{"pageNumber":"484","pageRowStart":"12075","pageSize":"25","recordCount":46651,"records":[{"id":70176621,"text":"70176621 - 2015 - Genetic diversity and host specificity varies across three genera of blood parasites in ducks of the Pacific Americas Flyway","interactions":[],"lastModifiedDate":"2018-08-16T21:28:57","indexId":"70176621","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Genetic diversity and host specificity varies across three genera of blood parasites in ducks of the Pacific Americas Flyway","docAbstract":"

Birds of the order Anseriformes, commonly referred to as waterfowl, are frequently infected by Haemosporidia of the genera Haemoproteus, Plasmodium, and Leucocytozoon via dipteran vectors. We analyzed nucleotide sequences of the Cytochrome b (Cytb) gene from parasites of these genera detected in six species of ducks from Alaska and California, USA to characterize the genetic diversity of Haemosporidia infecting waterfowl at two ends of the Pacific Americas Flyway. In addition, parasite Cytb sequences were compared to those available on a public database to investigate specificity of genetic lineages to hosts of the order Anseriformes. Haplotype and nucleotide diversity of Haemoproteus Cytb sequences was lower than was detected for Plasmodium and Leucocytozoon parasites. Although waterfowl are presumed to be infected by only a single species of Leucocytozoon, L. simondi, diversity indices were highest for haplotypes from this genus and sequences formed five distinct clades separated by genetic distances of 4.9%–7.6%, suggesting potential cryptic speciation. All Haemoproteus andLeucocytozoon haplotypes derived from waterfowl samples formed monophyletic clades in phylogenetic analyses and were unique to the order Anseriformes with few exceptions. In contrast, waterfowl-origin Plasmodium haplotypes were identical or closely related to lineages found in other avian orders. Our results suggest a more generalist strategy for Plasmodiumparasites infecting North American waterfowl as compared to those of the generaHaemoproteus and Leucocytozoon.

","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0116661","usgsCitation":"Reeves, A.B., Smith, M.M., Meixell, B.W., Fleskes, J.P., and Ramey, A.M., 2015, Genetic diversity and host specificity varies across three genera of blood parasites in ducks of the Pacific Americas Flyway: PLoS ONE, v. 10, no. 2, e0116661; 15 p., https://doi.org/10.1371/journal.pone.0116661.","productDescription":"e0116661; 15 p.","ipdsId":"IP-059454","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":472310,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0116661","text":"Publisher Index Page"},{"id":328891,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"2","noUsgsAuthors":false,"publicationDate":"2015-02-24","publicationStatus":"PW","scienceBaseUri":"57f7ee45e4b0bc0bec09e977","contributors":{"authors":[{"text":"Reeves, Andrew B. 0000-0002-7526-0726 areeves@usgs.gov","orcid":"https://orcid.org/0000-0002-7526-0726","contributorId":167362,"corporation":false,"usgs":true,"family":"Reeves","given":"Andrew","email":"areeves@usgs.gov","middleInitial":"B.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":649402,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Matthew M. 0000-0002-2259-5135 mmsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-2259-5135","contributorId":5115,"corporation":false,"usgs":true,"family":"Smith","given":"Matthew","email":"mmsmith@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":649403,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Meixell, Brandt W. 0000-0002-6738-0349 bmeixell@usgs.gov","orcid":"https://orcid.org/0000-0002-6738-0349","contributorId":138716,"corporation":false,"usgs":true,"family":"Meixell","given":"Brandt","email":"bmeixell@usgs.gov","middleInitial":"W.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":649404,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fleskes, Joseph P. 0000-0001-5388-6675 joe_fleskes@usgs.gov","orcid":"https://orcid.org/0000-0001-5388-6675","contributorId":1889,"corporation":false,"usgs":true,"family":"Fleskes","given":"Joseph","email":"joe_fleskes@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":649405,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":649406,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70126403,"text":"sir20145173 - 2015 - Geochemical conditions and the occurrence of selected trace elements in groundwater basins used for public drinking-water supply, Desert and Basin and Range hydrogeologic provinces, 2006-11: California GAMA Priority Basin Project","interactions":[],"lastModifiedDate":"2015-01-30T16:23:46","indexId":"sir20145173","displayToPublicDate":"2015-01-30T17:15:00","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":"2014-5173","title":"Geochemical conditions and the occurrence of selected trace elements in groundwater basins used for public drinking-water supply, Desert and Basin and Range hydrogeologic provinces, 2006-11: California GAMA Priority Basin Project","docAbstract":"

The geochemical conditions, occurrence of selected trace elements, and processes controlling the occurrence of selected trace elements in groundwater were investigated in groundwater basins of the Desert and Basin and Range (DBR) hydrogeologic provinces in southeastern California as part of the Priority Basin Project (PBP) of the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The GAMA PBP is designed to provide an assessment of the quality of untreated (raw) groundwater in the aquifer systems that are used for public drinking-water supply. The GAMA PBP is being conducted by the California State Water Resources Control Board in collaboration with the U.S. Geological Survey and the Lawrence Livermore National Laboratory.

\n

The DBR hydrogeologic provinces consist of 141 defined groundwater basins separated by mountain ranges, faults, and other features. This report presents analyses of data collected from nine study areas within the DBR hydrogeologic provinces: Antelope Valley, Borrego Valley, the Central Desert area, Coachella Valley, Colorado River, Indian Wells Valley, Low-Use Basins of the Mojave and Sonoran Deserts, the Mojave, and Owens Valley. Collectively, these nine study areas are referred to as the DBR study unit. The study unit covers approximately 7,000 square miles and includes the 63 groundwater basins in the DBR hydrogeologic provinces in which groundwater is used for public drinking-water supply. The vast majority of the 223 wells sampled for this study were long-screened production wells used primarily for public supply.

\n

Uncorrected carbon-14 (14C) groundwater ages for samples collected in the DBR study unit ranged from less than (<) 100 to 33,700 years before present (BP). Sixty-six percent of sample ages were greater than (>) 100 years BP, and 40 percent were >3,800 years BP. Samples collected from wells located adjacent to mountain-front recharge areas or major surface-water features generally had younger groundwater ages than did samples collected from wells located away from mountain fronts or towards the distal ends of basin groundwater flow paths. Most groundwater sampled in the DBR study unit had alkaline pH: 89 percent of sample pH values ranged from 7.1 to 9.8, with 37 percent greater than or equal to (≥) 7.9. Groundwater age was significantly correlated (positively) with pH, likely because silicate weathering is a primary control on groundwater pH and is a slow process. The oxidation-reduction (redox) condition of the groundwater sampled in the DBR study unit was predominantly oxic (71 percent), except in the Colorado River study area where organic-rich fluvial aquifers provide the electron donors necessary to support iron-reducing (anoxic-Fe) redox processes. The cation type of 78 percent of the samples was either sodium- or mixed-type, and the anion type of 83 percent of the samples was either bicarbonate- or mixed-type. Sodium-type groundwaters generally were older and more alkaline than calcium-type groundwaters, consistent with the change in water chemistry expected from cation exchange between groundwater and aquifer sediments over long periods of time. Because of the correlation with young groundwater, calcium-type groundwater was predominantly from wells located adjacent to mountain-front recharge areas.

\n

Arsenic (As), boron (B), fluoride (F), molybdenum (Mo), strontium (Sr), uranium (U), and vanadium (V) were selected for assessment in this study because they occurred at concentrations greater than California Department of Public Health or U.S. Environmental Protection Agency regulatory or non-regulatory drinking-water-quality benchmarks in more than 2 percent of the 223 samples collected in the DBR study unit. As and F were detected most commonly (18 and 13 percent, respectively) at concentrations above associated water-quality benchmarks and Sr and V least frequently (both at 3 percent). Given that 14C groundwater ages are predominantly >100 years BP, land use in the study unit is primarily undeveloped, and chemicals derived from anthropogenic sources, such as volatile organic compounds, were infrequently detected, high concentrations of these trace elements in groundwater were most likely the result of natural factors and not anthropogenic factors.

\n

As, F, Mo, and V concentrations showed significant positive correlations to groundwater age and to pH. This relation is partly due to the sources of trace elements likely being the weathering of primary minerals, such as silicate minerals, which is a slow process that takes place over hundreds to thousands of years. This relation also reflects the positive correlation between groundwater age and pH. Geochemical modeling predicted that the dominant species of As, Mo, and V in solution were oxyanions (HAsO42–, MoO42–, and H2VO4–), which are likely to be mobile in alkaline groundwater because mineral surfaces composing aquifer matrices have a predominantly negative surface charge under alkaline conditions. F also exists predominantly as a negatively charged ion (F–). At pH values >7.5, saturation indices generated by the geochemical modeling program PHREEQC indicated that F solubility may be somewhat limited by the precipitation of the mineral fluorapatite [Ca5(PO4)3F]. Speciation modeling of As in anoxic-Fe groundwater (iron-reducing conditions) showed that samples were supersaturated with orpiment (As2S3), indicating that mineral precipitation may be responsible for low As concentrations observed in reducing groundwater.

\n

In contrast, U concentrations showed significant negative correlations to groundwater age and to pH. Higher U concentrations generally occurred in samples for which geochemical modeling indicated that the uncharged ternary complex Ca2UO2(CO3)3 was the dominant aqueous U species. This uncharged complex is not attracted to the charged surfaces of minerals and thus increases U solubility. Formation of Ca2UO2(CO3)3 was greater in younger groundwaters because calcium and uranium concentrations generally were lower in older groundwaters, likely due to cation-exchange processes and precipitation of the mineral calcite as groundwater pH increased. Co-precipitation of U with the calcite (CaCO3) may remove U from the aqueous phase. Saturation indices indicated that the anoxic-Fe groundwaters from the Colorado River study area were supersaturated with the mineral uraninite (UO2), suggesting that UO2 precipitation may be responsible for the low concentrations of U observed in these samples.

\n

Concentrations of strontium, which exists primarily in a cationic form (Sr2+), were not significantly correlated with either groundwater age or pH. Strontium concentrations showed a strong positive correlation with total dissolved solids (TDS). Dissolved constituents, such as Sr, that interact with mineral surfaces through outer-sphere complexation become increasingly soluble with increasing TDS concentrations of groundwater. Boron concentrations also showed a significant positive correlation with TDS, indicating the B may interact to a large degree with mineral surfaces through outer-sphere complexation.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145173","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Wright, M., Fram, M.S., and Belitz, K., 2015, Geochemical conditions and the occurrence of selected trace elements in groundwater basins used for public drinking-water supply, Desert and Basin and Range hydrogeologic provinces, 2006-11: California GAMA Priority Basin Project: U.S. Geological Survey Scientific Investigations Report 2014-5173, viii, 48 p., https://doi.org/10.3133/sir20145173.","productDescription":"viii, 48 p.","numberOfPages":"60","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2006-01-01","temporalEnd":"2011-12-31","ipdsId":"IP-037705","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":297661,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145173.jpg"},{"id":297659,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5173/"},{"id":297660,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5173/pdf/sir2014-5173.pdf","size":"6.7 MB","linkFileType":{"id":1,"text":"pdf"}}],"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 -120.39916992187499,\n 34.43409789359469\n ],\n [\n -117.103271484375,\n 32.52828936482526\n ],\n [\n -114.444580078125,\n 32.704111144407406\n ],\n [\n -114.114990234375,\n 34.32529192442733\n ],\n [\n -114.67529296874999,\n 35.06597313798418\n ],\n [\n -117.39990234375,\n 37.081475648860525\n ],\n [\n -120.39916992187499,\n 34.43409789359469\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a7de4b08de9379b30a2","contributors":{"authors":[{"text":"Wright, Michael T. 0000-0003-0653-6466","orcid":"https://orcid.org/0000-0003-0653-6466","contributorId":116545,"corporation":false,"usgs":false,"family":"Wright","given":"Michael T.","affiliations":[],"preferred":false,"id":539646,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fram, Miranda S. 0000-0002-6337-059X mfram@usgs.gov","orcid":"https://orcid.org/0000-0002-6337-059X","contributorId":1156,"corporation":false,"usgs":true,"family":"Fram","given":"Miranda","email":"mfram@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539647,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539648,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70137521,"text":"sir20155005 - 2015 - Data Collection and Simulation of Ecological Habitat and Recreational Habitat in the Shenandoah River, Virginia","interactions":[],"lastModifiedDate":"2016-03-21T15:08:10","indexId":"sir20155005","displayToPublicDate":"2015-01-30T14:30:00","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":"2015-5005","title":"Data Collection and Simulation of Ecological Habitat and Recreational Habitat in the Shenandoah River, Virginia","docAbstract":"

This report presents updates to methods, describes additional data collected, documents modeling results, and discusses implications from an updated habitat-flow model that can be used to predict ecological habitat for fish and recreational habitat for canoeing on the main stem Shenandoah River in Virginia. Given a 76-percent increase in population predictions for 2040 over 1995 records, increased water-withdrawal scenarios were evaluated to determine the effects on habitat and recreation in the Shenandoah River. Projected water demands for 2040 vary by watershed: the North Fork Shenandoah River shows a 55.9-percent increase, the South Fork Shenandoah River shows a 46.5-percent increase, and the main stem Shenandoah River shows a 52-percent increase; most localities are projected to approach the total permitted surface-water and groundwater withdrawals values by 2040, and a few localities are projected to exceed these values.

\n

The habitat model used for this study evaluates the suitability of ecological habitat, represented by fish, and recreational habitat, represented by canoeing, based on depth, velocity, and substrate conditions, which are weighted for the physical habitat types (riffles, runs, or pools) present within a stretch of river. Weighted usable-habitat area in the Lockes Mill reach was maximized for adult smallmouth bass and sub-adult smallmouth bass (Micropterus dolomieu) and river chub (Nocomis micropogon) when streamflows were equal to median flow (900 cubic feet per second) for summer months. Ecological maximum weighted usable-habitat areas for smaller fish, such as spotfin or satinfin shiner (Cyprinella spp.), margined madtom (Noturus insignis), and juvenile redbreast sunfish (Lepomis auritus) occurred with 10th percentile flows (482 cubic feet per second) and lower. Recreational weighted usable-habitat areas for canoeing were maximized when streamflows were above the 75th percentile (1,410 cubic feet per second). During historic droughts, streamflows were less than the 10th percentile, and adult smallmouth bass and sub-adult smallmouth bass habitat was below normal for the majority of days during at least 2 months of the summer. When streamflows were less than the lowest 7-day average in a 10-year period, or 7Q10 flow (357 cubic feet per second), margined madtom, river chub, and sub-adult redbreast sunfish habitat areas were below normal as well. Streamflows that limit most fish species habit availability range from 300 to 500 cubic feet per second. For the drought years simulated, flows that were equal to or less than the 10th percentile for summer months did not provide adequate depth for canoe passage through riffle habitats. A modeling limitation for higher flows than those studied during development of the habitat-suitability criteria is that modeled habitat availability will decrease as flows increase.

\n

Time-series analyses were used to investigate changes in habitat availability with increased water withdrawals of 10, 20, and almost 50 percent (48.6 percent) up to the 2040 amounts projected by local water supply plans. Adult and sub-adult smallmouth bass frequently had habitat availability outside the normal range for habitat conditions during drought years, yet 10- or 20-percent increases in withdrawals did not contribute to a large reduction in habitat. When withdrawals were increased by 50 percent, there was an additional decrease in habitat. During 2002 drought scenarios, reduced habitat availability for sub-adult redbreast sunfish or river chub was only slightly evident with 50-percent increased withdrawal scenarios. Recreational habitat represented by canoeing decreased lower than normal during the 2002 drought. For a recent normal year, like 2012, increased water-withdrawal scenarios did not affect habitat availability for fish such as adult and sub-adult smallmouth bass, sub-adult redbreast sunfish, or river chub. Canoeing habitat availability was within the normal range most of 2012, and increased water-withdrawal scenarios showed almost no affect. For both ecological fish habitat and recreational canoeing habitat, the antecedent conditions (habitat within normal range of habitat or below normal) appear to govern whether additional water withdrawals will affect habitat availability. As human populations and water demands increase, many of the ecological or recreational stresses may be lessened by managing the timing of water withdrawals from the system.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155005","collaboration":"Prepared in cooperation with Clarke County and Warren County, Virginia","usgsCitation":"Krstolic, J.L., 2015, Data Collection and Simulation of Ecological Habitat and Recreational Habitat in the Shenandoah River, Virginia: U.S. Geological Survey Scientific Investigations Report 2015-5005, v, 30 p., https://doi.org/10.3133/sir20155005.","productDescription":"v, 30 p.","numberOfPages":"40","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054536","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":297646,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155005.jpg"},{"id":297644,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5005/"},{"id":297645,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5005/pdf/sir2015-5005.pdf","text":"Report","size":"1.83 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"projection":"Universal Transverse Mercator projection, Zone 17N","datum":"North American Datum of 1983","country":"United States","state":"Virginia","otherGeospatial":"Shenandoah River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.97649383544922,\n 39.091699613104595\n ],\n [\n -77.97649383544922,\n 39.10695312754686\n ],\n [\n -77.9190731048584,\n 39.10695312754686\n ],\n [\n -77.9190731048584,\n 39.091699613104595\n ],\n [\n -77.97649383544922,\n 39.091699613104595\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a63e4b08de9379b3032","contributors":{"authors":[{"text":"Krstolic, Jennifer L. 0000-0003-2253-9886 jkrstoli@usgs.gov","orcid":"https://orcid.org/0000-0003-2253-9886","contributorId":3677,"corporation":false,"usgs":true,"family":"Krstolic","given":"Jennifer","email":"jkrstoli@usgs.gov","middleInitial":"L.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true},{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":537861,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70139715,"text":"70139715 - 2015 - Quantification of eDNA shedding rates from invasive bighead carp Hypophthalmichthys nobilis and silver carp Hypophthalmichthys molitrix","interactions":[],"lastModifiedDate":"2021-06-04T16:19:11.920957","indexId":"70139715","displayToPublicDate":"2015-01-30T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Quantification of eDNA shedding rates from invasive bighead carp Hypophthalmichthys nobilis and silver carp Hypophthalmichthys molitrix","title":"Quantification of eDNA shedding rates from invasive bighead carp Hypophthalmichthys nobilis and silver carp Hypophthalmichthys molitrix","docAbstract":"

Wildlife managers can more easily mitigate the effects of invasive species if action takes place before a population becomes established. Such early detection requires sensitive survey tools that can detect low numbers of individuals. Due to their high sensitivity, environmental DNA (eDNA) surveys hold promise as an early detection method for aquatic invasive species. Quantification of eDNA amounts may also provide data on species abundance and timing of an organism’s presence, allowing managers to successfully combat the spread of ecologically damaging species. To better understand the link between eDNA and an organism’s presence, it is crucial to know how eDNA is shed into the environment. Our study used quantitative PCR (qPCR) and controlled laboratory experiments to measure the amount of eDNA that two species of invasive bigheaded carps (Hypophthalmichthys nobilis and Hypophthalmichthys molitrix) shed into the water. We first measured how much eDNA a single fish sheds and the variability of these measurements. Then, in a series of manipulative lab experiments, we studied how temperature, biomass (grams of fish), and diet affect the shedding rate of eDNA by these fish. We found that eDNA amounts exhibit a positive relationship with fish biomass, and that feeding could increase the amount of eDNA shed by ten-fold, whereas water temperature did not have an effect. Our results demonstrate that quantification of eDNA may be useful for predicting carp density, as well as densities of other rare or invasive species.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2014.11.020","usgsCitation":"Klymus, K.E., Richter, C.A., Chapman, D., and Paukert, C.P., 2015, Quantification of eDNA shedding rates from invasive bighead carp Hypophthalmichthys nobilis and silver carp Hypophthalmichthys molitrix: Biological Conservation, v. 183, p. 77-84, https://doi.org/10.1016/j.biocon.2014.11.020.","productDescription":"8 p.","startPage":"77","endPage":"84","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053423","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":297640,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"183","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2aa5e4b08de9379b3165","chorus":{"doi":"10.1016/j.biocon.2014.11.020","url":"http://dx.doi.org/10.1016/j.biocon.2014.11.020","publisher":"Elsevier BV","authors":"Klymus Katy E., Richter Catherine A., Chapman Duane C., Paukert Craig","journalName":"Biological Conservation","publicationDate":"3/2015","auditedOn":"1/11/2015"},"contributors":{"authors":[{"text":"Klymus, Katy E. 0000-0002-8843-6241 kklymus@usgs.gov","orcid":"https://orcid.org/0000-0002-8843-6241","contributorId":5043,"corporation":false,"usgs":true,"family":"Klymus","given":"Katy","email":"kklymus@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":539585,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Richter, Cathy A. 0000-0001-7322-4206 crichter@usgs.gov","orcid":"https://orcid.org/0000-0001-7322-4206","contributorId":1878,"corporation":false,"usgs":true,"family":"Richter","given":"Cathy","email":"crichter@usgs.gov","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":539584,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chapman, Duane 0000-0002-1086-8853 dchapman@usgs.gov","orcid":"https://orcid.org/0000-0002-1086-8853","contributorId":1291,"corporation":false,"usgs":true,"family":"Chapman","given":"Duane","email":"dchapman@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":539586,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paukert, Craig P. 0000-0002-9369-8545 cpaukert@usgs.gov","orcid":"https://orcid.org/0000-0002-9369-8545","contributorId":879,"corporation":false,"usgs":true,"family":"Paukert","given":"Craig","email":"cpaukert@usgs.gov","middleInitial":"P.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":539587,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70139644,"text":"70139644 - 2015 - Intercontinental genetic structure and gene flow in Dunlin (Calidris alpina), a potential vector of avian influenza","interactions":[],"lastModifiedDate":"2017-11-24T18:07:02","indexId":"70139644","displayToPublicDate":"2015-01-30T11:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1601,"text":"Evolutionary Applications","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Intercontinental genetic structure and gene flow in Dunlin (Calidris alpina), a potential vector of avian influenza","title":"Intercontinental genetic structure and gene flow in Dunlin (Calidris alpina), a potential vector of avian influenza","docAbstract":"

Waterfowl (Anseriformes) and shorebirds (Charadriiformes) are the most common wild vectors of influenza A viruses. Due to their migratory behavior, some may transmit disease over long distances. Migratory connectivity studies can link breeding and nonbreeding grounds while illustrating potential interactions among populations that may spread diseases. We investigated Dunlin (Calidris alpina), a shorebird with a subspecies (C. a. arcticola) that migrates from nonbreeding areas endemic to avian influenza in eastern Asia to breeding grounds in northern Alaska. Using microsatellites and mitochondrial DNA, we illustrate genetic structure among six subspecies: C. a. arcticola, C. a. pacifica, C. a. hudsonia, C. a. sakhalina, C. a. kistchinski, and C. a. actites. We demonstrate that mitochondrial DNA can help distinguish C. a. arcticola on the Asian nonbreeding grounds with >70% accuracy depending on their relative abundance, indicating that genetics can help determine whether C. a. arcticola occurs where they may be exposed to highly pathogenic avian influenza (HPAI) during outbreaks. Our data reveal asymmetric intercontinental gene flow, with some C. a. arcticola short-stopping migration to breed with C. a. pacifica in western Alaska. Because C. a. pacifica migrates along the Pacific Coast of North America, interactions between these subspecies and other taxa provide route for transmission of HPAI into other parts of North America.

","language":"English","publisher":"Wiley","doi":"10.1111/eva.12239","usgsCitation":"Miller, M., Haig, S.M., Mullins, T.D., Ruan, L., Casler, B., Dondua, A., Gates, H.R., Johnson, J., Kendall, S.J., Tomkovich, P.S., Tracy, D., Valchuk, O.P., and Lanctot, R.B., 2015, Intercontinental genetic structure and gene flow in Dunlin (Calidris alpina), a potential vector of avian influenza: Evolutionary Applications, v. 8, no. 2, p. 149-171, https://doi.org/10.1111/eva.12239.","productDescription":"23 p.","startPage":"149","endPage":"171","numberOfPages":"23","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056312","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":472317,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/eva.12239","text":"External Repository"},{"id":297637,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Russia, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -205.13671875,\n 49.26780455063753\n ],\n [\n -205.13671875,\n 72.28906720017675\n ],\n [\n -128.84765625,\n 72.28906720017675\n ],\n [\n -128.84765625,\n 49.26780455063753\n ],\n [\n -205.13671875,\n 49.26780455063753\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.984375,\n 54.16243396806781\n ],\n [\n -108.984375,\n 72.55449849665266\n ],\n [\n -71.015625,\n 72.55449849665266\n ],\n [\n -71.015625,\n 54.16243396806781\n ],\n [\n -108.984375,\n 54.16243396806781\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-01-28","publicationStatus":"PW","scienceBaseUri":"54dd2a8ae4b08de9379b30e1","chorus":{"doi":"10.1111/eva.12239","url":"http://dx.doi.org/10.1111/eva.12239","publisher":"Wiley-Blackwell","authors":"Miller Mark P., Haig Susan M., Mullins Thomas D., Ruan Luzhang, Casler Bruce, Dondua Alexei, Gates H. River, Johnson J. Matthew, Kendall Steve, Tomkovich Pavel S., Tracy Diane, Valchuk Olga P., Lanctot Richard B.","journalName":"Evolutionary Applications","publicationDate":"1/28/2015"},"contributors":{"authors":[{"text":"Miller, Mark P. mpmiller@usgs.gov","contributorId":138965,"corporation":false,"usgs":true,"family":"Miller","given":"Mark P.","email":"mpmiller@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":539481,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haig, Susan M. 0000-0002-6616-7589 susan_haig@usgs.gov","orcid":"https://orcid.org/0000-0002-6616-7589","contributorId":719,"corporation":false,"usgs":true,"family":"Haig","given":"Susan","email":"susan_haig@usgs.gov","middleInitial":"M.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":539482,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mullins, Thomas D. 0000-0001-8948-9604 tom_mullins@usgs.gov","orcid":"https://orcid.org/0000-0001-8948-9604","contributorId":3615,"corporation":false,"usgs":true,"family":"Mullins","given":"Thomas","email":"tom_mullins@usgs.gov","middleInitial":"D.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":539483,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ruan, Luzhang","contributorId":138966,"corporation":false,"usgs":false,"family":"Ruan","given":"Luzhang","email":"","affiliations":[{"id":12597,"text":"School of Life Sciences and Food Engineering, Nanchang University, Nanchang, 330031, China","active":true,"usgs":false}],"preferred":false,"id":539484,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Casler, Bruce","contributorId":138967,"corporation":false,"usgs":false,"family":"Casler","given":"Bruce","email":"","affiliations":[{"id":12598,"text":"Izembek National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":539485,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dondua, Alexei","contributorId":138968,"corporation":false,"usgs":false,"family":"Dondua","given":"Alexei","email":"","affiliations":[{"id":12599,"text":"Gatchinskaya Str., 10-27, St. Petersburg, 197198 Russia","active":true,"usgs":false}],"preferred":false,"id":539486,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gates, H. 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Elevation data are essential to a broad range of applications important to New Hampshire, including flood mitigation, land development, agriculture, transportation planning and design, infrastructure asset inventory and management, and many others. For the State of New Hampshire, elevation data are critical for many business uses such as flood risk management, natural resources conservation, forest resources management, agriculture and precision farming, infrastructure and construction management, and geologic resource assessment and hazard mitigation. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.

\n

The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.

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Jr. carswell@usgs.gov","contributorId":1787,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":519924,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70147192,"text":"70147192 - 2015 - Mapping the distribution of malaria: current approaches and future directions","interactions":[],"lastModifiedDate":"2015-12-14T16:00:01","indexId":"70147192","displayToPublicDate":"2015-01-30T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Mapping the distribution of malaria: current approaches and future directions","docAbstract":"

Mapping the distribution of malaria has received substantial attention because the disease is a major source of illness and mortality in humans, especially in developing countries. It also has a defined temporal and spatial distribution. The distribution of malaria is most influenced by its mosquito vector, which is sensitive to extrinsic environmental factors such as rainfall and temperature. Temperature also affects the development rate of the malaria parasite in the mosquito. Here, we review the range of approaches used to model the distribution of malaria, from spatially explicit to implicit, mechanistic to correlative. Although current methods have significantly improved our understanding of the factors influencing malaria transmission, significant gaps remain, particularly in incorporating nonlinear responses to temperature and temperature variability. We highlight new methods to tackle these gaps and to integrate new data with models.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Analyzing and modeling spatial and temporal dynamics of infectious diseases","language":"English","publisher":"Wiley","doi":"10.1002/9781118630013.ch10","usgsCitation":"Johnson, L., Lafferty, K.D., McNally, A., Mordecai, E., Paaijmans, K.P., Pawar, S., and Ryan, S.J., 2015, Mapping the distribution of malaria: current approaches and future directions, chap. of Analyzing and modeling spatial and temporal dynamics of infectious diseases, p. 189-209, https://doi.org/10.1002/9781118630013.ch10.","productDescription":"21 p.","startPage":"189","endPage":"209","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054101","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":498956,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/9781118630013.ch10","text":"Publisher Index Page"},{"id":312272,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2015-01-30","publicationStatus":"PW","scienceBaseUri":"566ff653e4b09cfe53ca79ae","contributors":{"editors":[{"text":"Chen, Dongmei","contributorId":150562,"corporation":false,"usgs":false,"family":"Chen","given":"Dongmei","email":"","affiliations":[],"preferred":false,"id":582138,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Moulin, Bernard","contributorId":150563,"corporation":false,"usgs":false,"family":"Moulin","given":"Bernard","email":"","affiliations":[],"preferred":false,"id":582139,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Wu, Jianhong","contributorId":92413,"corporation":false,"usgs":false,"family":"Wu","given":"Jianhong","email":"","affiliations":[],"preferred":false,"id":582140,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Johnson, Leah R.","contributorId":83382,"corporation":false,"usgs":true,"family":"Johnson","given":"Leah R.","affiliations":[],"preferred":false,"id":545715,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":545714,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McNally, Amy","contributorId":53225,"corporation":false,"usgs":true,"family":"McNally","given":"Amy","affiliations":[],"preferred":false,"id":545716,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mordecai, Erin A.","contributorId":9113,"corporation":false,"usgs":true,"family":"Mordecai","given":"Erin A.","affiliations":[],"preferred":false,"id":545717,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Paaijmans, Krijn P.","contributorId":62459,"corporation":false,"usgs":true,"family":"Paaijmans","given":"Krijn","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":545718,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pawar, Samraat","contributorId":22622,"corporation":false,"usgs":true,"family":"Pawar","given":"Samraat","email":"","affiliations":[],"preferred":false,"id":545719,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ryan, Sadie J.","contributorId":102738,"corporation":false,"usgs":true,"family":"Ryan","given":"Sadie","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":545720,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70155959,"text":"70155959 - 2015 - Assessment of surface water chloride and conductivity trends in areas of unconventional oil and gas development — Why existing national data sets cannot tell us what we would like to know","interactions":[],"lastModifiedDate":"2022-11-15T17:04:15.648777","indexId":"70155959","displayToPublicDate":"2015-01-30T00:00:00","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":"Assessment of surface water chloride and conductivity trends in areas of unconventional oil and gas development — Why existing national data sets cannot tell us what we would like to know","docAbstract":"

Heightened concern regarding the potential effects of unconventional oil and gas development on regional water quality has emerged, but the few studies on this topic are limited in geographic scope. Here we evaluate the potential utility of national and publicly available water-quality data sets for addressing questions regarding unconventional oil and gas development. We used existing U.S. Geological Survey and U.S. Environmental Protection Agency data sets to increase understanding of the spatial distribution of unconventional oil and gas development in the U.S. and broadly assess surface water quality trends in these areas. Based on sample size limitations, we were able to estimate trends in specific conductance (SC) and chloride (Cl−) from 1970 to 2010 in 16% (n = 155) of the watersheds with unconventional oil and gas resources. We assessed these trends relative to spatiotemporal distributions of hydraulically fractured wells. Results from this limited analysis suggest no consistent and widespread trends in surface water quality for SC and Cl− in areas with increasing unconventional oil and gas development and highlight limitations of existing national databases for addressing questions regarding unconventional oil and gas development and water quality.

","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2014WR016382","usgsCitation":"Bowen, Z.H., Oelsner, G.P., Cade, B.S., Gallegos, T.J., Farag, A.M., Mott, D.N., Potter, C.J., Cinotto, P.J., Clark, M.L., Kappel, W.M., Kresse, T.M., Melcher, C.P., Paschke, S.S., Susong, D.D., and Varela, B., 2015, Assessment of surface water chloride and conductivity trends in areas of unconventional oil and gas development — Why existing national data sets cannot tell us what we would like to know: Water Resources Research, v. 51, no. 1, p. 704-715, https://doi.org/10.1002/2014WR016382.","productDescription":"12 p.","startPage":"704","endPage":"715","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051045","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science 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California","interactions":[],"lastModifiedDate":"2022-04-18T19:57:57.322391","indexId":"ofr20141260","displayToPublicDate":"2015-01-29T16:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1260","title":"California State Waters Map Series — Offshore of Pacifica, California","docAbstract":"

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within the 3-nautical-mile limit of California’s State Waters. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data, acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. 

\n

The Offshore of Pacifica map area is located in northern California, on the Pacific coast of the San Francisco Peninsula about 10 kilometers south of the Golden Gate. The map area extends from Daly City, through Pacifica, to the small coastal community of Montara. Much of the coastal zone is managed by either the State of California or local governments, including Thornton Beach State Park, Mussel Rock Park, Pacifica State Beach, Gray Whale Cove State Beach, and Montara State Beach.

\n

The major structure in the transform boundary between the Pacific and North American tectonic plates, the northwest-striking San Andreas Fault, cuts through the map area, crossing the shoreline near Mussel Rock before continuing offshore. The epicenter of the great 1906 California earthquake is located on the offshore part of the San Andreas Fault Zone a few kilometers north of the map area. 

\n

The map area is located at the northwest end of the Santa Cruz Mountains, much of which has been uplifted in the last 400,000 years. Southwest of the San Andreas Fault Zone, this uplift has resulted in a highly variable coastal morphology characterized by long, narrow beaches bounded by steep cliffs or marine terraces, small pocket beaches surrounded by rocky promontories, and steep, narrow coastal watersheds. Geologic units mapped along the coast include sedimentary, volcanic, and metamorphic rocks of the Franciscan Complex; Cretaceous granitic rocks; Tertiary sedimentary rocks; and Quaternary coastal marine terraces, deep-seated and shallow landslides, and beach and sand dune deposits, all of which contribute sediment to the coastal zone.

\n

In contrast to the more rural coastal zone to the south, the highly urbanized coastal zone north of Mussel Rock and the San Andreas Fault Zone is characterized by a narrow beach bounded by steep, 50- to 120-m-high cliffs made up of sand, silt, and clay of the Pliocene and Pleistocene Merced Formation, the source of numerous landslides. Two large landslides along “Northridge bluff” in 2003 and 2007 had estimated volumes of 305,800 to 382,300 m3 and 120,800 m3, respectively. Coastal landslides also are an issue to the south between Mussel Rock and Mori Point, even as bluffs diminish in height and pocket beaches transition to a more continuous strand bounded by Quaternary-age dunes and low-lying marine terraces. Mori Point, a coastal promontory in Pacifica underlain by rocks of the Franciscan Complex, rises abruptly to a height of 90 m from the shoreline. Pocket beaches characterize the shoreline from Mori Point south to Shelter Cove, the largest of which, Pacifica State Beach, is at the mouth of San Pedro Creek. 

\n

The coastal zone south of Pacifica, which stretches from Shelter Cove to Montara and includes Point San Pedro and Devils Slide, lies at the northwest end of San Pedro Mountain (underlain largely by early Tertiary sedimentary rocks) and Montara Mountain (underlain by Cretaceous granitic rocks). Elevations at Montara Mountain exceed 500 m just 4 km from the shoreline, and steep cliffs along the coast are as high as 275 m. This rugged terrain results in numerous rocky promontories, small pocket beaches, and large coastal landslides. Slope failures along Devils Slide are notorious for closing California Highway 1, creating such a large and persistent problem that the California Department of Transportation has bypassed this coastal section by tunneling through San Pedro Mountain; the tunnel was completed and the new section of highway opened in 2013. Coastal relief diminishes at Montara in the southernmost part of the map area, where the shoreline is bounded by 10- to 20-m-high marine terraces.

\n

Throughout the year, this part of the coast is exposed to the north Pacific swell, the southern swell, northwest wind waves, and local wind waves. The north Pacific swell dominates in winter months, having wave heights that range from 2 to 10 m at offshore buoys and wave periods that range from 10 to 25 s. During summer months, the largest waves come from the southern swell, generated by storms in the south Pacific and offshore of Central America. Characteristically, these swells have smaller wave heights (0.3–3 m) but similarly long wave periods (10–25 s). Local wind waves are most common from October to April, whereas northwest wind waves affect the coast throughout the year. These two wind-wave regimes typically have wave heights of 1 to 4 m and short wave periods (3–10 s). 

\n

Unlike many other parts of the California coast where sediment is supplied primarily from river and (or) stream runoff, sediment supply to the offshore along this part of northern California is a complex mixture of (1) sand transported from the coast north of the Golden Gate, (2) sediment transported to the coast through the San Francisco Bay via the Golden Gate and then dispersed over the adjacent ebb-tide delta, and (3) varying volumes of sediment eroded from adjacent steep coastal bluffs caused by wave-induced landslides and other erosional events. Additionally, since the 1980s, coastal erosion south of the Golden Gate has increased substantially between Ocean Beach (on the west coast of San Francisco, about 5 km north of the map area) and Point San Pedro. The combined sediment load is transported southward along the coast by the generally north-to-south alongshore current, which develops in response to the energetic winter-wave climate associated with the north Pacific swell. Overall, beaches in the map area have a long-term erosional trend, except near Mussel Rock where a long-term accretionary trend may reflect increased sediment supply from landslides. Beach-front riprap armoring and retaining walls are used locally to protect the shoreline from seasonal storm waves, most notably between Mussel Rock and Mori Point.

\n

The continental shelf in the map area is about 40 km wide, with water depths at the shelf break that range from about 80 to 120 m. Within California’s State Waters, the midshelf to inner shelf areas are characterized by a relatively flat, shallow (water depths of as much as 44 m) seafloor that dips gently (about 0.2° to 0.3°) westward. The seafloor is composed primarily of unconsolidated Holocene sediment (marine deposits), as well as some nearshore bedrock outcrops that consist primarily of rocks of the Tertiary Purisima Formation and also Cretaceous plutonic rocks (granite or granodiorite).

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E.","email":"ngolden@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":539536,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Watt, Janet Tilden 0000-0002-4759-3814 jwatt@usgs.gov","orcid":"https://orcid.org/0000-0002-4759-3814","contributorId":1754,"corporation":false,"usgs":true,"family":"Watt","given":"Janet","email":"jwatt@usgs.gov","middleInitial":"Tilden","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":539537,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Chinn, John L.","contributorId":97497,"corporation":false,"usgs":true,"family":"Chinn","given":"John","email":"","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":539538,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Erdey, Mercedes D. merdey@usgs.gov","contributorId":5411,"corporation":false,"usgs":true,"family":"Erdey","given":"Mercedes","email":"merdey@usgs.gov","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":539539,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Krigsman, Lisa M.","contributorId":43642,"corporation":false,"usgs":true,"family":"Krigsman","given":"Lisa M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":539540,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Manson, Michael W.","contributorId":48503,"corporation":false,"usgs":true,"family":"Manson","given":"Michael W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":539541,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Endris, Charles A.","contributorId":87824,"corporation":false,"usgs":true,"family":"Endris","given":"Charles","email":"","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":539542,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}} ,{"id":70139572,"text":"70139572 - 2015 - Direct and indirect effects of environmental variability on growth and survivorship of pre-reproductive Joshua trees, Yucca brevifolia Engelm (Agavaceae)","interactions":[],"lastModifiedDate":"2016-03-18T09:15:43","indexId":"70139572","displayToPublicDate":"2015-01-29T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":724,"text":"American Journal of Botany","active":true,"publicationSubtype":{"id":10}},"title":"Direct and indirect effects of environmental variability on growth and survivorship of pre-reproductive Joshua trees, Yucca brevifolia Engelm (Agavaceae)","docAbstract":"

• Premise of study: Accurate demographic information about long-lived plant species is important for understanding responses to large-scale disturbances, including climate change. It is challenging to obtain these data from desert perennial plants because seedling establishment is exceptionally rare, and estimates of survival are lacking for their vulnerable early stages. Desert wildfires, urbanization, and climate change influence the persistence of the long-lived Yucca brevifolia. Quantitative demographic attributes are crucial for understanding how populations will respond to disturbances and where populations will recede or advance under future climate scenarios.

\n

• Methods: We measured survival in a cohort of 53 pre-reproductive Y. brevifolia at Yucca Flat, Nevada, USA, for 22 yr and recorded their growth, nurse-plant relationships, and herbivory.

\n

• Key results: Herbivory by black-tailed jackrabbits (Lepus californicus) caused severe losses of plants during the first and second years (45% and 31%, respectively). Surviving plants experienced <2.5% annual mortality. Survival for the population was 19% over 22 yr. Plants <25 cm in height had lower life expectancy. Average growth rate (± SD) for plants that survived to the last census was 3.12 ± 1.96 cm yr−1, and growth rates were positively associated with precipitation. Thirty-year-old Y. brevifolia had not yet reproduced.

\n

• Conclusions: A rare establishment event for Y. brevifolia during 1983–1984, triggered by above-average summer rainfall, provided a unique opportunity to track early survival and growth. Infrequent but acute episodes of herbivory during drought influenced demography for decades. Variability in survival among young Y. brevifolia indicates that size-dependent demographic variables will improve forecasts for this long-lived desert species under predicted regional climate change.

","language":"English","publisher":"Botanical Society of America","doi":"10.3732/ajb.1400257","usgsCitation":"Esque, T., Medica, P.A., Shryock, D.F., Defalco, L., Webb, R., and Hunter, R., 2015, Direct and indirect effects of environmental variability on growth and survivorship of pre-reproductive Joshua trees, Yucca brevifolia Engelm (Agavaceae): American Journal of Botany, v. 102, no. 1, p. 85-91, https://doi.org/10.3732/ajb.1400257.","productDescription":"7 p.","startPage":"85","endPage":"91","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053990","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":488321,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3732/ajb.1400257","text":"Publisher Index Page"},{"id":297605,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Yucca Flat","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.41015624999999,\n 34.95799531086792\n ],\n [\n -120.41015624999999,\n 42.09822241118974\n ],\n [\n -114.08203125,\n 42.09822241118974\n ],\n [\n -114.08203125,\n 34.95799531086792\n ],\n [\n -120.41015624999999,\n 34.95799531086792\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"102","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a6ae4b08de9379b304a","contributors":{"authors":[{"text":"Esque, Todd C. tesque@usgs.gov","contributorId":127766,"corporation":false,"usgs":true,"family":"Esque","given":"Todd C.","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":539449,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Medica, Phil A. 0000-0002-5901-8841 pmedica@usgs.gov","orcid":"https://orcid.org/0000-0002-5901-8841","contributorId":3226,"corporation":false,"usgs":true,"family":"Medica","given":"Phil","email":"pmedica@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":539450,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shryock, Daniel F. dshryock@usgs.gov","contributorId":5139,"corporation":false,"usgs":true,"family":"Shryock","given":"Daniel","email":"dshryock@usgs.gov","middleInitial":"F.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":539451,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Defalco, Lesley A. ldefalco@usgs.gov","contributorId":2458,"corporation":false,"usgs":true,"family":"Defalco","given":"Lesley A.","email":"ldefalco@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":539452,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Webb, Robert H. rhwebb@usgs.gov","contributorId":1573,"corporation":false,"usgs":false,"family":"Webb","given":"Robert H.","email":"rhwebb@usgs.gov","affiliations":[{"id":12625,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, 85721, USA","active":true,"usgs":false}],"preferred":false,"id":539453,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hunter, Richard B.","contributorId":138962,"corporation":false,"usgs":false,"family":"Hunter","given":"Richard B.","affiliations":[{"id":12595,"text":"Salisbury University, Department of Biological Sciences, Salisbury, MD","active":true,"usgs":false}],"preferred":false,"id":539454,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70133413,"text":"fs20143115 - 2015 - The 3D Elevation Program: summary for Utah","interactions":[],"lastModifiedDate":"2016-08-17T15:07:01","indexId":"fs20143115","displayToPublicDate":"2015-01-27T12:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3115","title":"The 3D Elevation Program: summary for Utah","docAbstract":"

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Utah, elevation data are critical for infrastructure and construction management, natural resources conservation, geologic resource assessment and hazard mitigation, flood risk management, agriculture and precision farming, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.

\n

The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.

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Jr. carswell@usgs.gov","contributorId":1787,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":525126,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70138827,"text":"sir20145226 - 2015 - Hydrologic record extension of water-level data in the Everglades Depth Estimation Network (EDEN), 1991-99","interactions":[],"lastModifiedDate":"2017-01-18T13:16:53","indexId":"sir20145226","displayToPublicDate":"2015-01-27T09:15:00","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":"2014-5226","title":"Hydrologic record extension of water-level data in the Everglades Depth Estimation Network (EDEN), 1991-99","docAbstract":"

The real-time Everglades Depth Estimation Network (EDEN) has been established to support a variety of scientific and water management purposes. The expansiveness of the Everglades, limited number of gaging stations, and extreme sensitivity of the ecosystem to small changes in water depth have created a need for accurate water-level and water-depth maps. The EDEN water-surface elevation model uses data from approximately 240 gages in the Everglades to create daily continuous interpolations of the water-surface elevation and water depth for the freshwater portion of the Everglades from 2000 to the present (2014). These maps provide hydrologic data previously unavailable for assessing biological and ecological studies.

\n

Ecologists working in the Everglades expressed a need to the EDEN project team for daily EDEN water-level surfaces from 1990 to 1999. The additional 10 years of surfaces will provide ecologists and resource managers with two decades (1991–2011) of surfaces to analyze hydrologic dynamics. Before 2000, many of the EDEN gages used to generate water surfaces were not in operation. These datasets were extended to provide estimations of hydrologic time-series histories. The general approach to the record extension (hindcasts) was to (1) create a database of available data from 1990 to the present; (2) use dynamic cluster analysis to group stations with similar hydrologic behaviors for subareas of the Everglades with a large number of stations; (3) use results from the cluster analysis to select candidate explanatory variables; (4) develop linear regression or artificial neural network models to extend water-level records; and (5) evaluate record extensions by using model performance statistics and comparison of water-surface maps for similar hydrologic conditions for the hindcasted period (1991–99) and measured period (2000–11).

\n

To hindcast and fill data records, 214 empirical models were developed—189 are linear regression models and 25 are artificial neural network models. The coefficient of determination (R2) for 163 of the models is greater than 0.80 and the median percent model error (root mean square error divided by the range of the measured data) is 5 percent. To evaluate the performance of the hindcast models as a group, contour maps of modeled water-level surfaces at 2-centimeter (cm) intervals were generated using the hindcasted data. The 2-cm contour maps were examined for selected days to verify that water surfaces from the EDEN model are consistent with the input data. The biweekly 2-cm contour maps did show a higher number of issues during days in 1990 as compared to days after 1990. May 1990 had the lowest water levels in the Everglades of the 21-year dataset used for the hindcasting study. To hindcast these record low conditions in 1990, many of the hindcast models would require large extrapolations beyond the range of the predictive quality of the models. For these reasons, it was decided to limit the hindcasted data to the period January 1, 1991, to December 31, 1999. Overall, the hindcasted and gap-filled data are assumed to provide reasonable estimates of station-specific water-level data for an extended historical period to inform research and natural resource management in the Everglades.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145226","usgsCitation":"Conrads, P., Petkewich, M.D., O’Reilly, A.M., and Telis, P.A., 2015, Hydrologic record extension of water-level data in the Everglades Depth Estimation Network (EDEN), 1991-99: U.S. Geological Survey Scientific Investigations Report 2014-5226, Report: vi, 27 p.; 2 Tables; 2 Appendixes, https://doi.org/10.3133/sir20145226.","productDescription":"Report: vi, 27 p.; 2 Tables; 2 Appendixes","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"1991-01-01","temporalEnd":"1999-12-31","ipdsId":"IP-059254","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":297562,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145226.jpg"},{"id":297559,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5226/"},{"id":297560,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5226/pdf/sir2014-5226.pdf","size":"2.93 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":297561,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5226/downloads/sir2014-5226.xlsx","text":"Table 1 and 3, Appendixes 1-2","size":"149 kB","linkFileType":{"id":3,"text":"xlsx"}}],"projection":"Universal Transverse Mercator projection","country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.93328857421875,\n 25.063209244186485\n ],\n [\n -81.93328857421875,\n 26.649913524725044\n ],\n [\n -79.98596191406249,\n 26.649913524725044\n ],\n [\n -79.98596191406249,\n 25.063209244186485\n ],\n [\n -81.93328857421875,\n 25.063209244186485\n ]\n ]\n ]\n }\n }\n ]\n}","publicComments":"Prepared as part of the U.S. Geological Survey Greater Everglades Priority Ecosystem Science","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a87e4b08de9379b30d1","contributors":{"authors":[{"text":"Conrads, Paul 0000-0003-0408-4208 pconrads@usgs.gov","orcid":"https://orcid.org/0000-0003-0408-4208","contributorId":764,"corporation":false,"usgs":true,"family":"Conrads","given":"Paul","email":"pconrads@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":539310,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Petkewich, Matthew D. 0000-0002-5749-6356 mdpetkew@usgs.gov","orcid":"https://orcid.org/0000-0002-5749-6356","contributorId":982,"corporation":false,"usgs":true,"family":"Petkewich","given":"Matthew","email":"mdpetkew@usgs.gov","middleInitial":"D.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539311,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Reilly, Andrew M. 0000-0003-3220-1248 aoreilly@usgs.gov","orcid":"https://orcid.org/0000-0003-3220-1248","contributorId":2184,"corporation":false,"usgs":true,"family":"O’Reilly","given":"Andrew","email":"aoreilly@usgs.gov","middleInitial":"M.","affiliations":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"preferred":true,"id":539312,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Telis, Pamela A. patelis@usgs.gov","contributorId":1461,"corporation":false,"usgs":true,"family":"Telis","given":"Pamela","email":"patelis@usgs.gov","middleInitial":"A.","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"preferred":false,"id":539313,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70138808,"text":"ds914 - 2015 - Bathymetry of the Wilderness breach at Fire Island, New York, June 2013","interactions":[],"lastModifiedDate":"2016-02-08T12:36:53","indexId":"ds914","displayToPublicDate":"2015-01-26T16:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"914","title":"Bathymetry of the Wilderness breach at Fire Island, New York, June 2013","docAbstract":"

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center in St. Petersburg, Florida, collaborated with the U.S. Army Corps of Engineers Field Research Facility in Duck, North Carolina, to collect shallow water bathymetric data of the Wilderness breach on Fire Island, New York, in June 2013. The breach formed in October 2012 during Hurricane Sandy, and the USGS is involved in a post-Sandy effort to map, monitor, and model the morphologic evolution of the breach as part of Hurricane Sandy Supplemental Project GS2-2B: Linking Coastal Vulnerability and Process, Fire Island. This publication includes a bathymetric dataset of the breach and the adjacent nearshore on the ocean side of the island. The objective of the data collection and analysis is to map the bathymetry of the primary breach channel, ebb shoal, and nearshore bar system.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds914","usgsCitation":"Brownell, A.T., Hapke, C.J., Spore, N., and McNinch, J., 2015, Bathymetry of the Wilderness breach at Fire Island, New York, June 2013: U.S. Geological Survey Data Series 914, HTML Document, https://doi.org/10.3133/ds914.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059527","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":297555,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds914.jpg"},{"id":297554,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0914/ds914_abstract.html","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"Report"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.3502197265625,\n 40.588928169693745\n ],\n [\n -73.3502197265625,\n 40.81796653313175\n ],\n [\n -72.66357421875,\n 40.81796653313175\n ],\n [\n -72.66357421875,\n 40.588928169693745\n ],\n [\n -73.3502197265625,\n 40.588928169693745\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a58e4b08de9379b2ffa","contributors":{"authors":[{"text":"Brownell, Andrew T. abrownell@usgs.gov","contributorId":5801,"corporation":false,"usgs":true,"family":"Brownell","given":"Andrew","email":"abrownell@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":538902,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hapke, Cheryl J. 0000-0002-2753-4075 chapke@usgs.gov","orcid":"https://orcid.org/0000-0002-2753-4075","contributorId":2981,"corporation":false,"usgs":true,"family":"Hapke","given":"Cheryl","email":"chapke@usgs.gov","middleInitial":"J.","affiliations":[{"id":6676,"text":"USGS (retired)","active":true,"usgs":false}],"preferred":true,"id":538904,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spore, Nicholas J.","contributorId":138833,"corporation":false,"usgs":false,"family":"Spore","given":"Nicholas J.","affiliations":[{"id":12537,"text":"USACE","active":true,"usgs":false}],"preferred":false,"id":538903,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McNinch, Jesse E.","contributorId":93804,"corporation":false,"usgs":true,"family":"McNinch","given":"Jesse E.","affiliations":[],"preferred":false,"id":538905,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70134733,"text":"sir20145202 - 2015 - Flood-inundation maps for Indian Creek and Tomahawk Creek, Johnson County, Kansas, 2014","interactions":[],"lastModifiedDate":"2016-06-14T11:12:39","indexId":"sir20145202","displayToPublicDate":"2015-01-26T16:00:00","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":"2014-5202","title":"Flood-inundation maps for Indian Creek and Tomahawk Creek, Johnson County, Kansas, 2014","docAbstract":"

Digital flood-inundation maps for a 6.4-mile upper reach of Indian Creek from College Boulevard to the confluence with Tomahawk Creek, a 3.9-mile reach of Tomahawk Creek from 127th Street to the confluence with Indian Creek, and a 1.9-mile lower reach of Indian Creek from the confluence with Tomahawk Creek to just beyond the Kansas/Missouri border at State Line Road in Johnson County, Kansas, were created by the U.S. Geological Survey in cooperation with the city of Overland Park, Kansas. The flood-inundation maps, which can be accessed through the U.S. Geological Survey Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the U.S. Geological Survey streamgages on Indian Creek at Overland Park, Kansas; Indian Creek at State Line Road, Leawood, Kansas; and Tomahawk Creek near Overland Park, Kansas. Near real time stages at these streamgages may be obtained on the Web from the U.S. Geological Survey National Water Information System at http://waterdata.usgs.gov/nwis or the National Weather Service Advanced Hydrologic Prediction Service at http://water.weather.gov/ahps/, which also forecasts flood hydrographs at these sites.

Flood profiles were computed for the stream reaches by means of a one-dimensional step-backwater model. The model was calibrated for each reach by using the most current stage-discharge relations at the streamgages. The hydraulic models were then used to determine 15 water-surface profiles for Indian Creek at Overland Park, Kansas; 17 water-surface profiles for Indian Creek at State Line Road, Leawood, Kansas; and 14 water-surface profiles for Tomahawk Creek near Overland Park, Kansas, for flood stages at 1-foot intervals referenced to the streamgage datum and ranging from bankfull to the next interval above the 0.2-percent annual exceedance probability flood level (500-year recurrence interval). The simulated water-surface profiles were then combined in a geographic information system with a digital elevation model derived from light detection and ranging data (having a 0.429-foot vertical and 0.228-foot horizontal accuracy) to delineate the area flooded at each water level.

The availability of these maps, along with Web information regarding current stage from the U.S. Geological Survey streamgages and forecasted high-flow stages from the National Weather Service, will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations, road closures, and postflood recovery efforts.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145202","collaboration":"Prepared in cooperation with the City of Overland Park, Kansas","usgsCitation":"Peters, A.J., and Studley, S.E., 2014, Flood-inundation maps for Indian Creek and Tomahawk Creek, Johnson County, Kansas, 2014 (ver. 1.1, January 2016): U.S. Geological Survey Scientific Investigations Report 2014–5202, 11 p., https://dx.doi.org/10.3133/sir20145202.","productDescription":"vi, 11 p.","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-056342","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":323570,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5202/downloads/","text":"Downloads Directory","linkHelpText":"Contains: geospatial database. Refer to the Metadata file for more information."},{"id":323571,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2014/5202/downloads/metadata.docx"},{"id":297546,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2014/5202/pdf/coverthb.jpg"},{"id":297545,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5202/pdf/sir20145202.pdf","text":"Report","size":"10.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297536,"rank":3,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5202/"},{"id":314701,"rank":6,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2014/5202/versionhist.txt","size":"1 kb","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2014-5202 version history"}],"country":"United States","state":"Kansas","county":"Johnson County","otherGeospatial":"Indian Creek, Tomahawk Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -102.1728515625,\n 40.01078714046552\n ],\n [\n -94.833984375,\n 39.9434364619742\n ],\n [\n -94.833984375,\n 37.020098201368114\n ],\n [\n -102.0849609375,\n 37.020098201368114\n ],\n [\n -102.1728515625,\n 40.01078714046552\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally posted January 26, 2015; Version 1.1: January 25, 2016","contact":"

Director, USGS Kansas Water Science Center
4821 Quail Crest Place
Lawrence, KS 66049

\n

http://ks.water.usgs.gov

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2016-01-25","noUsgsAuthors":false,"publicationDate":"2016-01-25","publicationStatus":"PW","scienceBaseUri":"54dd2a78e4b08de9379b3089","contributors":{"authors":[{"text":"Peters, Arin J. ajpeters@usgs.gov","contributorId":5862,"corporation":false,"usgs":true,"family":"Peters","given":"Arin","email":"ajpeters@usgs.gov","middleInitial":"J.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":539268,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Studley, Seth E. sstudley@usgs.gov","contributorId":5916,"corporation":false,"usgs":true,"family":"Studley","given":"Seth","email":"sstudley@usgs.gov","middleInitial":"E.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":539267,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70123438,"text":"70123438 - 2015 - Landscape-level terrestrial methane flux observed from a very tall tower","interactions":[],"lastModifiedDate":"2015-01-28T08:44:48","indexId":"70123438","displayToPublicDate":"2015-01-26T15:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":681,"text":"Agricultural and Forest Meteorology","active":true,"publicationSubtype":{"id":10}},"title":"Landscape-level terrestrial methane flux observed from a very tall tower","docAbstract":"

Simulating the magnitude and variability of terrestrial methane sources and sinks poses a challenge to ecosystem models because the biophysical and biogeochemical processes that lead to methane emissions from terrestrial and freshwater ecosystems are, by their nature, episodic and spatially disjunct. As a consequence, model predictions of regional methane emissions based on field campaigns from short eddy covariance towers or static chambers have large uncertainties, because measurements focused on a particular known source of methane emission will be biased compared to regional estimates with regards to magnitude, spatial scale, or frequency of these emissions. Given the relatively large importance of predicting future terrestrial methane fluxes for constraining future atmospheric methane growth rates, a clear need exists to reduce spatiotemporal uncertainties. In 2010, an Ameriflux tower (US-PFa) near Park Falls, WI, USA, was instrumented with closed-path methane flux measurements at 122 m above ground in a mixed wetland–upland landscape representative of the Great Lakes region. Two years of flux observations revealed an average annual methane (CH4) efflux of 785 ± 75 mg C\"singleCH4 m−2 yr−1, compared to a mean CO2 sink of −80 g C\"singleCO2 m−2 yr−1, a ratio of 1% in magnitude on a mole basis. Interannual variability in methane flux was 30% of the mean flux and driven by suppression of methane emissions during dry conditions in late summer 2012. Though relatively small, the magnitude of the methane source from the very tall tower measurements was mostly within the range previously measured using static chambers at nearby wetlands, but larger than a simple scaling of those fluxes to the tower footprint. Seasonal patterns in methane fluxes were similar to those simulated in the Dynamic Land Ecosystem Model (DLEM), but magnitude depends on model parameterization and input data, especially regarding wetland extent. The model was unable to simulate short-term (sub-weekly) variability. Temperature was found to be a stronger driver of regional CH4flux than moisture availability or net ecosystem production at the daily to monthly scale. Taken together, these results emphasize the multi-timescale dependence of drivers of regional methane flux and the importance of long, continuous time series for their characterization.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.agrformet.2014.10.017","usgsCitation":"Desai, A.R., Xu, K., Tian, H., Weishampel, P., Thom, J., Baumann, D.D., Andrews, A.E., Cook, B.D., King, J.Y., and Kolka, R., 2015, Landscape-level terrestrial methane flux observed from a very tall tower: Agricultural and Forest Meteorology, v. 201, p. 61-75, https://doi.org/10.1016/j.agrformet.2014.10.017.","productDescription":"15 p.","startPage":"61","endPage":"75","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057381","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":297533,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","city":"Park Falls","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.5048828125,\n 46.800059446787316\n ],\n [\n -87.4951171875,\n 46.6795944656402\n ],\n [\n -87.451171875,\n 42.42345651793833\n ],\n [\n -92.6806640625,\n 42.779275360241904\n ],\n [\n -92.5048828125,\n 46.800059446787316\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"201","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a8ee4b08de9379b30f2","contributors":{"authors":[{"text":"Desai, Ankur R. 0000-0002-5226-6041","orcid":"https://orcid.org/0000-0002-5226-6041","contributorId":20622,"corporation":false,"usgs":false,"family":"Desai","given":"Ankur","email":"","middleInitial":"R.","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":519367,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Xu, Ke","contributorId":115559,"corporation":false,"usgs":false,"family":"Xu","given":"Ke","email":"","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":519368,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tian, Hanqin","contributorId":117981,"corporation":false,"usgs":true,"family":"Tian","given":"Hanqin","email":"","affiliations":[],"preferred":false,"id":519372,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weishampel, Peter","contributorId":116746,"corporation":false,"usgs":true,"family":"Weishampel","given":"Peter","email":"","affiliations":[],"preferred":false,"id":519370,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thom, Jonthan","contributorId":118322,"corporation":false,"usgs":true,"family":"Thom","given":"Jonthan","email":"","affiliations":[],"preferred":false,"id":519373,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baumann, Daniel D. dbaumann@usgs.gov","contributorId":5950,"corporation":false,"usgs":true,"family":"Baumann","given":"Daniel","email":"dbaumann@usgs.gov","middleInitial":"D.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":519366,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Andrews, Arlyn E.","contributorId":117698,"corporation":false,"usgs":false,"family":"Andrews","given":"Arlyn","email":"","middleInitial":"E.","affiliations":[{"id":12448,"text":"U.S. National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":519371,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cook, Bruce D.","contributorId":118323,"corporation":false,"usgs":false,"family":"Cook","given":"Bruce","email":"","middleInitial":"D.","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":519374,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"King, Jennifer Y.","contributorId":120697,"corporation":false,"usgs":false,"family":"King","given":"Jennifer","email":"","middleInitial":"Y.","affiliations":[{"id":6710,"text":"University of California, Santa Barbara, CA","active":true,"usgs":false}],"preferred":false,"id":519375,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kolka, Randall","contributorId":115924,"corporation":false,"usgs":false,"family":"Kolka","given":"Randall","affiliations":[],"preferred":false,"id":519369,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70134271,"text":"ds902 - 2015 - Digital geospatial presentation of geoelectrical and geotechnical data for the lower American River and flood plain, east Sacramento, California","interactions":[],"lastModifiedDate":"2019-11-07T12:36:20","indexId":"ds902","displayToPublicDate":"2015-01-26T15:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"902","title":"Digital geospatial presentation of geoelectrical and geotechnical data for the lower American River and flood plain, east Sacramento, California","docAbstract":"

To characterize the extent and thickness of lithologic units that may have differing scour potential, the U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, has performed several geoelectrical surveys of the lower American River channel and flood plain between Cal Expo and the Rio Americano High School in east Sacramento, California. Additional geotechnical data have been collected by the U.S. Army Corps of Engineers and its contractors. Data resulting from these surveys have been compiled into similar database formats and converted to uniform geospatial datums and projections. These data have been visualized in a digital three-dimensional framework project that can be viewed using freely available software. These data facilitate a comprehensive analysis of the resistivity structure underlying the lower American River corridor and assist in levee system management.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds902","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Sacramento District","usgsCitation":"Ball, L.B., Burton, B., Powers, M.H., and Asch, T.H., 2015, Digital geospatial presentation of geoelectrical and geotechnical data for the lower American River and flood plain, east Sacramento, California: U.S. Geological Survey Data Series 902, Report: iv, 12 p.; 3D Framework; Source Data, https://doi.org/10.3133/ds902.","productDescription":"Report: iv, 12 p.; 3D Framework; Source Data","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-046347","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":297540,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0902/downloads/SOURCE_DATA.zip","text":"Source Data","description":"Source Data"},{"id":297538,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0902/pdf/ds902.pdf","text":"Report","size":"1.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297539,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/0902/downloads/3DFRAMEWORK.zip","text":"3D Framework","description":"3D Framework"},{"id":297532,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0902/"},{"id":297541,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds902.jpg"}],"country":"United States","state":"California","city":"Sacramento","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.42656326293945,\n 38.55783104069692\n ],\n [\n -121.34519577026367,\n 38.55783104069692\n ],\n [\n -121.34519577026367,\n 38.5896378526013\n ],\n [\n -121.42656326293945,\n 38.5896378526013\n ],\n [\n -121.42656326293945,\n 38.55783104069692\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a6ae4b08de9379b3048","contributors":{"authors":[{"text":"Ball, Lyndsay B. 0000-0002-6356-4693 lbball@usgs.gov","orcid":"https://orcid.org/0000-0002-6356-4693","contributorId":1138,"corporation":false,"usgs":true,"family":"Ball","given":"Lyndsay","email":"lbball@usgs.gov","middleInitial":"B.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":539257,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burton, Bethany L. 0000-0001-5011-7862 blburton@usgs.gov","orcid":"https://orcid.org/0000-0001-5011-7862","contributorId":1341,"corporation":false,"usgs":true,"family":"Burton","given":"Bethany L.","email":"blburton@usgs.gov","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":539256,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Powers, Michael H. 0000-0002-4480-7856 mhpowers@usgs.gov","orcid":"https://orcid.org/0000-0002-4480-7856","contributorId":851,"corporation":false,"usgs":true,"family":"Powers","given":"Michael","email":"mhpowers@usgs.gov","middleInitial":"H.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":539258,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Asch, Theodore H.","contributorId":127592,"corporation":false,"usgs":false,"family":"Asch","given":"Theodore","email":"","middleInitial":"H.","affiliations":[{"id":6766,"text":"former USGS NOROCK Step-Student","active":true,"usgs":false}],"preferred":false,"id":539259,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70139241,"text":"ofr20141219 - 2015 - USGS compilation of geographic information system (GIS) data representing coal mines and coal-bearing areas in China","interactions":[],"lastModifiedDate":"2015-01-26T15:00:21","indexId":"ofr20141219","displayToPublicDate":"2015-01-26T14:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1219","title":"USGS compilation of geographic information system (GIS) data representing coal mines and coal-bearing areas in China","docAbstract":"

Geographic information system (GIS) information may facilitate energy studies, which in turn provide input for energy policy decisions. The U.S. Geological Survey (USGS) has compiled geographic information system (GIS) data representing the known coal mine locations and coal-mining areas of China as of 2001. These data are now available for download, and may be used in a GIS for a variety of energy resource and environmental studies of China. Province-scale maps were also created to display the point locations of coal mines and the coal-mining areas. In addition, coal-field outlines from a previously published map by Dai and others (2012) were also digitized and are available for download as a separate GIS data file, and shown in a nation-scale map of China. Chemical data for 332 coal samples from a previous USGS study of China and Taiwan (Tewalt and others, 2010) are included in a downloadable GIS point shapefile, and shown on a nation-scale map of China. A brief report summarizes the methodology used for creation of the shapefiles and the chemical analyses run on the samples.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141219","usgsCitation":"Trippi, M.H., Belkin, H.E., Dai, S., Tewalt, S.J., and Chou, C., 2015, USGS compilation of geographic information system (GIS) data representing coal mines and coal-bearing areas in China: U.S. Geological Survey Open-File Report 2014-1219, Report: iv, 135 p.; Downloads Directory, https://doi.org/10.3133/ofr20141219.","productDescription":"Report: iv, 135 p.; Downloads Directory","numberOfPages":"140","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-051519","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":297544,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141219.jpg"},{"id":297542,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1219/pdf/of2014-1219.pdf","text":"Report","size":"17.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297543,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1219/downloads","text":"Downloads Directory","description":"Downloads Directory"},{"id":297535,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1219/"}],"country":"China","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 73.47656249999999,\n 17.895114303749143\n ],\n [\n 73.47656249999999,\n 53.592504809039376\n ],\n [\n 135.17578125,\n 53.592504809039376\n ],\n [\n 135.17578125,\n 17.895114303749143\n ],\n [\n 73.47656249999999,\n 17.895114303749143\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2ac6e4b08de9379b31f8","contributors":{"compilers":[{"text":"Trippi, Michael H. 0000-0002-1398-3427 mtrippi@usgs.gov","orcid":"https://orcid.org/0000-0002-1398-3427","contributorId":941,"corporation":false,"usgs":true,"family":"Trippi","given":"Michael","email":"mtrippi@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":539271,"contributorType":{"id":3,"text":"Compilers"},"rank":1},{"text":"Belkin, Harvey E. 0000-0001-7879-6529 hbelkin@usgs.gov","orcid":"https://orcid.org/0000-0001-7879-6529","contributorId":581,"corporation":false,"usgs":true,"family":"Belkin","given":"Harvey","email":"hbelkin@usgs.gov","middleInitial":"E.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":539272,"contributorType":{"id":3,"text":"Compilers"},"rank":2},{"text":"Dai, Shifeng","contributorId":138922,"corporation":false,"usgs":false,"family":"Dai","given":"Shifeng","email":"","affiliations":[{"id":12582,"text":"State Key Laboratory of Coal Resources and Safe Mining, University of Mining and Technology, Beijing, People’s Republic of China","active":true,"usgs":false}],"preferred":false,"id":539273,"contributorType":{"id":3,"text":"Compilers"},"rank":3},{"text":"Tewalt, Susan J. stewalt@usgs.gov","contributorId":138923,"corporation":false,"usgs":false,"family":"Tewalt","given":"Susan","email":"stewalt@usgs.gov","middleInitial":"J.","affiliations":[{"id":12545,"text":"USGS retired","active":true,"usgs":false}],"preferred":false,"id":539274,"contributorType":{"id":3,"text":"Compilers"},"rank":4},{"text":"Chou, Chiu-Jung","contributorId":138924,"corporation":false,"usgs":false,"family":"Chou","given":"Chiu-Jung","email":"","affiliations":[{"id":7053,"text":"Volunteer, USGS, WFRC, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":539275,"contributorType":{"id":3,"text":"Compilers"},"rank":5}],"authors":[{"text":"Trippi, Michael H. 0000-0002-1398-3427 mtrippi@usgs.gov","orcid":"https://orcid.org/0000-0002-1398-3427","contributorId":941,"corporation":false,"usgs":true,"family":"Trippi","given":"Michael","email":"mtrippi@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":539262,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belkin, Harvey E. 0000-0001-7879-6529 hbelkin@usgs.gov","orcid":"https://orcid.org/0000-0001-7879-6529","contributorId":581,"corporation":false,"usgs":true,"family":"Belkin","given":"Harvey","email":"hbelkin@usgs.gov","middleInitial":"E.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":539263,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dai, Shifeng","contributorId":138922,"corporation":false,"usgs":false,"family":"Dai","given":"Shifeng","email":"","affiliations":[{"id":12582,"text":"State Key Laboratory of Coal Resources and Safe Mining, University of Mining and Technology, Beijing, People’s Republic of China","active":true,"usgs":false}],"preferred":false,"id":539264,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tewalt, Susan J. stewalt@usgs.gov","contributorId":138923,"corporation":false,"usgs":false,"family":"Tewalt","given":"Susan","email":"stewalt@usgs.gov","middleInitial":"J.","affiliations":[{"id":12545,"text":"USGS retired","active":true,"usgs":false}],"preferred":false,"id":539265,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chou, Chiu-Jung","contributorId":138924,"corporation":false,"usgs":false,"family":"Chou","given":"Chiu-Jung","email":"","affiliations":[{"id":7053,"text":"Volunteer, USGS, WFRC, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":539266,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70137299,"text":"ofr20151001 - 2015 - Future wave and wind projections for United States and United-States-affiliated Pacific Islands","interactions":[],"lastModifiedDate":"2019-12-27T10:41:57","indexId":"ofr20151001","displayToPublicDate":"2015-01-26T12:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1001","title":"Future wave and wind projections for United States and United-States-affiliated Pacific Islands","docAbstract":"

Changes in future wave climates in the tropical Pacific Ocean from global climate change are not well understood. Spatially and temporally varying waves dominate coastal morphology and ecosystem structure of the islands throughout the tropical Pacific. Waves also impact coastal infrastructure, natural and cultural resources, and coastal-related economic activities of the islands. Wave heights, periods, and directions were forecast through the year 2100 using wind parameter outputs from four atmosphere-ocean global climate models from the Coupled Model Inter-Comparison Project, Phase 5, for Representative Concentration Pathways (RCP) scenarios 4.5 and 8.5 that correspond to moderately mitigated and unmitigated greenhouse gas emissions, respectively. Wind fields from the global climate models were used to drive a global WAVEWATCH-III wave model and generate hourly time-series of bulk wave parameters for 25 islands in the mid to western tropical Pacific for the years 1976–2005 (historical), 2026–2045 (mid-century projection), and 2085–2100 (end-of-century projection). Although the results show some spatial heterogeneity, overall the December-February extreme significant wave heights, defined as the mean of the top 5 percent of significant wave height time-series data modeled within a specific period, increase from present to mid-century and then decrease toward the end of the century; June-August extreme wave heights increase throughout the century within the Central region of the study area; and September-November wave heights decrease strongly throughout the 21st century, displaying the largest and most widespread decreases of any season. Peak wave periods increase east of the International Date Line during the December-February and June-August seasons under RCP4.5. Under the RCP8.5 scenario, wave periods decrease west of the International Date Line during December-February but increase in the eastern half of the study area. Otherwise, wave periods decrease throughout the study area during other seasons. Extreme wave directions in equatorial Micronesia during June-August undergo an approximate 30° clockwise rotation from primarily west to northwest. September-November RCP4.5 extreme mean wave directions rotate counterclockwise by approximately 30 to 45° in equatorial Micronesia; September-November RCP8.5 extreme mean wave directions within equatorial Micronesia rotate clockwise by approximately 20 to 30°. Extreme wind speeds decreased within both scenarios, with the largest decreases occurring in the September-November season. Extreme wind directions under RCP4.5 rotated clockwise by more than 60° in equatorial Micronesia during the September-November season and by approximately 30° during June-August. RCP8.5 extreme wind directions rotated counterclockwise during September-November within the same region by 30 to 50° and clockwise by 30 to 40° at one island. The spatial patterns and trends are similar between the two different greenhouse gas emission scenarios, with the magnitude and extent of the trends generally greater for the higher (RCP8.5) scenario.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151001","usgsCitation":"Storlazzi, C., Shope, J.B., Erikson, L., Hegermiller, C.A., and Barnard, P.L., 2015, Future wave and wind projections for United States and United-States-affiliated Pacific Islands: U.S. Geological Survey Open-File Report 2015-1001, xxvii, 426 p., https://doi.org/10.3133/ofr20151001.","productDescription":"xxvii, 426 p.","numberOfPages":"455","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059375","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":297525,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151001.gif"},{"id":297524,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1001/downloads/ofr2015-1001_report.pdf","text":"Report","size":"32.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","otherGeospatial":"Micronesia, Pacific Ocean","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a7ae4b08de9379b3095","contributors":{"authors":[{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":2333,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt D.","email":"cstorlazzi@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":539241,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shope, James B.","contributorId":135949,"corporation":false,"usgs":false,"family":"Shope","given":"James","email":"","middleInitial":"B.","affiliations":[{"id":10653,"text":"University of California at Santa Cruz, Earth and Planetary Science Department","active":true,"usgs":false}],"preferred":false,"id":539242,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":3170,"corporation":false,"usgs":true,"family":"Erikson","given":"Li H.","email":"lerikson@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":539243,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hegermiller, Christine A.","contributorId":135950,"corporation":false,"usgs":false,"family":"Hegermiller","given":"Christine","email":"","middleInitial":"A.","affiliations":[{"id":10653,"text":"University of California at Santa Cruz, Earth and Planetary Science Department","active":true,"usgs":false}],"preferred":false,"id":539244,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":2880,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick","email":"pbarnard@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":539245,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70135976,"text":"ofr20141255 - 2015 - Depth-dependent groundwater quality sampling at City of Tallahassee test well 32, Leon County, Florida, 2013","interactions":[],"lastModifiedDate":"2015-01-26T10:10:09","indexId":"ofr20141255","displayToPublicDate":"2015-01-26T11:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1255","title":"Depth-dependent groundwater quality sampling at City of Tallahassee test well 32, Leon County, Florida, 2013","docAbstract":"

Public-supply wells sometimes produce water of less than desirable quality because contaminants can migrate to the open interval of wells through preferential pathways. If these pathways can be identified, zones that produce poor quality water can be excluded during the well-construction process. The U.S. Geological Survey has developed geophysical testing methods that can be used to delineate zones of high permeability in test wells. Once the highly permeable zones are identified, water-quality data can be collected from each zone to identify whether any of the zones produce water of poor quality. The zones producing poor quality water can then be cased off in the final well design so that they do not contribute flow to the production well, reducing subsequent water-treatment costs.

\n

A test well was drilled by the City of Tallahassee to assess the suitability of the site for the installation of a new well for public water supply. The test well is in Leon County in north-central Florida. The U.S. Geological Survey delineated high-permeability zones in the Upper Floridan aquifer, using borehole-geophysical data collected from the open interval of the test well. A composite water sample was collected from the open interval during high-flow conditions, and three discrete water samples were collected from specified depth intervals within the test well during low-flow conditions. Water-quality, source tracer, and age-dating results indicate that the open interval of the test well produces water of consistently high quality throughout its length. The cavernous nature of the open interval makes it likely that the highly permeable zones are interconnected in the aquifer by secondary porosity features.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141255","collaboration":"City of Tallahassee","usgsCitation":"McBride, W.S., and Wacker, M.A., 2015, Depth-dependent groundwater quality sampling at City of Tallahassee test well 32, Leon County, Florida, 2013: U.S. Geological Survey Open-File Report 2014-1255, Report: vi, 13 p.; 2 Appendices, https://doi.org/10.3133/ofr20141255.","productDescription":"Report: vi, 13 p.; 2 Appendices","numberOfPages":"23","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-059712","costCenters":[{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"links":[{"id":297511,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1255/"},{"id":297512,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1255/pdf/ofr2014-1255.pdf"},{"id":297516,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141255.jpg"},{"id":297514,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2014/1255/appendix/ofr2014-1255_appendix02.pdf","text":"Appendix 2","size":"16.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OF 2014-1255 Appendix 2","linkHelpText":"Comparison of borehole image, geophysical, water quality, flowmeter, and sonic logs showing evidence of three productive intervals in the City of Tallahassee test well 32 at Leon County, Florida, December 2013. The full geophysical log is displayed at 1 to 12 scale."},{"id":297513,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2014/1255/appendix/ofr2014-1255_appendix01.pdf","text":"Appendix 1","size":"3.39 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OF 2014-1255 Appendix 1","linkHelpText":"Comparison of borehole image, geophysical, water quality, flowmeter, and sonic logs showing evidence of three productive intervals in the City of Tallahassee test well 32 at Leon County, Florida, December 2013. Only the data collected in the open interval of the test well are displayed at 1 to 96 scale."}],"country":"United States","state":"Florida","county":"Leon County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.825439453125,\n 30.130875412002318\n ],\n [\n -84.825439453125,\n 30.770159115784214\n ],\n [\n -83.85314941406249,\n 30.770159115784214\n ],\n [\n -83.85314941406249,\n 30.130875412002318\n ],\n [\n -84.825439453125,\n 30.130875412002318\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a65e4b08de9379b3037","contributors":{"authors":[{"text":"McBride, W. Scott wmcbride@usgs.gov","contributorId":1096,"corporation":false,"usgs":true,"family":"McBride","given":"W.","email":"wmcbride@usgs.gov","middleInitial":"Scott","affiliations":[{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"preferred":false,"id":537009,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wacker, Michael A. mwacker@usgs.gov","contributorId":2162,"corporation":false,"usgs":true,"family":"Wacker","given":"Michael","email":"mwacker@usgs.gov","middleInitial":"A.","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"preferred":true,"id":537010,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70160443,"text":"70160443 - 2015 - Instrumenting caves to collect hydrologic and geochemical data: case study from James Cave, Virginia","interactions":[],"lastModifiedDate":"2016-09-06T14:41:12","indexId":"70160443","displayToPublicDate":"2015-01-24T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Instrumenting caves to collect hydrologic and geochemical data: case study from James Cave, Virginia","docAbstract":"

Karst aquifers are productive groundwater systems, supplying approximately 25 % of the world’s drinking water. Sustainable use of this critical water supply requires information about rates of recharge to karst aquifers. The overall goal of this project is to collect long-term, high-resolution hydrologic and geochemical datasets at James Cave, Virginia, to evaluate the quantity and quality of recharge to the karst system. To achieve this goal, the cave has been instrumented for continuous (10-min interval) measurement of the (1) temperature and rate of precipitation; (2) temperature, specific conductance, and rate of epikarst dripwater; (3) temperature of the cave air; and (4) temperature, conductivity, and discharge of the cave stream. Instrumentation has also been installed to collect both composite and grab samples of precipitation, soil water, the cave stream, and dripwater for geochemical analysis. This chapter provides detailed information about the instrumentation, data processing, and data management; shows examples of collected datasets; and discusses recommendations for other researchers interested in hydrologic and geochemical monitoring of cave systems. Results from the research, briefly described here and discussed in more detail in other publications, document a strong seasonality of the start of the recharge season, the extent of the recharge season, and the geochemistry of recharge.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Advances in watershed science and assessment","language":"English","publisher":"Springer International Publishing","doi":"10.1007/978-3-319-14212-8_8","usgsCitation":"Schreiber, M.E., Schwartz, B.F., Orndorff, W., Doctor, D.H., Eagle, S.D., and Gerst, J.D., 2015, Instrumenting caves to collect hydrologic and geochemical data: case study from James Cave, Virginia, chap. of Advances in watershed science and assessment, p. 205-231, https://doi.org/10.1007/978-3-319-14212-8_8.","productDescription":"27 p. ","startPage":"205","endPage":"231","ipdsId":"IP-060443","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":328273,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":312537,"type":{"id":15,"text":"Index Page"},"url":"https://link.springer.com/chapter/10.1007/978-3-319-14212-8_8"}],"country":"United States","state":"Virginia","otherGeospatial":"James Cave","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.73715209960938,\n 37.205175356202666\n ],\n [\n -80.47210693359375,\n 37.28388730761434\n ],\n [\n -80.36224365234375,\n 37.113240886048715\n ],\n [\n -80.69869995117188,\n 37.05298514989097\n ],\n [\n -80.73715209960938,\n 37.205175356202666\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-01-24","publicationStatus":"PW","scienceBaseUri":"57cfe8b7e4b04836416a0dca","contributors":{"authors":[{"text":"Schreiber, Madeline E.","contributorId":138959,"corporation":false,"usgs":false,"family":"Schreiber","given":"Madeline","email":"","middleInitial":"E.","affiliations":[{"id":12594,"text":"Department of Geosciences, Virginia Tech, Blacksburg, VA","active":true,"usgs":false}],"preferred":false,"id":582906,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schwartz, Benjamin F.","contributorId":150744,"corporation":false,"usgs":false,"family":"Schwartz","given":"Benjamin","email":"","middleInitial":"F.","affiliations":[{"id":18087,"text":"Texas State University, San Marcos","active":true,"usgs":false}],"preferred":false,"id":582907,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Orndorff, William","contributorId":150745,"corporation":false,"usgs":false,"family":"Orndorff","given":"William","email":"","affiliations":[{"id":18088,"text":"Virginia Dept. of Conservation and Recreation","active":true,"usgs":false}],"preferred":false,"id":582908,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Doctor, Daniel H. 0000-0002-8338-9722 dhdoctor@usgs.gov","orcid":"https://orcid.org/0000-0002-8338-9722","contributorId":2037,"corporation":false,"usgs":true,"family":"Doctor","given":"Daniel","email":"dhdoctor@usgs.gov","middleInitial":"H.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":582905,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eagle, Sarah D.","contributorId":150746,"corporation":false,"usgs":false,"family":"Eagle","given":"Sarah","email":"","middleInitial":"D.","affiliations":[{"id":18089,"text":"Virginia Tech, Dept. of Geosciences","active":true,"usgs":false}],"preferred":false,"id":582909,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gerst, Jonathan D.","contributorId":150747,"corporation":false,"usgs":false,"family":"Gerst","given":"Jonathan","email":"","middleInitial":"D.","affiliations":[{"id":18089,"text":"Virginia Tech, Dept. of Geosciences","active":true,"usgs":false}],"preferred":false,"id":582910,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70138822,"text":"ofr20151011 - 2015 - Simulated runoff at many stream locations in the Methow River Basin, Washington","interactions":[],"lastModifiedDate":"2015-01-23T08:36:20","indexId":"ofr20151011","displayToPublicDate":"2015-01-23T09:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1011","title":"Simulated runoff at many stream locations in the Methow River Basin, Washington","docAbstract":"

A collaborative Bureau of Reclamation-U.S. Geological Survey (USGS) team has been brought together to incorporate a conceptual geomorphic-habitat model with a process-based trophic model to understand the processes important to stream habitat for anadromous fish populations. The Methow River Basin was selected as a test basin for this hybrid geomorphic-habitat/trophic model, and one of the required model inputs is long-term daily runoff at reaches with potential habitat. Leveraging the existence of a watershed model that was constructed for the Methow River Basin by the USGS, the team approached the USGS at the Washington Water Science Center to resurrect the original model and to simulate runoff at many locations in the basin to test the trophic model. Thirteen new flow-routing sites were added to the model, creating a total of 61 sites in the basin where daily runoff was simulated and provided as output. The input file that contains observed meteorological data that drives the watershed model and observed runoff data for comparisons with simulated runoff was extended from water year 2001 to water year 2013 using data from 18 meteorological sites and 12 observed runoff sites. The watershed model included simulation of 16 irrigation diversions that simulated 50-percent water loss through canal seepage. Irrigation was simulated as a constant application of 0.2 inches per day to during the irrigation season, May 1–October 7.

\n

Comparisons of the simulated runoff with observed runoff at six selected long-term streamflow-gaging stations showed that the simulated annual runoff was within +15.4 to -9.6 percent of the annual observed runoff. The simulated runoff generally matched the seasonal flow patterns, with bias at some stations indicated by over-simulation of the October–November late autumn season and under-simulation of the snowmelt runoff months of May and June. Sixty-one time series of daily runoff for a 26-year period representative of the long-term runoff pattern, water years 1988–2013, were simulated and provided to the trophic modeling team.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151011","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Mastin, M.C., 2015, Simulated runoff at many stream locations in the Methow River Basin, Washington: U.S. Geological Survey Open-File Report 2015-1011, iv, 22 p., https://doi.org/10.3133/ofr20151011.","productDescription":"iv, 22 p.","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-061500","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":297472,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151011.JPG"},{"id":297470,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1011/"},{"id":297471,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1011/pdf/ofr2015-1011.pdf","size":"4.9 MB","linkFileType":{"id":1,"text":"pdf"}}],"scale":"100000","projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1983","country":"United States","state":"Washington","otherGeospatial":"Methow River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.41015624999999,\n 47.67278567576541\n ],\n [\n -120.41015624999999,\n 49.001843917978526\n ],\n [\n -119.14672851562499,\n 49.001843917978526\n ],\n [\n -119.14672851562499,\n 47.67278567576541\n ],\n [\n -120.41015624999999,\n 47.67278567576541\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2ab3e4b08de9379b3190","contributors":{"authors":[{"text":"Mastin, Mark C. 0000-0003-4018-7861 mcmastin@usgs.gov","orcid":"https://orcid.org/0000-0003-4018-7861","contributorId":1652,"corporation":false,"usgs":true,"family":"Mastin","given":"Mark","email":"mcmastin@usgs.gov","middleInitial":"C.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539014,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70146011,"text":"70146011 - 2015 - Spring resource phenology and timing of songbird migration across the Gulf of Mexico","interactions":[],"lastModifiedDate":"2018-01-04T12:49:08","indexId":"70146011","displayToPublicDate":"2015-01-23T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3489,"text":"Studies in Avian Biology","active":true,"publicationSubtype":{"id":10}},"title":"Spring resource phenology and timing of songbird migration across the Gulf of Mexico","docAbstract":"

Migratory songbirds are advancing their arrival to breeding areas in response to climatic warming at temperate latitudes. Less is understood about the impacts of climate changes outside the breeding period. Every spring, millions of migrating songbirds that overwinter in the Caribbean and Central and South America stop to rest and
refuel in the first available habitats after crossing the Gulf of Mexico. We used capture data from a long-term
banding station (20 years: 1993 to 2012) located on the northern coast of the Gulf to assess the passage timing of 17 species making northward migrations into eastern North America. We further assessed spring resource phenology as measured by normalized difference vegetation index (NDVI) on nonbreeding ranges and en route. We tested the hypotheses that spring passage timing has advanced during the past two decades and that annual variability in passage timing into eastern North America is related to spring resource phenology
on stationary nonbreeding ranges and during passage south of the Gulf. Further, we assessed whether annual variability in resource phenology south of the Gulf was a good indicator of the conditions that migrants encountered upon first landfall in eastern North America. We found no trend in migration timing for species that migrate from South America and annual variability in their passage timing was unrelated to environmental
conditions in nonbreeding ranges or en route. Species that migrate from Central America and the Caribbean delayed arrival by 2 to 3 days over the 20-year period and arrived later during years when conditions were dryer in nonbreeding ranges and passage areas south of the Gulf. Further, year to year variability in spring resource phenology in nonbreeding ranges and passage areas south of the Gulf were not good indicators of resource
phenology upon arrival in eastern North America. Therefore, despite the fact that many migrant species have been arriving increasingly earlier to breeding grounds, the passage timing of 17 species into eastern North America has either not changed or is slightly later, due to drying spring conditions in Central America and the Caribbean. Our results suggest that Nearctic–Neotropical migratory birds adjust the rate of migration primarily within eastern North America and, in light of warmer temperatures in the temperate zone and earlier arrival
timing to breeding ranges, species that overwinter in Central America and the Caribbean may be increasing the speed of migration within eastern North America.

","language":"English","publisher":"CRC Press","collaboration":"FWS","usgsCitation":"Paxton, E., Cohen, E.B., Nemeth, Z., Zenzal, T.J., Paxton, K.L., Diehl, R.H., and Moore, F.R., 2015, Spring resource phenology and timing of songbird migration across the Gulf of Mexico: Studies in Avian Biology, p. 63-82.","productDescription":"20 p.","startPage":"63","endPage":"82","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055670","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":310782,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":299588,"type":{"id":15,"text":"Index Page"},"url":"https://www.researchgate.net/publication/265612361_Spring_resource_phenology_and_timing_of_songbird_migration_across_the_Gulf_of_Mexico"}],"otherGeospatial":"Johnson’s Bayou, Louisiana and Yucatan Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.0205078125,\n 28.844673680771795\n ],\n [\n -96.70166015624999,\n 28.613459424004414\n ],\n [\n -96.3720703125,\n 28.246327971048842\n ],\n [\n -94.21875,\n 29.036960648558267\n ],\n [\n -93.22998046875,\n 29.53522956294847\n ],\n [\n -90.90087890624999,\n 29.075375179558346\n ],\n [\n -88.8134765625,\n 28.998531814051795\n ],\n [\n -89.2529296875,\n 30.088107753367257\n ],\n [\n -86.50634765625,\n 30.12612436422458\n ],\n [\n -85.60546875,\n 29.630771207229\n ],\n [\n -83.95751953125,\n 29.49698759653577\n ],\n [\n -83.6279296875,\n 29.99300228455108\n ],\n [\n -84.5947265625,\n 30.183121842195515\n ],\n [\n -86.24267578125,\n 30.543338954230222\n ],\n [\n -87.71484375,\n 30.770159115784214\n ],\n [\n -89.296875,\n 30.619004797647808\n ],\n [\n -90.28564453124999,\n 30.50548389892728\n ],\n [\n -90.966796875,\n 29.99300228455108\n ],\n [\n -92.70263671874999,\n 30.240086360983426\n ],\n [\n -94.46044921875,\n 30.031055426540206\n ],\n [\n -95.625,\n 29.401319510041485\n ],\n [\n -95.9326171875,\n 29.017748018496047\n ],\n [\n -96.0205078125,\n 28.844673680771795\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.04296874999999,\n 17.936928637549443\n ],\n [\n -87.71484375,\n 19.062117883514667\n ],\n [\n -86.77001953125,\n 21.166483858206583\n ],\n [\n -87.03369140625,\n 21.800308050972603\n ],\n [\n -89.01123046875,\n 21.57571893245848\n ],\n [\n -90.5712890625,\n 21.08450008351735\n ],\n [\n -91.34033203125,\n 19.642587534013046\n ],\n [\n -93.3837890625,\n 18.89589255941504\n ],\n [\n -94.19677734375,\n 18.646245142670608\n ],\n [\n -94.04296874999999,\n 17.936928637549443\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"47","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56334342e4b048076347eee7","contributors":{"authors":[{"text":"Paxton, Eben H. 0000-0001-5578-7689 epaxton@usgs.gov","orcid":"https://orcid.org/0000-0001-5578-7689","contributorId":438,"corporation":false,"usgs":true,"family":"Paxton","given":"Eben H.","email":"epaxton@usgs.gov","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":false,"id":544617,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cohen, Emily B.","contributorId":57774,"corporation":false,"usgs":false,"family":"Cohen","given":"Emily","email":"","middleInitial":"B.","affiliations":[{"id":7035,"text":"Smithsonian Conservation Biology Institute, National Zoological Park","active":true,"usgs":false}],"preferred":false,"id":544618,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nemeth, Zoltan","contributorId":140015,"corporation":false,"usgs":false,"family":"Nemeth","given":"Zoltan","email":"","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":544619,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zenzal, Theodore J. 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Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Vermont, elevation data are critical for hazard mitigation, geologic resource assessment, natural resources conservation, agriculture and precision farming, flood risk management, infrastructure and construction management, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.

\n

The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.

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Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Nebraska, elevation data are critical for agriculture and precision farming, natural resources conservation, flood risk management, infrastructure and construction management, geologic resource assessment and hazard mitigation, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.

\n

The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.

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Jr. carswell@usgs.gov","contributorId":1787,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":519922,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70138809,"text":"70138809 - 2015 - Growth rates and variances of unexploited wolf populations in dynamic equilibria","interactions":[],"lastModifiedDate":"2018-01-04T11:30:56","indexId":"70138809","displayToPublicDate":"2015-01-22T12:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Growth rates and variances of unexploited wolf populations in dynamic equilibria","docAbstract":"

Several states have begun harvesting gray wolves (Canis lupus), and these states and various European countries are closely monitoring their wolf populations. To provide appropriate perspective for determining unusual or extreme fluctuations in their managed wolf populations, we analyzed natural, long-term, wolf-population-density trajectories totaling 130 years of data from 3 areas: Isle Royale National Park in Lake Superior, Michigan, USA; the east-central Superior National Forest in northeastern Minnesota, USA; and Denali National Park, Alaska, USA. Ratios between minimum and maximum annual sizes for 2 mainland populations (n = 28 and 46 yr) varied from 2.5–2.8, whereas for Isle Royale (n = 56 yr), the ratio was 6.3. The interquartile range (25th percentile, 75th percentile) for annual growth rates, Nt+1/Nt, was (0.88, 1.14), (0.92, 1.11), and (0.86, 1.12) for Denali, Superior National Forest, and Isle Royale respectively. We fit a density-independent model and a Ricker model to each time series, and in both cases we considered the potential for observation error. Mean growth rates from the density-independent model were close to 0 for all 3 populations, with 95% credible intervals including 0. We view the estimated model parameters, including those describing annual variability or process variance, as providing useful summaries of the trajectories of these populations. The estimates of these natural wolf population parameters can serve as benchmarks for comparison with those of recovering wolf populations. Because our study populations were all from circumscribed areas, fluctuations in them represent fluctuations in densities (i.e., changes in numbers are not confounded by changes in occupied area as would be the case with populations expanding their range, as are wolf populations in many states).

","language":"English","publisher":"Wildlife Society Bulletin","doi":"10.1002/wsb.511","usgsCitation":"Mech, L.D., and Fieberg, J., 2015, Growth rates and variances of unexploited wolf populations in dynamic equilibria: Wildlife Society Bulletin, v. 39, no. 1, p. 41-48, https://doi.org/10.1002/wsb.511.","productDescription":"8 p.","startPage":"41","endPage":"48","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056273","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":499924,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/d85d63d4c7d448c2bb1d5681d53a1c7b","text":"External Repository"},{"id":297459,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska, Michigan, Minnesota","otherGeospatial":"Denali National Park, Isle Royale National Park, Superior National Forest","volume":"39","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-01-08","publicationStatus":"PW","scienceBaseUri":"54dd2a85e4b08de9379b30c4","contributors":{"authors":[{"text":"Mech, L. David 0000-0003-3944-7769 david_mech@usgs.gov","orcid":"https://orcid.org/0000-0003-3944-7769","contributorId":2518,"corporation":false,"usgs":true,"family":"Mech","given":"L.","email":"david_mech@usgs.gov","middleInitial":"David","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":538906,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fieberg, John","contributorId":44804,"corporation":false,"usgs":false,"family":"Fieberg","given":"John","affiliations":[{"id":7201,"text":"University of Minnesota-St. Paul","active":true,"usgs":false}],"preferred":false,"id":538907,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}