Monthly calibrated values of the Hamon PET coefficient (C) are determined for 109,951 hydrologic response units (HRUs) across the conterminous United States (U.S.). The calibrated coefficient values are determined by matching calculated mean monthly Hamon PET to mean monthly free-water surface evaporation. For most locations and months the calibrated coefficients are larger than the standard value reported by Hamon. The largest changes in the coefficients were for the late winter/early spring and fall months, whereas the smallest changes were for the summer months. Comparisons of PET computed using the standard value of C and computed using calibrated values of C indicate that for most of the conterminous U.S. PET is underestimated using the standard Hamon PET coefficient, except for the southeastern U.S.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2014.12.006","usgsCitation":"McCabe, G., Hay, L.E., Bock, A., Markstrom, S., and Atkinson, R., 2015, Inter-annual and spatial variability of Hamon potential evapotranspiration model coefficients: Journal of Hydrology, v. 521, p. 389-394, https://doi.org/10.1016/j.jhydrol.2014.12.006.","productDescription":"6 p.","startPage":"389","endPage":"394","ipdsId":"IP-058189","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":343611,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"521","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5965b4b0e4b0d1f9f05b382f","contributors":{"authors":[{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":1453,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory J.","email":"gmccabe@usgs.gov","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"preferred":false,"id":704307,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hay, Lauren E. 0000-0003-3763-4595 lhay@usgs.gov","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":1287,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","email":"lhay@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":704308,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bock, Andy 0000-0001-7222-6613 abock@usgs.gov","orcid":"https://orcid.org/0000-0001-7222-6613","contributorId":174776,"corporation":false,"usgs":true,"family":"Bock","given":"Andy","email":"abock@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":false,"id":704309,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Markstrom, Steven L. 0000-0001-7630-9547 markstro@usgs.gov","orcid":"https://orcid.org/0000-0001-7630-9547","contributorId":1986,"corporation":false,"usgs":true,"family":"Markstrom","given":"Steven L.","email":"markstro@usgs.gov","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":704310,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Atkinson, R. Dwight","contributorId":174777,"corporation":false,"usgs":false,"family":"Atkinson","given":"R. Dwight","affiliations":[{"id":27513,"text":"U.S. Environmental Protection Agency, Office of Water","active":true,"usgs":false}],"preferred":false,"id":704311,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70142152,"text":"70142152 - 2015 - Time scales of porphyry Cu deposit formation: insights from titanium diffusion in quartz","interactions":[],"lastModifiedDate":"2015-03-03T11:18:21","indexId":"70142152","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Time scales of porphyry Cu deposit formation: insights from titanium diffusion in quartz","docAbstract":"Porphyry dikes and hydrothermal veins from the porphyry Cu-Mo deposit at Butte, Montana, contain multiple generations of quartz that are distinct in scanning electron microscope-cathodoluminescence (SEM-CL) images and in Ti concentrations. A comparison of microprobe trace element profiles and maps to SEM-CL images shows that the concentration of Ti in quartz correlates positively with CL brightness but Al, K, and Fe do not. After calibrating CL brightness in relation to Ti concentration, we use the brightness gradient between different quartz generations as a proxy for Ti gradients that we model to determine time scales of quartz formation and cooling. Model results indicate that time scales of porphyry magma residence are ~1,000s of years and time scales from porphyry quartz phenocryst rim formation to porphyry dike injection and cooling are ~10s of years. Time scales for the formation and cooling of various generations of hydrothermal vein quartz range from 10s to 10,000s of years. These time scales are considerably shorter than the ~0.6 m.y. overall time frame for each porphyry-style mineralization pulse determined from isotopic studies at Butte, Montana. Simple heat conduction models provide a temporal reference point to compare chemical diffusion time scales, and we find that they support short dike and vein formation time scales. We interpret these relatively short time scales to indicate that the Butte porphyry deposit formed by short-lived episodes of hydrofracturing, dike injection, and vein formation, each with discrete thermal pulses, which repeated over the ~3 m.y. generation of the deposit.
","language":"English","publisher":"Society of Economic Geologists","doi":"10.2113/econgeo.110.3.587","usgsCitation":"Mercer, C.N., Reed, M.H., and Mercer, C., 2015, Time scales of porphyry Cu deposit formation: insights from titanium diffusion in quartz: Economic Geology, v. 110, no. 3, p. 587-602, https://doi.org/10.2113/econgeo.110.3.587.","productDescription":"16 p.","startPage":"587","endPage":"602","numberOfPages":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053533","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":298244,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","city":"Butte","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.35992431640625,\n 46.00089681276469\n ],\n [\n -112.35992431640625,\n 46.041663258553875\n ],\n [\n -112.2996711730957,\n 46.041663258553875\n ],\n [\n -112.2996711730957,\n 46.00089681276469\n ],\n [\n -112.35992431640625,\n 46.00089681276469\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"110","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-24","publicationStatus":"PW","scienceBaseUri":"54f6e949e4b02419550d30ab","contributors":{"authors":[{"text":"Mercer, Celestine N. 0000-0001-8359-4147 cmercer@usgs.gov","orcid":"https://orcid.org/0000-0001-8359-4147","contributorId":4006,"corporation":false,"usgs":true,"family":"Mercer","given":"Celestine","email":"cmercer@usgs.gov","middleInitial":"N.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":541622,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reed, Mark H.","contributorId":139519,"corporation":false,"usgs":false,"family":"Reed","given":"Mark","email":"","middleInitial":"H.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":541623,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mercer, Cameron M.","contributorId":139520,"corporation":false,"usgs":false,"family":"Mercer","given":"Cameron M.","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":541624,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70193932,"text":"70193932 - 2015 - Sources of fine sediment stored in agricultural lowland streams, Midwest, USA","interactions":[],"lastModifiedDate":"2017-11-10T10:52:27","indexId":"70193932","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Sources of fine sediment stored in agricultural lowland streams, Midwest, USA","docAbstract":"Agricultural activities can accelerate the offsite transport of productive soil from fields leading to stream water quality degradation. Identification of the nature and relative contribution of different sources to fine-grained sediment (e.g., silts, clays) in streams is important to effectively focus agricultural best management practices in watersheds. Sediment fingerprinting techniques through the use of geochemical tracers are commonly used to differentiate relative contribution from various sources. Research was conducted in lowland streams in the Pleasant Valley watershed in South Central Wisconsin (USA) to identify provenance of fine-grained sediment deposits and evaluate the impact of land use on relative contributions from the following potential sources: cropland, pasture, woodland, and eroding stream banks. Results show that both agriculture (croplands and pastures) and eroding stream banks are primary sources to fine sediment deposits on the stream bed with contributions ranging from 19 to 100% and 0 to 81%, respectively. The increase in area under agricultural land use within a subwatershed results in greater contribution from agriculture (R2 = 0.846, p = 0.0034). Relative contributions from eroding stream banks increased with increasing area under grasslands and woodlands within a subwatershed (R2 = 0.814, p = 0.0055). Subwatersheds with greater mass of fine sediment deposited on the stream bed per unit area should be prioritized for best management practices. The conservation practices should be targeted to stream banks or croplands depending on the dominant source of fine sediment within a subwatershed. Site specific changes in relative contributions from different sources to fine-grained sediment in this watershed highlights the complexities involved in sediment transport dynamics. The nested sampling sites helped determine that sediment dynamics at the subwatershed scale need to be considered for application of targeted conservation techniques.
A critical decision in species conservation is whether to target individual species or a complex of ecologically similar species. Management of multispecies complexes is likely to be most effective when species share similar distributions, threats, and response to threats. We used niche overlap analysis to assess ecological similarity of 3 sensitive desert fish species currently managed as an ecological complex. We measured the amount of shared distribution of multiple habitat and life history parameters between each pair of species. Habitat use and multiple life history parameters, including maximum body length, spawning temperature, and longevity, differed significantly among the 3 species. The differences in habitat use and life history parameters among the species suggest they are likely to respond differently to similar threats and that most management actions will not benefit all 3 species equally. Habitat restoration, frequency of stream dewatering, non-native species control, and management efforts in tributaries versus main stem rivers are all likely to impact each of the species differently. Our results demonstrate that niche overlap analysis provides a powerful tool for assessing the likely effectiveness of multispecies versus single-species conservation plans.
\nThe 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.
\nThe 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.
\nUncorrected 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.
\nArsenic (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.
\nAs, 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.
\nIn 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.
\nConcentrations 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":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539648,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70135239,"text":"sir20145223 - 2015 - Geomorphology and flood-plain vegetation of the Sprague and lower Sycan Rivers, Klamath Basin, Oregon","interactions":[],"lastModifiedDate":"2019-04-24T15:35:34","indexId":"sir20145223","displayToPublicDate":"2015-01-30T16:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5223","title":"Geomorphology and flood-plain vegetation of the Sprague and lower Sycan Rivers, Klamath Basin, Oregon","docAbstract":"This study provides information on channel and flood-plain processes and historical trends to guide effective restoration and monitoring strategies for the Sprague River Basin, a primary tributary (via the lower Williamson River) of Upper Klamath Lake, Oregon. The study area covered the lower, alluvial segments of the Sprague River system, including the lower parts of the Sycan River, North Fork Sprague River, South Fork Sprague River, and the entire main-stem Sprague River between the confluence of the North Fork Sprague and the South Fork Sprague Rivers and its confluence with the Williamson River at Chiloquin, Oregon. The study included mapping and stratigraphic analysis of flood-plain deposits and flanking features; evaluation of historical records, maps and photographs; mapping and analysis of flood-plain and channel characteristics (including morphologic and vegetation conditions); and a 2006 survey of depositional features left by high flows during the winter and spring of 2005–06.
\nAnalyses focused on the channel and flood plain within an area defined as the “geomorphic flood plain,” an area encompassing active fluvial and riparian processes. The geomorphic flood plain was subdivided into 13 valley segments of distinct fluvial environments on the basis of valley form and major tributary junctions: nine segments span the 136.1 kilometers of main-stem Sprague River, two segments for the lower Sycan River, and one segment for each part of the South Fork Sprague and North Fork Sprague Rivers within the study area. Segment characteristics range from steep and narrow canyons to low-gradient reaches with expansive flood plains. The wide flood-plain valley segments are broadly similar; most contain a sinuous, low-gradient channel that migrates slowly across the valley bottom. The narrow valley segments include the steep, boulder-and-cobble-bed reaches at downstream and upstream ends of the study area as well as other confined valley segments that have similar gradients and substrates as adjacent unconfined valley segments, but much lower sinuosities. Although the geologic setting of the expansive South Fork valley segment resulted in historical conditions of sinuous and poorly defined channels and wet meadows, flanking levees now narrowly confine the channelized South Fork Sprague River for much of its length.
\nStratigraphic analyses show that before the Mazama eruption of 7,700 calendar years before present, wetlands and low flood plains flanked the main rivers of the study area. The eruption, however, covered much of the northern basin with sand- and granule-size pumice clasts, transforming channels by increasing bed-material transport and promoting bar formation and channel migration, particularly for the Sycan and North Fork Sprague Rivers, and for the Sprague River downstream of the Sycan River confluence. The South Fork Sprague River, which had much less Mazama pumice deposited in its watershed, remained a wet-meadow fluvial system until historical channelization and diking.
\nThe analysis of historical maps and aerial photographs covering the geomorphic flood plain show changes in sinuosity, migration rates, and vegetation conditions since the 1800s. Most quantitative information is for the period between 1940 and 2000. The decrease in sinuosity since 1940 for nearly all the unconfined reaches resulted partly from decreased migration rates, but mostly from several cutoffs and avulsions formed between 1940 and 1975. The river shortening and steepening possibly resulted from (1) flood-plain confinement by levees, dikes, roads, and railroads leading to deeper and faster overbank flow, thereby promoting erosion of new flood-plain channels; and (2) flood-plain disturbances such as trails, ditches, and vegetation manipulation or eradication that locally concentrated overbank flow and decreased surface resistance to channel erosion.
\nThe most evident vegetation change has been the loss of short woody vegetation adjacent to the river channels: only one-half the near-channel area covered by short woody vegetation in 1940 was similarly covered in 2000. Woody vegetation removal in the 1950s and 1960s and continuing grazing and trampling by livestock probably are the main reasons for the decrease in short woody vegetation from the dense riparian corridors of willows (Salix sp.) and other riparian shrubs noted in the early 20th century.
\nThe alluvial corridor of the South Fork Sprague River, compared to other Sprague River Basin rivers, has been the most substantially transformed since first historical observations. The present channel is incised, straightened, and separated from the rarely inundated flood plain by levees.
\nDespite these effects of human disturbances, many of the fundamental physical processes forming the Sprague River fluvial systems over the last several thousand years still function. In particular, flows are unregulated, sediment transport processes are active, and overbank flooding allows for floodplain deposition and erosion. Therefore, restoration of many of the native physical conditions and processes is possible without substantial physical manipulation of current conditions for much of the Sprague River study area. An exception is the South Fork Sprague River, where historical trends are not likely to reverse until it attains a more natural channel and flood-plain geometry and the channel aggrades to the extent that overbank flow becomes common.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145223","collaboration":"Prepared in cooperation with the University of Oregon and the U.S. Fish and Wildlife Service","usgsCitation":"O'Connor, J., McDowell, P.F., Lind, P., Rasmussen, C.G., and Keith, M., 2015, Geomorphology and flood-plain vegetation of the Sprague and lower Sycan Rivers, Klamath Basin, Oregon: U.S. Geological Survey Scientific Investigations Report 2014-5223, Report: xi, 121 p.; 1 Plate: 34.11 x 20.80 inches; 8 Appendixes, https://doi.org/10.3133/sir20145223.","productDescription":"Report: xi, 121 p.; 1 Plate: 34.11 x 20.80 inches; 8 Appendixes","numberOfPages":"138","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-052624","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"links":[{"id":297653,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5223/downloads/sir2014-5223_appendixd.xlsx","text":"Appendix D","size":"10 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":297652,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5223/downloads/sir2014-5223_appendixa.xlsx","text":"Appendix A","size":"12 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":297654,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5223/downloads/sir2014-5223_appendixe.xlsx","text":"Appendix E","size":"12 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":297655,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5223/downloads/sir2014-5223_appendixf.xlsx","text":"Appendix F","size":"21 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":297656,"rank":10,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5223/downloads/sir2014-5223_appendixg.xlsx","text":"Appendix G","size":"31 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":297657,"rank":11,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5223/downloads/sir2014-5223_appendixh.xlsx","text":"Appendix H","size":"27 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":297647,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5223/"},{"id":297651,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5223/downloads/sir2014-5223_appendixc.xlsx","text":"Appendix C","size":"10 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":297648,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2014/5223/downloads/sir2014-5223_plate01.pdf","size":"14.9 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Oregon","active":true,"usgs":false}],"preferred":false,"id":539639,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lind, Pollyanna","contributorId":119823,"corporation":false,"usgs":false,"family":"Lind","given":"Pollyanna","email":"","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":539640,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rasmussen, Christine G.","contributorId":118634,"corporation":false,"usgs":false,"family":"Rasmussen","given":"Christine","email":"","middleInitial":"G.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":539641,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Keith, Mackenzie K.","contributorId":16560,"corporation":false,"usgs":true,"family":"Keith","given":"Mackenzie K.","affiliations":[],"preferred":false,"id":539642,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"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.
\nThe 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.
\nTime-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":70139739,"text":"70139739 - 2015 - Characterizing the distribution of an endangered salmonid using environmental DNA analysis","interactions":[],"lastModifiedDate":"2017-11-22T17:59:07","indexId":"70139739","displayToPublicDate":"2015-01-30T12:45:00","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}},"title":"Characterizing the distribution of an endangered salmonid using environmental DNA analysis","docAbstract":"Determining species distributions accurately is crucial to developing conservation and management strategies for imperiled species, but a challenging task for small populations. We evaluated the efficacy of environmental DNA (eDNA) analysis for improving detection and thus potentially refining the known distribution of Chinook salmon (Oncorhynchus tshawytscha) in the Methow and Okanogan Subbasins of the Upper Columbia River, which span the border between Washington, USA and British Columbia, Canada. We developed an assay to target a 90 base pair sequence of Chinook DNA and used quantitative polymerase chain reaction (qPCR) to quantify the amount of Chinook eDNA in triplicate 1-L water samples collected at 48 stream locations in June and again in August 2012. The overall probability of detecting Chinook with our eDNA method in areas within the known distribution was 0.77 (±0.05 SE). Detection probability was lower in June (0.62, ±0.08 SE) during high flows and at the beginning of spring Chinook migration than during base flows in August (0.93, ±0.04 SE). In the Methow subbasin, mean eDNA concentration was higher in August compared to June, especially in smaller tributaries, probably resulting from the arrival of spring Chinook adults, reduced discharge, or both. Chinook eDNA concentrations did not appear to change in the Okanogan subbasin from June to August. Contrary to our expectations about downstream eDNA accumulation, Chinook eDNA did not decrease in concentration in upstream reaches (0–120 km). Further examination of factors influencing spatial distribution of eDNA in lotic systems may allow for greater inference of local population densities along stream networks or watersheds. These results demonstrate the potential effectiveness of eDNA detection methods for determining landscape-level distribution of anadromous salmonids in large river systems.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2014.11.025","usgsCitation":"Laramie, M.B., Pilliod, D., and Goldberg, C.S., 2015, Characterizing the distribution of an endangered salmonid using environmental DNA analysis: Biological Conservation, v. 183, p. 29-37, https://doi.org/10.1016/j.biocon.2014.11.025.","productDescription":"9 p.","startPage":"29","endPage":"37","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059842","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":472314,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2014.11.025","text":"Publisher Index Page"},{"id":297643,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"British Columbia, Washington","otherGeospatial":"Upper Columbia River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.83312988281249,\n 48.026672195435985\n ],\n [\n -120.83312988281249,\n 49.66762782262192\n ],\n [\n -118.87207031250001,\n 49.66762782262192\n ],\n [\n -118.87207031250001,\n 48.026672195435985\n ],\n [\n -120.83312988281249,\n 48.026672195435985\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"183","publicComments":"Special Issue: Environmental DNA: A powerful new tool for biological conservation","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a5de4b08de9379b3014","contributors":{"authors":[{"text":"Laramie, Matthew B. mlaramie@usgs.gov","contributorId":5627,"corporation":false,"usgs":true,"family":"Laramie","given":"Matthew","email":"mlaramie@usgs.gov","middleInitial":"B.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":539624,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pilliod, David S. 0000-0003-4207-3518 dpilliod@usgs.gov","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":161,"corporation":false,"usgs":true,"family":"Pilliod","given":"David S.","email":"dpilliod@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":539625,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goldberg, Caren S.","contributorId":76879,"corporation":false,"usgs":false,"family":"Goldberg","given":"Caren","email":"","middleInitial":"S.","affiliations":[{"id":5132,"text":"Washington State University, Pullman","active":true,"usgs":false}],"preferred":false,"id":539626,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"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":70139713,"text":"70139713 - 2015 - Geographically isolated wetlands: Rethinking a misnomer","interactions":[],"lastModifiedDate":"2018-01-04T12:07:02","indexId":"70139713","displayToPublicDate":"2015-01-30T11:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Geographically isolated wetlands: Rethinking a misnomer","docAbstract":"We explore the category “geographically isolated wetlands” (GIWs; i.e., wetlands completely surrounded by uplands at the local scale) as used in the wetland sciences. As currently used, the GIW category (1) hampers scientific efforts by obscuring important hydrological and ecological differences among multiple wetland functional types, (2) aggregates wetlands in a manner not reflective of regulatory and management information needs, (3) implies wetlands so described are in some way “isolated,” an often incorrect implication, (4) is inconsistent with more broadly used and accepted concepts of “geographic isolation,” and (5) has injected unnecessary confusion into scientific investigations and discussions. Instead, we suggest other wetland classification systems offer more informative alternatives. For example, hydrogeomorphic (HGM) classes based on well-established scientific definitions account for wetland functional diversity thereby facilitating explorations into questions of connectivity without an a priori designation of “isolation.” Additionally, an HGM-type approach could be used in combination with terms reflective of current regulatory or policymaking needs. For those rare cases in which the condition of being surrounded by uplands is the relevant distinguishing characteristic, use of terminology that does not unnecessarily imply isolation (e.g., “upland embedded wetlands”) would help alleviate much confusion caused by the “geographically isolated wetlands” misnomer.
","language":"English","publisher":"Springer","doi":"10.1007/s13157-015-0631-9","usgsCitation":"Mushet, D.M., Calhoun, A.J., Alexander, L., Cohen, M.J., DeKeyser, E., Fowler, L.G., Lane, C., Lang, M.W., Rains, M.C., and Walls, S.C., 2015, Geographically isolated wetlands: Rethinking a misnomer: Wetlands, v. 35, no. 3, p. 423-431, https://doi.org/10.1007/s13157-015-0631-9.","productDescription":"9 p.","startPage":"423","endPage":"431","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056247","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":472316,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s13157-015-0631-9","text":"Publisher Index Page"},{"id":297639,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-01-27","publicationStatus":"PW","scienceBaseUri":"54dd2a7ee4b08de9379b30a6","contributors":{"authors":[{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":539573,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Calhoun, Aram J.K.","contributorId":93829,"corporation":false,"usgs":false,"family":"Calhoun","given":"Aram","email":"","middleInitial":"J.K.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":539574,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alexander, Laurie C.","contributorId":138989,"corporation":false,"usgs":false,"family":"Alexander","given":"Laurie C.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":539608,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cohen, Matthew J.","contributorId":138990,"corporation":false,"usgs":false,"family":"Cohen","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":539609,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DeKeyser, Edward S.","contributorId":138601,"corporation":false,"usgs":false,"family":"DeKeyser","given":"Edward S.","affiliations":[{"id":12459,"text":"NDSU","active":true,"usgs":false}],"preferred":false,"id":539575,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fowler, Laurie G.","contributorId":21199,"corporation":false,"usgs":false,"family":"Fowler","given":"Laurie","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":539576,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lane, Charles R.","contributorId":138991,"corporation":false,"usgs":false,"family":"Lane","given":"Charles R.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":539610,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lang, Megan W.","contributorId":131150,"corporation":false,"usgs":false,"family":"Lang","given":"Megan","email":"","middleInitial":"W.","affiliations":[{"id":7264,"text":"USDA Forest Service, Northern Research Station, Beltsville, MD 20705","active":true,"usgs":false}],"preferred":false,"id":539577,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rains, Mark C.","contributorId":138983,"corporation":false,"usgs":false,"family":"Rains","given":"Mark","email":"","middleInitial":"C.","affiliations":[{"id":12607,"text":"Univ of South florida, School of Geosciences, Tampa FL","active":true,"usgs":false}],"preferred":false,"id":539578,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Walls, Susan C. 0000-0001-7391-9155 swalls@usgs.gov","orcid":"https://orcid.org/0000-0001-7391-9155","contributorId":138952,"corporation":false,"usgs":true,"family":"Walls","given":"Susan","email":"swalls@usgs.gov","middleInitial":"C.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":539579,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70139682,"text":"70139682 - 2015 - The influence of disturbed habitat on the spatial ecology of Argentine black and white tegu (Tupinambis merianae), a recent invader in the Everglades ecosystem (Florida, USA)","interactions":[],"lastModifiedDate":"2015-11-30T10:25:38","indexId":"70139682","displayToPublicDate":"2015-01-30T11:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"The influence of disturbed habitat on the spatial ecology of Argentine black and white tegu (Tupinambis merianae), a recent invader in the Everglades ecosystem (Florida, USA)","docAbstract":"The threat of invasive species is often intensified in disturbed habitat. To optimize control programs, it is necessary to understand how degraded habitat influences the behavior of invasive species. We conducted a radio telemetry study to characterize movement and habitat use of introduced male Argentine black and white tegus (Tupinambis merianae) in the Everglades of southern Florida from May to August 2012 at the core and periphery of the introduced range. Tegus at the periphery moved farther per day (mean 131.7 ± 11.6 m, n = 6) compared to tegus at the core (mean 50.3 ± 12.4 m, n = 6). However, activity ranges were not significantly smaller in the core (mean 19.4 ± 8.4 ha, n = 6) compared to periphery (mean 29.1 ± 5.2 ha, n = 6). Peripheral activity ranges were more linear due to activity being largely restricted to levee habitat surrounded by open water or marsh. Tegus were located in shrub or tree habitat (mean 96%) more often than expected based on random locations (mean 58%), and the percent cover of trees and shrubs was higher in activity ranges (mean 61%) than the general study area (17%). Our study highlighted the ability of tegus to spread across the Florida landscape, especially in linear disturbed habitats where increased movement occurred and in areas of altered hydrology where movement is not restricted by water.
","language":"English","publisher":"Springer","doi":"10.1007/s10530-014-0834-7","usgsCitation":"Klug, P.E., Reed, R., Mazzotti, F., McEachern, M., Vinci, J.J., Craven, K.K., and Yackel Adams, A.A., 2015, The influence of disturbed habitat on the spatial ecology of Argentine black and white tegu (Tupinambis merianae), a recent invader in the Everglades ecosystem (Florida, USA): Biological Invasions, v. 17, no. 6, p. 1785-1797, https://doi.org/10.1007/s10530-014-0834-7.","productDescription":"13 p.","startPage":"1785","endPage":"1797","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054967","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":297638,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","county":"Miami-Dade County","otherGeospatial":"Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.947021484375,\n 25.055745117015316\n ],\n [\n -81.947021484375,\n 26.828972753817787\n ],\n [\n -79.7442626953125,\n 26.828972753817787\n ],\n [\n -79.7442626953125,\n 25.055745117015316\n ],\n [\n -81.947021484375,\n 25.055745117015316\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"17","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-01-04","publicationStatus":"PW","scienceBaseUri":"54dd2abfe4b08de9379b31d0","contributors":{"authors":[{"text":"Klug, Page E. pklug@usgs.gov","contributorId":5545,"corporation":false,"usgs":true,"family":"Klug","given":"Page","email":"pklug@usgs.gov","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":539556,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reed, Robert N. reedr@usgs.gov","contributorId":1686,"corporation":false,"usgs":true,"family":"Reed","given":"Robert N.","email":"reedr@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":539557,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mazzotti, Frank J.","contributorId":100018,"corporation":false,"usgs":false,"family":"Mazzotti","given":"Frank J.","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":539561,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McEachern, Michelle A. mmceachern@usgs.gov","contributorId":5539,"corporation":false,"usgs":true,"family":"McEachern","given":"Michelle A.","email":"mmceachern@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":539560,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vinci, Joy J.","contributorId":138977,"corporation":false,"usgs":false,"family":"Vinci","given":"Joy","email":"","middleInitial":"J.","affiliations":[{"id":12604,"text":"Department of Wildlife Ecology and Conservation, Fort Lauderdale Research and Education Center, 3205 College Avenue, University of Florida, Davie, FL 33314, USA","active":true,"usgs":false}],"preferred":false,"id":539562,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Craven, Katelin K. kcraven@usgs.gov","contributorId":5286,"corporation":false,"usgs":true,"family":"Craven","given":"Katelin","email":"kcraven@usgs.gov","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":539559,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Yackel Adams, Amy A. 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":3116,"corporation":false,"usgs":true,"family":"Yackel Adams","given":"Amy","email":"yackela@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":539558,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"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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Water samples were collected from 11 monitoring wells completed in about 250–750 feet of the upper part of the aquifer, and samples were analyzed for selected major ions, trace elements, nutrients, radiochemical constituents, and stable isotopes. Each well was equipped with a multilevel monitoring system containing four to seven sampling ports that were each isolated by permanent packer systems. The sampling ports were installed in aquifer zones that were highly transmissive and that represented the water chemistry of the top three to five model layers of a steady-state and transient groundwater‑flow model. The groundwater-flow model and water chemistry are being used to better define movement of wastewater constituents in the aquifer.
\nThe water-chemistry composition of all sampled zones for the five new multilevel wells is calcium plus magnesium bicarbonate. One of the zones in well USGS 131A has a slightly different chemistry from the rest of the zones and wells and the difference is attributed to more wastewater influence from the Idaho Nuclear Technology and Engineering Center. One well, USGS 135, was not influenced by wastewater disposal and consisted of mostly older water in all of its zones.
\nTritium concentrations in relation to basaltic flow units indicate the presence of wastewater influence in multiple basalt flow groups; however, tritium is most abundant in the South Late Matuyama flow group in the southern boundary wells. The concentrations of wastewater constituents in deep zones in wells Middle 2051, USGS 132, USGS 105, and USGS 103 support the concept of groundwater flow deepening in the southwestern corner of the INL, as indicated by the INL groundwater-flow model.
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\nThe 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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Hampshire\",\"nation\":\"USA \"}}]}","edition":"Version 1.0: Originally posted January 30, 2015; Version 1.1: June 29, 2015","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2abde4b08de9379b31be","contributors":{"authors":[{"text":"Carswell, William J. 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":70139250,"text":"70139250 - 2015 - Origin of Atlantic Sturgeon collected off the Delaware coast during spring months","interactions":[],"lastModifiedDate":"2015-01-30T08:48:32","indexId":"70139250","displayToPublicDate":"2015-01-30T08:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Origin of Atlantic Sturgeon collected off the Delaware coast during spring months","docAbstract":"Atlantic Sturgeon Acipenser oxyrinchus oxyrinchus was federally listed under the U.S. Endangered Species Act as five distinct population segments (DPS). Currently, at least 18 estuaries coastwide host spawning populations and the viability of these vary, requiring differing levels of protection. Subadults emigrate from their natal estuaries to marine waters where they are vulnerable to bycatch; one of the major threats to the rebuilding of populations. As a result, identifying the population origin of Atlantic Sturgeon in coastal waters is critical to development of management plans intended to minimize interactions of the most imperiled populations with damaging fisheries. We used mitochondrial DNA control region sequencing and microsatellite DNA analyses to determine the origin of 261 Atlantic Sturgeon collected off the Delaware coast during the spring months. Using individual-based assignment (IBA) testing and mixed stock analysis, we found that specimens originated from all nine of our reference populations and the five DPSs used in the listing determination. Using IBA, we found that the Hudson River population was the largest contributor (38.3%) to our coastal collection. The James (19.9%) and Delaware (13.8%) river populations, at one time thought to be extirpated or nearly so, were the next largest contributors. The three populations combined in the South Atlantic DPS contributed 21% of specimens; the Altamaha River, the largest population in the South Atlantic DPS, only contributed a single specimen to the collection. While the origin of specimens collected on the Delaware coast was most likely within rivers of the New York Bight DPS (52.1%), specimens that originated elsewhere were also well represented. Genetic analyses provide a robust tool to identify the population origin of individual sturgeon outside of their natal estuaries and to determine the quantitative contributions of individual populations to coastal aggregations that are vulnerable to bycatch and other anthropogenic threats.
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","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Analyzing and modeling spatial and temporal dynamics of infectious diseases","language":"English","publisher":"Wiley","doi":"10.1002/9781118630013.ch7","usgsCitation":"Bourouiba, L., Gourley, S.A., Liu, R., Takekawa, J.Y., and Wu, J., 2015, Avian Influenza spread and transmission dynamics, chap. of Analyzing and modeling spatial and temporal dynamics of infectious diseases, p. 137-162, https://doi.org/10.1002/9781118630013.ch7.","productDescription":"26 p.","startPage":"137","endPage":"162","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056959","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":319583,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2015-01-30","publicationStatus":"PW","scienceBaseUri":"56fba733e4b0a6037df1a083","contributors":{"editors":[{"text":"Chen, Dongmei","contributorId":150562,"corporation":false,"usgs":false,"family":"Chen","given":"Dongmei","email":"","affiliations":[],"preferred":false,"id":625550,"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":625551,"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":625552,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Bourouiba, Lydia","contributorId":167584,"corporation":false,"usgs":false,"family":"Bourouiba","given":"Lydia","email":"","affiliations":[{"id":24763,"text":"Civil & Environmental Engineering, MIT, MA, USA","active":true,"usgs":false}],"preferred":false,"id":622767,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gourley, Stephen A.","contributorId":60487,"corporation":false,"usgs":true,"family":"Gourley","given":"Stephen","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":622768,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liu, Rongsong","contributorId":43480,"corporation":false,"usgs":false,"family":"Liu","given":"Rongsong","email":"","affiliations":[],"preferred":false,"id":622769,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Takekawa, John Y. 0000-0003-0217-5907 john_takekawa@usgs.gov","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":176168,"corporation":false,"usgs":true,"family":"Takekawa","given":"John","email":"john_takekawa@usgs.gov","middleInitial":"Y.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":622766,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wu, Jianhong","contributorId":92413,"corporation":false,"usgs":false,"family":"Wu","given":"Jianhong","email":"","affiliations":[],"preferred":false,"id":622770,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"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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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":70138255,"text":"ofr20141260 - 2015 - California State Waters Map Series — Offshore of Pacifica, 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.
\nThe 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.
\nThe 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.
\nThe 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.
\nIn 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.
\nThe 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.
\nThroughout 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).
\nUnlike 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.
\nThe 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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encroaching coconut palm limits native forest water use and persistence on a Pacific atoll","docAbstract":"Competition for fresh water between native and introduced plants is one important challenge facing native forests as rainfall variability increases. Competition can be especially acute for vegetation on Pacific atolls, which depend upon consistent rainfall to replenish shallow groundwater stores. Patterns of sap flow, water use, and diameter growth of Pisonia grandis trees were investigated on Sand Islet, Palmyra Atoll, Line Islands, during a period of low rainfall. Sap flow in the outer sapwood was reduced by 53% for P. grandis trees growing within coconut palm (Cocos nucifera) stands (n = 9) versus away from coconut palm (n = 9). This suggested that water uptake was being limited by coconut palm. Radial patterns of sap flow into the sapwood of P. grandis also differed between stands with and without coconut palm, such that individual tree water use for P. grandis ranged from 14 to 67 L day−1, averaging 47·8 L day−1 without coconut palm and 23·6 L day−1 with coconut palm. Diameter growth of P. grandis was measured from nine islets. In contrast to sap flow, competition with coconut palm increased diameter growth by 89%, equating to an individual tree basal area increment of 5·4 versus 10·3 mm2 day−1. Greater diameter growth countered by lower rates of water use by P. grandis trees growing in competition with coconut palm suggests that stem swell may be associated with water storage when positioned in the understory of coconut palm, and may facilitate survival when water becomes limiting until too much shading overwhelms P. grandis.
","language":"English","publisher":"Wiley","doi":"10.1002/eco.1601","usgsCitation":"Krauss, K.W., Duberstein, J., Cormier, N., Young, H.S., and Hathaway, S.A., 2015, Proximity to encroaching coconut palm limits native forest water use and persistence on a Pacific atoll: Ecohydrology, v. 8, no. 8, p. 1514-1524, https://doi.org/10.1002/eco.1601.","productDescription":"11 p.","startPage":"1514","endPage":"1524","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052329","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":306941,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Palmyra Atoll","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -162.13760375976562,\n 5.912312054739402\n ],\n [\n -162.1365737915039,\n 5.848448533368537\n ],\n [\n -162.02362060546875,\n 5.848106997539167\n ],\n [\n -162.02722549438474,\n 5.909921573942511\n ],\n [\n -162.13760375976562,\n 5.912312054739402\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"8","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2015-01-29","publicationStatus":"PW","scienceBaseUri":"55d5a8b3e4b0518e3546a4de","chorus":{"doi":"10.1002/eco.1601","url":"http://dx.doi.org/10.1002/eco.1601","publisher":"Wiley-Blackwell","authors":"Krauss Ken W., Duberstein Jamie A., Cormier Nicole, Young Hillary S., Hathaway Stacie A.","journalName":"Ecohydrology","publicationDate":"1/29/2015","auditedOn":"2/8/2015"},"contributors":{"authors":[{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":568611,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duberstein, Jamie A.","contributorId":91007,"corporation":false,"usgs":false,"family":"Duberstein","given":"Jamie A.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":568612,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cormier, Nicole 0000-0003-2453-9900 cormiern@usgs.gov","orcid":"https://orcid.org/0000-0003-2453-9900","contributorId":4262,"corporation":false,"usgs":true,"family":"Cormier","given":"Nicole","email":"cormiern@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":568613,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Young, Hillary S.","contributorId":53711,"corporation":false,"usgs":false,"family":"Young","given":"Hillary","email":"","middleInitial":"S.","affiliations":[{"id":13007,"text":"Department of Ecology, Evolution and Marine Biology, University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":568614,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hathaway, Stacie A. 0000-0002-4167-8059 sahathaway@usgs.gov","orcid":"https://orcid.org/0000-0002-4167-8059","contributorId":3420,"corporation":false,"usgs":true,"family":"Hathaway","given":"Stacie","email":"sahathaway@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":568615,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70140273,"text":"70140273 - 2015 - Structural equation modeling: Building and evaluating causal models","interactions":[],"lastModifiedDate":"2022-12-06T23:58:27.684537","indexId":"70140273","displayToPublicDate":"2015-01-29T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"8","title":"Structural equation modeling: Building and evaluating causal models","docAbstract":"Scientists frequently wish to study hypotheses about causal relationships, rather than just statistical associations. This chapter addresses the question of how scientists might approach this ambitious task. Here we describe structural equation modeling (SEM), a general modeling framework for the study of causal hypotheses. Our goals are to (a) concisely describe the methodology, (b) illustrate its utility for investigating ecological systems, and (c) provide guidance for its application. Throughout our presentation, we rely on a study of the effects of human activities on wetland ecosystems to make our description of methodology more tangible. We begin by presenting the fundamental principles of SEM, including both its distinguishing characteristics and the requirements for modeling hypotheses about causal networks. We then illustrate SEM procedures and offer guidelines for conducting SEM analyses. Our focus in this presentation is on basic modeling objectives and core techniques. Pointers to additional modeling options are also given.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Ecological statistics: contemporary theory and application","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Oxford University Press","publisherLocation":"Oxford, UK","usgsCitation":"Grace, J.B., Scheiner, S.M., and Schoolmaster, D.R., 2015, Structural equation modeling: Building and evaluating causal models, chap. 8 of Ecological statistics: contemporary theory and application, p. 168-199.","productDescription":"32 p.","startPage":"168","endPage":"199","numberOfPages":"32","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057226","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":298333,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54faddbce4b02419550db6e4","contributors":{"authors":[{"text":"Grace, James B. 0000-0001-6374-4726 gracej@usgs.gov","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":884,"corporation":false,"usgs":true,"family":"Grace","given":"James","email":"gracej@usgs.gov","middleInitial":"B.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":539926,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scheiner, Samuel M.","contributorId":139066,"corporation":false,"usgs":false,"family":"Scheiner","given":"Samuel","email":"","middleInitial":"M.","affiliations":[{"id":12642,"text":"National Science Foundation","active":true,"usgs":false}],"preferred":false,"id":539927,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schoolmaster, Donald R. Jr. 0000-0003-0910-4458 schoolmasterd@usgs.gov","orcid":"https://orcid.org/0000-0003-0910-4458","contributorId":4746,"corporation":false,"usgs":true,"family":"Schoolmaster","given":"Donald","suffix":"Jr.","email":"schoolmasterd@usgs.gov","middleInitial":"R.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":539928,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"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":70139356,"text":"70139356 - 2015 - Value of information in natural resource management: technical developments and application to pink-footed geese","interactions":[],"lastModifiedDate":"2015-01-28T11:45:55","indexId":"70139356","displayToPublicDate":"2015-01-28T11:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Value of information in natural resource management: technical developments and application to pink-footed geese","docAbstract":"The “value of information” (VOI) is a generic term for the increase in value resulting from better information to guide management, or alternatively, the value foregone under uncertainty about the impacts of management (Yokota and Thompson, Medical Decision Making 2004;24: 287). The value of information can be characterized in terms of several metrics, including the expected value of perfect information and the expected value of partial information. We extend the technical framework for the value of information by further developing the relationship between value metrics for partial and perfect information and describing patterns of their performance. We use two different expressions for the expected value of partial information to highlight its relationship to the expected value of perfect information. We also develop the expected value of partial information for hierarchical uncertainties. We highlight patterns in the value of information for the Svalbard population of the pink-footed goose (Anser brachyrhynchus), a population that is subject to uncertainty in both reproduction and survival functions. The framework for valuing information is seen as having widespread potential in resource decision making, and serves as a motivation for resource monitoring, assessment, and collaboration.
","language":"English","publisher":"John Wiley & Sons Ltd.","doi":"10.1002/ece3.1363","usgsCitation":"Williams, B.K., and Johnson, F.A., 2015, Value of information in natural resource management: technical developments and application to pink-footed geese: Ecology and Evolution, v. 5, no. 2, p. 466-474, https://doi.org/10.1002/ece3.1363.","productDescription":"9 p.","startPage":"466","endPage":"474","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-050684","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":472319,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.1363","text":"Publisher Index Page"},{"id":297597,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Norway","otherGeospatial":"Svalbard","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 7.8662109375,\n 76.1744979490871\n ],\n [\n 7.8662109375,\n 81.1203884020757\n ],\n [\n 31.728515624999996,\n 81.1203884020757\n ],\n [\n 31.728515624999996,\n 76.1744979490871\n ],\n [\n 7.8662109375,\n 76.1744979490871\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"5","issue":"2","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-01-04","publicationStatus":"PW","scienceBaseUri":"54dd2ac8e4b08de9379b3202","chorus":{"doi":"10.1002/ece3.1363","url":"http://dx.doi.org/10.1002/ece3.1363","publisher":"Wiley-Blackwell","authors":"Williams Byron K., Johnson Fred A.","journalName":"Ecology and Evolution","publicationDate":"1/2015"},"contributors":{"authors":[{"text":"Williams, Byron K. 0000-0001-7644-1396","orcid":"https://orcid.org/0000-0001-7644-1396","contributorId":86616,"corporation":false,"usgs":true,"family":"Williams","given":"Byron","email":"","middleInitial":"K.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":false,"id":539320,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Fred A. 0000-0002-5854-3695 fjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-5854-3695","contributorId":2773,"corporation":false,"usgs":true,"family":"Johnson","given":"Fred","email":"fjohnson@usgs.gov","middleInitial":"A.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":539319,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70139461,"text":"70139461 - 2015 - The effect of pressurized magma chamber growth on melt migration and pre-caldera vent locations through time at Mount Mazama, Crater Lake, Oregon","interactions":[],"lastModifiedDate":"2018-10-24T09:08:08","indexId":"70139461","displayToPublicDate":"2015-01-28T10:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"The effect of pressurized magma chamber growth on melt migration and pre-caldera vent locations through time at Mount Mazama, Crater Lake, Oregon","docAbstract":"The pattern of eruptions at long-lived volcanic centers provides a window into the co-evolution of crustal magma transport, tectonic stresses, and unsteady magma generation at depth. Mount Mazama in the Oregon Cascades has seen variable activity over the last 400 ky, including the 50 km3 climactic eruption at ca. 7.7 ka that produced Crater Lake caldera. The physical mechanisms responsible for the assembly of silicic magma reservoirs that are the precursors to caldera-forming eruptions are poorly understood. Here we argue that the spatial and temporal distribution of geographically clustered volcanic vents near Mazama reflects the development of a centralized magma chamber that fed the climactic eruption. Time-averaged eruption rates at Mount Mazama imply an order of magnitude increase in deep magma influx prior to the caldera-forming event, suggesting that unsteady mantle melting triggered a chamber growth episode that culminated in caldera formation. We model magma chamber–dike interactions over ∼50 ky preceding the climactic eruption to fit the observed distribution of surface eruptive vents in space and time, as well as petrologically estimated deep influx rates. Best fitting models predict an expanding zone of dike capture caused by a growing, oblate spheroidal magma chamber with 10–30 MPa of overpressure. This growing zone of chamber influence causes closest approaching regional mafic vent locations as well as more compositionally evolved Mazama eruptions to migrate away from the climactic eruptive center, returning as observed to the center after the chamber drains during the caldera-forming eruption.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2014.12.001","usgsCitation":"Karlstrom, L., Wright, H.M., and Bacon, C.R., 2015, The effect of pressurized magma chamber growth on melt migration and pre-caldera vent locations through time at Mount Mazama, Crater Lake, Oregon: Earth and Planetary Science Letters, v. 412, p. 209-219, https://doi.org/10.1016/j.epsl.2014.12.001.","productDescription":"11 p.","startPage":"209","endPage":"219","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053451","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":297594,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Cascades, Crater Lake, Mount Mazama","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.33276367187499,\n 42.754071181010865\n ],\n [\n -122.33276367187499,\n 43.069891000631294\n ],\n [\n -121.82052612304688,\n 43.069891000631294\n ],\n [\n -121.82052612304688,\n 42.754071181010865\n ],\n [\n -122.33276367187499,\n 42.754071181010865\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"412","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2abfe4b08de9379b31cc","contributors":{"authors":[{"text":"Karlstrom, Leif","contributorId":23048,"corporation":false,"usgs":false,"family":"Karlstrom","given":"Leif","affiliations":[],"preferred":false,"id":539417,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wright, Heather M. 0000-0001-9013-507X hwright@usgs.gov","orcid":"https://orcid.org/0000-0001-9013-507X","contributorId":3949,"corporation":false,"usgs":true,"family":"Wright","given":"Heather","email":"hwright@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":539416,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bacon, Charles R. 0000-0002-2165-5618 cbacon@usgs.gov","orcid":"https://orcid.org/0000-0002-2165-5618","contributorId":2909,"corporation":false,"usgs":true,"family":"Bacon","given":"Charles","email":"cbacon@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":539418,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70138820,"text":"fs20153008 - 2015 - Flood-inundation mapping for the Blue River and selected tributaries in Kansas City, Missouri, and vicinity, 2012","interactions":[],"lastModifiedDate":"2015-01-28T09:48:59","indexId":"fs20153008","displayToPublicDate":"2015-01-28T09:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-3008","title":"Flood-inundation mapping for the Blue River and selected tributaries in Kansas City, Missouri, and vicinity, 2012","docAbstract":"Kansas City, Missouri, has severely flooded many times, most notably in 1951, 1961, 1977, 1984, 1990, 1998, and 2010. During the past 30 years these floods resulted in damages within Kansas City costing tens of millions of dollars and more than 25 casualties.
\nThe U.S. Geological Survey (USGS) and City of Kansas City, Missouri, operate multiple streamgages along the Blue River and tributaries in and near the city. Knowledge of water level at a streamgage is difficult to translate into depth and areal extent of flooding at points distant from the streamgage. One way to address these informational gaps is to produce a library of flood-inundation maps that are referenced to the stages recorded at a streamgage. By referring to the appropriate map, emergency responders can discern the severity of flooding (depth of water and areal extent), identify roads that are or may be flooded, and make plans for notification or evacuation of residents in harm’s way for some distance upstream and downstream from the streamgage. The USGS, in cooperation with the city of Kansas City, Missouri, developed a library of flood-inundation maps for the Blue River and selected tributaries.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153008","usgsCitation":"Heimann, D.C., Weilert, T.E., Kelly, B.P., and Studley, S.E., 2015, Flood-inundation mapping for the Blue River and selected tributaries in Kansas City, Missouri, and vicinity, 2012: U.S. Geological Survey Fact Sheet 2015-3008, 4 p., https://doi.org/10.3133/fs20153008.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-060253","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":297592,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20153008.jpg"},{"id":297591,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3008/pdf/fs2015_3008.pdf","text":"Report","size":"5.47 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297590,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2015/3008/"}],"projection":"Web Mercator projection","datum":"North American Datum of 1983","country":"United States","state":"Missouri","city":"Kansas City","otherGeospatial":"Blue River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.75364685058594,\n 38.78406349514289\n ],\n [\n -94.75364685058594,\n 39.184368717303144\n ],\n [\n -94.42955017089844,\n 39.184368717303144\n ],\n [\n -94.42955017089844,\n 38.78406349514289\n ],\n [\n -94.75364685058594,\n 38.78406349514289\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a77e4b08de9379b3084","contributors":{"authors":[{"text":"Heimann, David C. 0000-0003-0450-2545 dheimann@usgs.gov","orcid":"https://orcid.org/0000-0003-0450-2545","contributorId":3822,"corporation":false,"usgs":true,"family":"Heimann","given":"David","email":"dheimann@usgs.gov","middleInitial":"C.","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539381,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weilert, Trina E.","contributorId":138563,"corporation":false,"usgs":false,"family":"Weilert","given":"Trina","email":"","middleInitial":"E.","affiliations":[{"id":5108,"text":"U.S. Department of Agriculture Forest Service, Rocky Mountain Research Station, Missoula, Montana 59","active":true,"usgs":false}],"preferred":false,"id":539420,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelly, Brian P. 0000-0001-6378-2837 bkelly@usgs.gov","orcid":"https://orcid.org/0000-0001-6378-2837","contributorId":897,"corporation":false,"usgs":true,"family":"Kelly","given":"Brian","email":"bkelly@usgs.gov","middleInitial":"P.","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":539421,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":539422,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}