Homologous and heterologous (genogroup Ia) DNA vaccines against viral hemorrhagic septicemia virus (genogroup IVa) conferred partial protection in Pacific Herring Clupea pallasii. Early protection at 2 weeks postvaccination (PV) was low and occurred only at an elevated temperature (12.6°C, 189 degree days), where the relative percent survival following viral exposure was similar for the two vaccines (IVa and Ia) and higher than that of negative controls at the same temperature. Late protection at 10 weeks PV was induced by both vaccines but was higher with the homologous vaccine at both 9.0°C and 12.6°C. Virus neutralization titers were detected among 55% of all vaccinated fish at 10 weeks PV. The results suggest that the immune response profile triggered by DNA vaccination of herring was similar to that reported for Rainbow Trout Oncorhynchus mykiss by Lorenzen and LaPatra in 2005, who found interferon responses in the early days PV and the transition to adaptive response later. However, the protective effect was far less prominent in herring, possibly reflecting different physiologies or adaptations of the two fish species.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/08997659.2017.1307287","usgsCitation":"Hart, L., Lorenzen, N., Einer-Jensen, K., Purcell, M.K., and Hershberger, P., 2017, Influence of temperature on the efficacy of homologous and heterologous DNA vaccines against viral hemorrhagic septicemia in Pacific Herring: Journal of Aquatic Animal Health, v. 29, no. 3, p. 121-128, https://doi.org/10.1080/08997659.2017.1307287.","productDescription":"8 p.","startPage":"121","endPage":"128","ipdsId":"IP-078478","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":343876,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-11","publicationStatus":"PW","scienceBaseUri":"5969d828e4b0d1f9f060a175","contributors":{"authors":[{"text":"Hart, Lucas 0000-0001-7035-8778 lhart@usgs.gov","orcid":"https://orcid.org/0000-0001-7035-8778","contributorId":140133,"corporation":false,"usgs":true,"family":"Hart","given":"Lucas","email":"lhart@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":705104,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lorenzen, Niels","contributorId":194694,"corporation":false,"usgs":false,"family":"Lorenzen","given":"Niels","email":"","affiliations":[],"preferred":false,"id":705105,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Einer-Jensen, Katja","contributorId":169001,"corporation":false,"usgs":false,"family":"Einer-Jensen","given":"Katja","email":"","affiliations":[],"preferred":false,"id":705106,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Purcell, Maureen K. 0000-0003-0154-8433 mpurcell@usgs.gov","orcid":"https://orcid.org/0000-0003-0154-8433","contributorId":168475,"corporation":false,"usgs":true,"family":"Purcell","given":"Maureen","email":"mpurcell@usgs.gov","middleInitial":"K.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":705107,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hershberger, Paul 0000-0002-2261-7760 phershberger@usgs.gov","orcid":"https://orcid.org/0000-0002-2261-7760","contributorId":150816,"corporation":false,"usgs":true,"family":"Hershberger","given":"Paul","email":"phershberger@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":705103,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70189663,"text":"70189663 - 2017 - Assessment of PIT tag retention and post-tagging survival in metamorphosing juvenile Sea Lamprey","interactions":[],"lastModifiedDate":"2017-07-19T14:58:02","indexId":"70189663","displayToPublicDate":"2017-07-14T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":773,"text":"Animal Biotelemetry","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of PIT tag retention and post-tagging survival in metamorphosing juvenile Sea Lamprey","docAbstract":"Background: Passive integrated transponder (PIT) tags have been used to document and monitor the movement or behavior of numerous species of fishes. Data on short-term and long-term survival and tag retention are needed before initiating studies using PIT tags on a new species or life stage. We evaluated the survival and tag retention of 153 metamorphosing juvenile Sea Lamprey Petromyzon marinus tagged with 12 mm PIT tags on three occasions using a simple surgical procedure.
Results: Tag retention was 100% and 98.6% at 24 h and 28-105 d post-tagging. Of the lamprey that retained their tags, 87.3% had incisions sufficiently healed to prevent further loss. Survival was 100% and 92.7% at 24 h and 41-118 d post-tagging with no significant difference in survival between tagged and untagged control lamprey. Of the 11 lamprey that died, four had symptoms that indicated their death was directly related to tagging. Survival was positively correlated with Sea Lamprey length.
Conclusions: Given the overall high level of survival and tag retention in this study, future studies can utilize 12 mm PIT tags to monitor metamorphosing juvenile Sea Lamprey movement and migration patterns.
","language":"English","publisher":"BioMed Central","doi":"10.1186/s40317-017-0133-z","usgsCitation":"Simard, L.G., Sotola, V.A., Marsden, J., and Miehls, S.M., 2017, Assessment of PIT tag retention and post-tagging survival in metamorphosing juvenile Sea Lamprey: Animal Biotelemetry, v. 5, no. 18, p. 1-7, https://doi.org/10.1186/s40317-017-0133-z.","productDescription":"7 p. ","startPage":"1","endPage":"7","ipdsId":"IP-085186","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":469678,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40317-017-0133-z","text":"Publisher Index Page"},{"id":344067,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"18","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-14","publicationStatus":"PW","scienceBaseUri":"59706fb4e4b0d1f9f065a87c","contributors":{"authors":[{"text":"Simard, Lee G.","contributorId":194905,"corporation":false,"usgs":false,"family":"Simard","given":"Lee","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":705665,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sotola, V. Alex","contributorId":194906,"corporation":false,"usgs":false,"family":"Sotola","given":"V.","email":"","middleInitial":"Alex","affiliations":[],"preferred":false,"id":705666,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marsden, J. Ellen","contributorId":194907,"corporation":false,"usgs":false,"family":"Marsden","given":"J. Ellen","affiliations":[],"preferred":false,"id":705667,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miehls, Scott M. 0000-0002-5546-1854 smiehls@usgs.gov","orcid":"https://orcid.org/0000-0002-5546-1854","contributorId":5007,"corporation":false,"usgs":true,"family":"Miehls","given":"Scott","email":"smiehls@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":705664,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70188429,"text":"sir20175059 - 2017 - Estimation of salt loads for the Dolores River in the Paradox Valley, Colorado, 1980–2015","interactions":[],"lastModifiedDate":"2017-08-07T16:16:01","indexId":"sir20175059","displayToPublicDate":"2017-07-13T15:45:00","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":"2017-5059","title":"Estimation of salt loads for the Dolores River in the Paradox Valley, Colorado, 1980–2015","docAbstract":"Regression models that relate total dissolved solids (TDS) concentrations to specific conductance were used to estimate salt loads for two sites on the Dolores River in the Paradox Valley in western Colorado. The salt-load estimates will be used by the Bureau of Reclamation to evaluate salt loading to the river coming from the Paradox Valley and the effect of the Paradox Valley Unit (PVU), a project designed to reduce the salinity of the Colorado River. A second-order polynomial provided the best fit of the discrete data for both sites on the river. The largest bias occurred in samples with elevated sulfate concentrations (greater than 500 milligrams per liter), which were associated with short-duration runoff events in late summer and fall. Comparison of regression models from a period of time before operation began at the PVU and three periods after operation began suggests the relation between TDS and specific conductance has not changed over time. Net salt gain through the Paradox Valley was estimated as the TDS load at the downstream site minus the load at the upstream site. The mean annual salt gain was 137,900 tons per year prior to operation of the PVU (1980–1993) and 43,300 tons per year after the PVU began operation (1997–2015). The difference in annual salt gain in the river between the pre-PVU and post-PVU periods was 94,600 tons per year, which represents a nearly 70 percent reduction in salt loading to the river.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175059","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Mast, M.A., 2017, Estimation of salt loads for the Dolores River in the Paradox Valley, Colorado, 1980–2015: U.S. Geological Survey Scientific Investigations Report 2017–5059, 20 p., https://doi.org/10.3133/sir20175059.","productDescription":"v, 20 p.","numberOfPages":"29","onlineOnly":"Y","ipdsId":"IP-079370","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":343666,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5059/coverthb.jpg"},{"id":343668,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5059/sir20175059.pdf","text":"Report","size":"6.79 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5059"}],"country":"United States","state":"Colorado","otherGeospatial":"Dolores River, Paradox Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.907470703125,\n 38.30179226344099\n ],\n [\n -108.81906509399414,\n 38.30179226344099\n ],\n [\n -108.81906509399414,\n 38.36211833953394\n ],\n [\n -108.907470703125,\n 38.36211833953394\n ],\n [\n -108.907470703125,\n 38.30179226344099\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS-415
Denver, CO 80225-0046
Comparisons of pre-earthquake and post-earthquake microfossils in tidal sequences are accurate means to measure coastal subsidence during past subduction earthquakes, but the amount of subsidence is uncertain, because the response times of fossil taxa to coseismic relative sea-level (RSL) rise are unknown. We measured the response of diatoms and foraminifera to restoration of a salt marsh in southern Oregon, USA. Tidal flooding following dike removal caused an RSL rise of ∼1 m, as might occur by coseismic subsidence during momentum magnitude (Mw) 8.1–8.8 earthquakes on this section of the Cascadia subduction zone. Less than two weeks after dike removal, diatoms colonized low marsh and tidal flats in large numbers, showing that they can record seismically induced subsidence soon after earthquakes. In contrast, low-marsh foraminifera took at least 11 months to appear in sizeable numbers. Where subsidence measured with diatoms and foraminifera differs, their different response times may provide an estimate of postseismic vertical deformation in the months following past megathrust earthquakes.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/G38832.1","usgsCitation":"Horton, B.P., Milker, Y., Dura, T., Wang, K., Bridgeland, W., Brophy, L.S., Ewald, M., Khan, N., Engelhart, S., Nelson, A.R., and Witter, R., 2017, Microfossil measures of rapid sea-level rise: Timing of response of two microfossil groups to a sudden tidal-flooding experiment in Cascadia: Geology, v. 45, no. 6, p. 535-538, https://doi.org/10.1130/G38832.1.","productDescription":"4 p.","startPage":"535","endPage":"538","ipdsId":"IP-084807","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":490026,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://durham-repository.worktribe.com/output/1290766","text":"External Repository"},{"id":344683,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","volume":"45","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-27","publicationStatus":"PW","scienceBaseUri":"598acddce4b09fa1cb0e13d6","contributors":{"authors":[{"text":"Horton, B. P.","contributorId":96816,"corporation":false,"usgs":false,"family":"Horton","given":"B.","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":707385,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Milker, Yvonne","contributorId":193405,"corporation":false,"usgs":false,"family":"Milker","given":"Yvonne","email":"","affiliations":[],"preferred":false,"id":707386,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dura, T.","contributorId":193399,"corporation":false,"usgs":false,"family":"Dura","given":"T.","affiliations":[],"preferred":false,"id":707387,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wang, Kelin","contributorId":194791,"corporation":false,"usgs":false,"family":"Wang","given":"Kelin","email":"","affiliations":[],"preferred":false,"id":707388,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bridgeland, W.T.","contributorId":195549,"corporation":false,"usgs":false,"family":"Bridgeland","given":"W.T.","affiliations":[],"preferred":false,"id":707389,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brophy, Laura S.","contributorId":47266,"corporation":false,"usgs":false,"family":"Brophy","given":"Laura","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":707390,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ewald, M.","contributorId":195550,"corporation":false,"usgs":false,"family":"Ewald","given":"M.","email":"","affiliations":[],"preferred":false,"id":707391,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Khan, Nicole 0000-0002-9845-1103 nkhan@usgs.gov","orcid":"https://orcid.org/0000-0002-9845-1103","contributorId":194111,"corporation":false,"usgs":true,"family":"Khan","given":"Nicole","email":"nkhan@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":707392,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Engelhart, S.E.","contributorId":88586,"corporation":false,"usgs":true,"family":"Engelhart","given":"S.E.","email":"","affiliations":[],"preferred":false,"id":707393,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Nelson, Alan R. 0000-0001-7117-7098 anelson@usgs.gov","orcid":"https://orcid.org/0000-0001-7117-7098","contributorId":812,"corporation":false,"usgs":true,"family":"Nelson","given":"Alan","email":"anelson@usgs.gov","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":707394,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Witter, Robert C. 0000-0002-1721-254X rwitter@usgs.gov","orcid":"https://orcid.org/0000-0002-1721-254X","contributorId":4528,"corporation":false,"usgs":true,"family":"Witter","given":"Robert C.","email":"rwitter@usgs.gov","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":707395,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70189480,"text":"70189480 - 2017 - Improved efficiency of maximum likelihood analysis of time series with temporally correlated errors","interactions":[],"lastModifiedDate":"2017-07-13T15:08:25","indexId":"70189480","displayToPublicDate":"2017-07-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2303,"text":"Journal of Geodesy","active":true,"publicationSubtype":{"id":10}},"title":"Improved efficiency of maximum likelihood analysis of time series with temporally correlated errors","docAbstract":"Most time series of geophysical phenomena have temporally correlated errors. From these measurements, various parameters are estimated. For instance, from geodetic measurements of positions, the rates and changes in rates are often estimated and are used to model tectonic processes. Along with the estimates of the size of the parameters, the error in these parameters needs to be assessed. If temporal correlations are not taken into account, or each observation is assumed to be independent, it is likely that any estimate of the error of these parameters will be too low and the estimated value of the parameter will be biased. Inclusion of better estimates of uncertainties is limited by several factors, including selection of the correct model for the background noise and the computational requirements to estimate the parameters of the selected noise model for cases where there are numerous observations. Here, I address the second problem of computational efficiency using maximum likelihood estimates (MLE). Most geophysical time series have background noise processes that can be represented as a combination of white and power-law noise,
We evaluated the maternal transfer of mercury to eggs in songbirds, determined whether this relationship differed between songbird species, and developed equations for predicting mercury concentrations in eggs from maternal blood. We sampled blood and feathers from 44 house wren (Troglodytes aedon) and 34 tree swallow (Tachycineta bicolor) mothers and collected their full clutches (n = 476 eggs) within 3 days of clutch completion. Additionally, we sampled blood and feathers from 53 tree swallow mothers and randomly collected one egg from their clutches (n = 53 eggs) during mid to late incubation (6–10 days incubated) to evaluate whether the relationship varied with the timing of sampling the mother's blood. Mercury concentrations in eggs were positively correlated with mercury concentrations in maternal blood sampled at (1) the time of clutch completion for both house wrens (R2 = 0.97) and tree swallows (R2 = 0.97) and (2) during mid to late incubation for tree swallows (R2 = 0.71). The relationship between mercury concentrations in eggs and maternal blood did not differ with the stage of incubation when maternal blood was sampled. Importantly, the proportion of mercury transferred from mothers to their eggs decreased substantially with increasing blood mercury concentrations in tree swallows, but increased slightly with increasing blood mercury concentrations in house wrens. Additionally, the proportion of mercury transferred to eggs at the same maternal blood mercury concentration differed between species. Specifically, tree swallow mothers transferred 17%–107% more mercury to their eggs than house wren mothers over the observed mercury concentrations in maternal blood (0.15–1.92 μg/g ww). In contrast, mercury concentrations in eggs were not correlated with those in maternal feathers and, likewise, mercury concentrations in maternal blood were not correlated with those in feathers (all R2 < 0.01). We provide equations to translate mercury concentrations from maternal blood to eggs (and vice versa), which should facilitate comparisons among studies and help integrate toxicity benchmarks into a common tissue.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2017.06.099","usgsCitation":"Ackerman, J., Hartman, C.A., and Herzog, M.P., 2017, Maternal transfer of mercury to songbird eggs: Environmental Pollution, v. 230, p. 463-468, https://doi.org/10.1016/j.envpol.2017.06.099.","productDescription":"6 p.","startPage":"463","endPage":"468","ipdsId":"IP-085193","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":469681,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envpol.2017.06.099","text":"Publisher Index Page"},{"id":343830,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Cache Creek Settling Basin, Cosumnes River Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.75,\n 38.75\n ],\n [\n -121.65,\n 38.75\n ],\n [\n -121.65,\n 38.65\n ],\n [\n -121.75,\n 38.65\n ],\n [\n -121.75,\n 38.75\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.35,\n 38.35\n ],\n [\n -121.45,\n 38.35\n ],\n [\n -121.45,\n 38.25\n ],\n [\n -121.35,\n 38.25\n ],\n [\n -121.35,\n 38.35\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"230","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59688698e4b0d1f9f05f5946","contributors":{"authors":[{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":704908,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hartman, C. Alex 0000-0002-7222-1633 chartman@usgs.gov","orcid":"https://orcid.org/0000-0002-7222-1633","contributorId":131109,"corporation":false,"usgs":true,"family":"Hartman","given":"C.","email":"chartman@usgs.gov","middleInitial":"Alex","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":704909,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herzog, Mark P. 0000-0002-5203-2835 mherzog@usgs.gov","orcid":"https://orcid.org/0000-0002-5203-2835","contributorId":131158,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark","email":"mherzog@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":704910,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70189457,"text":"70189457 - 2017 - Sand ridge morphology and bedform migration patterns derived from bathymetry and backscatter on the inner-continental shelf offshore of Assateague Island, USA","interactions":[],"lastModifiedDate":"2017-07-13T11:12:25","indexId":"70189457","displayToPublicDate":"2017-07-13T00:00:00","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":"Sand ridge morphology and bedform migration patterns derived from bathymetry and backscatter on the inner-continental shelf offshore of Assateague Island, USA","docAbstract":"The U.S. Geological Survey and the National Oceanographic and Atmospheric Administration conducted\r\ngeophysical and hydrographic surveys, respectively, along the inner-continental shelf of Fenwick and\r\nAssateague Islands, Maryland and Virginia over the last 40 years. High resolution bathymetry and backscatter\r\ndata derived from surveys over the last decade are used to describe the morphology and presence of sand ridges\r\non the inner-continental shelf and measure the change in the position of smaller-scale (10–100 s of meters)\r\nseafloor features. Bathymetric surveys from the last 30 years link decadal-scale sand ridge migration patterns to\r\nthe high-resolution measurements of smaller-scale bedform features. Sand ridge morphology on the inner-shelf\r\nchanges across-shore and alongshore. Areas of similar sand ridge morphology are separated alongshore by\r\nzones where ridges are less pronounced or completely transected by transverse dunes. Seafloor-change analyses\r\nderived from backscatter data over a 4–7 year period show that southerly dune migration increases in\r\nmagnitude from north to south, and the east-west pattern of bedform migration changes ~ 10 km north of the\r\nMaryland-Virginia state line. Sand ridge morphology and occurrence and bedform migration changes may be\r\nconnected to observed changes in geologic framework including topographic highs, deflated zones, and sand\r\navailability. Additionally, changes in sand ridge occurrence and morphology may help explain changes in the\r\nlong-term shoreline trends along Fenwick and Assateague Islands. Although the data presented here cannot\r\nquantitatively link sand ridges to sediment transport and shoreline change, it does present a compelling\r\nrelationship between inner-shelf sand availability and movement, sand ridge occurrence and morphology,\r\ngeologic framework, and shoreline behavior.","language":"English","publisher":"Elsevier","doi":"10.1016/j.csr.2017.06.021","usgsCitation":"Pendleton, E.A., Brothers, L.L., Thieler, E.R., and Sweeney, E., 2017, Sand ridge morphology and bedform migration patterns derived from bathymetry and backscatter on the inner-continental shelf offshore of Assateague Island, USA: Continental Shelf Research, v. 144, p. 80-97, https://doi.org/10.1016/j.csr.2017.06.021.","productDescription":"18 p. ","startPage":"80","endPage":"97","ipdsId":"IP-077828","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469682,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.csr.2017.06.021","text":"Publisher Index Page"},{"id":343788,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States ","otherGeospatial":"Assateague Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.6630859375,\n 39.05758374935667\n ],\n [\n -76.4263916015625,\n 38.9807627650163\n ],\n [\n -76.4044189453125,\n 38.47939467327645\n ],\n [\n -76.256103515625,\n 38.28993659801203\n ],\n [\n -76.1517333984375,\n 38.151837403006766\n ],\n [\n -76.102294921875,\n 37.931200459333716\n ],\n [\n -76.036376953125,\n 37.76637243960179\n ],\n [\n -75.9210205078125,\n 37.80978395301097\n ],\n [\n -75.8331298828125,\n 37.9051994823157\n ],\n [\n -75.772705078125,\n 37.91820111976663\n ],\n [\n -75.87158203125,\n 37.77071473849609\n ],\n [\n -76.102294921875,\n 37.37888785004527\n ],\n [\n -75.992431640625,\n 36.954281585675965\n ],\n [\n -75.55847167968749,\n 37.35269280367274\n ],\n [\n -75.07507324218749,\n 38.11727165830543\n ],\n [\n -74.8223876953125,\n 38.64261790634527\n ],\n [\n -74.6630859375,\n 39.05758374935667\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"144","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5968869be4b0d1f9f05f595a","contributors":{"authors":[{"text":"Pendleton, Elizabeth A. 0000-0002-1224-4892 ependleton@usgs.gov","orcid":"https://orcid.org/0000-0002-1224-4892","contributorId":174845,"corporation":false,"usgs":true,"family":"Pendleton","given":"Elizabeth","email":"ependleton@usgs.gov","middleInitial":"A.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":704647,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brothers, Laura L. 0000-0003-2986-5166 lbrothers@usgs.gov","orcid":"https://orcid.org/0000-0003-2986-5166","contributorId":176698,"corporation":false,"usgs":true,"family":"Brothers","given":"Laura","email":"lbrothers@usgs.gov","middleInitial":"L.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":704648,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thieler, E. Robert 0000-0003-4311-9717 rthieler@usgs.gov","orcid":"https://orcid.org/0000-0003-4311-9717","contributorId":2488,"corporation":false,"usgs":true,"family":"Thieler","given":"E.","email":"rthieler@usgs.gov","middleInitial":"Robert","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":704649,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sweeney, Edward 0000-0003-4458-4493 emsweeney@usgs.gov","orcid":"https://orcid.org/0000-0003-4458-4493","contributorId":152121,"corporation":false,"usgs":true,"family":"Sweeney","given":"Edward","email":"emsweeney@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":704650,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70189473,"text":"70189473 - 2017 - Deepwater sculpin status and recovery in Lake Ontario","interactions":[],"lastModifiedDate":"2018-03-28T11:23:33","indexId":"70189473","displayToPublicDate":"2017-07-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Deepwater sculpin status and recovery in Lake Ontario","docAbstract":"Deepwater sculpin are important in oligotrophic lakes as one of the few fishes that use deep profundal habitats and link invertebrates in those habitats to piscivores. In Lake Ontario the species was once abundant, however drastic declines in the mid-1900s led some to suggest the species had been extirpated and ultimately led Canadian and U.S. agencies to elevate the species' conservation status. Following two decades of surveys with no captures, deepwater sculpin were first caught in low numbers in 1996 and by the early 2000s there were indications of population recovery. We updated the status of Lake Ontario deepwater sculpin through 2016 to inform resource management and conservation. Our data set was comprised of 8431 bottom trawls sampled from 1996 to 2016, in U.S. and Canadian waters spanning depths from 5 to 225 m. Annual density estimates generally increased from 1996 through 2016, and an exponential model estimated the rate of population increase was ~ 59% per year. The mean total length and the proportion of fish greater than the estimated length at maturation (~ 116 mm) generally increased until a peak in 2013. In addition, the mean length of all deepwater sculpin captured in a trawl significantly increased with depth. Across all years examined, deepwater sculpin densities generally increased with depth, increasing sharply at depths > 150 m. Bottom trawl observations suggest the Lake Ontario deepwater sculpin population has recovered and current densities and biomass densities may now be similar to the other Great Lakes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2016.12.011","usgsCitation":"Weidel, B., Walsh, M., Connerton, M., Lantry, B.F., Lantry, J.R., Holden, J.P., Yuille, M.J., and Hoyle, J., 2017, Deepwater sculpin status and recovery in Lake Ontario: Journal of Great Lakes Research, v. 43, no. 5, p. 854-862, https://doi.org/10.1016/j.jglr.2016.12.011.","productDescription":"9 p.","startPage":"854","endPage":"862","ipdsId":"IP-082229","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":469680,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2016.12.011","text":"Publisher Index Page"},{"id":343808,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Lake Ontario","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.91455078125,\n 43.14909399920127\n ],\n [\n -76.025390625,\n 43.14909399920127\n ],\n [\n -76.025390625,\n 44.276671273775186\n ],\n [\n -79.91455078125,\n 44.276671273775186\n ],\n [\n -79.91455078125,\n 43.14909399920127\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5968869be4b0d1f9f05f5955","contributors":{"authors":[{"text":"Weidel, Brian 0000-0001-6095-2773 bweidel@usgs.gov","orcid":"https://orcid.org/0000-0001-6095-2773","contributorId":2485,"corporation":false,"usgs":true,"family":"Weidel","given":"Brian","email":"bweidel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":704844,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walsh, Maureen 0000-0001-7846-5025 mwalsh@usgs.gov","orcid":"https://orcid.org/0000-0001-7846-5025","contributorId":3659,"corporation":false,"usgs":true,"family":"Walsh","given":"Maureen","email":"mwalsh@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":704845,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Connerton, Michael J.","contributorId":190416,"corporation":false,"usgs":false,"family":"Connerton","given":"Michael J.","affiliations":[],"preferred":false,"id":704846,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lantry, Brian F. 0000-0001-8797-3910 bflantry@usgs.gov","orcid":"https://orcid.org/0000-0001-8797-3910","contributorId":3435,"corporation":false,"usgs":true,"family":"Lantry","given":"Brian","email":"bflantry@usgs.gov","middleInitial":"F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":704847,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lantry, Jana R.","contributorId":28495,"corporation":false,"usgs":false,"family":"Lantry","given":"Jana","email":"","middleInitial":"R.","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":704848,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Holden, Jeremy P.","contributorId":190415,"corporation":false,"usgs":false,"family":"Holden","given":"Jeremy","email":"","middleInitial":"P.","affiliations":[{"id":16762,"text":"Ontario Ministry of Natural Resources and Forestry","active":true,"usgs":false}],"preferred":false,"id":704849,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Yuille, Michael J.","contributorId":194647,"corporation":false,"usgs":false,"family":"Yuille","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":704850,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":" Hoyle, James A.","contributorId":141108,"corporation":false,"usgs":false,"family":" Hoyle","given":"James A.","affiliations":[{"id":6780,"text":"Ontario Ministry of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":704851,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70189489,"text":"70189489 - 2017 - Behavioral flexibility as a mechanism for coping with climate change","interactions":[],"lastModifiedDate":"2017-12-04T11:40:54","indexId":"70189489","displayToPublicDate":"2017-07-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1701,"text":"Frontiers in Ecology and the Environment","active":true,"publicationSubtype":{"id":10}},"title":"Behavioral flexibility as a mechanism for coping with climate change","docAbstract":"Of the primary responses to contemporary climate change – “move, adapt, acclimate, or die” – that are available to organisms, “acclimate” may be effectively achieved through behavioral modification. Behavioral flexibility allows animals to rapidly cope with changing environmental conditions, and behavior represents an important component of a species’ adaptive capacity in the face of climate change. However, there is currently a lack of knowledge about the limits or constraints on behavioral responses to changing conditions. Here, we characterize the contexts in which organisms respond to climate variability through behavior. First, we quantify patterns in behavioral responses across taxa with respect to timescales, climatic stimuli, life-history traits, and ecology. Next, we identify existing knowledge gaps, research biases, and other challenges. Finally, we discuss how conservation practitioners and resource managers can incorporate an improved understanding of behavioral flexibility into natural resource management and policy decisions.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/fee.1502","usgsCitation":"Beever, E., Hall, L., Varner, J., Loosen, A.E., Dunham, J.B., Gahl, M.K., Smith, F.A., and Lawler, J.J., 2017, Behavioral flexibility as a mechanism for coping with climate change: Frontiers in Ecology and the Environment, v. 15, no. 6, p. 299-308, https://doi.org/10.1002/fee.1502.","productDescription":"10 p.","startPage":"299","endPage":"308","ipdsId":"IP-069304","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":343832,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-10","publicationStatus":"PW","scienceBaseUri":"59688699e4b0d1f9f05f594a","contributors":{"authors":[{"text":"Beever, Erik A. 0000-0002-9369-486X ebeever@usgs.gov","orcid":"https://orcid.org/0000-0002-9369-486X","contributorId":147685,"corporation":false,"usgs":true,"family":"Beever","given":"Erik A.","email":"ebeever@usgs.gov","affiliations":[{"id":5072,"text":"Office of Communication and Publishing","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":704895,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hall, L. Embere","contributorId":194654,"corporation":false,"usgs":false,"family":"Hall","given":"L. Embere","affiliations":[],"preferred":false,"id":704896,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Varner, Johanna","contributorId":147700,"corporation":false,"usgs":false,"family":"Varner","given":"Johanna","email":"","affiliations":[{"id":16911,"text":"Dept. of Biology, University of Utah, Salt Lake City, UT","active":true,"usgs":false}],"preferred":false,"id":704897,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Loosen, Anne E.","contributorId":194655,"corporation":false,"usgs":false,"family":"Loosen","given":"Anne","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":704898,"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":704899,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gahl, Megan K.","contributorId":194656,"corporation":false,"usgs":false,"family":"Gahl","given":"Megan","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":704900,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smith, Felisa A.","contributorId":194657,"corporation":false,"usgs":false,"family":"Smith","given":"Felisa","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":704901,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lawler, Joshua J.","contributorId":73327,"corporation":false,"usgs":false,"family":"Lawler","given":"Joshua","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":704902,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70189424,"text":"70189424 - 2017 - Coupling gene-based and classic veterinary diagnostics improves interpretation of health and immune function in the Agassiz’s desert tortoise (Gopherus agassizii)","interactions":[],"lastModifiedDate":"2017-07-13T08:53:06","indexId":"70189424","displayToPublicDate":"2017-07-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3919,"text":"Conservation Physiology","onlineIssn":"2051-1434","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Coupling gene-based and classic veterinary diagnostics improves interpretation of health and immune function in the Agassiz’s desert tortoise (Gopherus agassizii)","title":"Coupling gene-based and classic veterinary diagnostics improves interpretation of health and immune function in the Agassiz’s desert tortoise (Gopherus agassizii)","docAbstract":"The analysis of blood constituents is a widely used tool to aid in monitoring of animal health and disease. However, classic blood diagnostics (i.e. hematologic and plasma biochemical values) often do not provide sufficient information to determine the state of an animal’s health. Field studies on wild tortoises and other reptiles have had limited success in drawing significant inferences between blood diagnostics and physiological and immunological condition. However, recent research using gene transcription profiling in the threatened Mojave desert tortoise (Gopherus agassizii) has proved useful in identifying immune or physiologic responses and overall health. To improve our understanding of health and immune function in tortoises, we evaluated both standard blood diagnostic (body condition, hematologic, plasma biochemistry values, trace elements, plasma proteins, vitamin A levels) and gene transcription profiles in 21 adult tortoises (11 clinically abnormal; 10 clinically normal) from Clark County, NV, USA. Necropsy and histology evaluations from clinically abnormal tortoises revealed multiple physiological complications, with moderate to severe rhinitis or pneumonia being the primary cause of morbidity in all but one of the examined animals. Clinically abnormal tortoises had increased transcription for four genes (SOD, MyD88, CL and Lep), increased lymphocyte production, biochemical enzymes and organics, trace elements of copper, and decreased numbers of leukocytes. We found significant positive correlations between increased transcription for SOD and increased trace elements for copper, as well as genes MyD88 and Lep with increased inflammation and microbial insults. Improved methods for health assessments are an important element of monitoring tortoise population recovery and can support the development of more robust diagnostic measures for ill animals, or individuals directly impacted by disturbance.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/conphys/cox037","usgsCitation":"Drake, K.K., Bowen, L., Lewison, R.L., Esque, T., Nussear, K., Braun, J., Waters-Dynes, S.C., and Miles, A.K., 2017, Coupling gene-based and classic veterinary diagnostics improves interpretation of health and immune function in the Agassiz’s desert tortoise (Gopherus agassizii): Conservation Physiology, v. 5, no. 1, Article cox037; 17 p., https://doi.org/10.1093/conphys/cox037.","productDescription":"Article cox037; 17 p.","ipdsId":"IP-083337","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":469684,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/conphys/cox037","text":"Publisher Index Page"},{"id":343761,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-16","publicationStatus":"PW","scienceBaseUri":"5967353ce4b0d1f9f05dd7b6","contributors":{"authors":[{"text":"Drake, K. Kristina 0000-0003-0711-7634 kdrake@usgs.gov","orcid":"https://orcid.org/0000-0003-0711-7634","contributorId":3799,"corporation":false,"usgs":true,"family":"Drake","given":"K.","email":"kdrake@usgs.gov","middleInitial":"Kristina","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":704582,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bowen, Lizabeth 0000-0001-9115-4336 lbowen@usgs.gov","orcid":"https://orcid.org/0000-0001-9115-4336","contributorId":4539,"corporation":false,"usgs":true,"family":"Bowen","given":"Lizabeth","email":"lbowen@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":704583,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lewison, Rebecca L.","contributorId":194537,"corporation":false,"usgs":false,"family":"Lewison","given":"Rebecca","email":"","middleInitial":"L.","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":704586,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Esque, Todd C. 0000-0002-4166-6234 tesque@usgs.gov","orcid":"https://orcid.org/0000-0002-4166-6234","contributorId":168763,"corporation":false,"usgs":true,"family":"Esque","given":"Todd C.","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":704581,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nussear, Kenneth","contributorId":194538,"corporation":false,"usgs":false,"family":"Nussear","given":"Kenneth","affiliations":[{"id":24618,"text":"Department of Geography, University of Nevada, Reno, Reno, NV","active":true,"usgs":false}],"preferred":false,"id":704587,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Braun, Josephine","contributorId":194539,"corporation":false,"usgs":false,"family":"Braun","given":"Josephine","affiliations":[{"id":17905,"text":"San Diego Zoo Global, San Diego, CA, USA","active":true,"usgs":false}],"preferred":false,"id":704588,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Waters-Dynes, Shannon C. 0000-0002-9707-4684 swaters@usgs.gov","orcid":"https://orcid.org/0000-0002-9707-4684","contributorId":5826,"corporation":false,"usgs":true,"family":"Waters-Dynes","given":"Shannon","email":"swaters@usgs.gov","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":704584,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Miles, A. Keith 0000-0002-3108-808X keith_miles@usgs.gov","orcid":"https://orcid.org/0000-0002-3108-808X","contributorId":196,"corporation":false,"usgs":true,"family":"Miles","given":"A.","email":"keith_miles@usgs.gov","middleInitial":"Keith","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":704585,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70189423,"text":"70189423 - 2017 - The effects of varying injection rates in Osage County, Oklahoma, on the 2016 Mw5.8 Pawnee earthquake","interactions":[],"lastModifiedDate":"2017-07-12T17:58:31","indexId":"70189423","displayToPublicDate":"2017-07-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The effects of varying injection rates in Osage County, Oklahoma, on the 2016 Mw5.8 Pawnee earthquake","title":"The effects of varying injection rates in Osage County, Oklahoma, on the 2016 Mw5.8 Pawnee earthquake","docAbstract":"The 2016 Mw 5.8 Pawnee earthquake occurred in a region with active wastewater injection into a basal formation group. Prior to the earthquake, fluid injection rates at most wells were relatively steady, but newly collected data show significant increases in injection rate in the years leading up to earthquake. For the same time period, the total volumes of injected wastewater were roughly equivalent between variable‐rate and constant‐rate wells. To understand the possible influence of these changes in injection, we simulate the variable‐rate injection history and its constant‐rate equivalent in a layered poroelastic half‐space to explore the interplay between pore‐pressure effects and poroelastic effects on the fault leading up to the mainshock. In both cases, poroelastic stresses contribute a significant proportion of Coulomb failure stresses on the fault compared to pore‐pressure increases alone, but the resulting changes in seismicity rate, calculated using a rate‐and‐state frictional model, are many times larger when poroelastic effects are included, owing to enhanced stressing rates. In particular, the variable‐rate simulation predicts more than an order of magnitude increase in seismicity rate above background rates compared to the constant‐rate simulation with equivalent volume. The observed cumulative density of earthquakes prior to the mainshock within 10 km of the injection source exhibits remarkable agreement with seismicity predicted by the variable‐rate injection case.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220170003","usgsCitation":"Barbour, A., Norbeck, J.H., and Rubinstein, J.L., 2017, The effects of varying injection rates in Osage County, Oklahoma, on the 2016 Mw5.8 Pawnee earthquake: Seismological Research Letters, v. 88, no. 4, p. 1040-1053, https://doi.org/10.1785/0220170003.","productDescription":"14 p.","startPage":"1040","endPage":"1053","ipdsId":"IP-082545","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":343760,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"88","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-03","publicationStatus":"PW","scienceBaseUri":"5967353ee4b0d1f9f05dd7bb","contributors":{"authors":[{"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":704578,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Norbeck, Jack H.","contributorId":194536,"corporation":false,"usgs":true,"family":"Norbeck","given":"Jack","email":"","middleInitial":"H.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":704580,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rubinstein, Justin L. 0000-0003-1274-6785 jrubinstein@usgs.gov","orcid":"https://orcid.org/0000-0003-1274-6785","contributorId":2404,"corporation":false,"usgs":true,"family":"Rubinstein","given":"Justin","email":"jrubinstein@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":704579,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70189422,"text":"70189422 - 2017 - Ecohydrological role of biological soil crusts across a gradient in levels of development","interactions":[],"lastModifiedDate":"2017-10-08T11:50:25","indexId":"70189422","displayToPublicDate":"2017-07-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"Ecohydrological role of biological soil crusts across a gradient in levels of development","docAbstract":"Though biological soil crusts (biocrusts) form abundant covers in arid and semiarid regions, their competing effects on soil hydrologic conditions are rarely accounted for in models. This study presents the modification of a soil water balance model to account for the presence of biocrusts at different levels of development (LOD) and their impact on one-dimensional hydrologic processes during warm and cold seasons. The model is developed, tested, and applied to study the hydrologic controls of biocrusts in context of a long-term manipulative experiment equipped with meteorological and soil moisture measurements in a Colorado Plateau ecosystem near Moab, Utah. The climate manipulation treatments resulted in distinct biocrust communities, and model performance with respect to soil moisture was assessed in experimental plots with varying LOD as quantified through a field-based roughness index (RI). Model calibration and testing yielded excellent comparisons to observations and smooth variations of biocrust parameters with RI approximated through simple regressions. The model was then used to quantify how LOD affects soil infiltration, evapotranspiration, and runoff under calibrated conditions and in simulation experiments with gradual modifications in biocrust porosity and hydraulic conductivity. Simulation results show that highly developed biocrusts modulate soil moisture nonlinearly with LOD by altering soil infiltration and buffering against evapotranspiration losses, with small impacts on runoff. The nonlinear and threshold variations of the soil water balance in the presence of biocrusts of varying LOD helps explain conflicting outcomes of various field studies and sheds light on the ecohydrological role of biocrusts in arid and semiarid ecosystems.
","language":"English","publisher":"Wiley","doi":"10.1002/eco.1875","usgsCitation":"Whitney, K.M., Vivoni, E.R., Duniway, M.C., Bradford, J.B., Reed, S.C., and Belnap, J., 2017, Ecohydrological role of biological soil crusts across a gradient in levels of development: Ecohydrology, v. 10, no. 7, Article e1875; 18 p., https://doi.org/10.1002/eco.1875.","productDescription":"Article e1875; 18 p.","ipdsId":"IP-077787","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":343759,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","city":"Moab","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.51515197753906,\n 38.652807047773784\n ],\n [\n -109.34829711914062,\n 38.652807047773784\n ],\n [\n -109.34829711914062,\n 38.76318574559655\n ],\n [\n -109.51515197753906,\n 38.76318574559655\n ],\n [\n -109.51515197753906,\n 38.652807047773784\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-26","publicationStatus":"PW","scienceBaseUri":"5967353ee4b0d1f9f05dd7be","contributors":{"authors":[{"text":"Whitney, Kristen M.","contributorId":194535,"corporation":false,"usgs":false,"family":"Whitney","given":"Kristen","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":704573,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vivoni, Enrique R.","contributorId":139052,"corporation":false,"usgs":false,"family":"Vivoni","given":"Enrique","email":"","middleInitial":"R.","affiliations":[{"id":12634,"text":"School of Earth and Space Exploration and School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ","active":true,"usgs":false}],"preferred":false,"id":704574,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":704572,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":704575,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":462,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":704576,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":704577,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70189381,"text":"70189381 - 2017 - Dispersal hazards of Pseudogymnoascus destructans by bats and human activity at hibernacula in summer","interactions":[],"lastModifiedDate":"2023-06-30T14:46:42.911615","indexId":"70189381","displayToPublicDate":"2017-07-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Dispersal hazards of Pseudogymnoascus destructans by bats and human activity at hibernacula in summer","title":"Dispersal hazards of Pseudogymnoascus destructans by bats and human activity at hibernacula in summer","docAbstract":"Bats occupying hibernacula during summer are exposed to Pseudogymnoascus destructans (Pd), the causative agent of white-nose syndrome (WNS), and may contribute to its dispersal. Furthermore, equipment and clothing exposed to cave environments are a potential source for human-assisted spread of Pd. To explore dispersal hazards for Pd during the nonhibernal season, we tested samples that were collected from bats, the environment, and equipment at hibernacula in the eastern US between 18 July–22 August 2012. Study sites included six hibernacula known to harbor bats with Pd with varying winter-count impacts from WNS and two hibernacula (control sites) without prior history of WNS. Nucleic acid from Pd was detected from wing-skin swabs or guano from 40 of 617 bats (7% prevalence), including males and females of five species at five sites where WNS had previously been confirmed as well as from one control site. Analysis of guano collected during summer demonstrated a higher apparent prevalence of Pd among bats (17%, 37/223) than did analysis of wing-skin swabs (1%, 4/617). Viable Pd cultured from wing skin (2%, 1/56) and low recapture rates at all sites suggested bats harboring Pd during summer could contribute to pathogen dispersal. Additionally, Pd DNA was detected on clothing and trapping equipment used inside and near hibernacula, and Pd was detected in sediment more readily than in swabs of hibernaculum walls. Statistically significant differences in environmental abundance of Pd were not detected among sites, but prevalence of Pd differed between sites and among bat species. Overall, bats using hibernacula in summer can harbor Pd on their skin and in their guano, and demonstration of Pd on clothing, traps, and other equipment used at hibernacula during summertime within the WNS-affected region indicates risk for pathogen dispersal during the nonhibernal season.
","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/2016-09-206","usgsCitation":"Ballmann, A., Torkelson, M.R., Bohuski, E.A., Russell, R.E., and Blehert, D.S., 2017, Dispersal hazards of Pseudogymnoascus destructans by bats and human activity at hibernacula in summer: Journal of Wildlife Diseases, v. 53, no. 4, p. 725-735, https://doi.org/10.7589/2016-09-206.","productDescription":"11 p.","startPage":"725","endPage":"735","ipdsId":"IP-079434","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":469685,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7589/2016-09-206","text":"Publisher Index Page"},{"id":343641,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418656,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F78P5XRX","text":"USGS data release","description":"USGS data release","linkHelpText":"WNS Summer Surveillance: DATA"}],"country":"United States","state":"Indiana, Kentucky, Ohio, Tennessee, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.13232421875,\n 36.13787471840729\n ],\n [\n -82.0458984375,\n 36.13787471840729\n ],\n [\n -82.0458984375,\n 39.2832938689385\n ],\n [\n -88.13232421875,\n 39.2832938689385\n ],\n [\n -88.13232421875,\n 36.13787471840729\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"53","issue":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5967353ee4b0d1f9f05dd7c1","contributors":{"authors":[{"text":"Ballmann, Anne 0000-0002-0380-056X aballmann@usgs.gov","orcid":"https://orcid.org/0000-0002-0380-056X","contributorId":140319,"corporation":false,"usgs":true,"family":"Ballmann","given":"Anne","email":"aballmann@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":704438,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Torkelson, Miranda R.","contributorId":194524,"corporation":false,"usgs":false,"family":"Torkelson","given":"Miranda","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":704439,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bohuski, Elizabeth A. 0000-0001-8061-2151 ebohuski@usgs.gov","orcid":"https://orcid.org/0000-0001-8061-2151","contributorId":5890,"corporation":false,"usgs":true,"family":"Bohuski","given":"Elizabeth","email":"ebohuski@usgs.gov","middleInitial":"A.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":704440,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Russell, Robin E. 0000-0001-8726-7303 rerussell@usgs.gov","orcid":"https://orcid.org/0000-0001-8726-7303","contributorId":3998,"corporation":false,"usgs":true,"family":"Russell","given":"Robin","email":"rerussell@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":704441,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blehert, David S. 0000-0002-1065-9760 dblehert@usgs.gov","orcid":"https://orcid.org/0000-0002-1065-9760","contributorId":140397,"corporation":false,"usgs":true,"family":"Blehert","given":"David","email":"dblehert@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":704442,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70189377,"text":"70189377 - 2017 - The long-term legacy of geomorphic and riparian vegetation feedbacks on the dammed Bill Williams River, Arizona, USA","interactions":[],"lastModifiedDate":"2017-07-12T09:18:10","indexId":"70189377","displayToPublicDate":"2017-07-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"The long-term legacy of geomorphic and riparian vegetation feedbacks on the dammed Bill Williams River, Arizona, USA","docAbstract":"On alluvial rivers, fluvial landforms and riparian vegetation communities codevelop as a result of feedbacks between plants and abiotic processes. The influence of vegetation on river channel and floodplain geomorphology can be particularly strong on dammed rivers with altered hydrology and reduced flood disturbance. We used a 56-year series of aerial photos on the dammed Bill Williams River (Arizona, USA) to investigate how (a) different woody riparian vegetation types influence river channel planform and (b) how different fluvial landforms drive the composition of riparian plant communities over time. We mapped vegetation types and geomorphic surfaces and quantified how relations between fluvial and biotic processes covaried over time using linear mixed models. In the decades after the dam was built, woody plant cover within the river's bottomland nearly doubled, narrowing the active channel by 60% and transforming its planform from wide and braided to a single thread and more sinuous channel. Compared with native cottonwood–willow vegetation, nonnative tamarisk locally induced a twofold greater reduction in channel braiding. Vegetation expanded at different rates depending on the type of landform, with tamarisk cover on former high-flow channels increasing 17% faster than cottonwood–willow. Former low-flow channels with frequent inundation supported a greater increase in cottonwood–willow relative to tamarisk. These findings give insight into how feedbacks between abiotic and biotic processes in river channels accelerate and fortify changes triggered by dam construction, creating river systems increasingly distinct from predam ecological communities and landforms, and progressively more resistant to restoration of predam forms and processes.
Red-winged blackbirds (Agelaius phoeniceus) are protected under the Migratory Bird Treaty Act (MBTA), which has provisions against take. Blackbirds may be taken legally without a Federal permit, however, under an existing Depredation Order (50 CFR 21.43), which allows for take of blackbirds that are in the process of doing, or about to do, agricultural damage. Modeling the effect of take on blackbird population allows us to balance the conservation protections of the MBTA with the protection of agricultural interests. A quantitative framework based on harvest theory, demography, and population status has been used to assess the allowable take of a number of species of birds under the MBTA. In this chapter, we calculate allowable levels of take for two populations of red-winged blackbirds in the northern Great Plains from estimates of intrinsic growth rate and population size.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Ecology and management of blackbirds (Icteridae) in North America","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"CRC Press","publisherLocation":"Boca Raton, FL","isbn":"9781498799614","usgsCitation":"Runge, M.C., and Sauer, J.R., 2017, Allowable take of a population of red-winged blackbirds in the northern Great Plains, chap. of Ecology and management of blackbirds (Icteridae) in North America, p. 191-206.","productDescription":"16 p.","startPage":"191","endPage":"206","ipdsId":"IP-080852","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":343970,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":343962,"type":{"id":15,"text":"Index Page"},"url":"https://www.crcpress.com/Ecology-and-Management-of-Blackbirds-Icteridae-in-North-America/Linz-Avery-Dolbeer/p/book/9781498799614"}],"publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"596f1e22e4b0d1f9f0640750","contributors":{"authors":[{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":705298,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sauer, John R. 0000-0002-4557-3019 jrsauer@usgs.gov","orcid":"https://orcid.org/0000-0002-4557-3019","contributorId":146917,"corporation":false,"usgs":true,"family":"Sauer","given":"John","email":"jrsauer@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":705299,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70190049,"text":"70190049 - 2017 - The estimation of growth dynamics for Pomacea maculata from hatchling to adult","interactions":[],"lastModifiedDate":"2017-08-07T16:58:46","indexId":"70190049","displayToPublicDate":"2017-07-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The estimation of growth dynamics for Pomacea maculata from hatchling to adult","title":"The estimation of growth dynamics for Pomacea maculata from hatchling to adult","docAbstract":"Pomacea maculata is a relatively new invasive species to the Gulf Coast region and potentially threatens local agriculture (rice) and ecosystems (aquatic vegetation). The population dynamics of P. maculata have largely been unquantified, and therefore, scientists and field-workers are ill-equipped to accurately project population sizes and the resulting impact of this species. We studied the growth of P. maculata ranging in weights from 6 to 105 g, identifying the sex of the animals when possible. Our studied population had a 4:9 male:female sex ratio. We present the findings from initial analysis of the individual growth data of males and females, from which it was apparent that females were generally larger than males and that small snails grew faster than larger snails. Since efforts to characterize the male and female growth rates from individual data do not yield statistically supported estimates, we present the estimation of several parameterized growth rate functions within a population-level mathematical model. We provide a comparison of the results using these various growth functions and discuss which best characterizes the dynamics of our observed population. We conclude that both males and females exhibit biphasic growth rates, and thus, their growth is size-dependent. Further, our results suggest that there are notable differences between males and females that are important to take into consideration in order to accurately model this species' population dynamics. Lastly, we include preliminary analyses of ongoing experiments to provide initial estimates of growth in the earliest life stages (hatchling to ≈6 g).
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1840","usgsCitation":"Sutton, K.L., Zhao, L., and Carter, J., 2017, The estimation of growth dynamics for Pomacea maculata from hatchling to adult: Ecosphere, v. 8, no. 7, e01840: 22 p., https://doi.org/10.1002/ecs2.1840.","productDescription":"e01840: 22 p.","ipdsId":"IP-081732","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":469683,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1840","text":"Publisher Index Page"},{"id":438268,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7Q23XFZ","text":"USGS data release","linkHelpText":"Data for the estimation of growth dynamics for Pomacea maculata from hatchling to adult, 10/10/13 to 9/25/15"},{"id":344621,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"7","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-28","publicationStatus":"PW","scienceBaseUri":"59897c15e4b09fa1cb0c2bff","contributors":{"authors":[{"text":"Sutton, Karyn L.","contributorId":195516,"corporation":false,"usgs":false,"family":"Sutton","given":"Karyn","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":707324,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhao, Lihong","contributorId":187552,"corporation":false,"usgs":false,"family":"Zhao","given":"Lihong","email":"","affiliations":[],"preferred":false,"id":707325,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carter, Jacoby 0000-0003-0110-0284 carterj@usgs.gov","orcid":"https://orcid.org/0000-0003-0110-0284","contributorId":2399,"corporation":false,"usgs":true,"family":"Carter","given":"Jacoby","email":"carterj@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":707323,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70190128,"text":"70190128 - 2017 - Inland waters and their role in the carbon cycle of Alaska","interactions":[],"lastModifiedDate":"2018-01-30T21:10:04","indexId":"70190128","displayToPublicDate":"2017-07-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Inland waters and their role in the carbon cycle of Alaska","docAbstract":"The magnitude of Alaska (AK) inland waters carbon (C) fluxes is likely to change in the future due to amplified climate warming impacts on the hydrology and biogeochemical processes in high latitude regions. Although current estimates of major aquatic C fluxes represent an essential baseline against which future change can be compared, a comprehensive assessment for AK has not yet been completed. To address this gap, we combined available data sets and applied consistent methodologies to estimate river lateral C export to the coast, river and lake carbon dioxide (CO2) and methane (CH4) emissions, and C burial in lakes for the six major hydrologic regions in the state. Estimated total aquatic C flux for AK was 41 Tg C/yr. Major components of this total flux, in Tg C/yr, were 18 for river lateral export, 17 for river CO2 emissions, and 8 for lake CO2 emissions. Lake C burial offset these fluxes by 2 Tg C/yr. River and lake CH4 emissions were 0.03 and 0.10 Tg C/yr, respectively. The Southeast and South central regions had the highest temperature, precipitation, terrestrial net primary productivity (NPP), and C yields (fluxes normalized to land area) were 77 and 42 g C·m−2·yr−1, respectively. Lake CO2 emissions represented over half of the total aquatic flux from the Southwest (37 g C·m−2·yr−1). The North Slope, Northwest, and Yukon regions had lesser yields (11, 15, and 17 g C·m2·yr−1), but these estimates may be the most vulnerable to future climate change, because of the heightened sensitivity of arctic and boreal ecosystems to intensified warming. Total aquatic C yield for AK was 27 g C·m−2·yr−1, which represented 16% of the estimated terrestrial NPP. Freshwater ecosystems represent a significant conduit for C loss, and a more comprehensive view of land-water-atmosphere interactions is necessary to predict future climate change impacts on the Alaskan ecosystem C balance.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.1552","usgsCitation":"Stackpoole, S.M., Butman, D.E., Clow, D.W., Verdin, K.L., Gaglioti, B.V., Genet, H., and Striegl, R.G., 2017, Inland waters and their role in the carbon cycle of Alaska: Ecological Applications, v. 27, no. 5, p. 1403-1420, https://doi.org/10.1002/eap.1552.","productDescription":"18 p.","startPage":"1403","endPage":"1420","ipdsId":"IP-079185","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":487008,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.1552","text":"Publisher Index Page"},{"id":344775,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"27","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-05","publicationStatus":"PW","scienceBaseUri":"59901398e4b09fa1cb178925","contributors":{"authors":[{"text":"Stackpoole, Sarah M. 0000-0002-5876-4922 sstackpoole@usgs.gov","orcid":"https://orcid.org/0000-0002-5876-4922","contributorId":3784,"corporation":false,"usgs":true,"family":"Stackpoole","given":"Sarah","email":"sstackpoole@usgs.gov","middleInitial":"M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":707588,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Butman, David E.","contributorId":145535,"corporation":false,"usgs":false,"family":"Butman","given":"David","email":"","middleInitial":"E.","affiliations":[{"id":16142,"text":"School of Environmental and Forest Sciences & Environmental Engineering, University of Washington, Seattle","active":true,"usgs":false}],"preferred":false,"id":707589,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clow, David W. 0000-0001-6183-4824 dwclow@usgs.gov","orcid":"https://orcid.org/0000-0001-6183-4824","contributorId":1671,"corporation":false,"usgs":true,"family":"Clow","given":"David","email":"dwclow@usgs.gov","middleInitial":"W.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":707590,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Verdin, Kristine L. 0000-0002-6114-4660 kverdin@usgs.gov","orcid":"https://orcid.org/0000-0002-6114-4660","contributorId":3070,"corporation":false,"usgs":true,"family":"Verdin","given":"Kristine","email":"kverdin@usgs.gov","middleInitial":"L.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":707591,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gaglioti, Benjamin V. 0000-0003-0591-5253 bgaglioti@usgs.gov","orcid":"https://orcid.org/0000-0003-0591-5253","contributorId":4521,"corporation":false,"usgs":true,"family":"Gaglioti","given":"Benjamin","email":"bgaglioti@usgs.gov","middleInitial":"V.","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":707592,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Genet, Hélène","contributorId":195179,"corporation":false,"usgs":false,"family":"Genet","given":"Hélène","affiliations":[],"preferred":false,"id":707593,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Striegl, Robert G. 0000-0002-8251-4659 rstriegl@usgs.gov","orcid":"https://orcid.org/0000-0002-8251-4659","contributorId":1630,"corporation":false,"usgs":true,"family":"Striegl","given":"Robert","email":"rstriegl@usgs.gov","middleInitial":"G.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":false,"id":707594,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70188452,"text":"sim3381 - 2017 - Land area change in coastal Louisiana (1932 to 2016)","interactions":[],"lastModifiedDate":"2017-07-12T10:37:54","indexId":"sim3381","displayToPublicDate":"2017-07-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3381","title":"Land area change in coastal Louisiana (1932 to 2016)","docAbstract":"Coastal Louisiana wetlands are one of the most critically threatened environments in the United States. These wetlands are in peril because Louisiana currently experiences greater coastal wetland loss than all other States in the contiguous United States combined. The analyses of landscape change presented here have utilized historical surveys, aerial, and satellite data to quantify landscape changes from 1932 to 2016. Analyses show that coastal Louisiana has experienced a net change in land area of approximately -4,833 square kilometers (modeled estimate: -5,197 +/- 443 square kilometers) from 1932 to 2016. This net change in land area amounts to a decrease of approximately 25 percent of the 1932 land area. Previous studies have presented linear rates of change over multidecadal time periods which unintentionally suggest that wetland change occurs at a constant rate, although in many cases, wetland change rates vary with time. A penalized regression spline technique was used to determine the model that best fit the data, rather than fitting the data with linear trends. Trend analyses from model fits indicate that coastwide rates of wetland change have varied from -83.5 +/- 11.8 square kilometers per year to -28.01 +/- 16.37 square kilometers per year. To put these numbers into perspective, this equates to long-term average loss rates of approximately an American football field’s worth of coastal wetlands within 34 minutes when losses are rapid to within 100 minutes at more recent, slower rates. Of note is the slowing of the rate of wetland change since its peak in the mid- 1970s. Not only have rates of wetland loss been decreasing since that time, a further rate reduction has been observed since 2010. Possible reasons for this reduction include recovery from lows affected by the hurricanes of 2005 and 2008, the lack of major storms in the past 8 years, a possible slowing of subsidence rates, the reduction in and relocation of oil and gas extraction and infrastructure since the peak of such activities in the late 1960s, and restoration activities. In addition, many wetlands in more exposed positions in the landscape have already been lost. Most notable of the factors listed above is the lack of major storms over the past 8 years. The observed coastwide net “stability” in land area observed over the past 6–8 years does not imply that loss has ceased. Future disturbance events such as a major hurricane impact could change the trajectory of the rates. Sea-level rise is projected to increase at an exponential rate, and that would also expedite the rate of wetland loss.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3381","usgsCitation":"Couvillion, B.R., Beck, Holly, Schoolmaster, Donald, and Fischer, Michelle, 2017, Land area change in coastal Louisiana 1932 to 2016: U.S. Geological Survey Scientific Investigations Map 3381, 16 p. pamphlet, https://doi.org/10.3133/sim3381.","productDescription":"Pamphlet: vi, 16 p.; Map: 80 x 42 inches","onlineOnly":"N","ipdsId":"IP-085820","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":438270,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F74B30JM","text":"USGS data release","linkHelpText":"Land area change in Coastal Louisiana (1932 to 2016) - persistent land change spatial data"},{"id":343518,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3381/sim3381.pdf","text":"Map","size":"11.3 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U.S. Geological Survey
700 Cajundome Blvd.
Lafayette, LA 70506
Using a geology-based assessment methodology, the U.S. Geological Survey estimated mean undiscovered, technically recoverable conventional resources of 1.1 billion barrels of oil and 2.2 trillion cubic feet of gas in the West Korea Bay–North Yellow Sea Basin, North Korea and China.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173041","usgsCitation":"Schenk, C.J., Tennyson, M.E., Mercier, T.J., Hawkins, S.J., Finn, T.M., Gaswirth, S.B., Marra, K.R., Klett, T.R., Le, P.A., Leathers-Miller, H.M., and Woodall, C.A., 2017, Assessment of undiscovered conventional oil and gas resources in the West Korea Bay–North Yellow Sea Basin, North Korea and China, 2017: U.S. Geological Survey Fact Sheet 2017–3041, 2 p., https://doi.org/10.3133/fs20173041.","productDescription":"2 p.","onlineOnly":"N","ipdsId":"IP-085298","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":343503,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3041/coverthb2.jpg"},{"id":343504,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3041/fs20173041.pdf ","text":"Report","size":"372 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017-3041"}],"country":"China, North Korea","otherGeospatial":"North Yellow Sea Basin, West Korea Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 123.00292968749999,\n 37.92686760148135\n ],\n [\n 126.01318359375001,\n 39.57182223734374\n ],\n [\n 126.0186767578125,\n 39.977120098439634\n ],\n [\n 125.595703125,\n 40.15788524950653\n ],\n [\n 125.2880859375,\n 40.06125658140474\n ],\n [\n 121.13525390625,\n 38.59970036588819\n ],\n [\n 121.09130859375,\n 38.272688535980976\n ],\n [\n 121.59667968749999,\n 37.94419750075404\n ],\n [\n 123.00292968749999,\n 37.92686760148135\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
Dams have been a fundamental part of the U.S. national agenda over the past two hundred years. Recently, however, dam removal has emerged as a strategy for addressing aging, obsolete infrastructure and more than 1,100 dams have been removed since the 1970s. However, only 130 of these removals had any ecological or geomorphic assessments, and fewer than half of those included before- and after-removal (BAR) studies. In addition, this growing, but limited collection of dam-removal studies is limited to distinct landscape settings. We conducted a meta-analysis to compare the landscape context of existing and removed dams and assessed the biophysical responses to dam removal for 63 BAR studies. The highest concentration of removed dams was in the Northeast and Upper Midwest, and most have been removed from 3rd and 4th order streams, in low-elevation (< 500 m) and low-slope (< 5%) watersheds that have small to moderate upstream watershed areas (10–1000 km2) with a low risk of habitat degradation. Many of the BAR-studied removals also have these characteristics, suggesting that our understanding of responses to dam removals is based on a limited range of landscape settings, which limits predictive capacity in other environmental settings. Biophysical responses to dam removal varied by landscape cluster, indicating that landscape features are likely to affect biophysical responses to dam removal. However, biophysical data were not equally distributed across variables or clusters, making it difficult to determine which landscape features have the strongest effect on dam-removal response. To address the inconsistencies across dam-removal studies, we provide suggestions for prioritizing and standardizing data collection associated with dam removal activities.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0180107","usgsCitation":"Foley, M.M., Magilligan, F.J., Torgersen, C.E., Major, J.J., Anderson, C.W., Connolly, P., Wieferich, D.J., Shafroth, P.B., Evans, J.E., Infante, D.M., and Craig, L., 2017, Landscape context and the biophysical response of rivers to dam removal in the United States: PLoS ONE, v. 7, no. 12, e0180107: 24 p., https://doi.org/10.1371/journal.pone.0180107.","productDescription":"e0180107: 24 p.","ipdsId":"IP-084261","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and 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\"}}]}","volume":"7","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-10","publicationStatus":"PW","scienceBaseUri":"5965b1b5e4b0d1f9f05b3790","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":704106,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Magilligan, Francis J.","contributorId":194434,"corporation":false,"usgs":false,"family":"Magilligan","given":"Francis","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":704107,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Torgersen, Christian E. 0000-0001-8325-2737 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dwieferich@usgs.gov","orcid":"https://orcid.org/0000-0003-1554-7992","contributorId":176205,"corporation":false,"usgs":true,"family":"Wieferich","given":"Daniel","email":"dwieferich@usgs.gov","middleInitial":"J.","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true},{"id":5069,"text":"Office of the AD Core Science Systems","active":true,"usgs":true}],"preferred":true,"id":704112,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Shafroth, Patrick B. 0000-0002-6064-871X shafrothp@usgs.gov","orcid":"https://orcid.org/0000-0002-6064-871X","contributorId":2000,"corporation":false,"usgs":true,"family":"Shafroth","given":"Patrick","email":"shafrothp@usgs.gov","middleInitial":"B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":704113,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Evans, James E.","contributorId":194435,"corporation":false,"usgs":false,"family":"Evans","given":"James","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":704114,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Infante, Dana M.","contributorId":146114,"corporation":false,"usgs":false,"family":"Infante","given":"Dana","email":"","middleInitial":"M.","affiliations":[{"id":16583,"text":"Department of Fisheries and Wildlife, 480 Wilson Rd. 13 Natural Resources Building, Michigan State University, East Lansing, MI 48824","active":true,"usgs":false}],"preferred":false,"id":704115,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Craig, Laura","contributorId":173675,"corporation":false,"usgs":false,"family":"Craig","given":"Laura","affiliations":[{"id":27270,"text":"American Rivers","active":true,"usgs":false}],"preferred":false,"id":704143,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70189326,"text":"70189326 - 2017 - Revised tephra volumes for Cascade Range volcanoes","interactions":[],"lastModifiedDate":"2017-07-11T13:07:21","indexId":"70189326","displayToPublicDate":"2017-07-11T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Revised tephra volumes for Cascade Range volcanoes","docAbstract":"Isopach maps from tephra eruptions from Mount St. Helens were reported in Carey et al. (1995) and for tephra eruptions from Glacier Peak in Gardner et al. (1998). For exponential thinning, the isopach data only define a single slope on a log thickness versus square root of area plot. Carey et al. (1995) proposed a model that was used to estimate a second slope, and volumes were presented in both studies using this model. A study by Sulpizio (2005) for estimating the second slope and square root of area where the lines intersect involves a systematic analysis of many eruptions to provide correlation equations. The purpose of this paper is to recalculate the volumes of Cascades eruptions and compare results from the two methods. In order to gain some perspective on the methods for estimating the second slope, we use data for thickness versus distance beyond the last isopach that are available for some of the larger eruptions in the Cascades. The thickness versus square root of area method is extended to thickness versus distance by developing an approximate relation between the two assuming elliptical isopachs with the source at one of the foci. Based on the comparisons made between the Carey et al. (1995) and Sulpizio (2005) methods, it is felt that the later method provides a better estimate of the second slope. For Mount St. Helens, the estimates of total volume using the Sulpizio (2005) method are generally smaller than those using the Carey et al. (1995) method. For the volume estimates of Carey et al. (1995), the volume of the May 18, 1980, eruption of Mount St. Helens is smaller than six of the eight previous eruptions. With the new volumes using the Sulpizio (2005) method, the 1980 eruption is smaller in volume than the upper end of the range for only three of the layers (Wn, Ye, and Yn) and is the same size as layer We. Thus the 1980 eruption becomes representative of the mid-range of volumes rather than being in the lower range.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2017.04.021","usgsCitation":"Nathenson, M., 2017, Revised tephra volumes for Cascade Range volcanoes: Journal of Volcanology and Geothermal Research, v. 341, p. 42-52, https://doi.org/10.1016/j.jvolgeores.2017.04.021.","productDescription":"11 p.","startPage":"42","endPage":"52","ipdsId":"IP-082574","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":343573,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Cascade Range volcanoes","volume":"341","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5965b1b4e4b0d1f9f05b378e","contributors":{"authors":[{"text":"Nathenson, Manuel 0000-0002-5216-984X mnathnsn@usgs.gov","orcid":"https://orcid.org/0000-0002-5216-984X","contributorId":1358,"corporation":false,"usgs":true,"family":"Nathenson","given":"Manuel","email":"mnathnsn@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":704187,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70188613,"text":"sir20175066 - 2017 - Synthesis of data from high-frequency nutrient and associated biogeochemical monitoring for the Sacramento–San Joaquin Delta, northern California","interactions":[],"lastModifiedDate":"2017-07-12T09:16:30","indexId":"sir20175066","displayToPublicDate":"2017-07-11T00:00:00","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":"2017-5066","title":"Synthesis of data from high-frequency nutrient and associated biogeochemical monitoring for the Sacramento–San Joaquin Delta, northern California","docAbstract":"This report is the second in a series of three reports that provide information about high-frequency (HF) nutrient and biogeochemical monitoring in the Sacramento–San Joaquin Delta of northern California (Delta). The purpose of this report is to synthesize the data available from a nutrient and water-quality HF (about every 15 minutes) monitoring network operated by the U.S. Geological Survey in the northern Delta. In this report, we describe the network and focus on the purpose of each station. We then present and discuss the available data, at various timescales—first at the monthly, seasonal, and inter-annual timescales, and second, for comparison, at the tidal and event timescales. As expected, we determined that there is substantial variability in nitrate-N concentrations at short timescales within hours, but also significant variability at longer timescales such as months or years. Resolving this variability is made possible by the HF data, with the largest variability caused by storms, tides, and diel biological processes. Given this large temporal variability, calculations of cumulative nutrient fluxes (for example, daily, monthly, or annual loads) is difficult without HF data. For example, in the Cache Slough, calculation of the annual load without the tidal variability resulted in a 30 percent underestimation of the true annual load value. We conclude that HF measurements are important for accurate determination of fluxes and loads in tidal environments, but, more importantly, provide important insights into processes and rates of nutrient cycling.
This report, along with the other two reports of this series (Bergamaschi and others, 2017; Kraus, Bergamaschi, and others, 2017), was drafted in cooperation with the Delta Regional Monitoring Program to help scientists, managers, and planners understand how HF data improve our understanding of nutrient sources and sinks, drivers, and effects in the Delta. The first report in the series (Kraus, Bergamaschi, and others, 2017) provides an introduction to the reasons for and fundamental concepts behind using HF monitoring measurements, including a brief summary of nutrient status and trends in the Delta and an extensive literature review showing how and where other research and monitoring programs have used HF monitoring to improve our understanding of nutrient cycling. The report covers the various technologies available for HF nutrient monitoring and presents the different ways HF monitoring instrumentation may be used for fixed station and spatial assessments. Finally, it presents numerous examples of how HF measurements are currently (2017) being used in the Delta to examine how nutrients and nutrient cycling are related to aquatic habitat conditions.
The third report in the series (Bergamaschi and others, 2017) provides the background, principles, and considerations for designing an HF nutrient-monitoring network for the Delta to address high-priority, nutrient-management questions. The report starts with discussion of the high‑priority management questions to be addressed, continues through discussion of the questions and considerations that place demands and constraints on network design, discusses the principles applicable to network design, and concludes with the presentation of three example nutrient-monitoring network designs for the Delta, proposed to address high-priority questions identified by the Delta Regional Monitoring Program (Delta Regional Monitoring Program Technical Advisory Committee, 2015).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175066","collaboration":"Prepared in cooperation with the Delta Regional Monitoring Program","usgsCitation":"Downing, B.D., Bergamaschi, B.A., and Kraus, T.E.C., 2017, Synthesis of data from high-frequency nutrient and associated biogeochemical monitoring for the Sacramento–San Joaquin Delta, northern California: U.S. Geological Survey Scientific Investigations Report 2017–5066, 28 p., https://doi.org/10.3133/sir20175066.","productDescription":"vi, 28 p.","onlineOnly":"Y","ipdsId":"IP-081533","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":343628,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5066/sir20175066.pdf","text":"Report","size":"7.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5066"},{"id":343629,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175058","text":"SIR 2017–5058 —","description":"SIR 2017-5058","linkHelpText":"Designing a High-Frequency Nutrient and Biogeochemical Monitoring Network for the Sacramento–San Joaquin Delta, Northern California"},{"id":343627,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5066/coverthb.jpg"},{"id":343630,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175071","text":"SIR 2017–5071 —","description":"SIR 2017-5071","linkHelpText":"An Introduction to High-Frequency Nutrient and Biogeochemical Monitoring for the Sacramento–San Joaquin Delta, Northern California"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.15,\n 37.6\n ],\n [\n -121.15,\n 37.6\n ],\n [\n -121.15,\n 38.61\n ],\n [\n -122.15,\n 38.61\n ],\n [\n -122.15,\n 37.6\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
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California State University Placer Hall
6000 J Street
Sacramento, California 95819-6129
This report is the first in a series of three reports that provide information about high-frequency (HF) nutrient and biogeochemical monitoring in the Sacramento–San Joaquin Delta of northern California (Delta). This first report provides an introduction to the reasons for and fundamental concepts behind collecting HF measurements, and describes the benefits associated with a real-time, continuous, HF, multi-parameter water quality monitoring station network that is co-located with flow stations. It then provides examples of how HF nutrient measurements have improved our understating of nutrient sources and cycling in aquatic systems worldwide, followed by specific examples from the Delta. These examples describe the ways in which HF instrumentation may be used for both fixed-station and spatial assessments. The overall intent of this document is to describe how HF measurements currently (2017) are being used in the Delta to examine the relationship between nutrient concentrations, nutrient cycling, and aquatic habitat conditions.
The second report in the series (Downing and others, 2017) summarizes information about HF nutrient and associated biogeochemical monitoring in the northern Delta. The report synthesizes data available from the nutrient and water quality monitoring network currently operated by the U.S. Geological Survey in this ecologically important region of the Delta. In the report, we present and discuss the available data at various timescales—first, at the monthly, seasonal, and inter-annual timescales; and, second, for comparison, at the tidal and event (for example, storms, reservoir releases, phytoplankton blooms) timescales. As expected, we determined that there is substantial variability in nitrate concentrations at short timescales within hours, but also significant variability at longer timescales such as months or years. This multi-scale, high variability affects calculation of fluxes and loads, indicating that HF monitoring is necessary for understanding and assessing flux-based processes and outcomes in tidal environments, such as the Delta.
The third report in the series (Bergamaschi and others, 2017) provides information about how to design HF nutrient and biogeochemical monitoring for assessment of nutrient inputs and dynamics in the Delta. The report provides background, principles, and considerations for designing an HF nutrient-monitoring network for the Sacramento–San Joaquin Delta to address high-priority, nutrient-management questions. The report starts with high-priority management questions to be addressed, continues with questions and considerations that place demands and constraints on network design, discusses the principles applicable to network design, and concludes with the presentation of three example nutrient‑monitoring network designs for the Delta. For the three example networks, we assess how they would address high-priority questions identified by the Delta Regional Monitoring Program (Delta Regional Monitoring Program Technical Advisory Committee, 2015).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175071","collaboration":"Prepared in cooperation with the Delta Regional Monitoring Program","usgsCitation":"Kraus, T.E.C., Bergamaschi, B.A., and Downing, B.D., 2017, An introduction to high-frequency nutrient and biogeochemical monitoring for the Sacramento–San Joaquin Delta, northern California: U.S. Geological Survey Scientific Investigations Report 2017–5071, 41 p., https://doi.org/10.3133/sir20175071.","productDescription":"vi, 41 p.","onlineOnly":"Y","ipdsId":"IP-081539","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":343632,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175058","text":"SIR 2017–5058 —","description":"SIR 2017-5058","linkHelpText":"Designing a High-Frequency Nutrient and Biogeochemical Monitoring Network for the Sacramento–San Joaquin Delta, Northern California"},{"id":343624,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5071/coverthb.jpg"},{"id":343625,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5071/sir20175071.pdf","text":"Report","size":"6.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5071"},{"id":343633,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175066","text":"SIR 2017–5066 —","description":"SIR 2017-5066","linkHelpText":"Synthesis of Data from High-Frequency Nutrient and Associated Biogeochemical Monitoring for the Sacramento–San Joaquin Delta, Northern California"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.15,\n 37.6\n ],\n [\n -121.15,\n 37.6\n ],\n [\n -121.15,\n 38.61\n ],\n [\n -122.15,\n 38.61\n ],\n [\n -122.15,\n 37.6\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
California State University Placer Hall
6000 J Street
Sacramento, California 95819-6129
The inland extent of saltwater at the base of the Biscayne aquifer in the Model Land Area of Miami-Dade County, Florida, was mapped in 2011. Since that time, the saltwater interface has continued to move inland. The interface is near several active well fields; therefore, an updated approximation of the inland extent of saltwater and an improved understanding of the rate of movement of the saltwater interface are necessary. A geographic information system was used to create a map using the data collected by the organizations that monitor water salinity in this area. An average rate of saltwater interface movement of 140 meters per year was estimated by dividing the distance between two monitoring wells (TPGW-7L and Sec34-MW-02-FS) by the travel time. The travel time was determined by estimating the dates of arrival of the saltwater interface at the wells and computing the difference. This estimate assumes that the interface is traveling east to west between the two monitoring wells. Although monitoring is spatially limited in this area and some of the wells are not ideally designed for salinity monitoring, the monitoring network in this area is improving in spatial distribution and most of the new wells are well designed for salinity monitoring. The approximation of the inland extent of the saltwater interface and the estimated rate of movement of the interface are dependent on existing data. Improved estimates could be obtained by installing uniformly designed monitoring wells in systematic transects extending landward of the advancing saltwater interface.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3380","collaboration":"Prepared in cooperation with Miami-Dade County","usgsCitation":"Prinos, S.T., 2017, Map of the approximate inland extent of saltwater at the base of the Biscayne aquifer in the Model Land Area of Miami-Dade County, Florida, 2016: U.S. Geological Survey Scientific Investigations Map 3380, 8-p. pamphlet, 1 sheet, https://doi.org/10.3133/sim3380.","productDescription":"Pamphlet: vi, 8 p.; Sheet: 20.00 x 19.64 inches; Data Release","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-080722","costCenters":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"links":[{"id":343395,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7R78CF8","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Data pertaining to mapping the approximate inland extent of saltwater at the base of the Biscayne aquifer in the Model Land Area of Miami-Dade County, Florida, 2016"},{"id":343258,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3380/coverthb.jpg"},{"id":343259,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3380/sim3380.pdf","text":"Map","size":"867 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3380"},{"id":343260,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3380/sim3380_pamphlet.pdf","text":"Pamphlet","size":"503 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3380 Pamphlet"}],"country":"United States","state":"Florida","county":"Miami-Dade County","otherGeospatial":"Biscayne Aquifer, Model Land Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.595703125,\n 25.243453810607868\n ],\n [\n -80.25787353515625,\n 25.243453810607868\n ],\n [\n -80.25787353515625,\n 25.58456258101669\n ],\n [\n -80.595703125,\n 25.58456258101669\n ],\n [\n -80.595703125,\n 25.243453810607868\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
This report is the third in a series of three reports that provide information about how high-frequency (HF) nutrient monitoring may be used to assess nutrient inputs and dynamics in the Sacramento–San Joaquin Delta, California (Delta). The purpose of this report is to provide the background, principles, and considerations for designing an HF nutrient-monitoring network for the Delta to address high-priority, nutrient-management questions. The report starts with discussion of the high-priority management questions to be addressed, continues through discussion of the questions and considerations that place demands and constraints on network design, discusses the principles applicable to network design, and concludes with the presentation of three example nutrient-monitoring network designs for the Delta. For three example network designs, we assess how they would address high-priority questions that have been identified by the Delta Regional Monitoring Program (Delta Regional Monitoring Program Technical Advisory Committee, 2015).
This report, along with the other two reports of this series (Kraus and others, 2017; Downing and others, 2017), was drafted in cooperation with the Delta Regional Monitoring Program to help scientists, managers, and planners understand how HF data improve our understanding of nutrient sources and sinks, drivers, and effects in the Delta. The first report in the series (Kraus and others, 2017) provides an introduction to the reasons for and fundamental concepts behind using HF monitoring measurements, including a brief summary of nutrient status and trends in the Delta and an extensive literature review showing how and where other research and monitoring programs have used HF monitoring to improve our understanding of nutrient cycling. The report covers the various technologies available for HF nutrient monitoring and presents the different ways HF monitoring instrumentation may be used for both fixed station and spatial assessments. Finally, it presents numerous examples of how HF measurements are currently (2017) being used in the Delta to examine how nutrients and nutrient cycling are related to aquatic habitat conditions.
The second report in the series (Downing and others, 2017) summarizes information about HF nutrient and associated biogeochemical monitoring in the north Delta. The report synthesizes data available from the nutrient and water quality monitoring network currently (2017) operated by the U.S. Geological Survey in this ecologically important region of the Delta. In the report, we present and discuss the available data at various timescales—first at the monthly, seasonal, and inter-annual timescales; and, second, for comparison, at the tidal and event timescales. As expected, we determined that there is substantial variability in nitrate concentrations at short timescales, such as within a few hours, but also significant variability at longer timescales such as months or years. This high variability affects calculation of fluxes and loads, indicating that HF monitoring is necessary for understanding and assessing flux-based processes and outcomes in Delta tidal environments.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175058","collaboration":"Prepared in cooperation with the Delta Regional Monitoring Program","usgsCitation":"Bergamaschi, B.A., Downing, B.D., Kraus, T.E.C., and Pellerin, B.A., 2017, Designing a high-frequency nutrient and biogeochemical monitoring network for the Sacramento–San Joaquin Delta, northern California: U.S. Geological Survey Scientific Investigations Report 2017–5058, 40 p., https://doi.org/10.3133/sir20175058.","productDescription":"v, 40 p.","onlineOnly":"Y","ipdsId":"IP-070995","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":343622,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5058/coverthb.jpg"},{"id":343623,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5058/sir20175058.pdf","text":"Report","size":"7.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5058"},{"id":343634,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175066","text":"SIR 2017–5066 —","description":"SIR 2017-5066","linkHelpText":"Synthesis of Data from High-Frequency Nutrient and Associated Biogeochemical Monitoring for the Sacramento–San Joaquin Delta, Northern California"},{"id":343635,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175071","text":"SIR 2017–5071 —","description":"SIR 2017-5071","linkHelpText":"An Introduction to High-Frequency Nutrient and Biogeochemical Monitoring for the Sacramento–San Joaquin Delta, Northern California"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.15,\n 37.6\n ],\n [\n -121.15,\n 37.6\n ],\n [\n -121.15,\n 38.61\n ],\n [\n -122.15,\n 38.61\n ],\n [\n -122.15,\n 37.6\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
California State University Placer Hall
6000 J Street
Sacramento, California 95819-6129