The sources of terrestrial material delivered to the California margin over the past 7 Myr were assessed using 187Os/188Os, Nd, and Pb isotopes in hydrogenetic ferromanganese crusts from three seamounts along the central and southern California margin. From 6.8 to 4.5 (± 0.5) Ma, all three isotope systems show more radiogenic values at Davidson Seamount, located near the base of the Monterey Canyon System, than in Fe-Mn crusts from the more remote Taney and Hoss seamounts. At the Taney seamounts, approximately 225 km farther offshore from Davidson Seamount, 187Os/188Os values, but not Pb and Nd isotope ratios, also deviate from the Cenozoic seawater curve towards more radiogenic values from 6.8 to 4.5 (± 0.5) Ma. However, none of the isotope systems in Fe-Mn crusts deviate from seawater at Hoss Seamount located approximately 450 km to the south. The regional gradients in isotope ratios indicate that substantial input of dissolved and particulate terrestrial material into the Monterey Canyon System is responsible for the local deviations in the seawater Nd, Pb, and Os isotope compositions from 6.8 to 4.5 (± 0.5) Ma. The isotope ratios recorded in Fe-Mn crusts are consistent with a southern Sierra Nevada or western Basin and Range provenance of the terrestrial material which was delivered by rivers to the canyon. The exhumation of the modern Monterey Canyon must have begun between 10 and 6.8 ± 0.5 Ma, as indicated by our data, the age of incised strata, and paleo-location of the Monterey Canyon relative to the paleo-coastline.
","language":"English","publisher":"AGU","doi":"10.1002/2017GC007071","usgsCitation":"Conrad, T., Nielsen, S., Peucker-Ehrenbrink, B., Blusztajn, J., Winslow, D., Hein, J.R., and Paytan, A., 2017, Reconstructing the evolution of the submarine Monterey Canyon System from Os, Nd, and Pb isotopes in hydrogenetic Fe-Mn crusts: Geochemistry, Geophysics, Geosystems, v. 18, no. 11, p. 3946-3963, https://doi.org/10.1002/2017GC007071.","productDescription":"18 p.","startPage":"3946","endPage":"3963","ipdsId":"IP-088314","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469412,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/2017gc007071","text":"External Repository"},{"id":347291,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -126,\n 31\n ],\n [\n -114,\n 31\n ],\n [\n -114,\n 40\n ],\n [\n -126,\n 40\n ],\n [\n -126,\n 31\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"18","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-15","publicationStatus":"PW","scienceBaseUri":"59f0511fe4b0220bbd9a1d71","contributors":{"authors":[{"text":"Conrad, T.A.","contributorId":21791,"corporation":false,"usgs":true,"family":"Conrad","given":"T.A.","email":"","affiliations":[],"preferred":false,"id":713902,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nielsen, S.G.","contributorId":49171,"corporation":false,"usgs":true,"family":"Nielsen","given":"S.G.","email":"","affiliations":[],"preferred":false,"id":713903,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peucker-Ehrenbrink, Bernhard 0000-0002-3819-992X","orcid":"https://orcid.org/0000-0002-3819-992X","contributorId":78657,"corporation":false,"usgs":true,"family":"Peucker-Ehrenbrink","given":"Bernhard","email":"","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":713904,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blusztajn, J.","contributorId":16639,"corporation":false,"usgs":true,"family":"Blusztajn","given":"J.","email":"","affiliations":[],"preferred":false,"id":713905,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Winslow, D.","contributorId":197613,"corporation":false,"usgs":false,"family":"Winslow","given":"D.","email":"","affiliations":[],"preferred":false,"id":713906,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hein, James R. 0000-0002-5321-899X jhein@usgs.gov","orcid":"https://orcid.org/0000-0002-5321-899X","contributorId":140835,"corporation":false,"usgs":true,"family":"Hein","given":"James","email":"jhein@usgs.gov","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":713901,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Paytan, A.","contributorId":98926,"corporation":false,"usgs":true,"family":"Paytan","given":"A.","affiliations":[],"preferred":false,"id":713907,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70192024,"text":"70192024 - 2017 - HERA: A dynamic web application for visualizing community exposure to flood hazards based on storm and sea level rise scenarios","interactions":[],"lastModifiedDate":"2017-10-24T16:24:55","indexId":"70192024","displayToPublicDate":"2017-10-24T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1315,"text":"Computers & Geosciences","printIssn":"0098-3004","active":true,"publicationSubtype":{"id":10}},"title":"HERA: A dynamic web application for visualizing community exposure to flood hazards based on storm and sea level rise scenarios","docAbstract":"The Hazard Exposure Reporting and Analytics (HERA) dynamic web application was created to provide a platform that makes research on community exposure to coastal-flooding hazards influenced by sea level rise accessible to planners, decision makers, and the public in a manner that is both easy to use and easily accessible. HERA allows users to (a) choose flood-hazard scenarios based on sea level rise and storm assumptions, (b) appreciate the modeling uncertainty behind a chosen hazard zone, (c) select one or several communities to examine exposure, (d) select the category of population or societal asset, and (e) choose how to look at results. The application is designed to highlight comparisons between (a) varying levels of sea level rise and coastal storms, (b) communities, (c) societal asset categories, and (d) spatial scales. Through a combination of spatial and graphical visualizations, HERA aims to help individuals and organizations to craft more informed mitigation and adaptation strategies for climate-driven coastal hazards. This paper summarizes the technologies used to maximize the user experience, in terms of interface design, visualization approaches, and data processing.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.cageo.2017.08.012","usgsCitation":"Jones, J.M., Henry, K., Wood, N.J., Ng, P., and Jamieson, M., 2017, HERA: A dynamic web application for visualizing community exposure to flood hazards based on storm and sea level rise scenarios: Computers & Geosciences, v. 109, p. 124-133, https://doi.org/10.1016/j.cageo.2017.08.012.","productDescription":"8 p.","startPage":"124","endPage":"133","ipdsId":"IP-085912","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":469405,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.cageo.2017.08.012","text":"Publisher Index Page"},{"id":347292,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"109","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f0511fe4b0220bbd9a1d73","contributors":{"authors":[{"text":"Jones, Jeanne M. 0000-0001-7549-9270 jmjones@usgs.gov","orcid":"https://orcid.org/0000-0001-7549-9270","contributorId":4676,"corporation":false,"usgs":true,"family":"Jones","given":"Jeanne","email":"jmjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":713858,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Henry, Kevin 0000-0001-9314-2531 khenry@usgs.gov","orcid":"https://orcid.org/0000-0001-9314-2531","contributorId":176934,"corporation":false,"usgs":true,"family":"Henry","given":"Kevin","email":"khenry@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":713859,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wood, Nathan J. 0000-0002-6060-9729 nwood@usgs.gov","orcid":"https://orcid.org/0000-0002-6060-9729","contributorId":3347,"corporation":false,"usgs":true,"family":"Wood","given":"Nathan","email":"nwood@usgs.gov","middleInitial":"J.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":713860,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ng, Peter 0000-0001-8509-5544 png@usgs.gov","orcid":"https://orcid.org/0000-0001-8509-5544","contributorId":3317,"corporation":false,"usgs":true,"family":"Ng","given":"Peter","email":"png@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":713861,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jamieson, Matthew 0000-0002-9371-9182","orcid":"https://orcid.org/0000-0002-9371-9182","contributorId":197590,"corporation":false,"usgs":false,"family":"Jamieson","given":"Matthew","affiliations":[],"preferred":false,"id":713862,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70192110,"text":"70192110 - 2017 - Micronuclei and other erythrocyte nuclear abnormalities in fishes from the Great Lakes Basin, USA","interactions":[],"lastModifiedDate":"2017-10-23T15:28:18","indexId":"70192110","displayToPublicDate":"2017-10-23T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5524,"text":"Environmental and Molecular Mutagenesis","active":true,"publicationSubtype":{"id":10}},"title":"Micronuclei and other erythrocyte nuclear abnormalities in fishes from the Great Lakes Basin, USA","docAbstract":"Biological markers (biomarkers) sensitive to genotoxic and mutagenic contamination in fishes are widely used to identify exposure effects in aquatic environments. The micronucleus assay was incorporated into a suite of indicators to assess exposure to genotoxic and mutagenic contamination at five Great Lakes Areas of Concern (AOCs), as well as one non-AOC (reference) site. The assay allowed enumeration of micronuclei as well as other nuclear abnormalities for both site and species comparisons. Erythrocyte abnormality data was also compared to skin and liver tumor prevalence and hepatic transcript abundance. Erythrocyte abnormalities were observed at all sites with variable occurrence and severity among sites and species. Benthic-oriented brown bullhead (Ameiurus nebulosus) and white sucker (Catostomus commersonii) expressed lower rates of erythrocyte abnormalities, but higher rates of skin and liver neoplasms, when compared to pelagic-oriented largemouth bass (Micropterus salmoides) or smallmouth bass (Micropterus dolomieu) at the same site. The reduced erythrocyte abnormalities, increased transcript abundance associated with Phase I and II toxicant responsive pathways, and increased neoplastic lesions among benthic-oriented taxa may indicate the development of contaminant resistance of these species to more acute effects.
","language":"English","publisher":"Wiley","doi":"10.1002/em.22123","usgsCitation":"Braham, R.P., Blazer, V., Shaw, C., and Mazik, P.M., 2017, Micronuclei and other erythrocyte nuclear abnormalities in fishes from the Great Lakes Basin, USA: Environmental and Molecular Mutagenesis, v. 58, no. 8, p. 570-581, https://doi.org/10.1002/em.22123.","productDescription":"12 p.","startPage":"570","endPage":"581","ipdsId":"IP-084355","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":469418,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/em.22123","text":"Publisher Index Page"},{"id":347159,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.2958984375,\n 41.44272637767212\n ],\n [\n -76.2451171875,\n 41.44272637767212\n ],\n [\n -76.2451171875,\n 47.69497434186282\n ],\n [\n -93.2958984375,\n 47.69497434186282\n ],\n [\n -93.2958984375,\n 41.44272637767212\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"58","issue":"8","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-04","publicationStatus":"PW","scienceBaseUri":"59eeffa3e4b0220bbd988f61","contributors":{"authors":[{"text":"Braham, Ryan P. 0000-0002-2102-0989","orcid":"https://orcid.org/0000-0002-2102-0989","contributorId":197772,"corporation":false,"usgs":false,"family":"Braham","given":"Ryan","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":714274,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blazer, Vicki S. 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":150384,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":714273,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shaw, Cassidy H. 0000-0003-2639-1241","orcid":"https://orcid.org/0000-0003-2639-1241","contributorId":197773,"corporation":false,"usgs":true,"family":"Shaw","given":"Cassidy H.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":714275,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mazik, Patricia M. 0000-0002-8046-5929 pmazik@usgs.gov","orcid":"https://orcid.org/0000-0002-8046-5929","contributorId":2318,"corporation":false,"usgs":true,"family":"Mazik","given":"Patricia","email":"pmazik@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":714276,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70192212,"text":"70192212 - 2017 - Seasonality of stable isotope composition of atmospheric water input at the southern slopes of Mt. Kilimanjaro, Tanzania","interactions":[],"lastModifiedDate":"2017-10-23T13:30:53","indexId":"70192212","displayToPublicDate":"2017-10-23T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Seasonality of stable isotope composition of atmospheric water input at the southern slopes of Mt. Kilimanjaro, Tanzania","docAbstract":"To understand the moisture regime at the southern slopes of Mt. Kilimanjaro, we analysed the isotopic variability of oxygen (δ18O) and hydrogen (δD) of rainfall, throughfall, and fog from a total of 2,140 samples collected weekly over 2 years at 9 study sites along an elevation transect ranging from 950 to 3,880 m above sea level. Precipitation in the Kilimanjaro tropical rainforests consists of a combination of rainfall, throughfall, and fog. We defined local meteoric water lines for all 3 precipitation types individually and the overall precipitation, δDprec = 7.45 (±0.05) × δ18Oprec + 13.61 (±0.20), n = 2,140, R2 = .91, p < .001. We investigated the precipitation-type-specific stable isotope composition and analysed the effects of amount, altitude, and temperature. Aggregated annual mean values revealed isotope composition of rainfall as most depleted and fog water as most enriched in heavy isotopes at the highest elevation research site. We found an altitude effect of δ18Orain = −0.11‰ × 100 m−1, which varied according to precipitation type and season. The relatively weak isotope or altitude gradient may reveal 2 different moisture sources in the research area: (a) local moisture recycling and (b) regional moisture sources. Generally, the seasonality of δ18Orain values follows the bimodal rainfall distribution under the influences of south- and north-easterly trade winds. These seasonal patterns of isotopic composition were linked to different regional moisture sources by analysing Hybrid Single Particle Lagrangian Integrated Trajectory backward trajectories. Seasonality of dexcess values revealed evidence of enhanced moisture recycling after the onset of the rainy seasons. This comprehensive dataset is essential for further research using stable isotopes as a hydrological tracer of sources of precipitation that contribute to water resources of the Kilimanjaro region.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.11311","usgsCitation":"Otte, I., Detsch, F., Gutlein, A., Scholl, M.A., Kiese, R., Appelhans, T., and Nauss, T., 2017, Seasonality of stable isotope composition of atmospheric water input at the southern slopes of Mt. Kilimanjaro, Tanzania: Hydrological Processes, v. 31, no. 22, p. 3932-3947, https://doi.org/10.1002/hyp.11311.","productDescription":"16 p.","startPage":"3932","endPage":"3947","ipdsId":"IP-089904","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":469417,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.11311","text":"Publisher Index Page"},{"id":347122,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Tanzania","otherGeospatial":"Mt. Kilimanjaro","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 37.14202880859375,\n -3.2412964891479614\n ],\n [\n 37.57530212402344,\n -3.2412964891479614\n ],\n [\n 37.57530212402344,\n -2.956069891317356\n ],\n [\n 37.14202880859375,\n -2.956069891317356\n ],\n [\n 37.14202880859375,\n -3.2412964891479614\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"31","issue":"22","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-15","publicationStatus":"PW","scienceBaseUri":"59eeffa0e4b0220bbd988f4d","contributors":{"authors":[{"text":"Otte, Insa","contributorId":198023,"corporation":false,"usgs":false,"family":"Otte","given":"Insa","email":"","affiliations":[],"preferred":false,"id":714826,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Detsch, Florian","contributorId":198024,"corporation":false,"usgs":false,"family":"Detsch","given":"Florian","email":"","affiliations":[],"preferred":false,"id":714827,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gutlein, Adrian","contributorId":198025,"corporation":false,"usgs":false,"family":"Gutlein","given":"Adrian","email":"","affiliations":[],"preferred":false,"id":714828,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Scholl, Martha A. 0000-0001-6994-4614 mascholl@usgs.gov","orcid":"https://orcid.org/0000-0001-6994-4614","contributorId":1920,"corporation":false,"usgs":true,"family":"Scholl","given":"Martha","email":"mascholl@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":714825,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kiese, Ralf","contributorId":198026,"corporation":false,"usgs":false,"family":"Kiese","given":"Ralf","email":"","affiliations":[],"preferred":false,"id":714829,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Appelhans, Tim","contributorId":198027,"corporation":false,"usgs":false,"family":"Appelhans","given":"Tim","email":"","affiliations":[],"preferred":false,"id":714830,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nauss, Thomas","contributorId":198028,"corporation":false,"usgs":false,"family":"Nauss","given":"Thomas","email":"","affiliations":[],"preferred":false,"id":714831,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70191807,"text":"sir20175097 - 2017 - Simulation of groundwater and surface-water flow in the upper Deschutes Basin, Oregon","interactions":[],"lastModifiedDate":"2017-10-23T11:30:00","indexId":"sir20175097","displayToPublicDate":"2017-10-20T00:00:00","publicationYear":"2017","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":"2017-5097","title":"Simulation of groundwater and surface-water flow in the upper Deschutes Basin, Oregon","docAbstract":"This report describes a hydrologic model for the upper Deschutes Basin in central Oregon developed using the U.S. Geological Survey (USGS) integrated Groundwater and Surface-Water Flow model (GSFLOW). The upper Deschutes Basin, which drains much of the eastern side of the Cascade Range in Oregon, is underlain by large areas of permeable volcanic rock. That permeability, in combination with the large annual precipitation at high elevations, results in a substantial regional aquifer system and a stream system that is heavily groundwater dominated.
The upper Deschutes Basin is also an area of expanding population and increasing water demand for public supply and agriculture. Surface water was largely developed for agricultural use by the mid-20th century, and is closed to additional appropriations. Consequently, water users look to groundwater to satisfy the growing demand. The well‑documented connection between groundwater and the stream system, and the institutional and legal restrictions on streamflow depletion by wells, resulted in the Oregon Water Resources Department (OWRD) instituting a process whereby additional groundwater pumping can be permitted only if the effects to streams are mitigated, for example, by reducing permitted surface-water diversions. Implementing such a program requires understanding of the spatial and temporal distribution of effects to streams from groundwater pumping. A groundwater model developed in the early 2000s by the USGS and OWRD has been used to provide insights into the distribution of streamflow depletion by wells, but lacks spatial resolution in sensitive headwaters and spring areas.
The integrated model developed for this project, based largely on the earlier model, has a much finer grid spacing allowing resolution of sensitive headwater streams and important spring areas, and simulates a more complete set of surface processes as well as runoff and groundwater flow. In addition, the integrated model includes improved representation of subsurface geology and explicitly simulates the effects of hydrologically important fault zones not included in the previous model.
The upper Deschutes Basin GSFLOW model was calibrated using an iterative trial and error approach using measured water-level elevations (water levels) from 800 wells, 144 of which have time series of 10 or more measurements. Streamflow was calibrated using data from 21 gage locations. At 14 locations where measured flows are heavily influenced by reservoir operations and irrigation diversions, so called “naturalized” flows, with the effects of reservoirs and diversion removed, developed by the Bureau of Reclamation, were used for calibration. Surface energy and moisture processes such as solar radiation, snow accumulation and melting, and evapotranspiration were calibrated using national datasets as well as data from long-term measurement sites in the basin. The calibrated Deschutes GSFLOW model requires daily precipitation, minimum and maximum air temperature data, and monthly data describing groundwater pumping and artificial recharge from leaking irrigation canals (which are a significant source of groundwater recharge).
The calibrated model simulates the geographic distribution of hydraulic head over the 5,000 ft range measured in the basin, with a median absolute residual of about 53 ft. Temporal variations in head resulting from climate cycles, pumping, and canal leakage are well simulated over the model area. Simulated daily streamflow matches gaged flows or calculated naturalized flows for streams including the Crooked and Metolius Rivers, and lower parts of the mainstem Deschutes River. Seasonal patterns of runoff are less well fit in some upper basin streams. Annual water balances of streamflow are good over most of the model domain. Model fit and overall capabilities are appropriate for the objectives of the project.
The integrated model results confirm findings from other studies and models indicating that most streamflow in the upper Deschutes Basin comes directly from groundwater discharge. The integrated model provides additional insights about the components of streamflow including direct groundwater discharge to streams, interflow, groundwater discharge to the land surface (Dunnian flow), and direct runoff (Hortonian flow). The new model provides improved capability for exploring the timing and distribution of
streamflow capture by wells, and the hydrologic response to changes in other external stresses such as canal operation, irrigation, and drought. Because the model uses basic meteorological data as the primary input; and simulates surface energy and moisture balances, groundwater recharge and flow, and all components of streamflow; it is well suited for exploring the hydrologic response to climate change, although no such simulations are included in this report.
The model was developed as a tool for future application; however, example simulations are provided in this report. In the example simulations, the model is used to explore the influence of well location and geologic structure on stream capture by pumping wells. Wells were simulated at three locations within a 12-mi area close to known groundwater discharge areas and crossed by a regional fault zone. Simulations indicate that the magnitude and timing of stream capture from pumping is largely controlled by the geographic location of the wells, but that faults can have a large influence on the propagation of pumping stresses.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175097","collaboration":"Prepared in cooperation with the Oregon Water Resources Department","usgsCitation":"Gannett, M.W., Lite, K.E., Jr., Risley, J.C., Pischel, E.M., and La Marche, J.L., 2017, Simulation of groundwater and surface-water flow in the upper Deschutes Basin, Oregon: U.S. Geological Survey Scientific Investigations Report 2017-5097, 68 p., https://doi.org/10.3133/sir20175097.","productDescription":"Report: viii, 68 p.; Model Archive","numberOfPages":"80","onlineOnly":"Y","ipdsId":"IP-085102","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":347011,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://doi.org/10.5066/F7154F9K","text":"Model Archive","description":"SIR 2017-5097 Model Archive"},{"id":346984,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5097/coverthb.jpg"},{"id":346985,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5097/sir20175097.pdf","text":"Report","size":"5.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5097"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Deschutes Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.19268798828126,\n 43.395069512861355\n ],\n [\n -120.7452392578125,\n 43.395069512861355\n ],\n [\n -120.7452392578125,\n 44.939529212272305\n ],\n [\n -122.19268798828126,\n 44.939529212272305\n ],\n [\n -122.19268798828126,\n 43.395069512861355\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
The Southern Great Plains Rapid Ecoregional Assessment was conducted in partnership with the Bureau of Land Management (BLM) and the Great Plains Landscape Conservation Cooperative. The overall goal of the Rapid Ecoregional Assessments (REAs) is to compile and synthesize regional datasets to facilitate evaluation of the cumulative effects of change agents on priority ecological communities and species. In particular, the REAs identify and map the distribution of communities and wildlife habitats at broad spatial extents and provide assessments of ecological conditions. The REAs also identify where and to what degree ecological resources are currently at risk from change agents, such as development, fire, invasive species, and climate change. The REAs can help managers identify and prioritize potential areas for conservation or restoration, assess cumulative effects as required by the National Environmental Policy Act, and inform landscape-level planning and management decisions for multiple uses of public lands.
Management questions form the basis for the REA framework and were developed in conjunction with the BLM and other stakeholders. Conservation elements are communities and species that are of regional management concern. Core management questions relate to the key ecological attributes and change agents associated with each conservation element. Integrated management questions synthesize the results of the primary core management questions into overall landscape-level ranks for each conservation element.
The ecological communities evaluated as conservation elements are shortgrass, mixed-grass, and sand prairies; all grasslands; riparian and nonplaya wetlands; playa wetlands and saline lakes; and prairie streams and rivers. Species and species assemblages evaluated are the freshwater mussel assemblage, Arkansas River shiner (Notropis girardi), ferruginous hawk (Buteo regalis), lesser prairie chicken (Tympanuchus pallidicinctus), snowy plover (Charadrius nivosus), mountain plover (Charadrius montanus), long-billed curlew (Numenius americanus), interior least tern (Sternula antillarum athalassos), burrowing owl (Athene cunicularia hypugaea), black-tailed prairie dog (Cynomys ludovicianus), bat assemblage, swift fox (Vulpes velox), and mule deer (Odocoileus hemionus).
The Southern Great Plains REA is summarized in a series of three reports and associated datasets. The pre-assessment report (available online at https://pubs.usgs.gov/of/2015/1003/) summarizes the process used by the REA stakeholders to select management questions, conservation elements, and change agents. It also provides background information for each conservation element. Volume I of the Southern Great Plains REA report (this volume) addresses the ecological communities. Volume II will address the species and species assemblages. All source and derived datasets used to produce the maps and graphs for REAs are available online at the BLM Landscape Approach Data Portal (https://landscape.blm.gov/geoportal/catalog/REAs/REAs.page).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171100","collaboration":"Prepared in cooperation with the Bureau of Land Management and the Great Plains Landscape Conservation Cooperative","usgsCitation":"Reese, G.C., Burris, Lucy, Carr, N.B., Leinwand, I.I.F., and Melcher, C.P., 2017, Southern Great Plains Rapid Ecoregional assessment—Volume I. Ecological communities: U.S. Geological Survey Open-File Report 2017–1100, 126 p., https://doi.org/10.3133/ofr20171100.","productDescription":"xiii, 126 p.","numberOfPages":"144","onlineOnly":"N","ipdsId":"IP-080929","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":346770,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1100/coverthb.jpg"},{"id":346771,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1100/ofr20171100.pdf","text":"Report","size":"15.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1100"}],"country":"United States","state":"Colorado, Kansas, Nebraska, New Mexico, Oklahoma, Texas, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.14990234375,\n 30.939924331023445\n ],\n [\n -96.2841796875,\n 30.939924331023445\n ],\n [\n -96.2841796875,\n 43.08493742707592\n ],\n [\n -106.14990234375,\n 43.08493742707592\n ],\n [\n -106.14990234375,\n 30.939924331023445\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Fort Collins Science Center
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Temporal symmetry models (TSM) represent advances in the analytical application of mark–recapture data to population status assessments. For a population of char, we employed 10 years of active and passive mark–recapture data to quantify population growth rates using different data sources and analytical approaches. Estimates of adult population growth rate were 1.01 (95% confidence interval = 0.84–1.20) using a temporal symmetry model (λTSM), 0.96 (0.68–1.34) based on logistic regressions of annual snorkel data (λA), and 0.92 (0.77–1.11) from redd counts (λR). Top-performing TSMs included an increasing time trend in recruitment (f) and changes in capture probability (p). There was only a 1% chance the population decreased ≥50%, and a 10% chance it decreased ≥30% (λMCMC; based on Bayesian Markov chain Monte Carlo procedure). Size structure was stable; however, the adult population was dominated by small adults, and over the study period there was a decline in the contribution of large adults to total biomass. Juvenile condition decreased with increasing adult densities. Utilization of these different information sources provided a robust weight-of-evidence approach to identifying population status and potential mechanisms driving changes in population growth rates.
","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2016-0336","usgsCitation":"Budy, P., Bowerman, T., Al-Chokhachy, R.K., Conner, M., and Schaller, H., 2017, Quantifying long-term population growth rates of threatened bull trout: challenges, lessons learned, and opportunities: Canadian Journal of Fisheries and Aquatic Sciences, v. 74, no. 12, p. 2131-2143, https://doi.org/10.1139/cjfas-2016-0336.","productDescription":"13 p.","startPage":"2131","endPage":"2143","ipdsId":"IP-066765","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":346991,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"South Fork Walla Walla River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.22250366210938,\n 45.81970781149485\n ],\n [\n -117.9773712158203,\n 45.81970781149485\n ],\n [\n -117.9773712158203,\n 45.8842726860033\n ],\n [\n -118.22250366210938,\n 45.8842726860033\n ],\n [\n -118.22250366210938,\n 45.81970781149485\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"74","issue":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59e9b990e4b05fe04cd65c33","contributors":{"authors":[{"text":"Budy, Phaedra E. 0000-0002-9918-1678 pbudy@usgs.gov","orcid":"https://orcid.org/0000-0002-9918-1678","contributorId":140028,"corporation":false,"usgs":true,"family":"Budy","given":"Phaedra","email":"pbudy@usgs.gov","middleInitial":"E.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":714039,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bowerman, Tracy","contributorId":95796,"corporation":false,"usgs":true,"family":"Bowerman","given":"Tracy","email":"","affiliations":[],"preferred":false,"id":714102,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Al-Chokhachy, Robert K. 0000-0002-2136-5098 ral-chokhachy@usgs.gov","orcid":"https://orcid.org/0000-0002-2136-5098","contributorId":1674,"corporation":false,"usgs":true,"family":"Al-Chokhachy","given":"Robert","email":"ral-chokhachy@usgs.gov","middleInitial":"K.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":714040,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conner, Mary","contributorId":197694,"corporation":false,"usgs":false,"family":"Conner","given":"Mary","affiliations":[],"preferred":false,"id":714103,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schaller, Howard","contributorId":177727,"corporation":false,"usgs":false,"family":"Schaller","given":"Howard","affiliations":[],"preferred":false,"id":714104,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70192018,"text":"70192018 - 2017 - A comparison of four porewater sampling methods for metal mixtures and dissolved organic carbon and the implications for sediment toxicity evaluations","interactions":[],"lastModifiedDate":"2017-11-10T14:11:06","indexId":"70192018","displayToPublicDate":"2017-10-19T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"A comparison of four porewater sampling methods for metal mixtures and dissolved organic carbon and the implications for sediment toxicity evaluations","docAbstract":"Evaluations of sediment quality conditions are commonly conducted using whole-sediment chemistry analyses but can be enhanced by evaluating multiple lines of evidence, including measures of the bioavailable forms of contaminants. In particular, porewater chemistry data provide information that is directly relevant for interpreting sediment toxicity data. Various methods for sampling porewater for trace metals and dissolved organic carbon (DOC), which is an important moderator of metal bioavailability, have been employed. The present study compares the peeper, push point, centrifugation, and diffusive gradients in thin films (DGT) methods for the quantification of 6 metals and DOC. The methods were evaluated at low and high concentrations of metals in 3 sediments having different concentrations of total organic carbon and acid volatile sulfide and different particle-size distributions. At low metal concentrations, centrifugation and push point sampling resulted in up to 100 times higher concentrations of metals and DOC in porewater compared with peepers and DGTs. At elevated metal levels, the measured concentrations were in better agreement among the 4 sampling techniques. The results indicate that there can be marked differences among operationally different porewater sampling methods, and it is unclear if there is a definitive best method for sampling metals and DOC in porewater.
","language":"English","publisher":"Wiley","doi":"10.1002/etc.3884","usgsCitation":"Cleveland, D.M., Brumbaugh, W.G., and MacDonald, D.D., 2017, A comparison of four porewater sampling methods for metal mixtures and dissolved organic carbon and the implications for sediment toxicity evaluations: Environmental Toxicology and Chemistry, v. 36, no. 11, p. 2906-2915, https://doi.org/10.1002/etc.3884.","productDescription":"10 p.","startPage":"2906","endPage":"2915","ipdsId":"IP-085651","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":438184,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7HD7SVS","text":"USGS data release","linkHelpText":"A comparison of four pore water sampling methods for mixed metals and dissolved organic carbon, and implications for toxicity evaluations-Data"},{"id":346950,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"11","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-09","publicationStatus":"PW","scienceBaseUri":"59e9b990e4b05fe04cd65c39","contributors":{"authors":[{"text":"Cleveland, Danielle M. 0000-0003-3880-4584 dcleveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3880-4584","contributorId":187471,"corporation":false,"usgs":true,"family":"Cleveland","given":"Danielle","email":"dcleveland@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":713847,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brumbaugh, William G.","contributorId":187473,"corporation":false,"usgs":false,"family":"Brumbaugh","given":"William","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":713848,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"MacDonald, Donald D.","contributorId":176179,"corporation":false,"usgs":false,"family":"MacDonald","given":"Donald","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":713849,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70188854,"text":"ofr20171073 - 2017 - Design and methods of the Midwest Stream Quality Assessment (MSQA), 2013","interactions":[],"lastModifiedDate":"2017-10-19T09:39:41","indexId":"ofr20171073","displayToPublicDate":"2017-10-18T16:45:00","publicationYear":"2017","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":"2017-1073","title":"Design and methods of the Midwest Stream Quality Assessment (MSQA), 2013","docAbstract":"During 2013, the U.S. Geological Survey (USGS) National Water-Quality Assessment Project (NAWQA), in collaboration with the USGS Columbia Environmental Research Center, the U.S. Environmental Protection Agency (EPA) National Rivers and Streams Assessment (NRSA), and the EPA Office of Pesticide Programs assessed stream quality across the Midwestern United States. This Midwest Stream Quality Assessment (MSQA) simultaneously characterized watershed and stream-reach water-quality stressors along with instream biological conditions, to better understand regional stressor-effects relations. The MSQA design focused on effects from the widespread agriculture in the region and urban development because of their importance as ecological stressors of particular concern to Midwest region resource managers.
A combined random stratified selection and a targeted selection based on land-use data were used to identify and select sites representing gradients in agricultural intensity across the region. During a 14-week period from May through August 2013, 100 sites were selected and sampled 12 times for contaminants, nutrients, and sediment. This 14-week water-quality “index” period culminated with an ecological survey of habitat, periphyton, benthic macroinvertebrates, and fish at all sites. Sediment was collected during the ecological survey for analysis of sediment chemistry and toxicity testing. Of the 100 sites, 50 were selected for the MSQA random stratified group from 154 NRSA sites planned for the region, and the other 50 MSQA sites were selected as targeted sites to more evenly cover agricultural and urban stressor gradients in the study area. Of the 50 targeted sites, 12 were in urbanized watersheds and 21 represented “good” biological conditions or “least disturbed” conditions. The remaining 17 targeted sites were selected to improve coverage of the agricultural intensity gradient or because of historical data collection to provide temporal context for the study.
This report provides a detailed description of the MSQA study components, including surveys of ecological conditions, routine water sampling, deployment of passive polar organic compound integrative samplers, and stream sediment sampling at all sites. Component studies that were completed to provide finer scale temporal data or more extensive analysis at selected sites, included continuous water-quality monitoring, daily pesticide sampling, laboratory and in-stream water toxicity testing efforts, and deployment of passive suspended-sediment samplers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171073","collaboration":"National Water-Quality Program Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Garrett, J.D., Frey, J.W., Van Metre, P.C., Journey, C.A., Nakagaki, Naomi, Button, D.T., and Howell, L.H., 2017, Design and methods of the Midwest Stream Quality Assessment (MSQA), 2013: U.S. Geological Survey Open-File Report 2017–1073, 59 p., 4 app., https://doi.org/10.3133/ofr20171073.","productDescription":"Report: x, 57 p.; 4 Appendixes","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-075316","costCenters":[{"id":451,"text":"National Water Quality Assessment 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Reach, and Watershed Characteristics of Selected Sites Assessed as Part of the U.S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) Midwest Stream Quality Assessment (MSQA) in 2013"},{"id":346661,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2017/1073/ofr20171073_appendix3_SampleCounts.xlsx","text":"Appendix 3","size":"50.5 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix 3","linkHelpText":"- Description of Quality Control Samples"},{"id":346662,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2017/1073/ofr20171073_appendix4_Workplan.xlsx","text":"Appendix 4","size":"27.5 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix 4","linkHelpText":"- Description of the Sampling Timelines, Matrix, Collection, and Processing for Water, Sediment, and Ecological Samples"}],"country":"United States","state":"Illinois, Indiana, Iowa, Kansas, Kentucky, Michigan, Minnesota, Missouri, Nebraska, 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The In-Situ Aqua TROLL 400 (Aqua TROLL 400) was tested at the U.S. Geological Survey (USGS) Hydrologic Instrumentation Facility (HIF) against known standards over the Aqua TROLL 400’s operating temperature to verify the manufacturer’s stated accuracy specifications and the USGS recommendations for pH, dissolved oxygen (DO), and specific conductance (SC). The Aqua TROLL 400 manufacturer’s specifications are within the USGS recommendations for all parameters tested, except for DO, which is outside the USGS recommendation at DO concentrations of 8.0 milligrams per liter (mg/L) and higher. The Aqua TROLL 400 was compliant with Serial Digital Interface at 1200 baud (SDI-12) version 1.3. During laboratory testing of pH, the Aqua TROLL 400 sonde met the U.S. Geological Survey “National Field Manual for the Collection of Water-Quality Data” (NFM) recommendations for pH at all values tested, except at 4 degrees Celsius (°C) at pH 9.395 and pH 3.998. The Aqua TROLL 400 met the manufacturer specifications for pH at all values tested, except for pH buffers 3.998, 9.395, and 10.245 at 4 °C; pH 2.990 and 3.998 at 15 °C; and pH 3.040 at 40 °C. The Aqua TROLL 400 met the NFM recommendations at 93.7 percent of the SC values tested and met the manufacturer’s accuracy specifications at 56.3 percent of the SC values tested. During the laboratory testing for DO, the Aqua TROLL 400 met the manufacturer specifications, except at 5.55 mg/L, and met the NFM recommendations at all concentrations tested. An Aqua TROLL 400 was field tested at USGS Station 02492620, National Space Technology Laboratories (NSTL) Station, Mississippi, on the Pearl River for 6 weeks and showed good agreement with the well-maintained site sonde data for pH, DO, temperature, and SC.
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Stennis Space Center, MS 39529
The U.S. Geological Survey (USGS) Geomagnetism Program has developed and tested the residual method of absolutes, with the assistance of the Danish Technical University's (DTU) Geomagnetism Program. Three years of testing were performed at College Magnetic Observatory (CMO), Fairbanks, Alaska, to compare the residual method with the null method. Results show that the two methods compare very well with each other and both sets of baseline data were used to process the 2015 definitive data. The residual method will be implemented at the other USGS high-latitude geomagnetic observatories in the summer of 2017 and 2018.
","language":"English","publisher":"EGU","doi":"10.5194/gi-6-419-2017","usgsCitation":"Worthington, E.W., and Matzka, J., 2017, U.S. Geological Survey experience with the residual absolutes method: Geoscientific Instrumentation, Methods and Data Systems, v. 6, p. 419-427, https://doi.org/10.5194/gi-6-419-2017.","productDescription":"9 p.","startPage":"419","endPage":"427","ipdsId":"IP-085974","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":469431,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/gi-6-419-2017","text":"Publisher Index Page"},{"id":346870,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-17","publicationStatus":"PW","scienceBaseUri":"59e86830e4b05fe04cd4d1b7","contributors":{"authors":[{"text":"Worthington, E. William 0000-0002-5879-0477 bworth@usgs.gov","orcid":"https://orcid.org/0000-0002-5879-0477","contributorId":2570,"corporation":false,"usgs":true,"family":"Worthington","given":"E.","email":"bworth@usgs.gov","middleInitial":"William","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":713419,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Matzka, Jurgen","contributorId":197403,"corporation":false,"usgs":false,"family":"Matzka","given":"Jurgen","email":"","affiliations":[],"preferred":false,"id":713420,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70191842,"text":"70191842 - 2017 - Ephemeral seafloor sedimentation during dam removal: Elwha River, Washington","interactions":[],"lastModifiedDate":"2017-11-29T16:23:38","indexId":"70191842","displayToPublicDate":"2017-10-18T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1333,"text":"Continental Shelf Research","active":true,"publicationSubtype":{"id":10}},"title":"Ephemeral seafloor sedimentation during dam removal: Elwha River, Washington","docAbstract":"The removal of the Elwha and Glines Canyon dams from the Elwha River in Washington, USA, resulted in the erosion and transport of over 10 million m3 of sediment from the former reservoirs and into the river during the first two years of the dam removal process. Approximately 90% of this sediment was transported through the Elwha River and to the coast at the Strait of Juan de Fuca. To evaluate the benthic dynamics of increased sediment loading to the nearshore, we deployed a tripod system in ten meters of water to the east of the Elwha River mouth that included a profiling current meter and a camera system. With these data, we were able to document the frequency and duration of sedimentation and turbidity events, and correlate these events to physical oceanographic and river conditions. We found that seafloor sedimentation occurred regularly during the heaviest sediment loading from the river, but that this sedimentation was ephemeral and exhibited regular cycles of deposition and erosion caused by the strong tidal currents in the region. Understanding the frequency and duration of short-term sediment disturbance events is instrumental to interpreting the ecosystem-wide changes that are occurring in the nearshore habitats around the Elwha River delta.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.csr.2017.09.005","usgsCitation":"Foley, M.M., and Warrick, J.A., 2017, Ephemeral seafloor sedimentation during dam removal: Elwha River, Washington: Continental Shelf Research, v. 150, p. 36-47, https://doi.org/10.1016/j.csr.2017.09.005.","productDescription":"12 p.","startPage":"36","endPage":"47","ipdsId":"IP-084897","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469424,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.csr.2017.09.005","text":"Publisher Index Page"},{"id":438186,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7CR5RW8","text":"USGS data release","linkHelpText":"Oceanographic measurements obtained offshore of the Elwha River delta in coordination with the Elwha River Restoration Project, Washington, USA, 2010-2014"},{"id":438185,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7MC8XHX","text":"USGS data release","linkHelpText":"Characterization of seafloor photographs near the mouth of the Elwha River during the first two years of dam removal (2011-2013)"},{"id":346906,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Elwha River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.59258651733398,\n 48.13424631889282\n ],\n [\n -123.51722717285155,\n 48.13424631889282\n ],\n [\n -123.51722717285155,\n 48.163566497754275\n ],\n [\n -123.59258651733398,\n 48.163566497754275\n ],\n [\n -123.59258651733398,\n 48.13424631889282\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"150","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59e86831e4b05fe04cd4d1c1","contributors":{"authors":[{"text":"Foley, Melissa M. 0000-0002-5832-6404 mfoley@usgs.gov","orcid":"https://orcid.org/0000-0002-5832-6404","contributorId":4861,"corporation":false,"usgs":true,"family":"Foley","given":"Melissa","email":"mfoley@usgs.gov","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":713356,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Warrick, Jonathan A. 0000-0002-0205-3814 jwarrick@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":167736,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan","email":"jwarrick@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":713357,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70191837,"text":"70191837 - 2017 - Multistressor predictive models of invertebrate condition in the Corn Belt, USA","interactions":[],"lastModifiedDate":"2017-11-29T16:22:43","indexId":"70191837","displayToPublicDate":"2017-10-18T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Multistressor predictive models of invertebrate condition in the Corn Belt, USA","docAbstract":"Understanding the complex relations between multiple environmental stressors and ecological conditions in streams can help guide resource-management decisions. During 14 weeks in spring/summer 2013, personnel from the US Geological Survey and the US Environmental Protection Agency sampled 98 wadeable streams across the Midwest Corn Belt region of the USA for water and sediment quality, physical and habitat characteristics, and ecological communities. We used these data to develop independent predictive disturbance models for 3 macroinvertebrate metrics and a multimetric index. We developed the models based on boosted regression trees (BRT) for 3 stressor categories, land use/land cover (geographic information system [GIS]), all in-stream stressors combined (nutrients, habitat, and contaminants), and for GIS plus in-stream stressors. The GIS plus in-stream stressor models had the best overall performance with an average cross-validation R2 across all models of 0.41. The models were generally consistent in the explanatory variables selected within each stressor group across the 4 invertebrate metrics modeled. Variables related to riparian condition, substrate size or embeddedness, velocity and channel shape, nutrients (primarily NH3), and contaminants (pyrethroid degradates) were important descriptors of the invertebrate metrics. Models based on all measured in-stream stressors performed comparably to models based on GIS landscape variables, suggesting that the in-stream stressor characterization reasonably represents the dominant factors affecting invertebrate communities and that GIS variables are acting as surrogates for in-stream stressors that directly affect in-stream biota.
","language":"English","publisher":"University of Chicago Press","doi":"10.1086/694894","usgsCitation":"Waite, I.R., and Van Metre, P., 2017, Multistressor predictive models of invertebrate condition in the Corn Belt, USA: Freshwater Science, v. 36, no. 4, p. 901-914, https://doi.org/10.1086/694894.","productDescription":"14 p.","startPage":"901","endPage":"914","ipdsId":"IP-069783","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":346921,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Indiana, Iowa, Kansas, Kentucky, Minnesota, Missouri, Nebraska, Ohio, South Dakota, Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.41552734375,\n 37.61423141542417\n ],\n [\n -82.30957031249999,\n 37.61423141542417\n ],\n [\n -82.30957031249999,\n 44.77793589631623\n ],\n [\n -98.41552734375,\n 44.77793589631623\n ],\n [\n -98.41552734375,\n 37.61423141542417\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59e86831e4b05fe04cd4d1c5","contributors":{"authors":[{"text":"Waite, Ian R. 0000-0003-1681-6955 iwaite@usgs.gov","orcid":"https://orcid.org/0000-0003-1681-6955","contributorId":616,"corporation":false,"usgs":true,"family":"Waite","given":"Ian","email":"iwaite@usgs.gov","middleInitial":"R.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":713306,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Metre, Peter C. 0000-0001-7564-9814 pcvanmet@usgs.gov","orcid":"https://orcid.org/0000-0001-7564-9814","contributorId":197363,"corporation":false,"usgs":true,"family":"Van Metre","given":"Peter C.","email":"pcvanmet@usgs.gov","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":false,"id":713307,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70191881,"text":"70191881 - 2017 - Urban landscapes can change virus gene flow and evolution in a fragmentation-sensitive carnivore","interactions":[],"lastModifiedDate":"2017-12-12T12:43:53","indexId":"70191881","displayToPublicDate":"2017-10-18T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2774,"text":"Molecular Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Urban landscapes can change virus gene flow and evolution in a fragmentation-sensitive carnivore","docAbstract":"Urban expansion has widespread impacts on wildlife species globally, including the transmission and emergence of infectious diseases. However, there is almost no information about how urban landscapes shape transmission dynamics in wildlife. Using an innovative phylodynamic approach combining host and pathogen molecular data with landscape characteristics and host traits, we untangle the complex factors that drive transmission networks of Feline Immunodeficiency Virus (FIV) in bobcats (Lynx rufus). We found that the urban landscape played a significant role in shaping FIV transmission. Even though bobcats were often trapped within the urban matrix, FIV transmission events were more likely to occur in areas with more natural habitat elements. Urban fragmentation also resulted in lower rates of pathogen evolution, possibly owing to a narrower range of host genotypes in the fragmented area. Combined, our findings show that urban landscapes can have impacts on a pathogen and its evolution in a carnivore living in one of the most fragmented and urban systems in North America. The analytical approach used here can be broadly applied to other host-pathogen systems, including humans.
","language":"English","publisher":"Wiley","doi":"10.1111/mec.14375","usgsCitation":"Fountain-Jones, N.M., Craft, M.E., Funk, W.C., Kozakiewicz, C., Trumbo, D., Boydston, E.E., Lyren, L.M., Crooks, K.R., Lee, J.S., VandeWoude, S., and Carver, S., 2017, Urban landscapes can change virus gene flow and evolution in a fragmentation-sensitive carnivore: Molecular Ecology, v. 26, no. 22, p. 6487-6498, https://doi.org/10.1111/mec.14375.","productDescription":"13 p.","startPage":"6487","endPage":"6498","ipdsId":"IP-077795","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":502520,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/journal_contribution/Urban_Landscapes_can_change_virus_gene_flow_and_evolution_in_a_fragmentation-sensitive_carnivore/22964129","text":"External Repository"},{"id":346895,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"22","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59e8682ee4b05fe04cd4d1a9","contributors":{"authors":[{"text":"Fountain-Jones, Nicholas M. 0000-0001-9248-8493","orcid":"https://orcid.org/0000-0001-9248-8493","contributorId":197452,"corporation":false,"usgs":false,"family":"Fountain-Jones","given":"Nicholas","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":713521,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Craft, Meggan E.","contributorId":168372,"corporation":false,"usgs":false,"family":"Craft","given":"Meggan","email":"","middleInitial":"E.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":713522,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Funk, W. Chris 0000-0002-9254-6718","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":97589,"corporation":false,"usgs":false,"family":"Funk","given":"W.","email":"","middleInitial":"Chris","affiliations":[{"id":6998,"text":"Department of Biology, Colorado State University","active":true,"usgs":false}],"preferred":false,"id":713523,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kozakiewicz, Chris","contributorId":197453,"corporation":false,"usgs":false,"family":"Kozakiewicz","given":"Chris","email":"","affiliations":[],"preferred":false,"id":713524,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Trumbo, Daryl","contributorId":197454,"corporation":false,"usgs":false,"family":"Trumbo","given":"Daryl","affiliations":[],"preferred":false,"id":713525,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boydston, Erin E. 0000-0002-8452-835X eboydston@usgs.gov","orcid":"https://orcid.org/0000-0002-8452-835X","contributorId":1705,"corporation":false,"usgs":true,"family":"Boydston","given":"Erin","email":"eboydston@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":713520,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lyren, Lisa M.","contributorId":197457,"corporation":false,"usgs":false,"family":"Lyren","given":"Lisa","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":713530,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Crooks, Kevin R.","contributorId":51137,"corporation":false,"usgs":false,"family":"Crooks","given":"Kevin","email":"","middleInitial":"R.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":713526,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lee, Justin S.","contributorId":197455,"corporation":false,"usgs":false,"family":"Lee","given":"Justin","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":713527,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"VandeWoude, Sue","contributorId":179201,"corporation":false,"usgs":false,"family":"VandeWoude","given":"Sue","affiliations":[],"preferred":false,"id":713528,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Carver, Scott 0000-0002-3579-7588","orcid":"https://orcid.org/0000-0002-3579-7588","contributorId":197456,"corporation":false,"usgs":false,"family":"Carver","given":"Scott","email":"","affiliations":[],"preferred":false,"id":713529,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70191655,"text":"70191655 - 2017 - Oxygen stable isotopic disparities among sympatric small land snail species from northwest Minnesota, USA","interactions":[],"lastModifiedDate":"2017-10-18T14:29:36","indexId":"70191655","displayToPublicDate":"2017-10-18T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2996,"text":"Palaeogeography, Palaeoclimatology, Palaeoecology","printIssn":"0031-0182","active":true,"publicationSubtype":{"id":10}},"title":"Oxygen stable isotopic disparities among sympatric small land snail species from northwest Minnesota, USA","docAbstract":"The oxygen isotopic composition (δ18O) of land snail shells can be a valuable paleoenvironmental archive if the climatic parameters that influence the isotopic system are fully understood. Previous calibration studies have examined a limited number of species or individuals, and most have focused on larger (> 10 mm) taxa, which do not represent the dominant shell material in the Quaternary fossil record. In this study, we evaluate the δ18O values of small land snails (< 10 mm), which are common in modern settings and are often preserved in a wide array of Quaternary geologic and archeologic deposits. Our primary goal was to determine if coexisting species record equivalent isotopic information in their shells, regardless of differences in their ecology, dietary habits, behavior, and/or body size. We collected and analyzed 265 individuals of 11 species from 12 sites in northwest Minnesota (USA), which exhibits extremely abundant and diverse terrestrial malacofauna in North America. We did not observe significant correlations between shell δ18O values and the type of ecosystem (forest/grassland) or hydrologic setting (upland/lowland). However, the majority of species differed significantly in shell δ18O values. Larger taxa (Catinella, Succinea, Discus) consistently yielded higher δ18O values than smaller taxa (Euconulus, Gastrocopta, Hawaiia, Vallonia), by up to ~ 3‰. These isotopic offsets among sympatric taxa could be attributed to a number of physical, behavioral, and/or evolutionary traits, including the ability of larger species to tolerate drier conditions better than their smaller counterparts, differences in their preferred microhabitats or phylogentic non-independence. Regardless of the reason, our results imply that researchers should not combine isotopic data from different types of land snails without first investigating modern specimens to determine if it is appropriate. Moreover, our data suggest that combining instrumental climate data, a snail flux-balance model, and shell δ18O values can help us to better understand the ecology of land snails.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.palaeo.2017.07.029","usgsCitation":"Yanes, Y., Nekola, J.C., Rech, J.A., and Pigati, J., 2017, Oxygen stable isotopic disparities among sympatric small land snail species from northwest Minnesota, USA: Palaeogeography, Palaeoclimatology, Palaeoecology, v. 485, p. 715-722, https://doi.org/10.1016/j.palaeo.2017.07.029.","productDescription":"8 p.","startPage":"715","endPage":"722","ipdsId":"IP-088424","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":469430,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1776162","text":"Publisher Index Page"},{"id":346883,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.22351074218749,\n 46\n ],\n [\n -95,\n 46\n ],\n [\n -95,\n 48.99824008113872\n ],\n [\n -97.22351074218749,\n 48.99824008113872\n ],\n [\n -97.22351074218749,\n 46\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"485","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59e86831e4b05fe04cd4d1cc","contributors":{"authors":[{"text":"Yanes, Yurena","contributorId":197219,"corporation":false,"usgs":false,"family":"Yanes","given":"Yurena","email":"","affiliations":[],"preferred":false,"id":712969,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nekola, Jeffrey C.","contributorId":26214,"corporation":false,"usgs":false,"family":"Nekola","given":"Jeffrey","email":"","middleInitial":"C.","affiliations":[{"id":7000,"text":"Department of Biology, University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":712970,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rech, Jason A.","contributorId":117323,"corporation":false,"usgs":false,"family":"Rech","given":"Jason","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":712971,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pigati, Jeffery S. jpigati@usgs.gov","contributorId":140289,"corporation":false,"usgs":true,"family":"Pigati","given":"Jeffery S.","email":"jpigati@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":712968,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70191552,"text":"70191552 - 2017 - Forecast first: An argument for groundwater modeling in reverse","interactions":[],"lastModifiedDate":"2017-10-17T10:24:51","indexId":"70191552","displayToPublicDate":"2017-10-17T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Forecast first: An argument for groundwater modeling in reverse","docAbstract":"Numerical groundwater models are important compo-nents of groundwater analyses that are used for makingcritical decisions related to the management of ground-water resources. In this support role, models are oftenconstructed to serve a specific purpose that is to provideinsights, through simulation, related to a specific func-tion of a complex aquifer system that cannot be observeddirectly (Anderson et al. 2015).
For any given modeling analysis, several modelinput datasets must be prepared. Herein, the datasetsrequired to simulate the historical conditions are referredto as the calibration model, and the datasets requiredto simulate the model’s purpose are referred to as theforecast model. Future groundwater conditions or otherunobserved aspects of the groundwater system may besimulated by the forecast model—the outputs of interestfrom the forecast model represent the purpose of themodeling analysis. Unfortunately, the forecast model,needed to simulate the purpose of the modeling analysis,is seemingly an afterthought—calibration is where themajority of time and effort are expended and calibrationis usually completed before the forecast model is evenconstructed. Herein, I am proposing a new groundwatermodeling workflow, referred to as the “forecast first”workflow, where the forecast model is constructed at anearlier stage in the modeling analysis and the outputsof interest from the forecast model are evaluated duringsubsequent tasks in the workflow.
","language":"English","publisher":"Wiley","doi":"10.1111/gwat.12558","usgsCitation":"White, J.T., 2017, Forecast first: An argument for groundwater modeling in reverse: Groundwater, v. 55, no. 5, p. 660-664, https://doi.org/10.1111/gwat.12558.","productDescription":"5 p.","startPage":"660","endPage":"664","ipdsId":"IP-085148","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":346670,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"55","issue":"5","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-03","publicationStatus":"PW","scienceBaseUri":"59e7168ee4b05fe04cd33174","contributors":{"authors":[{"text":"White, Jeremy T. 0000-0002-4950-1469 jwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-4950-1469","contributorId":167708,"corporation":false,"usgs":true,"family":"White","given":"Jeremy","email":"jwhite@usgs.gov","middleInitial":"T.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":712742,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70192081,"text":"70192081 - 2017 - Forest harvest patterns on private lands in the Cascade Mountains, Washington, USA","interactions":[],"lastModifiedDate":"2017-10-25T09:44:31","indexId":"70192081","displayToPublicDate":"2017-10-17T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1689,"text":"Forests","active":true,"publicationSubtype":{"id":10}},"title":"Forest harvest patterns on private lands in the Cascade Mountains, Washington, USA","docAbstract":"Forests in Washington State generate substantial economic revenue from commercial timber harvesting on private lands. To investigate the rates, causes, and spatial and temporal patterns of forest harvest on private tracts throughout the Cascade Mountains, we relied on a new generation of annual land-use/land-cover (LULC) products created from the application of the Continuous Change Detection and Classification (CCDC) algorithm to Landsat satellite imagery collected from 1985 to 2014. We calculated metrics of landscape pattern using patches of intact and harvested forest in each annual layer to identify changes throughout the time series. Patch dynamics revealed four distinct eras of logging trends that align with prevailing regulations and economic conditions. We used multiple logistic regression to determine the biophysical and anthropogenic factors that influence fine-scale selection of harvest stands in each time period. Results show that private lands forest cover became significantly reduced and more fragmented from 1985 to 2014. Variables linked to parameters of site conditions, location, climate, and vegetation greenness consistently distinguished harvest selection for each distinct era. This study demonstrates the utility of annual LULC data for investigating the underlying factors that influence land cover change.
","language":"English","publisher":"MDPI","doi":"10.3390/f8100383","usgsCitation":"Soulard, C.E., Walker, J.J., and Griffith, G.E., 2017, Forest harvest patterns on private lands in the Cascade Mountains, Washington, USA: Forests, v. 8, no. 10, p. 1-18, https://doi.org/10.3390/f8100383.","productDescription":"Article 383; 18 p.","startPage":"1","endPage":"18","ipdsId":"IP-090964","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":469435,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/f8100383","text":"Publisher Index Page"},{"id":438189,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7X63KWW","text":"USGS data release","linkHelpText":"Data - Forest harvest patterns on private lands in the Cascade Mountains, Washington, USA"},{"id":347269,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Cascade Mountains","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 45.767522962149876\n ],\n [\n -119.80590820312499,\n 45.767522962149876\n ],\n [\n -119.80590820312499,\n 49.009050809382046\n ],\n [\n -122.33276367187499,\n 49.009050809382046\n ],\n [\n -122.33276367187499,\n 45.767522962149876\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-07","publicationStatus":"PW","scienceBaseUri":"59f05120e4b0220bbd9a1d79","contributors":{"authors":[{"text":"Soulard, Christopher E. 0000-0002-5777-9516 csoulard@usgs.gov","orcid":"https://orcid.org/0000-0002-5777-9516","contributorId":2642,"corporation":false,"usgs":true,"family":"Soulard","given":"Christopher","email":"csoulard@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":714098,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walker, Jessica J. 0000-0002-3225-0317 jjwalker@usgs.gov","orcid":"https://orcid.org/0000-0002-3225-0317","contributorId":169458,"corporation":false,"usgs":true,"family":"Walker","given":"Jessica","email":"jjwalker@usgs.gov","middleInitial":"J.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":714099,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Griffith, Glenn E. 0000-0001-7966-4720 ggriffith@usgs.gov","orcid":"https://orcid.org/0000-0001-7966-4720","contributorId":4053,"corporation":false,"usgs":true,"family":"Griffith","given":"Glenn","email":"ggriffith@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":714100,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70191664,"text":"70191664 - 2017 - The importance of parameterization when simulating the hydrologic response of vegetative land-cover change","interactions":[],"lastModifiedDate":"2020-05-19T17:59:45.012244","indexId":"70191664","displayToPublicDate":"2017-10-17T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"The importance of parameterization when simulating the hydrologic response of vegetative land-cover change","docAbstract":"Computer models of hydrologic systems are frequently used to investigate the hydrologic response of land-cover change. If the modeling results are used to inform resource-management decisions, then providing robust estimates of uncertainty in the simulated response is an important consideration. Here we examine the importance of parameterization, a necessarily subjective process, on uncertainty estimates of the simulated hydrologic response of land-cover change. Specifically, we applied the soil water assessment tool (SWAT) model to a 1.4 km2 watershed in southern Texas to investigate the simulated hydrologic response of brush management (the mechanical removal of woody plants), a discrete land-cover change. The watershed was instrumented before and after brush-management activities were undertaken, and estimates of precipitation, streamflow, and evapotranspiration (ET) are available; these data were used to condition and verify the model. The role of parameterization in brush-management simulation was evaluated by constructing two models, one with 12 adjustable parameters (reduced parameterization) and one with 1305 adjustable parameters (full parameterization). Both models were subjected to global sensitivity analysis as well as Monte Carlo and generalized likelihood uncertainty estimation (GLUE) conditioning to identify important model inputs and to estimate uncertainty in several quantities of interest related to brush management. Many realizations from both parameterizations were identified as behavioral
in that they reproduce daily mean streamflow acceptably well according to Nash–Sutcliffe model efficiency coefficient, percent bias, and coefficient of determination. However, the total volumetric ET difference resulting from simulated brush management remains highly uncertain after conditioning to daily mean streamflow, indicating that streamflow data alone are not sufficient to inform the model inputs that influence the simulated outcomes of brush management the most. Additionally, the reduced-parameterization model grossly underestimates uncertainty in the total volumetric ET difference compared to the full-parameterization model; total volumetric ET difference is a primary metric for evaluating the outcomes of brush management. The failure of the reduced-parameterization model to provide robust uncertainty estimates demonstrates the importance of parameterization when attempting to quantify uncertainty in land-cover change simulations.
Coseismic strain is fundamentally important for understanding crustal response to changes of stress after earthquakes. The elastic dislocation model has been widely applied to interpreting observed shear deformation caused by earthquakes. The application of the same theory to interpreting volumetric strain, however, has met with difficulty, especially in the far field of earthquakes. Predicted volumetric strain with dislocation model often differs substantially, and sometimes of opposite signs, from observed coseismic volumetric strains. The disagreement suggests that some processes unaccounted for by the dislocation model may occur during earthquakes. Several hypotheses have been suggested, but none have been tested quantitatively. In this paper we first examine published data to highlight the difference between the measured and calculated static coseismic volumetric strains; we then use these data to provide quantitative test of the model that the disagreement may be explained by the change of pore pressure in the shallow crust. The test allows us to conclude that coseismic change of pore pressure may be an important mechanism for coseismic crustal strain and, in the far field, may even be the dominant mechanism. Thus in the interpretation of observed coseismic crustal strain, one needs to account not only for the elastic strain due to fault rupture but also for the strain due to coseismic change of pore pressure.
","language":"English","publisher":"Springer","doi":"10.1016/j.epsl.2017.07.034","usgsCitation":"Wang, C., and Barbour, A., 2017, Influence of pore pressure change on coseismic volumetric strain: Earth and Planetary Science Letters, v. 475, p. 152-159, https://doi.org/10.1016/j.epsl.2017.07.034.","productDescription":"8 p.","startPage":"152","endPage":"159","ipdsId":"IP-085682","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":469434,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2017.07.034","text":"Publisher Index Page"},{"id":346678,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"475","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59e7168ee4b05fe04cd3317d","contributors":{"authors":[{"text":"Wang, Chi-Yuen","contributorId":20001,"corporation":false,"usgs":true,"family":"Wang","given":"Chi-Yuen","affiliations":[],"preferred":false,"id":712711,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barbour, Andrew J. 0000-0002-6890-2452 abarbour@usgs.gov","orcid":"https://orcid.org/0000-0002-6890-2452","contributorId":140443,"corporation":false,"usgs":true,"family":"Barbour","given":"Andrew J.","email":"abarbour@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":712710,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70204371,"text":"70204371 - 2017 - The NorWeST summer stream temperature model and scenarios for the western U.S.: A crowd-sourced database and new geospatial tools foster a user-community and predict broad climate warming of rivers and streams","interactions":[],"lastModifiedDate":"2019-12-22T14:51:52","indexId":"70204371","displayToPublicDate":"2017-10-16T13:40:18","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"The NorWeST summer stream temperature model and scenarios for the western U.S.: A crowd-sourced database and new geospatial tools foster a user-community and predict broad climate warming of rivers and streams","docAbstract":"Thermal regimes are fundamental determinants of aquatic ecosystems, which makes description and prediction of temperatures critical during a period of rapid global change. The advent of inexpensive temperature sensors dramatically increased monitoring in recent decades, and although most monitoring is done by individuals for agency‐specific purposes, collectively these efforts constitute a massive distributed sensing array that generates an untapped wealth of data. Using the framework provided by the National Hydrography Dataset, we organized temperature records from dozens of agencies in the western U.S. to create the NorWeST database that hosts >220,000,000 temperature recordings from >22,700 stream and river sites. Spatial‐stream‐network models were fit to a subset of those data that described mean August water temperatures (AugTw) during 63,641 monitoring site‐years to develop accurate temperature models (r2 = 0.91; RMSPE = 1.10°C; MAPE = 0.72°C), assess covariate effects, and make predictions at 1 km intervals to create summer climate scenarios. AugTw averaged 14.2°C (SD = 4.0°C) during the baseline period of 1993–2011 in 343,000 km of western perennial streams but trend reconstructions also indicated warming had occurred at the rate of 0.17°C/decade (SD = 0.067°C/decade) during the 40 year period of 1976–2015. Future scenarios suggest continued warming, although variation will occur within and among river networks due to differences in local climate forcing and stream responsiveness. NorWeST scenarios and data are available online in user‐friendly digital formats and are widely used to coordinate monitoring efforts among agencies, for new research, and for conservation planning.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017WR020969","usgsCitation":"Isaak, D.J., Wenger, S.J., Peterson, E.E., Ver Hoef, J.M., Nagel, D., Luce, C.H., Hostetler, S.W., Dunham, J.B., Roper, B.B., Wollrab, S., Chandler, G.L., Horan, D., and Parkes-Payne, S., 2017, The NorWeST summer stream temperature model and scenarios for the western U.S.: A crowd-sourced database and new geospatial tools foster a user-community and predict broad climate warming of rivers and streams: Water Resources Research, v. 53, no. 11, p. 9181-9205, https://doi.org/10.1002/2017WR020969.","productDescription":"25 p.","startPage":"9181","endPage":"9205","ipdsId":"IP-090157","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"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},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":469437,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017wr020969","text":"Publisher Index Page"},{"id":365806,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, 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M","contributorId":217318,"corporation":false,"usgs":false,"family":"Ver Hoef","given":"Jay","email":"","middleInitial":"M","affiliations":[{"id":39604,"text":"NOAA-NMFS Alaska Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":766578,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nagel, David E","contributorId":217319,"corporation":false,"usgs":false,"family":"Nagel","given":"David E","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":766579,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Luce, Charlie H.","contributorId":173471,"corporation":false,"usgs":false,"family":"Luce","given":"Charlie","email":"","middleInitial":"H.","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":766580,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hostetler, Steven W. 0000-0003-2272-8302 swhostet@usgs.gov","orcid":"https://orcid.org/0000-0003-2272-8302","contributorId":3249,"corporation":false,"usgs":true,"family":"Hostetler","given":"Steven","email":"swhostet@usgs.gov","middleInitial":"W.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":766581,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science 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Dona L","contributorId":217322,"corporation":false,"usgs":false,"family":"Horan","given":"Dona L","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":766585,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Parkes-Payne, Sharon","contributorId":217323,"corporation":false,"usgs":false,"family":"Parkes-Payne","given":"Sharon","email":"","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":766586,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70204370,"text":"70204370 - 2017 - Viability analysis for multiple populations","interactions":[],"lastModifiedDate":"2019-07-22T13:39:20","indexId":"70204370","displayToPublicDate":"2017-10-13T13:35:43","publicationYear":"2017","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":"Viability analysis for multiple populations","docAbstract":"Many species of conservation interest exist solely or largely in isolated populations. Ideally, prioritization of management actions among such populations would be guided by quantitative estimates of extinction risk, but conventional methods of demographic population viability analysis (PVA) model each population separately and require temporally extensive datasets that are rarely available in practice. We introduce a general class of statistical PVA that can be applied to many populations at once, which we term multiple population viability analysis or MPVA. The approach combines models of abundance at multiple spatial locations with temporal models of population dynamics, effectively borrowing information from more data-rich populations to inform inferences for data-poor populations. Covariates are used to explain population variability in space and time. Using Bayesian analysis, we illustrate the method with a dataset of Lahontan cutthroat trout (Oncorhynchus clarkii henshawi) observations that previously had been analyzed with conventional PVA. We find that MPVA predictions are similar in bias and higher in precision than predictions from simple PVA models that treat each population individually; moreover, the use of covariates in MPVA allows for predictions in minimally-sampled and unsampled populations. The basic MPVA model can be extended in multiple ways, such as by linking to a sampling and observation model to provide a full accounting of uncertainty. We conclude that the approach has great potential to expand the use of PVA for species that exist in multiple, isolated populations.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2017.10.006","usgsCitation":"Wenger, S.J., Leasure, D.R., Dauwalter, D.C., Peacock, M.M., Dunham, J.B., Chelgren, N., and Neville, H.M., 2017, Viability analysis for multiple populations: Biological Conservation, v. 216, p. 69-77, https://doi.org/10.1016/j.biocon.2017.10.006.","productDescription":"9 p.","startPage":"69","endPage":"77","ipdsId":"IP-090218","costCenters":[{"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}],"links":[{"id":365804,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"216","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wenger, Seth J.","contributorId":64786,"corporation":false,"usgs":true,"family":"Wenger","given":"Seth","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":766568,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leasure, Douglas R.","contributorId":145643,"corporation":false,"usgs":false,"family":"Leasure","given":"Douglas","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":766569,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dauwalter, Daniel C.","contributorId":214339,"corporation":false,"usgs":false,"family":"Dauwalter","given":"Daniel","email":"","middleInitial":"C.","affiliations":[{"id":37131,"text":"Trout Unlimited","active":true,"usgs":false}],"preferred":false,"id":766570,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peacock, Mary M.","contributorId":167605,"corporation":false,"usgs":false,"family":"Peacock","given":"Mary","email":"","middleInitial":"M.","affiliations":[{"id":24774,"text":"Department of Natural Resources, College of Agriculture and Life","active":true,"usgs":false}],"preferred":false,"id":766571,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":766567,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chelgren, Nathan 0000-0003-0944-9165 nchelgren@usgs.gov","orcid":"https://orcid.org/0000-0003-0944-9165","contributorId":3134,"corporation":false,"usgs":true,"family":"Chelgren","given":"Nathan","email":"nchelgren@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":766573,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Neville, Helen M.","contributorId":214338,"corporation":false,"usgs":false,"family":"Neville","given":"Helen","email":"","middleInitial":"M.","affiliations":[{"id":37131,"text":"Trout Unlimited","active":true,"usgs":false}],"preferred":false,"id":766572,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70190840,"text":"sir20175103 - 2017 - Hydraulic and biological analysis of the passability of select fish species at the U.S. Geological Survey streamgaging weir at Blackwells Mills, New Jersey","interactions":[],"lastModifiedDate":"2024-03-04T19:40:56.663002","indexId":"sir20175103","displayToPublicDate":"2017-10-13T03:00:00","publicationYear":"2017","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":"2017-5103","title":"Hydraulic and biological analysis of the passability of select fish species at the U.S. Geological Survey streamgaging weir at Blackwells Mills, New Jersey","docAbstract":"Recent efforts to advance river connectivity for the Millstone River watershed in New Jersey have led to the evaluation of a low-flow gauging weir that spans the full width of the river. The methods and results of a desktop modelling exercise were used to evaluate the potential ability of three anadromous fish species (Alosa sapidissima [American shad], Alosa pseudoharengus [alewife], and Alosa aestivalis [blueback herring]) to pass upstream over the U.S. Geological Survey Blackwells Mills streamgage (01402000) and weir on the Millstone River, New Jersey, at various streamflows, and to estimate the probability that the weir will be passable during the spring migratory season.
Based on data from daily fishway counts downstream from the Blackwells Mills streamgage and weir between 1996 and 2014, the general migratory period was defined as April 14 to May 28. Recorded water levels and flow data were used to theoretically estimate water depths and velocities over the weir, as well as flow exceedances occurring during the migratory period.
Results indicate that the weir is a potential depth barrier to fish passage when streamflows are below 200 cubic feet per second using a 1-body-depth criterion for American shad (the largest fish among the target species). Streamflows in that range occur on average 35 percent of the time during the migratory period. An increase of the depth criterion to 2 body depths causes the weir to become a possible barrier to passage when flows are below 400 cubic feet per second. Streamflows in that range occur on average 73 percent of the time during the migration season. Average cross-sectional velocities at several points along the weir do not seem to be limiting to the fish migration, but maximum theoretical velocities estimated without friction loss over the face of the weir could be potentially limiting.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175103","usgsCitation":"Haro, Alex, Mulligan, Kevin, Suro, T.P., Noreika, John, and McHugh, Amy, 2017, Hydraulic and biological analysis of the passability of select fish species at the U.S. Geological Survey streamgaging weir at Blackwells Mills, New Jersey: U.S. Geological Survey Scientific Investigations Report 2017–5103, 15 p., https://doi.org/10.3133/sir20175103.","productDescription":"viii, 15 p.","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-082637","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":346487,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5103/coverthb.jpg"},{"id":346491,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5103/sir20175103.pdf","text":"Report","size":"3.53 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5103"}],"country":"United States","state":"New Jersey","otherGeospatial":"Millstone River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.66995239257812,\n 40.45060475430765\n ],\n [\n -74.48867797851562,\n 40.45060475430765\n ],\n [\n -74.48867797851562,\n 40.567545853080496\n ],\n [\n -74.66995239257812,\n 40.567545853080496\n ],\n [\n -74.66995239257812,\n 40.45060475430765\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430
Email: gs_nea_lsc_publications@usgs.gov
Many ecosystem processes that influence Earth system feedbacks, including vegetation growth, water and nutrient cycling, and disturbance regimes, are strongly influenced by multi-decadal to millennial-scale variations in climate that cannot be captured by instrumental climate observations. Paleoclimate information is therefore essential for understanding contemporary ecosystems and their potential trajectories under a variety of future climate conditions. With the exception of fossil pollen records, there are a limited number of northeastern US (NE US) paleoclimate archives that can provide constraints on its temperature and hydroclimate history. Moreover, the records that do exist have not been considered together. Tree-ring data indicate that the 20th century was one of the wettest of the past 500 years in the eastern US (Pederson et al., 2014), and lake-level records suggest it was one of the wettest in the Holocene (Newby et al., 2014); how such results compare with other available data remains unclear, however. Here we conduct a systematic review, assessment, and comparison of paleotemperature and paleohydrological proxies from the NE US for the last 3000 years. Regional temperature reconstructions are consistent with the long-term cooling trend (1000 BCE–1700 CE) evident in hemispheric-scale reconstructions, but hydroclimate reconstructions reveal new information, including an abrupt transition from wet to dry conditions around 550–750 CE. NE US paleo data suggest that conditions during the Medieval Climate Anomaly were warmer and drier than during the Little Ice Age, and drier than today. There is some evidence for an acceleration over the past century of a longer-term wetting trend in the NE US, and coupled with the abrupt shift from a cooling trend to a warming trend from increased greenhouse gases, may have wide-ranging implications for species distributions, ecosystem dynamics, and extreme weather events. More work is needed to gather paleoclimate data in the NE US, make inter-proxy comparisons, and improve estimates of uncertainty in the reconstructions.
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/cp-2016-104","usgsCitation":"Marlon, J.R., Pederson, N., Nolan, C., Goring, S., Shuman, B., Robertson, A., Booth, R.K., Bartlein, P.J., Berke, M.A., Clifford, M., Cook, E., Dieffenbacher-Krall, A., Dietze, M.C., Hessl, A., Hubeny, J.B., Jackson, S.T., Marsicek, J., McLachlan, J.S., Mock, C.J., Moore, D.J., Nichols, J., Peteet, D.M., Schaefer, K., Trouet, V., Umbanhowar, C., Williams, J.W., and Yu, Z., 2017, Climatic history of the northeastern United States during the past 3000 years: Climate of the Past, v. 13, p. 1355-1379, https://doi.org/10.5194/cp-2016-104.","productDescription":"25 p.","startPage":"1355","endPage":"1379","ipdsId":"IP-080505","costCenters":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"links":[{"id":461389,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/cp-2016-104","text":"Publisher Index Page"},{"id":346607,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"13","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59e1d097e4b05fe04cd117a0","contributors":{"authors":[{"text":"Marlon, Jennifer R.","contributorId":23432,"corporation":false,"usgs":true,"family":"Marlon","given":"Jennifer","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":712391,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pederson, Neil","contributorId":149422,"corporation":false,"usgs":false,"family":"Pederson","given":"Neil","email":"","affiliations":[{"id":17731,"text":"Research Scientist, Tree Ring Laboratory, Lamont-Doherty Earth Observatory","active":true,"usgs":false}],"preferred":false,"id":712392,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nolan, Connor","contributorId":197051,"corporation":false,"usgs":false,"family":"Nolan","given":"Connor","affiliations":[],"preferred":false,"id":712393,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goring, Simon","contributorId":167180,"corporation":false,"usgs":false,"family":"Goring","given":"Simon","affiliations":[],"preferred":false,"id":712491,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shuman, Bryan","contributorId":99039,"corporation":false,"usgs":true,"family":"Shuman","given":"Bryan","affiliations":[],"preferred":false,"id":712492,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Robertson, Ann","contributorId":197075,"corporation":false,"usgs":false,"family":"Robertson","given":"Ann","email":"","affiliations":[],"preferred":false,"id":712493,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Booth, Robert K.","contributorId":17177,"corporation":false,"usgs":true,"family":"Booth","given":"Robert","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":712494,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bartlein, Patrick J.","contributorId":106879,"corporation":false,"usgs":true,"family":"Bartlein","given":"Patrick","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":712495,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Berke, Melissa A.","contributorId":197076,"corporation":false,"usgs":false,"family":"Berke","given":"Melissa","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":712496,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Clifford, Michael","contributorId":197077,"corporation":false,"usgs":false,"family":"Clifford","given":"Michael","email":"","affiliations":[],"preferred":false,"id":712497,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Cook, Edward","contributorId":197078,"corporation":false,"usgs":false,"family":"Cook","given":"Edward","affiliations":[],"preferred":false,"id":712498,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Dieffenbacher-Krall, Ann","contributorId":197079,"corporation":false,"usgs":false,"family":"Dieffenbacher-Krall","given":"Ann","email":"","affiliations":[],"preferred":false,"id":712499,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Dietze, Michael C.","contributorId":15908,"corporation":false,"usgs":true,"family":"Dietze","given":"Michael","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":712500,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Hessl, Amy","contributorId":50594,"corporation":false,"usgs":true,"family":"Hessl","given":"Amy","affiliations":[],"preferred":false,"id":712501,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Hubeny, J. Bradford","contributorId":197080,"corporation":false,"usgs":false,"family":"Hubeny","given":"J.","email":"","middleInitial":"Bradford","affiliations":[],"preferred":false,"id":712502,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Jackson, Stephen T. 0000-0002-1487-4652 stjackson@usgs.gov","orcid":"https://orcid.org/0000-0002-1487-4652","contributorId":344,"corporation":false,"usgs":true,"family":"Jackson","given":"Stephen","email":"stjackson@usgs.gov","middleInitial":"T.","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":560,"text":"South Central Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":712503,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Marsicek, Jeremiah","contributorId":197081,"corporation":false,"usgs":false,"family":"Marsicek","given":"Jeremiah","email":"","affiliations":[],"preferred":false,"id":712504,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"McLachlan, Jason S.","contributorId":167179,"corporation":false,"usgs":false,"family":"McLachlan","given":"Jason","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":712505,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Mock, Cary J.","contributorId":87323,"corporation":false,"usgs":true,"family":"Mock","given":"Cary","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":712506,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Moore, David J. P.","contributorId":169810,"corporation":false,"usgs":false,"family":"Moore","given":"David","email":"","middleInitial":"J. P.","affiliations":[],"preferred":false,"id":712507,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Nichols, Jonathan M.","contributorId":45945,"corporation":false,"usgs":true,"family":"Nichols","given":"Jonathan M.","affiliations":[],"preferred":false,"id":712508,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Peteet, Dorothy M. 0000-0003-3029-7506","orcid":"https://orcid.org/0000-0003-3029-7506","contributorId":147523,"corporation":false,"usgs":false,"family":"Peteet","given":"Dorothy","email":"","middleInitial":"M.","affiliations":[{"id":16858,"text":"Goddard Institute","active":true,"usgs":false}],"preferred":false,"id":712509,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Schaefer, Kevin","contributorId":63323,"corporation":false,"usgs":true,"family":"Schaefer","given":"Kevin","affiliations":[],"preferred":false,"id":712510,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Trouet, Valerie","contributorId":197082,"corporation":false,"usgs":false,"family":"Trouet","given":"Valerie","email":"","affiliations":[],"preferred":false,"id":712511,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Umbanhowar, Charles","contributorId":197083,"corporation":false,"usgs":false,"family":"Umbanhowar","given":"Charles","affiliations":[],"preferred":false,"id":712512,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Williams, John W.","contributorId":16761,"corporation":false,"usgs":true,"family":"Williams","given":"John","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":712513,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Yu, Zicheng 0000-0003-2358-2712","orcid":"https://orcid.org/0000-0003-2358-2712","contributorId":147521,"corporation":false,"usgs":false,"family":"Yu","given":"Zicheng","email":"","affiliations":[{"id":16857,"text":"Lehigh Univ.","active":true,"usgs":false}],"preferred":false,"id":712514,"contributorType":{"id":1,"text":"Authors"},"rank":27}]}} ,{"id":70191459,"text":"70191459 - 2017 - Changes in habitat availability for multiple life stages of diamondback terrapins (Malaclemys terrapin) in Chesapeake Bay in response to sea level rise","interactions":[],"lastModifiedDate":"2017-10-13T10:57:57","indexId":"70191459","displayToPublicDate":"2017-10-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Changes in habitat availability for multiple life stages of diamondback terrapins (Malaclemys terrapin) in Chesapeake Bay in response to sea level rise","title":"Changes in habitat availability for multiple life stages of diamondback terrapins (Malaclemys terrapin) in Chesapeake Bay in response to sea level rise","docAbstract":"Global sea level rise (SLR) will significantly alter\ncoastal landscapes through inundation and erosion of lowlying\nareas. Animals that display area fidelity and rely on\nfringing coastal habitats during multiple life stages, such as\ndiamondback terrapins (Malaclemys terrapin Schoepff 1793),\nare likely to be particularly vulnerable to SLR-induced changes.\nWe used a combination of empirical nest survey data and\nresults from a regional SLR model to explore the long-term\navailability of known nesting locations and the modeled availability\nof fringing coastal habitats under multiple SLR scenarios\nfor diamondback terrapin in the MD portion of\nChesapeake Bay and the MD coastal bays. All SLR scenarios\nprojected the rapid inundation of historically used nesting locations\nof diamondback terrapins with 25%–55% loss within\nthe next 10 years and over 80% loss by the end of the century.\nModel trajectories of habitat losses or gains depended on habitat\ntype and location. A key foraging habitat, brackish marsh,\nwas projected to decline 6%–94%, with projections varying\nspatially and among scenarios. Despite predicted losses of\nextant beach habitats, future gains in beach habitat due to\nerosion and overwash were projected to reach 40%–600%.\nThese results demonstrate the potential vulnerability of diamondback terrapins to SLR in Chesapeake Bay and underscore\nthe possibility of compounding negative effects of SLR\non animals whose habitat requirements differ among life\nstages. More broadly, this study highlights the vulnerability\nof species dependent on fringing coastal habitats and emphasizes\nthe need for a long-term perspective for coastal development\nin the face of SLR.","language":"English","publisher":"Springer","doi":"10.1007/s12237-017-0209-2","usgsCitation":"Woodland, R.J., Rowe, C.L., and Henry, P.F., 2017, Changes in habitat availability for multiple life stages of diamondback terrapins (Malaclemys terrapin) in Chesapeake Bay in response to sea level rise: Estuaries and Coasts, v. 40, no. 5, p. 1502-1515, https://doi.org/10.1007/s12237-017-0209-2.","productDescription":"14 p.","startPage":"1502","endPage":"1515","ipdsId":"IP-077271","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":346567,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.62139892578125,\n 37.88569271818349\n ],\n [\n -75.60516357421874,\n 37.88569271818349\n ],\n [\n -75.60516357421874,\n 39.612036199336956\n ],\n [\n -76.62139892578125,\n 39.612036199336956\n ],\n [\n -76.62139892578125,\n 37.88569271818349\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","issue":"5","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-11","publicationStatus":"PW","scienceBaseUri":"59e1d097e4b05fe04cd117a3","contributors":{"authors":[{"text":"Woodland, Ryan J.","contributorId":197043,"corporation":false,"usgs":false,"family":"Woodland","given":"Ryan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":712365,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rowe, Christopher L.","contributorId":197044,"corporation":false,"usgs":false,"family":"Rowe","given":"Christopher","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":712366,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Henry, Paula F. P. 0000-0002-7601-5546 phenry@usgs.gov","orcid":"https://orcid.org/0000-0002-7601-5546","contributorId":4485,"corporation":false,"usgs":true,"family":"Henry","given":"Paula","email":"phenry@usgs.gov","middleInitial":"F. P.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":712351,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}