The objectives of the SCoRR strategy pilot study are (1) to create a baseline of soil-, sand-, marsh sediment-, and bed-sediment-quality data from sites located in the coastal counties from Maine to Virginia based on their potential risk of being contaminated in the event of a major coastal storm or flooding (defined as Resiliency mode); and (2) respond to major coastal storms and flooding by reoccupying select baseline sites and sampling within days of the event (defined as Response mode). For both modes, samples are collected in a consistent manner to minimize bias and maximize quality control by ensuring that all sampling personnel across the region collect, document, and process soil and sediment samples following the procedures outlined in this SOP. Samples are analyzed using four USGS-developed screening methods—inorganic geochemistry, organic geochemistry, pathogens, and biological assays—which are also outlined in this SOP. Because the SCoRR strategy employs a multi-metric approach for sample analyses, this protocol expands upon and reconciles differences in the sample collection protocols outlined in the USGS “National Field Manual for the Collection of Water-Quality Data,” which should be used in conjunction with this SOP. A new data entry and sample tracking system also is presented to ensure all relevant data and metadata are gathered at the sample locations and in the laboratories.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151188B","collaboration":"Toxic Substances Hydrology Program","usgsCitation":"Fisher, S.C., Reilly, T.J., Jones, D.K., Benzel, W.M., Griffin, D.W., Loftin, K.A., Iwanowicz, L.R., and Cohl, J.A., 2015, Standard operating procedure for collection of soil and sediment samples for the Sediment-bound Contaminant Resiliency and Response (SCoRR) strategy pilot study: U.S. Geological Survey Open-File Report 2015–1188b, 37 p., https://dx.doi.org/10.3133/ofr20151188B.","productDescription":"v, 37 p.","numberOfPages":"48","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-066316","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":312385,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/ofr20151188A","text":"Open-File Report 2015-1188A","description":"OFR 2015-1188B","linkHelpText":"Strategy to Evaluate Persistent Contaminant Hazards Resulting from Sea-Level RiseToxic Substances Hydrology Program
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, Virginia 20192
http://www.usgs.gov/envirohealth/
http://health.usgs.gov/scorr/
Ungulate browsing in predator depleted North American landscapes is believed to be causing widespread tree recruitment failures. However, canopy disturbances and variations in ungulate densities are sources of heterogeneity that can buffer ecosystems against herbivory. Relatively little is known about the functional response (the rate of consumption in relation to food availability) of ungulates in eastern temperate forests, and therefore how “top down” control of vegetation may vary with disturbance type, intensity, and timing. This knowledge gap is relevant in the Northeastern United States today with the recent arrival of hemlock woolly adelgid (HWA; Adelges tsugae) that is killing eastern hemlocks (Tsuga canadensis) and initiating salvage logging as a management response. We used an existing experiment in central New England begun in 2005, which simulated severe adelgid infestation and intensive logging of intact hemlock forest, to examine the functional response of combined moose (Alces americanus) and white-tailed deer (Odocoileus virginianus) foraging in two different time periods after disturbance (3 and 7 years). We predicted that browsing impacts would be linear or accelerating (Type I or Type III response) in year 3 when regenerating stem densities were relatively low and decelerating (Type II response) in year 7 when stem densities increased. We sampled and compared woody regeneration and browsing among logged and simulated insect attack treatments and two intact controls (hemlock and hardwood forest) in 2008 and again in 2012. We then used AIC model selection to compare the three major functional response models (Types I, II, and III) of ungulate browsing in relation to forage density. We also examined relative use of the different stand types by comparing pellet group density and remote camera images. In 2008, total and proportional browse consumption increased with stem density, and peaked in logged plots, revealing a Type I response. In 2012, stem densities were greatest in girdled plots, but proportional browse consumption was highest at intermediate stem densities in logged plots, exhibiting a Type III (rather than a Type II) functional response. Our results revealed shifting top–down control by herbivores at different stages of stand recovery after disturbance and in different understory conditions resulting from logging vs. simulated adelgid attack. If forest managers wish to promote tree regeneration in hemlock stands that is more resistant to ungulate browsers, leaving HWA-infested stands unmanaged may be a better option than preemptively logging them.
","language":"English","publisher":"Elsevier Science Pub. Co.","publisherLocation":"New York, NY","doi":"10.1016/j.foreco.2015.12.006","usgsCitation":"DeStefano, S., 2015, Functional response of ungulate browsers in disturbed eastern hemlock forests: Forest Ecology and Management, v. 32, p. 177-183, https://doi.org/10.1016/j.foreco.2015.12.006.","productDescription":"7 p.","startPage":"177","endPage":"183","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069358","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":318100,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Harvard Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.2,\n 42.45\n ],\n [\n -72.2,\n 42.5\n ],\n [\n -72.25,\n 42.5\n ],\n [\n -72.25,\n 42.45\n ],\n [\n -72.2,\n 42.45\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"32","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56c45642e4b0946c6521852d","contributors":{"authors":[{"text":"DeStefano, Stephen 0000-0003-2472-8373 destef@usgs.gov","orcid":"https://orcid.org/0000-0003-2472-8373","contributorId":166706,"corporation":false,"usgs":true,"family":"DeStefano","given":"Stephen","email":"destef@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":619787,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70157095,"text":"70157095 - 2015 - Quantifying 10 years of improved earthquake-monitoring performance in the Caribbean region","interactions":[],"lastModifiedDate":"2016-02-05T08:30:23","indexId":"70157095","displayToPublicDate":"2015-12-16T16:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying 10 years of improved earthquake-monitoring performance in the Caribbean region","docAbstract":"Over 75 tsunamis have been documented in the Caribbean and adjacent regions during the past 500 years. Since 1500, at least 4484 people are reported to have perished in these killer waves. Hundreds of thousands are currently threatened along the Caribbean coastlines. Were a great tsunamigenic earthquake to occur in the Caribbean region today, the effects would potentially be catastrophic due to an increasingly vulnerable region that has seen significant population increases in the past 40–50 years and currently hosts an estimated 500,000 daily beach visitors from North America and Europe, a majority of whom are not likely aware of tsunami and earthquake hazards. Following the magnitude 9.1 Sumatra–Andaman Islands earthquake of 26 December 2004, the United Nations Educational, Scientific and Cultural Organization (UNESCO) Intergovernmental Coordination Group (ICG) for the Tsunami and other Coastal Hazards Early Warning System for the Caribbean and Adjacent Regions (CARIBE‐EWS) was established and developed minimum performance standards for the detection and analysis of earthquakes. In this study, we model earthquake‐magnitude detection threshold and P‐wave detection time and demonstrate that the requirements established by the UNESCO ICG CARIBE‐EWS are met with 100% of the network operating. We demonstrate that earthquake‐monitoring performance in the Caribbean Sea region has improved significantly in the past decade as the number of real‐time seismic stations available to the National Oceanic and Atmospheric Administration tsunami warning centers have increased. We also identify weaknesses in the current international network and provide guidance for selecting the optimal distribution of seismic stations contributed from existing real‐time broadband national networks in the region.
","language":"English","publisher":"Seismological Society of America","publisherLocation":"El Cerrito, CA","doi":"10.1785/0220150095","usgsCitation":"McNamara, D.E., Hillebrandt-Andrade, C., Saurel, J., Huerfano-Moreno, V., and Lynch, L., 2015, Quantifying 10 years of improved earthquake-monitoring performance in the Caribbean region: Seismological Research Letters, v. 87, no. 1, 11 p., https://doi.org/10.1785/0220150095.","productDescription":"11 p.","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068902","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":312662,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Caribbean region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.875,\n 3.250208561653181\n ],\n [\n -106.875,\n 31.353636941500987\n ],\n [\n -56.25,\n 31.353636941500987\n ],\n [\n -56.25,\n 3.250208561653181\n ],\n [\n -106.875,\n 3.250208561653181\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"87","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-16","publicationStatus":"PW","scienceBaseUri":"567930d1e4b0da412f4fb588","contributors":{"authors":[{"text":"McNamara, Daniel E. 0000-0001-6860-0350 mcnamara@usgs.gov","orcid":"https://orcid.org/0000-0001-6860-0350","contributorId":402,"corporation":false,"usgs":true,"family":"McNamara","given":"Daniel","email":"mcnamara@usgs.gov","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":571609,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hillebrandt-Andrade, Christa","contributorId":147412,"corporation":false,"usgs":false,"family":"Hillebrandt-Andrade","given":"Christa","email":"","affiliations":[{"id":16844,"text":"NOAA CTWP","active":true,"usgs":false}],"preferred":false,"id":571610,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Saurel, Jean-Marie","contributorId":147413,"corporation":false,"usgs":false,"family":"Saurel","given":"Jean-Marie","email":"","affiliations":[{"id":25474,"text":"Institut de Physique du Globe, Paris, France","active":true,"usgs":false}],"preferred":false,"id":571611,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Huerfano-Moreno, V.","contributorId":40447,"corporation":false,"usgs":true,"family":"Huerfano-Moreno","given":"V.","email":"","affiliations":[],"preferred":false,"id":571612,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lynch, Lloyd","contributorId":11232,"corporation":false,"usgs":true,"family":"Lynch","given":"Lloyd","email":"","affiliations":[],"preferred":false,"id":571613,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70155855,"text":"70155855 - 2015 - Mudpuppy (Necturus maculosus maculosus ) spatial distribution, breeding water depth, and use of artificial spawning habitat in the Detroit River","interactions":[],"lastModifiedDate":"2016-01-06T15:12:57","indexId":"70155855","displayToPublicDate":"2015-12-16T16:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1894,"text":"Herpetological Conservation and Biology","onlineIssn":"2151-0733","printIssn":"1931-7603","active":true,"publicationSubtype":{"id":10}},"title":"Mudpuppy (Necturus maculosus maculosus ) spatial distribution, breeding water depth, and use of artificial spawning habitat in the Detroit River","docAbstract":"Mudpuppy (Necturus maculosus maculosus) populations have been declining in the Great Lakes region of North America. However, during fisheries assessments in the Detroit River, we documented Mudpuppy reproduction when we collected all life stages from egg through adult as by-catch in fisheries assessments. Ten years of fisheries sampling resulted in two occurrences of Mudpuppy egg collection and 411 Mudpuppies ranging in size from 37–392 mm Total Length, collected from water 3.5–15.1 m deep. Different types of fisheries gear collected specific life stages; spawning females used cement structures for egg deposition, larval Mudpuppies found refuge in eggmats, and we caught adults with baited setlines and minnow traps. Based on logistic regression models for setlines and minnow traps, there was a higher probability of catching adult Mudpuppies at lower temperatures and in shallower water with reduced clarity. In addition to documenting the presence of all life stages of this sensitive species in a deep and fast-flowing connecting channel, we were also able to show that standard fisheries research equipment can be used for Mudpuppy research in areas not typically sampled in herpetological studies. Our observations show that typical fisheries assessments and gear can play an important role in data collection for Mudpuppy population and spawning assessments.
","language":"English","publisher":"Partners in Amphibian and Reptile Conservation","publisherLocation":"Texarkana, TX","usgsCitation":"Craig, J.M., Mifsud, D.A., Briggs, A., Boase, J., and Kennedy, G.W., 2015, Mudpuppy (Necturus maculosus maculosus ) spatial distribution, breeding water depth, and use of artificial spawning habitat in the Detroit River: Herpetological Conservation and Biology, v. 10, no. 3, p. 926-934.","productDescription":"9 p.","startPage":"926","endPage":"934","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059198","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":313969,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":313967,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.herpconbio.org/Volume_10/Issue_3/Craig_etal_2015.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"Canada, United States","state":"Michigan, Ontario","otherGeospatial":"Detroit River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.91107177734375,\n 42.37985076434416\n ],\n [\n -82.90145874023438,\n 42.33215399891373\n ],\n [\n -82.97286987304688,\n 42.32606244456202\n ],\n [\n -83.0511474609375,\n 42.30879983710441\n ],\n [\n -83.09234619140625,\n 42.272228095985675\n ],\n [\n -83.09371948242188,\n 42.21122801157102\n ],\n [\n -83.09371948242188,\n 42.14507804381756\n ],\n [\n -83.08273315429688,\n 42.042153895364\n ],\n [\n -83.21456909179688,\n 42.03501434990212\n ],\n [\n -83.19808959960936,\n 42.13082130188811\n ],\n [\n -83.15826416015625,\n 42.207159242513335\n ],\n [\n -83.1610107421875,\n 42.24173542549948\n ],\n [\n -83.1390380859375,\n 42.26917949243506\n ],\n [\n -83.09097290039062,\n 42.31997030030751\n ],\n [\n -83.02780151367188,\n 42.355499492256534\n ],\n [\n -82.99621582031249,\n 42.36869093640926\n ],\n [\n -82.91107177734375,\n 42.37985076434416\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"568e491de4b0e7a44bc41a0a","contributors":{"authors":[{"text":"Craig, Jaquelyn M. 0000-0002-7601-8616 jcraig@usgs.gov","orcid":"https://orcid.org/0000-0002-7601-8616","contributorId":146209,"corporation":false,"usgs":true,"family":"Craig","given":"Jaquelyn","email":"jcraig@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":566610,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mifsud, David A.","contributorId":146210,"corporation":false,"usgs":false,"family":"Mifsud","given":"David","email":"","middleInitial":"A.","affiliations":[{"id":16628,"text":"Herpetological Resource and Management, LLC","active":true,"usgs":false}],"preferred":false,"id":566611,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Briggs, Andrew S.","contributorId":32796,"corporation":false,"usgs":true,"family":"Briggs","given":"Andrew S.","affiliations":[],"preferred":false,"id":566612,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boase, James C.","contributorId":38077,"corporation":false,"usgs":false,"family":"Boase","given":"James C.","affiliations":[{"id":12428,"text":"U. 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Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":566613,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kennedy, Gregory W. 0000-0003-1686-6960 gkennedy@usgs.gov","orcid":"https://orcid.org/0000-0003-1686-6960","contributorId":3700,"corporation":false,"usgs":true,"family":"Kennedy","given":"Gregory","email":"gkennedy@usgs.gov","middleInitial":"W.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":566614,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70159940,"text":"sir20105090Y - 2015 - Qualitative assessment of selected areas of the world for undiscovered sediment-hosted stratabound copper deposits: Chapter Y in Global mineral resource assessment","interactions":[{"subject":{"id":70159940,"text":"sir20105090Y - 2015 - Qualitative assessment of selected areas of the world for undiscovered sediment-hosted stratabound copper deposits: Chapter Y in Global mineral resource assessment","indexId":"sir20105090Y","publicationYear":"2015","noYear":false,"chapter":"Y","title":"Qualitative assessment of selected areas of the world for undiscovered sediment-hosted stratabound copper deposits: Chapter Y in Global mineral resource assessment"},"predicate":"IS_PART_OF","object":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"id":1}],"isPartOf":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"lastModifiedDate":"2018-10-29T11:14:23","indexId":"sir20105090Y","displayToPublicDate":"2015-12-14T12:00:00","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":"2010-5090","chapter":"Y","title":"Qualitative assessment of selected areas of the world for undiscovered sediment-hosted stratabound copper deposits: Chapter Y in Global mineral resource assessment","docAbstract":"A qualitative mineral resource assessment of sediment-hosted stratabound copper mineralized areas for undiscovered copper deposits was performed for 10 selected areas of the world. The areas, in alphabetical order, are (1) Belt-Purcell Basin, United States and Canada; (2) Benguela and Cuanza Basins, Angola; (3) Chuxiong Basin, China; (4) Dongchuan Group rocks, China; (5) Egypt–Israel–Jordan Rift, Egypt, Israel, and Jordan; (6) Maritimes Basin, Canada; (7) Neuquén Basin, Argentina; (8) Northwest Botswana Rift, Botswana and Namibia; (9) Redstone Copperbelt, Canada; and (10) Salta Rift System, Argentina. This assessment (1) outlines the main characteristics of the areas, (2) classifies known deposits by deposit model subtypes, and (3) ranks the areas according to their potential to contain undiscovered copper deposits.
\nAn analytic hierarchy process (AHP) was used to rank assessment areas according to their potential for undiscovered copper deposits. Once the main characteristics of each area were compiled (age of host rock, geologic setting, stratigraphy, host lithology, deposit subtype(s), known deposits and occurrences, and mineral system components), three criteria (mineralization, extent of study area, and lithostratigraphic framework, each with multiple subcriteria) were scored for all assessment areas. Relative weights and scores were assigned to all criteria by three geologists. In addition, the assessment areas were ranked for comparison exclusively on the basis of professional opinion. The AHP and professional opinion lists are similar but not the same. Both the professional opinion and the cumulative AHP lists rate the Northwest Botswana Rift in Botswana and Namibia as the area most likely to contain the most undiscovered copper deposits. The Salta Rift System in Argentina is rated lowest among the 10 qualitatively assessed areas.
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U.S. Geological Survey
12201 Sunrise Valley Drive
913 National Center
Reston, VA 20192
http://minerals.usgs.gov/
Quantifying the impact of anthropogenic development on local populations is important for conservation biology and wildlife management. However, these local populations are often subject to demographic stochasticity because of their small population size. Traditional modeling efforts such as population projection matrices do not consider this source of variation whereas individual-based models, which include demographic stochasticity, are computationally intense and lack analytical tractability. One compromise between approaches is branching process models because they accommodate demographic stochasticity and are easily calculated. These models are known within some sub-fields of probability and mathematical ecology but are not often applied in conservation biology and applied ecology. We applied branching process models to quantitatively compare and prioritize species locally vulnerable to the development of wind energy facilities. Specifically, we examined species vulnerability using branching process models for four representative species: A cave bat (a long-lived, low fecundity species), a tree bat (short-lived, moderate fecundity species), a grassland songbird (a short-lived, high fecundity species), and an eagle (a long-lived, slow maturation species). Wind turbine-induced mortality has been observed for all of these species types, raising conservation concerns. We simulated different mortality rates from wind farms while calculating local extinction probabilities. The longer-lived species types (e.g., cave bats and eagles) had much more pronounced transitions from low extinction risk to high extinction risk than short-lived species types (e.g., tree bats and grassland songbirds). High-offspring-producing species types had a much greater variability in baseline risk of extinction than the lower-offspring-producing species types. Long-lived species types may appear stable until a critical level of incidental mortality occurs. After this threshold, the risk of extirpation for a local population may rapidly increase with only minimal increases in wind mortality. Conservation biologists and wildlife managers may need to consider this mortality pattern when issuing take permits and developing monitoring protocols for wind facilities. We also describe how our branching process models may be generalized across a wider range of species for a larger assessment project and then describe how our methods may be applied to other stressors in addition to wind.
The Kootenai River white sturgeon (Acipenser transmontanus) and other native fish species are culturally important to the Kootenai Tribe of Idaho, but their habitat and recruitment have been affected by anthropogenic changes to the river. Although the interconnections among anthropogenic changes and their impacts on fish are complex, the Kootenai Tribe of Idaho, in cooperation with other agencies, has been trying to understand and promote native fish recruitment through the development and implementation of the Kootenai River Habitat Restoration Program. As part of this effort, the U.S. Geological Survey collected sediment and streamflow information and evaluated use of acoustic backscatter as a sediment surrogate for estimating continuous suspended-sediment concentration at three sites in the Kootenai River white sturgeon critical habitat during water years 2011–14.
\nDuring the study, total suspended-sediment and fines concentrations were driven primarily by contributions from tributaries flowing into the Kootenai River between Libby Dam and the study area and were highest during rain-on-snow events in those tributary watersheds. On average, the relative percentage of suspended-sediment concentration in equal-width-increment samples collected in water years 2011–14 composed of fines less than 0.0625 mm (called washload) was 73, 71, and 70 percent at the Below Moyie, Crossport, and Tribal Hatchery sites, respectively. Suspended sand transport often increased with high streamflows, typically but not always associated with releases from Libby Dam. Bedload measured at the Crossport site was about 5 percent, on average, of the total sediment load measured in samples collected in water years 2011–13 and was positively correlated with suspended-sediment load. Comparisons with regional regression and envelope lines for suspended-sediment and bedload transport in relation to unregulated drainage area (drainage area downstream of Libby Dam) show that sediment transport was substantially less in the Kootenai River than in selected, minimally regulated Rocky Mountain rivers.
\nAcoustic surrogate ratings were developed between backscatter data collected using acoustic Doppler velocity meters (ADVMs) and results of suspended-sediment samples. Ratings were successfully fit to various sediment size classes (total, fines, and sands) using ADVMs of different frequencies (1.5 and 3 megahertz). Surrogate ratings also were developed using variations of streamflow and seasonal explanatory variables. The streamflow surrogate ratings produced average annual sediment load estimates that were 8–32 percent higher, depending on site and sediment type, than estimates produced using the acoustic surrogate ratings. The streamflow surrogate ratings tended to overestimate suspended-sediment concentrations and loads during periods of elevated releases from Libby Dam as well as on the falling limb of the streamflow hydrograph. Estimates from the acoustic surrogate ratings more closely matched suspended-sediment sample results than did estimates from the streamflow surrogate ratings during these periods as well as for rating validation samples collected in water year 2014. Acoustic surrogate technologies are an effective means to obtain continuous, accurate estimates of suspended-sediment concentrations and loads for general monitoring and sediment-transport modeling. In the Kootenai River, continued operation of the acoustic surrogate sites and use of the acoustic surrogate ratings to calculate continuous suspended-sediment concentrations and loads will allow for tracking changes in sediment transport over time.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155169","collaboration":"Prepared in cooperation with the Kootenai Tribe of Idaho","usgsCitation":"Wood, M.S., Fosness, R.L., and Etheridge, A.B., 2015, Sediment transport and evaluation of sediment surrogate ratings in the Kootenai River near Bonners Ferry, Idaho, water years 2011–14: U.S. Geological Survey Scientific Investigations Report 2015–5169, 48 p., https://dx.doi.org/10.3133/sir20155169.","productDescription":"Report:vi, 45 p.; Appendix","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-046285","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":312256,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5169/sir20155169.pdf","text":"Report","size":"2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5169 Report PDF"},{"id":312257,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5169/sir20155169_appendixA.xlsx","text":"Appendix A","size":"87 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5169 Appendix A"},{"id":312255,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5169/coverthb.jpg"}],"country":"United States","state":"Idaho","city":"Bonners Ferry","otherGeospatial":"Kootenai River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.57318115234375,\n 48.65014969395597\n ],\n [\n -116.57318115234375,\n 48.94505319583951\n ],\n [\n -116.04858398437499,\n 48.94505319583951\n ],\n [\n -116.04858398437499,\n 48.65014969395597\n ],\n [\n -116.57318115234375,\n 48.65014969395597\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
http://id.water.usgs.gov
Empirical impedance tensors obtained from EarthScope magnetotelluric data at sites distributed across the midwestern United States are used to examine the feasibility of mapping magnetic storm induction of geoelectric fields. With these tensors, in order to isolate the effects of Earth conductivity structure, we perform a synthetic analysis—calculating geoelectric field variations induced by a geomagnetic field that is geographically uniform but varying sinusoidally with a chosen set of oscillation frequencies that are characteristic of magnetic storm variations. For north-south oriented geomagnetic oscillations at a period of T0=100 s, induced geoelectric field vectors show substantial geographically distributed differences in amplitude (approximately a factor of 100), direction (up to 130∘), and phase (over a quarter wavelength). These differences are the result of three-dimensional Earth conductivity structure, and they highlight a shortcoming of one-dimensional conductivity models (and other synthetic models not derived from direct geophysical measurement) that are used in the evaluation of storm time geoelectric hazards for the electric power grid industry. A hypothetical extremely intense magnetic storm having 500 nT amplitude at T0=100 s would induce geoelectric fields with an average amplitude across the midwestern United States of about 2.71 V/km, but with a representative site-to-site range of 0.15 V/km to 16.77 V/km. Significant improvement in the evaluation of such hazards will require detailed knowledge of the Earth's interior three-dimensional conductivity structure.
\n","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015GL066636","usgsCitation":"Bedrosian, P.A., and Love, J.J., 2015, Mapping geoelectric fields during magnetic storms: Synthetic analysis of empirical United States impedances: Geophysical Research Letters, v. 42, no. 23, p. 10160-10170, https://doi.org/10.1002/2015GL066636.","productDescription":"11 p.","startPage":"10160","endPage":"10170","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070730","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":471565,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015gl066636","text":"Publisher Index Page"},{"id":316741,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"42","issue":"23","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-14","publicationStatus":"PW","scienceBaseUri":"56bb1bc7e4b08d617f654e29","contributors":{"authors":[{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":597711,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Love, Jeffrey J. 0000-0002-3324-0348 jlove@usgs.gov","orcid":"https://orcid.org/0000-0002-3324-0348","contributorId":760,"corporation":false,"usgs":true,"family":"Love","given":"Jeffrey","email":"jlove@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":597712,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70161863,"text":"70161863 - 2015 - The role of dynamic surface water-groundwater exchange on streambed denitrification in a first-order, low-relief agricultural watershed","interactions":[],"lastModifiedDate":"2016-12-16T10:44:50","indexId":"70161863","displayToPublicDate":"2015-12-13T15:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"The role of dynamic surface water-groundwater exchange on streambed denitrification in a first-order, low-relief agricultural watershed","docAbstract":"
The role of temporally varying surface water-groundwater (SW-GW) exchange on nitrate removal by streambed denitrification was examined along a reach of Leary Weber Ditch (LWD), Indiana, a small, first-order, low-relief agricultural watershed within the Upper Mississippi River basin, using data collected in 2004 and 2005. Stream stage, GW heads (H), and temperatures (T) were continuously monitored in streambed piezometers and stream bank wells for two transects across LWD accompanied by synoptic measurements of stream stage, H, T, and nitrate (NO3) concentrations along the reach. The H and T data were used to develop and calibrate vertical two-dimensional, models of streambed water flow and heat transport across and along the axis of the stream. Model-estimated SW-GW exchange varied seasonally and in response to high-streamflow events due to dynamic interactions between SW stage and GW H. Comparison of 2004 and 2005 conditions showed that small changes in precipitation amount and intensity, evapotranspiration, and/or nearby GW levels within a low-relief watershed can readily impact SW-GW interactions. The calibrated LWD flow models and observed stream and streambed NO3 concentrations were used to predict temporal variations in streambed NO3 removal in response to dynamic SW-GW exchange. NO3 removal rates underwent slow seasonal changes, but also underwent rapid changes in response to high-flow events. These findings suggest that increased temporal variability of SW-GW exchange in low-order, low-relief watersheds may be a factor contributing their more efficient removal of NO3.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2014WR016739","usgsCitation":"Rahimi Kazerooni, M.N., Essaid, H.I., and Wilson, J.T., 2015, The role of dynamic surface water-groundwater exchange on streambed denitrification in a first-order, low-relief agricultural watershed: Water Resources Research, v. 51, no. 12, p. 9514-9538, https://doi.org/10.1002/2014WR016739.","productDescription":"25 p.","startPage":"9514","endPage":"9538","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061362","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":471568,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2014wr016739","text":"Publisher Index Page"},{"id":314041,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Indiana","otherGeospatial":"Leary Weber Ditch","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.83828449249268,\n 39.854443814802465\n ],\n [\n -85.84047317504883,\n 39.85763940869116\n ],\n [\n -85.84309101104736,\n 39.85974776029954\n ],\n [\n -85.84562301635741,\n 39.86034072251865\n ],\n [\n -85.84811210632324,\n 39.85987953012439\n ],\n [\n -85.84965705871582,\n 39.85796884289973\n ],\n [\n -85.84982872009277,\n 39.85609104672825\n ],\n [\n -85.84794044494629,\n 39.85605810247719\n ],\n [\n -85.84725379943846,\n 39.85757352165968\n ],\n [\n -85.8457088470459,\n 39.85819944590483\n ],\n [\n -85.84377765655518,\n 39.85721114185585\n ],\n [\n -85.83987236022949,\n 39.853323674511145\n ],\n [\n -85.83871364593504,\n 39.85137985826863\n ],\n [\n -85.83768367767334,\n 39.84798628442432\n ],\n [\n -85.83673954010008,\n 39.846108215141285\n ],\n [\n -85.8330488204956,\n 39.84561397784372\n ],\n [\n -85.8301305770874,\n 39.84479024110811\n ],\n [\n -85.82794189453125,\n 39.841989462283536\n ],\n [\n -85.82360744476318,\n 39.84192356022963\n ],\n [\n -85.82369327545166,\n 39.84334044044997\n ],\n [\n -85.82661151885986,\n 39.843406341144004\n ],\n [\n -85.82824230194092,\n 39.84558102856405\n ],\n [\n -85.82961559295654,\n 39.8466353976705\n ],\n [\n -85.83193302154541,\n 39.847294370139366\n ],\n [\n -85.8345079421997,\n 39.84782154356041\n ],\n [\n -85.83566665649414,\n 39.84834871293334\n ],\n [\n -85.83600997924805,\n 39.85049029688317\n ],\n [\n -85.83828449249268,\n 39.854443814802465\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"51","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-13","publicationStatus":"PW","scienceBaseUri":"5690ebd1e4b09c7f9a218bec","contributors":{"authors":[{"text":"Rahimi Kazerooni, Mina N. mrahimikazerooni@usgs.gov","contributorId":5706,"corporation":false,"usgs":true,"family":"Rahimi Kazerooni","given":"Mina","email":"mrahimikazerooni@usgs.gov","middleInitial":"N.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":false,"id":587984,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Essaid, Hedeff I. 0000-0003-0154-8628 hiessaid@usgs.gov","orcid":"https://orcid.org/0000-0003-0154-8628","contributorId":2284,"corporation":false,"usgs":true,"family":"Essaid","given":"Hedeff","email":"hiessaid@usgs.gov","middleInitial":"I.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":587983,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilson, John T. 0000-0001-6752-4069 jtwilson@usgs.gov","orcid":"https://orcid.org/0000-0001-6752-4069","contributorId":1954,"corporation":false,"usgs":true,"family":"Wilson","given":"John","email":"jtwilson@usgs.gov","middleInitial":"T.","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":false,"id":587985,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70159654,"text":"fs20153079 - 2015 - Shift in Global Tantalum Mine Production, 2000–2014","interactions":[],"lastModifiedDate":"2016-02-02T13:22:21","indexId":"fs20153079","displayToPublicDate":"2015-12-10T15:00:00","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":"2015-3079","title":"Shift in Global Tantalum Mine Production, 2000–2014","docAbstract":"Tantalum has a unique set of properties that make it useful in a number of diverse applications. The ability of the metal to store and release electrical energy makes it ideally suited for use in certain types of capacitors that are widely used in modern electronics. Approximately 60 percent of global tantalum consumption is in the electronics industry. The ductility and corrosion resistance of the metal lends itself to application in the chemical processing industry, and its high melting point and high strength retention at elevated temperatures make it an important component of super alloys used in aircraft engines.
\nAs a major industrialized nation, the United States is a leading consumer of tantalum and tantalum-containing products. Domestic deposits typically are of low grade, and no tantalum has been recovered from mining activities in the United States since 1959. Consequently, the United States is nearly completely reliant on imports to meet its domestic consumption of tantalum for economic and national security needs. The recovery of tantalum from mine production is economically viable in only a few countries.
\nAlthough developed countries dominated tantalum mine production in the early 2000s, production today is dominated by countries in the Great Lakes Region of Africa. There is concern that the sales of minerals, including columbite-tantalite or “coltan,” a mineral from which tantalum is derived, have helped finance rebel groups accused of violating human rights as part of the continuing armed conflict in the Democratic Republic of the Congo (DRC) and neighboring countries. These accusations have prompted the passage of legislation in the United States to curb the procurement of these mineral commodities, referred to as “conflict minerals,” from the DRC. Specifically, section 1502 of the 2010 Dodd-Frank Wall Street Reform and Consumer Protection Act (Public Law 111–203, 124 Stat. 2213–2218) requires companies that source tantalum, tin, tungsten, and gold (3TG) to perform due diligence on their supply chains to determine if the materials they use originate from the DRC or adjoining countries (defined as sharing a border with the DRC).
\nThe DRC, Rwanda, and surrounding countries are not globally significant sources of tin, tungsten, or gold, accounting for only about 2 percent of the mined world supply for each of these elements. The region has, however, evolved to become the world’s largest producer of mined tantalum.
\nA further complication of the production of tantalum stems from the opacity of the tantalum market. Unlike most base and precious metals, tantalum concentrates are not publicly traded through commodities exchanges but are bought and sold through networks of dealers and on contract between producers and consumers, some of whom may not provide accurate statistical data concerning the amounts, origins, and destination of the concentrates. Some price data can be found in trade journals or in other publications; however, there are no recognized official set exchange prices for either concentrate or tantalum metal. Because price is determined by negotiation between buyer and seller, published prices for concentrate are probably not representative of global prices paid for concentrate. The development of a mine-to-market supply-chain analysis is complicated and difficult because many of the industry participants that produce, trade, and consume tantalum do not publish statistical information, contracts are long term between miners and buyers, and much of the industry is vertically integrated.
\nAs a result of these and other considerations, tantalum is considered by many to be a “critical” commodity. This fact sheet identifies and addresses the major geographic shifts in the source of mine production of tantalum which have occurred over the past 15 years, some of the factors that drove this shift, and some of the related consequences.
\nOne of the activities of the U.S. Geological Survey National Minerals Information Center (USGS-NMIC) is to analyze global supply chains and characterize major components of mineral and material flows from ore extraction through processing to first tier products. These analyses support the core mission of the USGS-NMIC as the Federal entity responsible for the collection, analysis, and dissemination of objective, unbiased, factual information on minerals essential to the U.S. economy and national security.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153079","usgsCitation":"Bleiwas, D.I., Papp, J.F., and Yager, T.R., 2015, Shift in global tantalum mine production, 2000–2014: U.S. Geological Survey Fact Sheet 2015–3079, 6 p., https://dx.doi.org/10.3133/fs20153079.","productDescription":"6 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070022","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":312092,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3079/fs20153079.pdf","text":"Report","size":"469 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2015-3079"},{"id":312091,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2015/3079/coverthb.jpg"}],"contact":"Director, National Minerals Information Center
U.S. Geological Survey
12201 Sunrise Valley Drive
988 National Center
Reston, VA 20192
Email: nmicrecordsmgt@usgs.gov
Or visit the USGS Minerals Information Web site at http://minerals.usgs.gov/minerals/
","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2015-12-10","noUsgsAuthors":false,"publicationDate":"2015-12-10","publicationStatus":"PW","scienceBaseUri":"566aa23ee4b09cfe53ca44df","contributors":{"authors":[{"text":"Bleiwas, Donald I. bleiwas@usgs.gov","contributorId":1434,"corporation":false,"usgs":true,"family":"Bleiwas","given":"Donald","email":"bleiwas@usgs.gov","middleInitial":"I.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":579900,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Papp, John F. jpapp@usgs.gov","contributorId":2895,"corporation":false,"usgs":true,"family":"Papp","given":"John","email":"jpapp@usgs.gov","middleInitial":"F.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":579901,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yager, Thomas R. tyager@usgs.gov","contributorId":499,"corporation":false,"usgs":true,"family":"Yager","given":"Thomas","email":"tyager@usgs.gov","middleInitial":"R.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":false,"id":579902,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70160084,"text":"70160084 - 2015 - A new method to generate a high-resolution global distribution map of lake chlorophyll","interactions":[],"lastModifiedDate":"2015-12-10T13:35:13","indexId":"70160084","displayToPublicDate":"2015-12-10T14:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2068,"text":"International Journal of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"A new method to generate a high-resolution global distribution map of lake chlorophyll","docAbstract":"A new method was developed, evaluated, and applied to generate a global dataset of growing-season chlorophyll-a (chl) concentrations in 2011 for freshwater lakes. Chl observations from freshwater lakes are valuable for estimating lake productivity as well as assessing the role that these lakes play in carbon budgets. The standard 4 km NASA OceanColor L3 chlorophyll concentration products generated from MODIS and MERIS sensor data are not sufficiently representative of global chl values because these can only resolve larger lakes, which generally have lower chl concentrations than lakes of smaller surface area. Our new methodology utilizes the 300 m-resolution MERIS full-resolution full-swath (FRS) global dataset as input and does not rely on the land mask used to generate standard NASA products, which masks many lakes that are otherwise resolvable in MERIS imagery. The new method produced chl concentration values for 78,938 and 1,074 lakes in the northern and southern hemispheres, respectively. The mean chl for lakes visible in the MERIS composite was 19.2 ± 19.2, the median was 13.3, and the interquartile range was 3.90–28.6 mg m−3. The accuracy of the MERIS-derived values was assessed by comparison with temporally near-coincident and globally distributed in situmeasurements from the literature (n = 185, RMSE = 9.39, R2 = 0.72). This represents the first global-scale dataset of satellite-derived chl estimates for medium to large lakes.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/01431161.2015.1029099","usgsCitation":"Sayers, M., Grimm, A.G., Shuchman, R.A., Deines, A., Bunnell, D., Raymer, Z., Rogers, M.W., Woelmer, W., Bennion, D., Brooks, C., Whitley, M.A., Warner, D.M., and Mychek-Londer, J., 2015, A new method to generate a high-resolution global distribution map of lake chlorophyll: International Journal of Remote Sensing, v. 36, no. 7, p. 1942-1964, https://doi.org/10.1080/01431161.2015.1029099.","productDescription":"23 p.","startPage":"1942","endPage":"1964","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062466","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":471569,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/01431161.2015.1029099","text":"Publisher Index 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Volumes A, B, and D provide similar analyses for the Western United States, the Great Plains of the United States, and the Eastern United States, respectively. The assessments of land-use and land-cover trends are conducted on an ecoregion-by-ecoregion basis, and each ecoregion assessment is guided by a nationally consistent study design that includes mapping, statistical methods, field studies, and analysis. Individual assessments provide a picture of the characteristics of land change occurring in a given ecoregion; in combination, they provide a framework for understanding the complex national mosaic of change and also the causes and consequences of change. Thus, each volume in this series provides a regional assessment of how (and how fast) land use and land cover are changing, and why. The four volumes together form the first comprehensive picture of land change across the Nation.
Geographic understanding of land-use and land-cover change is directly relevant to a wide variety of stakeholders, including land and resource managers, policymakers, and scientists. The chapters in this volume present brief summaries of the patterns and rates of land change observed in each ecoregion in the Midwest–South Central United States, together with field photographs, statistics, and comparisons with other assessments. In addition, a synthesis chapter summarizes the scope of land change observed across the entire Midwest–South Central United States. The studies provide a way of integrating information across the landscape, and they form a critical component in the efforts to understand how land use and land cover affect important issues such as the provision of ecological goods and services and also the determination of risks to, and vulnerabilities of, human communities. Results from this project also are published in peer-reviewed journals, and they are further used to produce maps of change and other tools for land management, as well as to provide inputs for carbon-cycle modeling and other climate change research.
Contact information, U.S. Geological Survey
Earth Resources Observation and Science (EROS) Center
47914 252nd Street
Sioux Falls, SD 57198-0001
This report summarizes outcomes from a two-day scenario planning workshop for Acadia National Park, Maine. The primary objective of the workshop was to help Acadia senior leadership make management and planning decisions based on up-to-date climate science and assessments of future uncertainty. The workshop was also designed as a training program, helping build participants' capabilities to develop and use scenarios. The details of the workshop are given in later sections. The climate scenarios presented here are based on published global climate model output. The scenario implications for resources and management decisions are based on expert knowledge distilled through scientist-manager interaction during workgroup break-out sessions at the workshop. Thus, the descriptions below are from these small-group discussions in a workshop setting and should not be taken as vetted research statements of responses to the climate scenarios, but rather as insights and examinations of possible futures. Here we provide the main conclusions from the scenario planning workshop.
","language":"English","publisher":"National Park Service","usgsCitation":"Star, J., Fisichelli, N., Bryan, A., Babson, A., Cole-Will, R., and Miller-Rushing, A.J., 2015, Acadia National Park climate change scenario planning workshop summary, 50 p.","productDescription":"50 p.","ipdsId":"IP-069634","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":381169,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":381167,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://home.nps.gov/subjects/climatechange/acadiaworkshop.htm"}],"country":"United States","state":"Maine","otherGeospatial":"Acadia National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.45100402832031,\n 44.22650439062394\n ],\n [\n -68.13789367675781,\n 44.22650439062394\n ],\n [\n -68.13789367675781,\n 44.42446328709913\n ],\n [\n -68.45100402832031,\n 44.42446328709913\n ],\n [\n -68.45100402832031,\n 44.22650439062394\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Star, Jonathan","contributorId":168823,"corporation":false,"usgs":false,"family":"Star","given":"Jonathan","email":"","affiliations":[{"id":25365,"text":"Scenario Insight","active":true,"usgs":false}],"preferred":false,"id":806566,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fisichelli, Nicholas","contributorId":168824,"corporation":false,"usgs":false,"family":"Fisichelli","given":"Nicholas","affiliations":[{"id":25366,"text":"National Park Service, Climate Change Response Program","active":true,"usgs":false}],"preferred":false,"id":806567,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bryan, Alexander 0000-0003-2040-7636 abryan@usgs.gov","orcid":"https://orcid.org/0000-0003-2040-7636","contributorId":168822,"corporation":false,"usgs":true,"family":"Bryan","given":"Alexander","email":"abryan@usgs.gov","affiliations":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":806568,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Babson, Amanda","contributorId":168825,"corporation":false,"usgs":false,"family":"Babson","given":"Amanda","email":"","affiliations":[{"id":25367,"text":"National Park Service, Northeast Region","active":true,"usgs":false}],"preferred":false,"id":806569,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cole-Will, Rebecca","contributorId":168826,"corporation":false,"usgs":false,"family":"Cole-Will","given":"Rebecca","email":"","affiliations":[{"id":25368,"text":"National Park Service, Acadia National Park","active":true,"usgs":false}],"preferred":false,"id":806570,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miller-Rushing, Abraham J.","contributorId":149650,"corporation":false,"usgs":false,"family":"Miller-Rushing","given":"Abraham","email":"","middleInitial":"J.","affiliations":[{"id":7237,"text":"NPS, Olympic National Park","active":true,"usgs":false}],"preferred":false,"id":806571,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70216840,"text":"70216840 - 2015 - Indicators of climate impacts for forests: Recommendations for the U.S. National Climate Assessment Indicators system","interactions":[],"lastModifiedDate":"2020-12-09T14:26:06.364871","indexId":"70216840","displayToPublicDate":"2015-12-09T08:18:32","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Indicators of climate impacts for forests: Recommendations for the U.S. National Climate Assessment Indicators system","docAbstract":"The Third National Climate Assessment (NCA) process for the United States focused in part on developing a system of indicators to communicate key aspects of the physical climate, climate impacts, vulnerabilities, and preparedness to inform decisionmakers and the public. Initially, 13 active teams were formed to recommend indicators in a range of categories, including forest, agriculture, grassland, phenology, mitigation, and physical climate. This publication describes the work of the Forest Indicators Technical Team. We briefly describe the NCA indicator system effort, propose and explain our conceptual model for the forest system, present our methods, and discuss our recommendations. Climate is only one driver of changes in U.S. forests; other drivers include socioeconomic drivers such as population and culture, and other environmental drivers such as nutrients, light, and disturbance. We offer additional details of our work for transparency and to inform an NCA indicator Web portal. We recommend metrics for 11 indicators of climate impacts on forest, spanning the range of important aspects of forest as an ecological type and as a sector. Some indicators can be reported in a Web portal now; others need additional work for reporting in the near future. Indicators such as budburst, which are important to forest but more relevant to other NCA indicator teams, are identified. Potential indicators that need more research are also presented.
","language":"English","publisher":"U.S. Forest Service","doi":"10.2737/NRS-GTR-155","collaboration":"USDA Forest Service, Northern Research Station, USGCRP","usgsCitation":"Heath, L.S., Anderson, S., Emery, M.R., Hicke, J., Littell, J.S., Lucier, A., Masek, J.G., Peterson, D.L., Pouyat, R., Potter, K.M., Robertson, G., Sperry, J., Bytnerowicz, A., Jovan, S.E., Mockrin, M.H., Musselman, R., Schulz, B.K., Smith, R.J., and Stewart, S.I., 2015, Indicators of climate impacts for forests: Recommendations for the U.S. National Climate Assessment Indicators system, 143 p., https://doi.org/10.2737/NRS-GTR-155.","productDescription":"143 p.","ipdsId":"IP-065101","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":471570,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2737/nrs-gtr-155","text":"Publisher Index 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Central Valley, California, USA","interactions":[],"lastModifiedDate":"2015-12-08T13:39:29","indexId":"70157562","displayToPublicDate":"2015-12-08T14:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"A statistical learning framework for groundwater nitrate models of the Central Valley, California, USA","docAbstract":"We used a statistical learning framework to evaluate the ability of three machine-learning methods to predict nitrate concentration in shallow groundwater of the Central Valley, California: boosted regression trees (BRT), artificial neural networks (ANN), and Bayesian networks (BN). Machine learning methods can learn complex patterns in the data but because of overfitting may not generalize well to new data. The statistical learning framework involves cross-validation (CV) training and testing data and a separate hold-out data set for model evaluation, with the goal of optimizing predictive performance by controlling for model overfit. The order of prediction performance according to both CV testing R2 and that for the hold-out data set was BRT > BN > ANN. For each method we identified two models based on CV testing results: that with maximum testing R2 and a version with R2 within one standard error of the maximum (the 1SE model). The former yielded CV training R2 values of 0.94–1.0. Cross-validation testing R2 values indicate predictive performance, and these were 0.22–0.39 for the maximum R2 models and 0.19–0.36 for the 1SE models. Evaluation with hold-out data suggested that the 1SE BRT and ANN models predicted better for an independent data set compared with the maximum R2 versions, which is relevant to extrapolation by mapping. Scatterplots of predicted vs. observed hold-out data obtained for final models helped identify prediction bias, which was fairly pronounced for ANN and BN. Lastly, the models were compared with multiple linear regression (MLR) and a previous random forest regression (RFR) model. Whereas BRT results were comparable to RFR, MLR had low hold-out R2 (0.07) and explained less than half the variation in the training data. Spatial patterns of predictions by the final, 1SE BRT model agreed reasonably well with previously observed patterns of nitrate occurrence in groundwater of the Central Valley.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2015.10.025","usgsCitation":"Nolan, B.T., Fienen, M., and Lorenz, D.L., 2015, A statistical learning framework for groundwater nitrate models of the Central Valley, California, USA: Journal of Hydrology, v. 531, no. 3, p. 902-911, https://doi.org/10.1016/j.jhydrol.2015.10.025.","productDescription":"10 p.","startPage":"902","endPage":"911","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065964","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":471571,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2015.10.025","text":"Publisher Index Page"},{"id":312041,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.025146484375,\n 40.73893324113603\n ],\n [\n -122.93701171874999,\n 40.38002840251183\n ],\n [\n -122.16796875,\n 38.048091067457236\n ],\n [\n -119.39941406249999,\n 34.95799531086792\n ],\n [\n -118.67431640625,\n 34.97600151317591\n ],\n [\n -118.795166015625,\n 36.19995805932895\n ],\n [\n -120.92651367187499,\n 38.38472766885085\n ],\n [\n -122.025146484375,\n 40.73893324113603\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"531","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5667ff32e4b06a3ea36c8e04","contributors":{"authors":[{"text":"Nolan, Bernard T. 0000-0002-6945-9659 btnolan@usgs.gov","orcid":"https://orcid.org/0000-0002-6945-9659","contributorId":2190,"corporation":false,"usgs":true,"family":"Nolan","given":"Bernard","email":"btnolan@usgs.gov","middleInitial":"T.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":573640,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fienen, Michael N. 0000-0002-7756-4651 mnfienen@usgs.gov","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":893,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","email":"mnfienen@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":573641,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lorenz, David L. 0000-0003-3392-4034 lorenz@usgs.gov","orcid":"https://orcid.org/0000-0003-3392-4034","contributorId":1384,"corporation":false,"usgs":true,"family":"Lorenz","given":"David","email":"lorenz@usgs.gov","middleInitial":"L.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":573642,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70160008,"text":"70160008 - 2015 - Surprise and opportunity for learning in Grand Canyon: the Glen Canyon Dam Adaptive Management Program","interactions":[],"lastModifiedDate":"2015-12-08T12:25:42","indexId":"70160008","displayToPublicDate":"2015-12-08T13:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1468,"text":"Ecology and Society","active":true,"publicationSubtype":{"id":10}},"title":"Surprise and opportunity for learning in Grand Canyon: the Glen Canyon Dam Adaptive Management Program","docAbstract":"With a focus on resources of the Colorado River ecosystem below Glen Canyon Dam, the Glen Canyon Dam Adaptive Management Program has included a variety of experimental policy tests, ranging from manipulation of water releases from the dam to removal of non-native fish within Grand Canyon National Park. None of these field-scale experiments has yet produced unambiguous results in terms of management prescriptions. But there has been adaptive learning, mostly from unanticipated or surprising resource responses relative to predictions from ecosystem modeling. Surprise learning opportunities may often be viewed with dismay by some stakeholders who might not be clear about the purpose of science and modeling in adaptive management. However, the experimental results from the Glen Canyon Dam program actually represent scientific successes in terms of revealing new opportunities for developing better river management policies. A new long-term experimental management planning process for Glen Canyon Dam operations, started in 2011 by the U.S. Department of the Interior, provides an opportunity to refocus management objectives, identify and evaluate key uncertainties about the influence of dam releases, and refine monitoring for learning over the next several decades. Adaptive learning since 1995 is critical input to this long-term planning effort. Embracing uncertainty and surprise outcomes revealed by monitoring and ecosystem modeling will likely continue the advancement of resource objectives below the dam, and may also promote efficient learning in other complex programs.
","language":"English","publisher":"The Resilience Alliance","doi":"10.5751/ES-07621-200322","usgsCitation":"Melis, T., Walters, C., and Korman, J., 2015, Surprise and opportunity for learning in Grand Canyon: the Glen Canyon Dam Adaptive Management Program: Ecology and Society, v. 20, no. 3, Art22; 33 p., https://doi.org/10.5751/ES-07621-200322.","productDescription":"Art22; 33 p.","numberOfPages":"33","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-022401","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":471572,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/es-07621-200322","text":"Publisher Index Page"},{"id":312037,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Nevada, Utah","otherGeospatial":"Colorado River, Glen Canyon Dam, Grand Canyon National Park, Lake Mead","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.60937499999999,\n 35.33977430038646\n ],\n [\n -114.60937499999999,\n 37.37015718405753\n ],\n [\n -110.76416015625,\n 37.37015718405753\n ],\n [\n -110.76416015625,\n 35.33977430038646\n ],\n [\n -114.60937499999999,\n 35.33977430038646\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"20","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5667ff3ce4b06a3ea36c8e12","contributors":{"authors":[{"text":"Melis, Theodore S. 0000-0003-0473-3968 tmelis@usgs.gov","orcid":"https://orcid.org/0000-0003-0473-3968","contributorId":1829,"corporation":false,"usgs":true,"family":"Melis","given":"Theodore S.","email":"tmelis@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":581538,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walters, Carl","contributorId":66156,"corporation":false,"usgs":true,"family":"Walters","given":"Carl","affiliations":[],"preferred":false,"id":581539,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Korman, Josh","contributorId":29922,"corporation":false,"usgs":true,"family":"Korman","given":"Josh","affiliations":[],"preferred":false,"id":581540,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70159406,"text":"sir20155153 - 2015 - Simulation of the effects of different inflows on hydrologic conditions in Lake Houston with a three-dimensional hydrodynamic model, Houston, Texas, 2009–10","interactions":[],"lastModifiedDate":"2020-05-19T18:00:59.387807","indexId":"sir20155153","displayToPublicDate":"2015-12-08T12:00:00","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":"2015-5153","title":"Simulation of the effects of different inflows on hydrologic conditions in Lake Houston with a three-dimensional hydrodynamic model, Houston, Texas, 2009–10","docAbstract":"Lake Houston, an important water resource for the Houston, Texas, area, receives inflows from seven major tributaries that compose the San Jacinto River Basin upstream from the reservoir. The effects of different inflows from the watersheds drained by these tributaries on the residence time of water in Lake Houston and closely associated physical and chemical properties including lake elevation, salinity, and water temperature are not well known. Accordingly, the U.S. Geological Survey (USGS), in cooperation with the City of Houston, developed a three-dimensional hydrodynamic model of Lake Houston as a tool for evaluating the effects of different inflows on residence time of water in the lake and associated physical and chemical properties. The Environmental Fluid Dynamics Code (EFDC), a grid-based, surface-water modeling package for simulating three-dimensional circulation, mass transport, sediments, and biogeochemical processes, was used to develop the model of Lake Houston. The Lake Houston EFDC model was developed and calibrated by using 2009 data and verified by using 2010 data. Three statistics (mean error, root mean square error, and the Nash-Sutcliffe model efficiency coefficient) were used to evaluate how well the Lake Houston EFDC model simulated lake elevation, salinity, and water temperature. The residence time of water in reservoirs is associated with various physical and chemical properties (including lake elevation, salinity, and water temperature). Simulated and measured lake-elevation values were compared at USGS reservoir station 08072000 Lake Houston near Sheldon, Tex. The accuracy of simulated salinity and water temperature values was assessed by using the salinity (computed from measured specific conductance) and water temperature at two USGS monitoring stations: 295826095082200 Lake Houston south Union Pacific Railroad Bridge near Houston, Tex., and 295554095093401 Lake Houston at mouth of Jack’s Ditch near Houston, Tex. Specific conductance and water temperature were measured at as many as four different depths at each of the two monitoring stations during 2009 and then used for assessing the accuracy of simulated values of salinity and water temperature during 2010. The performance evaluation statistics indicate that the model performed satisfactorily. The calibrated model was used to simulate two possible inflow scenarios to evaluate the changes in the residence time of water in Lake Houston. The two scenarios tested were an increased inflow of approximately 300 cubic feet per second for 1 month (May 2010) from two watersheds: the West Fork San Jacinto River and Luce Bayou. These scenarios were chosen to mimic the effects of possible small releases or diversions of water from outside the San Jacinto River Basin into the basin (or directly into the lake) on the residence time of water in Lake Houston. During the time of increased inflow for the two scenarios tested, maximum residence time decreased slightly from approximately 106 to 97 days.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155153","collaboration":"Prepared in cooperation with the City of Houston","usgsCitation":"Rendon, S.H., and Lee, M.T., 2015, Simulation of the effects of different inflows on hydrologic conditions in Lake Houston with a three-dimensional hydrodynamic model, Houston, Texas, 2009–10: U.S. Geological Survey Scientific Investigations Report 2015–5153, 42 p., https://dx.doi.org/10.3133/sir20155153.","productDescription":"vi, 42 p.","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-060635","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":311980,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5153/sir20155153.pdf","text":"Report","size":"13.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5153"},{"id":311979,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5153/coverthb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Lake Houston","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.99578857421875,\n 29.90256760730233\n ],\n [\n -95.99578857421875,\n 30.62845887475364\n ],\n [\n -95.10040283203125,\n 30.62845887475364\n ],\n [\n -95.10040283203125,\n 29.90256760730233\n ],\n [\n -95.99578857421875,\n 29.90256760730233\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, Texas 78754–4501
http://tx.usgs.gov/
Geologic cross section I‒I’ is the fourth in a series of cross sections constructed by the U.S. Geological Survey to document and improve understanding of the geologic framework and petroleum systems of the Appalachian basin. Cross section I‒I’ provides a regional view of the structural and stratigraphic framework of the Appalachian basin from the eastern margin of the Illinois basin in central Kentucky, across the Cincinnati arch (Lexington dome), to the Valley and Ridge province in southwestern Virginia, a distance of approximately 280 miles. This cross section is a companion to cross sections E‒E’, D‒D’, and C‒C’ that are located about 200 to 300 miles to the northeast. Cross section I‒I’ either updates or complements earlier geologic cross sections through the central Kentucky and southwestern Virginia part of the Appalachian basin. Although other published cross sections through parts of the basin show more structural and stratigraphic detail, these other cross sections are of more limited extent geographically and (or) stratigraphically.
\nCross section I‒I ’ contains much information that is useful for evaluating energy resources in the Appalachian basin. Many of the key elements of the Appalachian basin petroleum systems (such as source rocks, reservoir rocks, seals, and traps) can be inferred from lithologic units, unconformities, and geologic structures shown on the cross section. Other aspects of petroleum systems (such as the timing of petroleum generation and petroleum migration pathways) may be evaluated by burial history, thermal history, and fluid flow models on the basis of what is shown on the cross section. Cross section I‒I’ also provides a stratigraphic and structural framework for the Pennsylvanian coal-bearing section. In addition, geologists and engineers could use cross section I‒I’ as a reconnaissance tool to identify plausible geologic structures and strata for the subsurface storage of liquid waste or for the sequestration of carbon dioxide.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3343","usgsCitation":"Ryder, R.T., Trippi, M.H., and Swezey, C.S., 2015, Geologic cross section I–I′ through the Appalachian basin from the eastern margin of the Illinois basin, Jefferson County, Kentucky, to the Valley and Ridge province, Scott County, Virginia: U.S. Geological Survey Scientific Investigations Map 3343, 2 sheets and pamphlet A, 41 p.; pamphlet B, 102 p., https://dx.doi.org/10.3133/sim3343.","productDescription":"Pamphlet A: iii, 41 p.; Pamphlet B: Appendix; 2 Sheets: 51.0 x 41.0 inches and 47.31 x 41.00 inches","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-021269","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":311693,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3343/sim3343_sheet2.pdf","text":"SIM 3343 - Sheet 2","size":"4.98 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Energy Resources Science Center
U.S. Geological Survey
954 National Center
12201 Sunrise Valley Drive
Reston, Virginia 20192
http://energy.usgs.gov/GeneralInfo/
ScienceCenters/Eastern.aspx
Or
Michael H. Trippi
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, Virginia 20192