Using three resolutions of the Lyon-Fedder-Mobarry global magnetosphere-ionosphere model (LFM) and the Weimer 2005 empirical model we examine the structure of the high latitude field-aligned current patterns. Each resolution was run for the entire Whole Heliosphere Interval which contained two high speed solar wind streams and modest interplanetary magnetic field strengths. Average states of the field-aligned current (FAC) patterns for 8 interplanetary magnetic field clock angle directions are computed using data from these runs. Generally speaking the patterns obtained agree well with results obtained from the Weimer 2005 computing using the solar wind and IMF conditions that correspond to each bin. As the simulation resolution increases the currents become more intense and narrow. A machine learning analysis of the FAC patterns shows that the ratio of Region 1 (R1) to Region 2 (R2) currents decreases as the simulation resolution increases. This brings the simulation results into better agreement with observational predictions and the Weimer 2005 model results. The increase in R2 current strengths also results in the cross polar cap potential (CPCP) pattern being concentrated in higher latitudes. Current-voltage relationships between the R1 and CPCP are quite similar at the higher resolution indicating the simulation is converging on a common solution. We conclude that LFM simulations are capable of reproducing the statistical features of FAC patterns.
","language":"English","publisher":"Springer","doi":"10.1007/s11214-016-0271-2","usgsCitation":"Wiltberger, M., Rigler, E.J., Merkin, V., and Lyon, J.G., 2016, Structure of high latitude currents in global magnetospheric-ionospheric models: Space Science Reviews, v. 206, no. 1, p. 575-598, https://doi.org/10.1007/s11214-016-0271-2.","productDescription":"24 p.","startPage":"575","endPage":"598","ipdsId":"IP-077646","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":336986,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"206","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-12","publicationStatus":"PW","scienceBaseUri":"58bfd4f5e4b014cc3a3ba4c4","contributors":{"authors":[{"text":"Wiltberger, M","contributorId":187628,"corporation":false,"usgs":false,"family":"Wiltberger","given":"M","affiliations":[],"preferred":false,"id":681102,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rigler, E. J.","contributorId":187639,"corporation":false,"usgs":false,"family":"Rigler","given":"E.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":681103,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Merkin, V","contributorId":187629,"corporation":false,"usgs":false,"family":"Merkin","given":"V","email":"","affiliations":[],"preferred":false,"id":681104,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lyon, J. G","contributorId":187630,"corporation":false,"usgs":false,"family":"Lyon","given":"J.","email":"","middleInitial":"G","affiliations":[],"preferred":false,"id":681105,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70184330,"text":"70184330 - 2016 - Predicting arsenic in drinking water wells of the Central Valley, California","interactions":[],"lastModifiedDate":"2018-09-12T16:43:45","indexId":"70184330","displayToPublicDate":"2016-07-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Predicting arsenic in drinking water wells of the Central Valley, California","docAbstract":"Probabilities of arsenic in groundwater at depths used for domestic and public supply in the Central Valley of California are predicted using weak-learner ensemble models (boosted regression trees, BRT) and more traditional linear models (logistic regression, LR). Both methods captured major processes that affect arsenic concentrations, such as the chemical evolution of groundwater, redox differences, and the influence of aquifer geochemistry. Inferred flow-path length was the most important variable but near-surface-aquifer geochemical data also were significant. A unique feature of this study was that previously predicted nitrate concentrations in three dimensions were themselves predictive of arsenic and indicated an important redox effect at >10 μg/L, indicating low arsenic where nitrate was high. Additionally, a variable representing three-dimensional aquifer texture from the Central Valley Hydrologic Model was an important predictor, indicating high arsenic associated with fine-grained aquifer sediment. BRT outperformed LR at the 5 μg/L threshold in all five predictive performance measures and at 10 μg/L in four out of five measures. BRT yielded higher prediction sensitivity (39%) than LR (18%) at the 10 μg/L threshold–a useful outcome because a major objective of the modeling was to improve our ability to predict high arsenic areas.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.6b01914","usgsCitation":"Ayotte, J.D., Nolan, B.T., and Gronberg, J.M., 2016, Predicting arsenic in drinking water wells of the Central Valley, California: Environmental Science & Technology, v. 50, no. 14, p. 7555-7563, https://doi.org/10.1021/acs.est.6b01914.","productDescription":"9 p.","startPage":"7555","endPage":"7563","ipdsId":"IP-074943","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":336970,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Central Valley","volume":"50","issue":"14","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-11","publicationStatus":"PW","scienceBaseUri":"58bfd4f6e4b014cc3a3ba4c8","contributors":{"authors":[{"text":"Ayotte, Joseph D. 0000-0002-1892-2738 jayotte@usgs.gov","orcid":"https://orcid.org/0000-0002-1892-2738","contributorId":149619,"corporation":false,"usgs":true,"family":"Ayotte","given":"Joseph","email":"jayotte@usgs.gov","middleInitial":"D.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":681021,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nolan, Bernard T. 0000-0002-6945-9659 btnolan@usgs.gov","orcid":"https://orcid.org/0000-0002-6945-9659","contributorId":2190,"corporation":false,"usgs":true,"family":"Nolan","given":"Bernard","email":"btnolan@usgs.gov","middleInitial":"T.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":681022,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gronberg, JoAnn M. 0000-0003-4822-7434 jmgronbe@usgs.gov","orcid":"https://orcid.org/0000-0003-4822-7434","contributorId":3548,"corporation":false,"usgs":true,"family":"Gronberg","given":"JoAnn","email":"jmgronbe@usgs.gov","middleInitial":"M.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":681023,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70193671,"text":"70193671 - 2016 - A long-term study of ecological impacts of river channelization on the population of an endangered fish: Lessons learned for assessment and restoration","interactions":[],"lastModifiedDate":"2017-11-13T14:13:43","indexId":"70193671","displayToPublicDate":"2016-07-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"A long-term study of ecological impacts of river channelization on the population of an endangered fish: Lessons learned for assessment and restoration","docAbstract":"Projects to assess environmental impact or restoration success in rivers focus on project-specific questions but can also provide valuable insights for future projects. Both restoration actions and impact assessments can become “adaptive” by using the knowledge gained from long-term monitoring and analysis to revise the actions, monitoring, conceptual model, or interpretation of findings so that subsequent actions or assessments are better informed. Assessments of impact or restoration success are especially challenging when the indicators of interest are imperiled species and/or the impacts being addressed are complex. From 1997 to 2015, we worked closely with two federal agencies to monitor habitat availability for and population density of Roanoke logperch (Percina rex), an endangered fish, in a 24-km-long segment of the upper Roanoke River, VA. We primarily used a Before-After-Control-Impact analytical framework to assess potential impacts of a river channelization project on the P. rex population. In this paper, we summarize how our extensive monitoring facilitated the evolution of our (a) conceptual understanding of the ecosystem and fish population dynamics; (b) choices of ecological indicators and analytical tools; and (c) conclusions regarding the magnitude, mechanisms, and significance of observed impacts. Our experience with this case study taught us important lessons about how to adaptively develop and conduct a monitoring program, which we believe are broadly applicable to assessments of environmental impact and restoration success in other rivers. In particular, we learned that (a) pre-treatment planning can enhance monitoring effectiveness, help avoid unforeseen pitfalls, and lead to more robust conclusions; (b) developing adaptable conceptual and analytical models early was crucial to organizing our knowledge, guiding our study design, and analyzing our data; (c) catchment-wide processes that we did not monitor, or initially consider, had profound implications for interpreting our findings; and (d) using multiple analytical frameworks, with varying assumptions, led to clearer interpretation of findings than the use of a single framework alone. Broader integration of these guiding principles into monitoring studies, though potentially challenging, could lead to more scientifically defensible assessments of project effects.
","language":"English","publisher":"MDPI","doi":"10.3390/w8060240","usgsCitation":"Roberts, J.H., Anderson, G.B., and Angermeier, P.L., 2016, A long-term study of ecological impacts of river channelization on the population of an endangered fish: Lessons learned for assessment and restoration: Water, v. 8, no. 6, p. 1-38, https://doi.org/10.3390/w8060240.","productDescription":"Article 240; 38 p.","startPage":"1","endPage":"38","ipdsId":"IP-073154","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":470796,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w8060240","text":"Publisher Index Page"},{"id":348710,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-03","publicationStatus":"PW","scienceBaseUri":"5a60fd1fe4b06e28e9c24779","contributors":{"authors":[{"text":"Roberts, James H.","contributorId":83811,"corporation":false,"usgs":true,"family":"Roberts","given":"James","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":721841,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Gregory B.","contributorId":65988,"corporation":false,"usgs":true,"family":"Anderson","given":"Gregory","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":721842,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Angermeier, Paul L. 0000-0003-2864-170X biota@usgs.gov","orcid":"https://orcid.org/0000-0003-2864-170X","contributorId":166679,"corporation":false,"usgs":true,"family":"Angermeier","given":"Paul","email":"biota@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":719847,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70170965,"text":"sir20165060 - 2016 - Flood-inundation maps for Lake Champlain in Vermont and in northern Clinton County, New York","interactions":[{"subject":{"id":70170965,"text":"sir20165060 - 2016 - Flood-inundation maps for Lake Champlain in Vermont and in northern Clinton County, New York","indexId":"sir20165060","publicationYear":"2016","noYear":false,"title":"Flood-inundation maps for Lake Champlain in Vermont and in northern Clinton County, New York"},"predicate":"SUPERSEDED_BY","object":{"id":70202005,"text":"sir20185169 - 2019 - Flood-inundation maps for Lake Champlain in Vermont and New York","indexId":"sir20185169","publicationYear":"2019","noYear":false,"title":"Flood-inundation maps for Lake Champlain in Vermont and New York"},"id":1}],"supersededBy":{"id":70202005,"text":"sir20185169 - 2019 - Flood-inundation maps for Lake Champlain in Vermont and New York","indexId":"sir20185169","publicationYear":"2019","noYear":false,"title":"Flood-inundation maps for Lake Champlain in Vermont and New York"},"lastModifiedDate":"2022-11-02T14:53:45.691442","indexId":"sir20165060","displayToPublicDate":"2016-06-30T14:00:00","publicationYear":"2016","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":"2016-5060","title":"Flood-inundation maps for Lake Champlain in Vermont and in northern Clinton County, New York","docAbstract":"Digital flood-inundation maps for an approximately100-mile length of Lake Champlain in Addison, Chittenden, Franklin, and Grand Isle Counties in Vermont and northern Clinton County in New York were created by the U.S. Geological Survey (USGS) in cooperation with the International Joint Commission (IJC). The flood-inundationmaps, which can be accessed through the International Joint Commission (IJC) Web site at http://www.ijc.org/en_/, depict estimates of the areal extent flooding correspondingto selected water levels (stages) at the USGS lake gage on the Richelieu River (Lake Champlain) at Rouses Point, N.Y. (station number 04295000). In this study, wind and seiche effects (standing oscillating wave with a long wavelength) were not taken into account and the flood-inundation mapsreflect 11 stages (elevations) for Lake Champlain that are static for the study length of the lake. Near-real-time stages at this lake gage, and others on Lake Champlain, may be obtained on the Internet from the USGS National Water Information System at http://waterdata.usgs.gov/ or the National Weather Service Advanced Hydrologic Prediction Service at http:/water.weather.gov/ahps/, which also forecasts flood hydrographs at the Richelieu River (Lake Champlain) at Rouses Point.
Static flood boundary extents were determined for LakeChamplain in Addison, Chittenden, Franklin, and Grand Isle Counties in Vermont and northern Clinton County in New York using recently acquired (2013–2014) lidar (light detection and ranging) and may be referenced to any of the five USGS lake gages on Lake Champlain. Of these five lakgages, USGS lake gage 04295000, Richelieu River (Lake Champlain) at Rouses Point, N.Y., is the only USGS lake gage that is also a National Weather Service prediction location. Flood boundary extents for the Lake Champlain static flood-inundation map corresponding to the May 201 flood(103.2 feet [ft], National Geodetic Vertical Datum [NGVD] 29) were evaluated by comparing these boundary extents against the inundation area extents determined for the May 2011 flood (which incorporated documented high-water marksfrom the flood of May 201) (Bjerklie and others, 2014).
A digital elevation model (DEM) was created by USGS, within a geographic information system (GIS), from the recently flown and processed light detection and ranging(lidar) data (2013–2014) in Vermont and the lake shore area of northern Clinton County in New York. The lidar data have a vertical accuracy of 0.3 to 0.6-ft (9.6 to 18.0-centimeters [cm]) and a horizontal resolution of 2.3 to 4.6 ft (0.7 to 1.4 meters). This DEM was used in determining the floodboundary for 11 flood stages at 0.5-ft intervals from 100.0 to104.0 ft (NGVD 29) and 1-ft intervals from 104.0 to 106.0 ft (NGVD 29) as referenced to the USGS lake gage 04295000, Richelieu River (Lake Champlain) at Rouses Point, N.Y. In addition, the May 2011 flood-inundation area for elevation103.20 ft (NGVD 29) (102.77 ft, North American Vertical Datum [NAVD] 88) was determined from this DEM. The May 2011 flood is the highest recorded lake water level (stage)at the Rouses Point, N.Y., lake gage. Flood stages greater than 101.5 ft (NGVD 29) exceed the “major flood stage”as defined by the NationalWeather Service for USGS lake gage 04295000.
The availability of these maps, along with Internet information regarding current stage from the USGS lake gage and forecasted high-flow stages from the NationalWeather Service, will provide emergency management personnel and residents with information that is critical for flood responseactivities such as evacuations and road closures, as well as for post-flood recovery eforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165060","collaboration":"Prepared in cooperation with the International Joint Commission","usgsCitation":"Flynn, R.H., and Hayes, Laura, 2016, Flood-inundation maps for Lake Champlain in Vermont and in northern Clinton County, New York: U.S. Geological Survey Scientific Investigations Report 2016–5060, 11 p., https://dx.doi.org/10.3133/sir20165060.","productDescription":"vi, 11 p.","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-068359","costCenters":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"links":[{"id":323821,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5060/sir20165060.pdf","text":"Report","size":"1.54 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5060"},{"id":323820,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5060/coverthb.jpg"}],"country":"United States","state":"New York, Vermont","otherGeospatial":"Lake Champlain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.4600830078125,\n 43.614205328810954\n ],\n [\n -73.4600830078125,\n 45.00753503123719\n ],\n [\n -73.11676025390625,\n 45.00753503123719\n ],\n [\n -73.11676025390625,\n 43.614205328810954\n ],\n [\n -73.4600830078125,\n 43.614205328810954\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
331 Commerce Way, Suite 2
Pembroke, NH 03275
Or visit our Web site at:
http://newengland.water.usgs.gov
Bed sediment samples from 79 coastal New York and New Jersey, USA sites were analyzed for 75 compounds including wastewater associated contaminants, PAHs, and other organic compounds to assess the post-Hurricane Sandy distribution of organic contaminants among six regions. These results provide the first assessment of wastewater compounds, hormones, and PAHs in bed sediment for this region. Concentrations of most wastewater contaminants and PAHs were highest in the most developed region (Upper Harbor/Newark Bay, UHNB) and reflected the wastewater inputs to this area. Although the lack of pre-Hurricane Sandy data for most of these compounds make it impossible to assess the effect of the storm on wastewater contaminant concentrations, PAH concentrations in the UHNB region reflect pre-Hurricane Sandy conditions in this region. Lower hormone concentrations than predicted by the total organic carbon relation occurred in UHNB samples, suggesting that hormones are being degraded in the UHNB region.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpolbul.2016.04.050","usgsCitation":"Phillips, P.J., Gibson, C.A., Fisher, S.C., Fisher, I., Reilly, T.J., Smalling, K., Romanok, K., Foreman, W., ReVello, R., Focazio, M.J., and Jones, D.K., 2016, Regional variability in bed-sediment concentrations of wastewater compounds, hormones and PAHs for portions of coastal New York and New Jersey impacted by hurricane Sandy: Marine Pollution Bulletin, v. 107, no. 2, p. 489-498, https://doi.org/10.1016/j.marpolbul.2016.04.050.","productDescription":"9 p.","startPage":"489","endPage":"498","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069674","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":324936,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New 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","email":"ksmall@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":false,"id":641948,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Romanok, Kristin M. 0000-0002-8472-8765 kromanok@usgs.gov","orcid":"https://orcid.org/0000-0002-8472-8765","contributorId":169543,"corporation":false,"usgs":true,"family":"Romanok","given":"Kristin M. ","email":"kromanok@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":false,"id":641953,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Foreman, William T. 0000-0002-2530-3310 wforeman@usgs.gov","orcid":"https://orcid.org/0000-0002-2530-3310","contributorId":169108,"corporation":false,"usgs":true,"family":"Foreman","given":"William T. ","email":"wforeman@usgs.gov","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"preferred":false,"id":641949,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"ReVello, Rhiannon C. rcrevell@usgs.gov","contributorId":4128,"corporation":false,"usgs":true,"family":"ReVello","given":"Rhiannon C.","email":"rcrevell@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":641950,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Focazio, Michael J. 0000-0003-0967-5576 mfocazio@usgs.gov","orcid":"https://orcid.org/0000-0003-0967-5576","contributorId":1276,"corporation":false,"usgs":true,"family":"Focazio","given":"Michael","email":"mfocazio@usgs.gov","middleInitial":"J.","affiliations":[{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true},{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true}],"preferred":true,"id":641951,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Jones, Daniel K. 0000-0003-0724-8001 dkjones@usgs.gov","orcid":"https://orcid.org/0000-0003-0724-8001","contributorId":4959,"corporation":false,"usgs":true,"family":"Jones","given":"Daniel","email":"dkjones@usgs.gov","middleInitial":"K.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":641952,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70174026,"text":"ofr20161106 - 2016 - Updated logistic regression equations for the calculation of post-fire debris-flow likelihood in the western United States","interactions":[],"lastModifiedDate":"2016-06-30T14:43:17","indexId":"ofr20161106","displayToPublicDate":"2016-06-30T13:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1106","title":"Updated logistic regression equations for the calculation of post-fire debris-flow likelihood in the western United States","docAbstract":"Wildfire can significantly alter the hydrologic response of a watershed to the extent that even modest rainstorms can generate dangerous flash floods and debris flows. To reduce public exposure to hazard, the U.S. Geological Survey produces post-fire debris-flow hazard assessments for select fires in the western United States. We use publicly available geospatial data describing basin morphology, burn severity, soil properties, and rainfall characteristics to estimate the statistical likelihood that debris flows will occur in response to a storm of a given rainfall intensity. Using an empirical database and refined geospatial analysis methods, we defined new equations for the prediction of debris-flow likelihood using logistic regression methods. We showed that the new logistic regression model outperformed previous models used to predict debris-flow likelihood.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161106","usgsCitation":"Staley, D.M., Negri, J.A., Kean, J.W., Laber, J.M., Tillery, A.C., and Youberg, A.M., 2016, Updated logistic regression equations for the calculation of post-fire debris-flow likelihood in the western United States: U.S. Geological Survey Open-File Report 2016–1106, 13 p., https://dx.doi.org/ofr20161106.","productDescription":"Report: iv, 13 p.; Appendix 1","numberOfPages":"17","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-076051","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":324673,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1106/ofr20161106.pdf","text":"Report","size":"1.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1106 Report"},{"id":324672,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1106/coverthb.jpg"},{"id":324675,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1106/ofr20161106_appx-1.xlsx","text":"Appendix 1","size":"268 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1106 Appendix 1"}],"contact":"Center Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, MS 966
Denver, CO 80225-0046
We documented puma (Puma concolor) and jaguar (Panthera onca) prey consumption in northeastern Sonora, Mexico, by investigating global positioning system cluster sites (n = 220), and conducting molecular analyses of scat (n = 116) collected between 2011 and 2013. We used camera trap data (n = 8,976 camera days) to estimate relative abundances of pumas and jaguars. Deer (Odocoileus virginianus) was the most frequent prey for puma found at kill sites (67%) and identified from scat (74%), although based on relative numbers of prey consumed, deer represented 45% and lagomorphs 20% of the proportion of all individuals eaten. A variety of small prey (weighing <15 kg) comprised the majority (52%) of the jaguar kill sites. From prey found at kill sites, jaguars killed calves (Bos taurus) at a lower frequency than previously reported, whereas pumas preyed on calves at a higher frequency than previously reported in the same area. In our study area, jaguars preyed on calves at approximately the same rate as pumas (jaguars 3.7 calves per year, pumas 4.9 calves per year). Calculated predation rates were limited only to collared animals within our study area and therefore should not be considered applicable to all pumas and jaguars in Sonora.
","language":"English","publisher":"Southwestern Association of Naturalists","publisherLocation":"Dallas, TX","doi":"10.1894/0038-4909-61.2.125","usgsCitation":"Cassaigne, I., Medellin, R., Thompson, R.W., Culver, M., Ochoa, A., Vargas, K., Childs, J.L., Sanderson, J., List, R., and Torres-Gomez, A., 2016, Diet of pumas (Puma concolor) in Sonora, Mexico, as determined by GPS kill sites and molecular identified scat, with comments on jaguar (Panthera onca) diet: Southwestern Naturalist, v. 61, no. 2, p. 125-132, https://doi.org/10.1894/0038-4909-61.2.125.","startPage":"125","endPage":"132","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070010","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":325899,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico","state":"Sonora","volume":"61","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-27","publicationStatus":"PW","scienceBaseUri":"57a1c42fe4b006cb45552c0a","contributors":{"authors":[{"text":"Cassaigne, Ivonne","contributorId":173305,"corporation":false,"usgs":false,"family":"Cassaigne","given":"Ivonne","email":"","affiliations":[],"preferred":false,"id":644216,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Medellin, Rodrigo A.","contributorId":77456,"corporation":false,"usgs":true,"family":"Medellin","given":"Rodrigo A.","affiliations":[],"preferred":false,"id":644217,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Ron W.","contributorId":170001,"corporation":false,"usgs":false,"family":"Thompson","given":"Ron","email":"","middleInitial":"W.","affiliations":[{"id":24784,"text":"Arizona Game and Fish Department, 5000 West Carefree Highway, Phoenix, Arizona 85086, United States","active":true,"usgs":false}],"preferred":false,"id":644218,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Culver, Melanie 0000-0001-5380-3059 mculver@usgs.gov","orcid":"https://orcid.org/0000-0001-5380-3059","contributorId":4327,"corporation":false,"usgs":true,"family":"Culver","given":"Melanie","email":"mculver@usgs.gov","affiliations":[{"id":127,"text":"Arizona Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":12625,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, 85721, USA","active":true,"usgs":false}],"preferred":false,"id":631724,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ochoa, Alexander","contributorId":169994,"corporation":false,"usgs":false,"family":"Ochoa","given":"Alexander","email":"","affiliations":[{"id":17653,"text":"School of Natural Resources & the Environment, The University of Arizona, Tucson","active":true,"usgs":false}],"preferred":false,"id":644219,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vargas, Karla","contributorId":173306,"corporation":false,"usgs":false,"family":"Vargas","given":"Karla","email":"","affiliations":[],"preferred":false,"id":644220,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Childs, Jack L.","contributorId":147124,"corporation":false,"usgs":false,"family":"Childs","given":"Jack","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":644221,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sanderson, Jim","contributorId":173307,"corporation":false,"usgs":false,"family":"Sanderson","given":"Jim","email":"","affiliations":[],"preferred":false,"id":644222,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"List, Rurik","contributorId":167139,"corporation":false,"usgs":false,"family":"List","given":"Rurik","email":"","affiliations":[{"id":17657,"text":"Instituto de Ecología, Universidad Nacional Autónoma de Mexico","active":true,"usgs":false}],"preferred":false,"id":644223,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Torres-Gomez, Armando","contributorId":173309,"corporation":false,"usgs":false,"family":"Torres-Gomez","given":"Armando","email":"","affiliations":[],"preferred":false,"id":644224,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70173856,"text":"sir20165088 - 2016 - Completion summary for boreholes TAN-2271 and TAN‑2272 at Test Area North, Idaho National Laboratory, Idaho","interactions":[],"lastModifiedDate":"2016-07-01T11:34:45","indexId":"sir20165088","displayToPublicDate":"2016-06-30T00:00:00","publicationYear":"2016","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":"2016-5088","title":"Completion summary for boreholes TAN-2271 and TAN‑2272 at Test Area North, Idaho National Laboratory, Idaho","docAbstract":"In 2015, the U.S. Geological Survey, in cooperation with the U.S. Department of Energy, drilled and constructed boreholes TAN-2271 and TAN-2272 for stratigraphic framework analyses and long-term groundwater monitoring of the eastern Snake River Plain aquifer at the Idaho National Laboratory in southeast Idaho. Borehole TAN-2271 initially was cored to collect continuous geologic data, and then re-drilled to complete construction as a monitor well. Borehole TAN-2272 was partially cored between 210 and 282 feet (ft) below land surface (BLS) then drilled and constructed as a monitor well. Boreholes TAN-2271 and TAN-2272 are separated by about 63 ft and have similar geologic layers and hydrologic characteristics based on geologic, geophysical, and aquifer test data collected. The final construction for boreholes TAN-2271 and TAN-2272 required 10-inch (in.) diameter carbon-steel well casing and 9.9-in. diameter open-hole completion below the casing to total depths of 282 and 287 ft BLS, respectively. Depth to water is measured near 228 ft BLS in both boreholes. Following construction and data collection, temporary submersible pumps and water-level access lines were placed to allow for aquifer testing, for collecting periodic water samples, and for measuring water levels.
Borehole TAN-2271 was cored continuously, starting at the first basalt contact (about 33 ft BLS) to a depth of 284 ft BLS. Excluding surface sediment, recovery of basalt and sediment core at borehole TAN-2271 was better than 98 percent. Based on visual inspection of core and geophysical data, material examined from 33 to 211ft BLS primarily consists of two massive basalt flows that are about 78 and 50 ft in thickness and three sediment layers near 122, 197, and 201 ft BLS. Between 211 and 284 ft BLS, geophysical data and core material suggest a high occurrence of fractured and vesicular basalt. For the section of aquifer tested, there are two primary fractured aquifer intervals: the first between 235 and 255 ft BLS and the second between 272 and 282 ft BLS. Basalt texture for borehole TAN-2271 generally was described as aphanitic, phaneritic, and porphyritic. Sediment layers, starting near 122 ft BLS, generally were composed of fine-grained sand and silt with a lesser amount of clay. Basalt flows generally ranged in thickness from 2 to 78 ft and varied from highly fractured to dense with high to low vesiculation. Geophysical data and limited core material collected from TAN-2272 show similar lithologic sequences to those reported for TAN-2271.
Geophysical and borehole video logs were collected during certain stages of the drilling and construction process at boreholes TAN-2271 and TAN-2272. Geophysical logs were examined synergistically with available core material to confirm geologic and hydrologic similarities and suggest possible fractured network interconnection between boreholes TAN-2271 and TAN-2272. Natural gamma log measurements were used to assess the completeness of the vapor port lines behind 10-in. diameter well casing. Electromagnetic flow meter results were used to identify downward flow conditions that exist for boreholes TAN-2271 and TAN-2272. Furthermore, gyroscopic deviation measurements were used to measure horizontal and vertical displacement at all depths in boreholes TAN-2271 and TAN-2272.
After borehole construction was completed, single‑well aquifer tests were done within wells TAN-2271 and TAN‑2272 to provide estimates of transmissivity and hydraulic conductivity. The transmissivity and hydraulic conductivity were estimated for the pumping well and observation well during the aquifer tests conducted on August 25 and August 27, 2015. Estimates for transmissivity range from 4.1 . 103 feet squared per day (ft2/d) to 8.1 . 103 ft2/d; estimates for hydraulic conductivity range from 5.8 to 11.5 feet per day (ft/d). Both TAN-2271 and TAN‑2272 show sustained pumping rates of about 30 gallons per minute (gal/min) with measured drawdown in the pumping well of 1.96 ft and 1.14 ft, respectively. The transmissivity estimates for wells tested were within the range of values determined from previous aquifer tests in other wells near Test Area North.
Groundwater samples were collected from both wells and were analyzed for cations, anions, metals, nutrients, volatile organic compounds, stable isotopes, and radionuclides. Groundwater samples for most of the inorganic constituents showed similar water chemistry in both wells. Groundwater samples for strontium-90, trichloroethene, and vinyl chloride exceeded maximum contaminant levels for public drinking water supplies in one or both wells.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165088","collaboration":"DOE/ID-22239Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
http://id.water.usgs.gov
Excess sediment in rivers and estuaries poses serious environmental and economic challenges. The U.S. Army Corps of Engineers (USACE) routinely dredges sediment in Federal navigation channels to maintain commercial shipping operations. The USACE initiated a 3-year pilot project in 2013 to use navigation channel dredged material to aid in restoration of shoreline habitat in the 21st Avenue West Channel Embayment of the Duluth-Superior Harbor. Placing dredged material in the 21st Avenue West Channel Embayment supports the restoration of shallow bay aquatic habitat aiding in the delisting of the St. Louis River Estuary Area of Concern.
The U.S. Geological Survey, in cooperation with the USACE, collected turbidity and suspended-sediment concentrations (SSCs) in 2014 and 2015 to measure the horizontal and vertical distribution of SSCs during placement operations of dredged materials. These data were collected to help the USACE evaluate the use of several best management practices, including various dredge material placement techniques and a silt curtain, to mitigate the dispersion of suspended sediment.
Three-dimensional visualization maps are a valuable tool for assessing the spatial displacement of SSCs. Data collection was designed to coincide with four dredged placement configurations that included periods with and without a silt curtain as well as before and after placement of dredged materials. Approximately 230 SSC samples and corresponding turbidity values collected in 2014 and 2015 were used to develop a simple linear regression model between SSC and turbidity. Using the simple linear regression model, SSCs were estimated for approximately 3,000 turbidity values at approximately 100 sampling sites in the 21st Avenue West Channel Embayment of the Duluth-Superior Harbor. The estimated SSCs served as input for development of 12 three-dimensional visualization maps.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165086","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Groten, J.T., Ellison, C.A., and Mahoney, M.H., 2016, Three-dimensional visualization maps of suspended-sediment concentrations during placement of dredged material in 21st Avenue West Channel Embayment, Duluth-Superior Harbor, Duluth, Minnesota, 2015: U.S. Geological Survey Scientific Investigations Report 2016–5086, 26 p., https://dx.doi.org/10.3133/sir20165086.","productDescription":"Report: vi, 26 p.; Appendix Tables: 1-1 through 1-4","startPage":"1","endPage":"26","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-069759","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":324664,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5086/sir20165086_appendix1.xlsx","text":"Appendix Tables 1–1 through 1–4","size":"277 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016–5086 Appendix Tables"},{"id":324663,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5086/sir20165086.pdf","text":"Report","size":"8.41 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5086"},{"id":324662,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5086/coverthb.jpg"}],"country":"United States","state":"Minnesota","city":"Duluth","otherGeospatial":"Duluth-Superior Harbor","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.12679862976073,\n 46.75162347434115\n ],\n [\n -92.12679862976073,\n 46.76626466624822\n ],\n [\n -92.10474014282227,\n 46.76626466624822\n ],\n [\n -92.10474014282227,\n 46.75162347434115\n ],\n [\n -92.12679862976073,\n 46.75162347434115\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Minnesota Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, Minnesota 55112
The effects of urbanization on annual maximum peak discharges in northeastern Illinois and nearby areas from 1945 to 2009 were analyzed with a two-step longitudinal-quantile linear regression approach. The peak discharges were then adjusted to 2010 land-use conditions. The explanatory variables used were daily precipitation at the time of the peak discharge event and a housing density-based measure of developed land use. The effect of the implementation of stormwater detention was assessed indirectly. Peak discharge records affected by the construction of large reservoirs that affect channel routing were identified and were split into segments at the time of completion of the reservoir. Longitudinal regressions of the peak discharge records on linear and logarithmic transformations of the selected measures of urbanization and precipitation were tested, and the best fitting model was selected for quantile regression and adjustment of the peak discharges.
\nBecause the uncertainties of streamgage-by-streamgage regressions of peak discharges as a function of urbanization are so large, a regional urbanization response was computed. Streamgages used in this study fit the following two criteria: (1) drainage area is at most 200 square miles and, (2) at least 10 consecutive years of peak discharge record are available. In the first step of the regression analysis, linear longitudinal regression models with fixed intercepts estimated for each segment of the peak discharge records were computed. The segment intercepts were then subtracted from the discharge records to homogenize the discharge dataset across the segments in preparation for the quantile regression analysis. From the quantile regression analysis, the effect of urbanization on peak discharge varies strongly with the exceedance probability of the peak discharge event; coefficients monotonically increase from 0.340 to 0.969 over exceedance probabilities from 0.002 to 0.99. The regression analyses yield estimates of the population-wide effect of the explanatory variables on the dependent variables as a function of exceedance probability. These estimates are similar to the coefficients of the regional regression relations in USGS regional flood-frequency studies such as those implemented in the Web application StreamStats; although in the longitudinal analysis used in this study, it is the temporal not the spatial (between-streamgage) variations that are taken into account.
\nThe observed and adjusted values for each streamgage are tabulated. To illustrate the overall effect of the adjustments, differences in the mean, standard deviation, and skewness of the log-transformed observed and urbanization-adjusted peak discharge series by streamgage are computed. For almost every streamgage where an adjustment was applied (no increase in urbanization was reported for a few streamgages), the mean increased and the standard deviation decreased; the effect on skewness values was more variable but usually they increased. Significant positive peak discharge trends were common in the observed values, occurring at 27.3 percent of streamgages at a p-value of 0.05 according to a Kendall’s tau correlation test; in the adjusted values, the incidence of such trends was reduced to 7.0 percent.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165049","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers—Chicago District, the Illinois Center for Transportation, the Illinois Department of Transportation, and the Federal Highway Administration","usgsCitation":"Over, T.M., Saito, R.J., and Soong, D.T., 2016, Adjusting annual maximum peak discharges at selected stations in northeastern Illinois for changes in land-use conditions: U.S. Geological Survey Scientific Investigations Report 2016–5049, 33 p., https://dx.doi.org/10.3133/sir20165049.","productDescription":"Report: viii, 33 p.; Tables; Spatial Data","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-050378","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":324541,"rank":4,"type":{"id":23,"text":"Spatial 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U.S. Geological Survey
405 North Goodwin Avenue
Urbana, IL 61801
Stonecats Noturus flavus in Vermont conform to a rare distribution pattern (as designated by Rabinowitz 1981) because their known distribution within the state is limited to the LaPlatte and Missisquoi rivers. We focused on Stonecats in the LaPlatte River to predict the stability of the population. During 2012–2014, we captured Stonecats via backpack electrofishing; fish were PIT-tagged (>90 mm TL) and marked with visible implant elastomer. Among the 1,671 Stonecats that were captured, 1,252 were PIT-tagged. Only 156 (12%) of the PIT-tagged fish were recaptured, and only 22 of those individuals were recaptured more than once. The Pradel model in Program MARK was used to estimate apparent survival (Φ) and seniority, which were used to derive the rate of population change (λ) for the Stonecat encounter histories we studied. We examined a total of 64 models in our candidate set, with the following covariates: TL at first capture, maximum temperature, season, maximum discharge, and area sampled. Survival estimates were highest in the spring (range of daily Φ = 0.9993–0.9995) and increased with greater TL at first capture. We also estimated increases in capture probability with increasing area sampled. We derived an annual λ of 0.9794, which indicates a slightly decreasing population. However, our λ estimate contained uncertainty that was likely increased due to the low recapture rates. Additional years of data could increase the accuracy of the λ estimate. In the meantime, we have provided insight into Stonecat population parameters that were otherwise unknown.
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2016 - Misapplied survey data and model uncertainty result in incorrect conclusions about the role of predation on alewife population dynamics in Lake Huron: a comment on He et al. (2015)","interactions":[],"lastModifiedDate":"2016-06-29T16:02:13","indexId":"70156604","displayToPublicDate":"2016-06-29T17:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Misapplied survey data and model uncertainty result in incorrect conclusions about the role of predation on alewife population dynamics in Lake Huron: a comment on He et al. (2015)","docAbstract":"Drastic recent and ongoing changes to fish populations and food webs in the Great Lakes have been well-described (Riley et al. 2008; Barbiero et al. 2009; Nalepa et al. 2009; Fahnenstiel et al. 2010;Evans et al. 2011; Gobin et al. 2015), and uncertainty regarding their potential effects on fisheries has caused concern among scientists and fishery managers (e.g., Dettmers et al. 2012). In particular, the relative importance of “bottom-up” (e.g., lower trophic level changes) versus “top-down” (e.g., predation) factors to fish community changes in the Great Lakes have been widely debated (e.g.,Barbiero et al. 2011; Eshenroder and Lantry 2012; Bunnell et al. 2014). In Lake Huron, recent ecosystem changes have been particularly profound, and populations of alewife (Alosa pseudoharengus), an offshore pelagic prey fish, collapsed in 2003 and have yet to recover (Riley et al. 2008, 2014). He et al. (2015) recently used a series of linked ecological models to assess the role of predation in the dynamics of the offshore prey fish community in Lake Huron. While we believe that they provide a novel method for combining bioenergetics and stock assessment modeling, we question the validity of their conclusions because of the misapplication of survey data and the lack of critical interpretation of their modeling efforts. Here we describe how He et al. (2015) have misapplied bottom trawl data from Lake Huron, and we provide examples of how this has resulted in erroneous conclusions regarding the importance of predation to the population dynamics and collapse of alewife in Lake Huron.
","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2015-0237","usgsCitation":"Riley, S.C., and Dunlop, E.S., 2016, Misapplied survey data and model uncertainty result in incorrect conclusions about the role of predation on alewife population dynamics in Lake Huron: a comment on He et al. (2015): Canadian Journal of Fisheries and Aquatic Sciences, v. 73, no. 5, p. 860-864, https://doi.org/10.1139/cjfas-2015-0237.","productDescription":"5 p.","startPage":"860","endPage":"864","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065429","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":488468,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/cjfas-2015-0237","text":"Publisher Index Page"},{"id":324654,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"73","issue":"5","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5774e346e4b07dd077c5fcb3","contributors":{"authors":[{"text":"Riley, Stephen C. 0000-0002-8968-8416 sriley@usgs.gov","orcid":"https://orcid.org/0000-0002-8968-8416","contributorId":2661,"corporation":false,"usgs":true,"family":"Riley","given":"Stephen","email":"sriley@usgs.gov","middleInitial":"C.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":569644,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunlop, Erin S.","contributorId":146961,"corporation":false,"usgs":false,"family":"Dunlop","given":"Erin","email":"","middleInitial":"S.","affiliations":[{"id":16762,"text":"Ontario Ministry of Natural Resources and Forestry","active":true,"usgs":false}],"preferred":false,"id":569645,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70169334,"text":"70169334 - 2016 - Modeled historical land use and land cover for the conterminous United States","interactions":[],"lastModifiedDate":"2018-03-08T12:52:07","indexId":"70169334","displayToPublicDate":"2016-06-29T16:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2367,"text":"Journal of Land Use Science","active":true,"publicationSubtype":{"id":10}},"title":"Modeled historical land use and land cover for the conterminous United States","docAbstract":"Animal movements can determine the population dynamics of wildlife. We used telemetry data to provide insight into the causes and consequences of local and long-distance movements of multiple age classes of conservation-reliant golden eagles (Aquila chrysaetos) in the foothills and mountains near Tehachapi, California. We estimated size and habitat-related correlates of 324 monthly 95 % home ranges and 317 monthly 50 % core areas for 25 birds moving locally over 2.5 years. We also calculated daily, hourly, and total distances traveled for the five of these birds that engaged in long-distance movements. Mean (±SD) monthly home-range size was 253.6 ± 429.4 km2 and core-area size was 26.4 ± 49.7 km2. Consistent with expectations, space used by pre-adults increased with age and was season-dependent but, unexpectedly, was not sex-dependent. For all ages and sexes, home ranges and core areas were dominated by both forest & woodland and shrubland & grassland habitat types. When moving long distances, eagles traveled up to 1588.4 km (1-way) in a season at highly variable speeds (63.7 ± 69.0 km/day and 5.2 ± 10.4 km/h) that were dependent on time of day. Patterns of long-distance movements by eagles were determined by age, yet these movements had characteristics of more than one previously described movement category (migration, dispersal, etc.). Our results provide a context for differentiating among types of movement behaviors and their population-level consequences and, thus, have implications for management and conservation of golden eagle populations.
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2016 - Selection and quality assessment of Landsat data for the North American forest dynamics forest history maps of the US","interactions":[],"lastModifiedDate":"2017-01-17T19:16:04","indexId":"70170970","displayToPublicDate":"2016-06-29T15:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2035,"text":"International Journal of Digital Earth","active":true,"publicationSubtype":{"id":10}},"title":"Selection and quality assessment of Landsat data for the North American forest dynamics forest history maps of the US","docAbstract":"Using the NASA Earth Exchange platform, the North American Forest Dynamics (NAFD) project mapped forest history wall-to-wall, annually for the contiguous US (1986–2010) using the Vegetation Change Tracker algorithm. As with any effort to identify real changes in remotely sensed time-series, data gaps, shifts in seasonality, misregistration, inconsistent radiometry and cloud contamination can be sources of error. We discuss the NAFD image selection and processing stream (NISPS) that was designed to minimize these sources of error. The NISPS image quality assessments highlighted issues with the Landsat archive and metadata including inadequate georegistration, unreliability of the pre-2009 L5 cloud cover assessments algorithm, missing growing-season imagery and paucity of clear views. Assessment maps of Landsat 5–7 image quantities and qualities are presented that offer novel perspectives on the growing-season archive considered for this study. Over 150,000+ Landsat images were considered for the NAFD project. Optimally, one high quality cloud-free image in each year or a total of 12,152 images would be used. However, to accommodate data gaps and cloud/shadow contamination 23,338 images were needed. In 220 specific path-row image years no acceptable images were found resulting in data gaps in the annual national map products.
","language":"English","publisher":"Taylor and Francis","doi":"10.1080/17538947.2016.1158876","usgsCitation":"Schleeweis, K., Goward, S.N., Huang, C., Dwyer, J.L., Dungan, J.L., Lindsey, M.A., Michaelis, A., Rishmawi, K., and Masek, J.G., 2016, Selection and quality assessment of Landsat data for the North American forest dynamics forest history maps of the US: International Journal of Digital Earth, v. 9, no. 10, p. 963-980, https://doi.org/10.1080/17538947.2016.1158876.","productDescription":"18 p.","startPage":"963","endPage":"980","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073476","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":324639,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"10","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-20","publicationStatus":"PW","scienceBaseUri":"5774e34fe4b07dd077c5fcf9","contributors":{"authors":[{"text":"Schleeweis, Karen","contributorId":169308,"corporation":false,"usgs":false,"family":"Schleeweis","given":"Karen","email":"","affiliations":[{"id":6679,"text":"US Forest Service, Rocky Mountain Research Station","active":true,"usgs":false}],"preferred":false,"id":629277,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goward, Samuel N.","contributorId":44459,"corporation":false,"usgs":true,"family":"Goward","given":"Samuel","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":629278,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huang, Chengquan","contributorId":25378,"corporation":false,"usgs":true,"family":"Huang","given":"Chengquan","affiliations":[],"preferred":false,"id":629279,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dwyer, John L. 0000-0002-8281-0896 dwyer@usgs.gov","orcid":"https://orcid.org/0000-0002-8281-0896","contributorId":3481,"corporation":false,"usgs":true,"family":"Dwyer","given":"John","email":"dwyer@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":629276,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dungan, Jennifer L.","contributorId":172579,"corporation":false,"usgs":false,"family":"Dungan","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":641329,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lindsey, Mary A.","contributorId":169309,"corporation":false,"usgs":false,"family":"Lindsey","given":"Mary","email":"","middleInitial":"A.","affiliations":[{"id":25467,"text":"Climate Program Office, NOAA","active":true,"usgs":false}],"preferred":false,"id":629280,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Michaelis, Andrew","contributorId":169311,"corporation":false,"usgs":false,"family":"Michaelis","given":"Andrew","email":"","affiliations":[{"id":25468,"text":"University Corporation Monterey Bay / NASA Ames Research Center","active":true,"usgs":false}],"preferred":false,"id":629282,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rishmawi, Khaldoun","contributorId":169310,"corporation":false,"usgs":false,"family":"Rishmawi","given":"Khaldoun","email":"","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":629281,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Masek, Jeffery G.","contributorId":87438,"corporation":false,"usgs":true,"family":"Masek","given":"Jeffery","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":629283,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70169350,"text":"70169350 - 2016 - Prospective earthquake forecasts at the Himalayan Front after the 25 April 2015 M 7.8 Gorkha Mainshock","interactions":[],"lastModifiedDate":"2016-10-05T11:47:44","indexId":"70169350","displayToPublicDate":"2016-06-29T14:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Prospective earthquake forecasts at the Himalayan Front after the 25 April 2015 M 7.8 Gorkha Mainshock","docAbstract":"When a major earthquake strikes, the resulting devastation can be compounded or even exceeded by the subsequent cascade of triggered seismicity. As the Nepalese recover from the 25 April 2015 shock, knowledge of what comes next is essential. We calculate the redistribution of crustal stresses and implied earthquake probabilities for different periods, from daily to 30 years into the future. An initial forecast was completed before an M 7.3 earthquake struck on 12 May 2015 that enables a preliminary assessment; postforecast seismicity has so far occurred within a zone of fivefold probability gain. Evaluation of the forecast performance, using two months of seismic data, reveals that stress‐based approaches present improved skill in higher‐magnitude triggered seismicity. Our results suggest that considering the total stress field, rather than only the coseismic one, improves the spatial performance of the model based on the estimation of a wide range of potential triggered faults following a mainshock.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220150195","usgsCitation":"Segou, M., and Parsons, T.E., 2016, Prospective earthquake forecasts at the Himalayan Front after the 25 April 2015 M 7.8 Gorkha Mainshock: Seismological Research Letters, v. 87, no. 4, p. 816-825, https://doi.org/10.1785/0220150195.","productDescription":"10 p.","startPage":"816","endPage":"825","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065687","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":470810,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://nora.nerc.ac.uk/id/eprint/514329/1/SegouParsons-SRL-2016-NORA-all.pdf","text":"External Repository"},{"id":324624,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"87","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-08","publicationStatus":"PW","scienceBaseUri":"5774e33fe4b07dd077c5fc6b","contributors":{"authors":[{"text":"Segou, Margaret","contributorId":140800,"corporation":false,"usgs":false,"family":"Segou","given":"Margaret","email":"","affiliations":[{"id":13572,"text":"Geoscience Azur","active":true,"usgs":false}],"preferred":false,"id":623869,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parsons, Thomas E. 0000-0002-0582-4338 tparsons@usgs.gov","orcid":"https://orcid.org/0000-0002-0582-4338","contributorId":2314,"corporation":false,"usgs":true,"family":"Parsons","given":"Thomas","email":"tparsons@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":623868,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70174187,"text":"70174187 - 2016 - Chemical abrasion-SIMS (CA-SIMS) U-Pb dating of zircon from the late Eocene Caetano caldera, Nevada","interactions":[],"lastModifiedDate":"2019-11-14T12:29:22","indexId":"70174187","displayToPublicDate":"2016-06-29T13:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"title":"Chemical abrasion-SIMS (CA-SIMS) U-Pb dating of zircon from the late Eocene Caetano caldera, Nevada","docAbstract":"Zircon geochronology is a critical tool for establishing geologic ages and time scales of processes in the Earth's crust. However, for zircons compromised by open system behavior, achieving robust dates can be difficult. Chemical abrasion (CA) is a routine step prior to thermal ionization mass spectrometry (TIMS) dating of zircon to remove radiation-damaged parts of grains that may have experienced open system behavior and loss of radiogenic Pb. While this technique has been shown to improve the accuracy and precision of TIMS dating, its application to high-spatial resolution dating methods, such as secondary ion mass spectrometry (SIMS), is relatively uncommon. In our efforts to U-Pb date zircons from the late Eocene Caetano caldera by SIMS (SHRIMP-RG: sensitive high resolution ion microprobe, reverse geometry), some grains yielded anomalously young U-Pb ages that implicated Pb-loss and motivated us to investigate with a comparative CA and non-CA dating study. We present CA and non-CA 206Pb/238U ages and trace elements determined by SHRIMP-RG for zircons from three Caetano samples (Caetano Tuff, Redrock Canyon porphyry, and a silicic ring-fracture intrusion) and for R33 and TEMORA-2 reference zircons. We find that non-CA Caetano zircons have weighted mean or bimodal U-Pb ages that are 2–4% younger than CA zircons for the same samples. CA Caetano zircons have mean U-Pb ages that are 0.4–0.6 Myr older than the 40Ar/39Ar sanidine eruption age (34.00 ± 0.03 Ma; error-weighted mean, 2σ), whereas non-CA zircons have ages that are 0.7–1.3 Myr younger. U-Pb ages do not correlate with U (~ 100–800 ppm), Th (~ 50–300 ppm) or any other measured zircon trace elements (Y, Hf, REE), and CA and non-CA Caetano zircons define identical trace element ranges. No statistically significant difference in U-Pb age is observed for CA versus non-CA R33 or TEMORA-2 zircons. Optical profiler measurements of ion microprobe pits demonstrate consistent depths of ~ 1.6 μm for CA and non-CA Caetano, R33 and TEMORA-2 zircons, and do not indicate variations in secondary ion sputtering rates due to chemical or structural changes from the CA treatment. Our new data underscore the potential for cryptic Pb-loss to go unrecognized in other geologically young magmatic centers that do not have zircons with high U, statistically discordant isotope ratios, high common Pb, or metamict textures.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemgeo.2016.06.013","usgsCitation":"Watts, K.E., Coble, M., Vazquez, J.A., Henry, C., Colgan, J.P., and John, D.A., 2016, Chemical abrasion-SIMS (CA-SIMS) U-Pb dating of zircon from the late Eocene Caetano caldera, Nevada: Chemical Geology, v. 439, no. 7, p. 139-151, https://doi.org/10.1016/j.chemgeo.2016.06.013.","productDescription":"13 p.","startPage":"139","endPage":"151","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052891","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":324622,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Caetano Tuff, Red Rock Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.55694580078125,\n 35.90406844132011\n ],\n [\n -115.55694580078125,\n 36.38922936340128\n ],\n [\n -115.36056518554686,\n 36.38922936340128\n ],\n [\n -115.36056518554686,\n 35.90406844132011\n ],\n [\n -115.55694580078125,\n 35.90406844132011\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"439","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5774e32be4b07dd077c5fbf3","contributors":{"authors":[{"text":"Watts, Kathryn E. 0000-0002-6110-7499 kwatts@usgs.gov","orcid":"https://orcid.org/0000-0002-6110-7499","contributorId":5081,"corporation":false,"usgs":true,"family":"Watts","given":"Kathryn","email":"kwatts@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":641192,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coble, Matthew A.","contributorId":86622,"corporation":false,"usgs":true,"family":"Coble","given":"Matthew A.","affiliations":[],"preferred":false,"id":641194,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vazquez, Jorge A. 0000-0003-2754-0456 jvazquez@usgs.gov","orcid":"https://orcid.org/0000-0003-2754-0456","contributorId":4458,"corporation":false,"usgs":true,"family":"Vazquez","given":"Jorge","email":"jvazquez@usgs.gov","middleInitial":"A.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true}],"preferred":true,"id":641195,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Henry, Christopher D.","contributorId":36556,"corporation":false,"usgs":true,"family":"Henry","given":"Christopher D.","affiliations":[],"preferred":false,"id":641197,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Colgan, Joseph P. 0000-0001-6671-1436 jcolgan@usgs.gov","orcid":"https://orcid.org/0000-0001-6671-1436","contributorId":1649,"corporation":false,"usgs":true,"family":"Colgan","given":"Joseph","email":"jcolgan@usgs.gov","middleInitial":"P.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":641193,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"John, David A. 0000-0001-7977-9106 djohn@usgs.gov","orcid":"https://orcid.org/0000-0001-7977-9106","contributorId":1748,"corporation":false,"usgs":true,"family":"John","given":"David","email":"djohn@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":641196,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70170935,"text":"70170935 - 2016 - Manual hierarchical clustering of regional geochemical data using a Bayesian finite mixture model","interactions":[],"lastModifiedDate":"2025-05-14T18:39:18.093972","indexId":"70170935","displayToPublicDate":"2016-06-29T11:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Manual hierarchical clustering of regional geochemical data using a Bayesian finite mixture model","docAbstract":"Interpretation of regional scale, multivariate geochemical data is aided by a statistical technique called “clustering.” We investigate a particular clustering procedure by applying it to geochemical data collected in the State of Colorado, United States of America. The clustering procedure partitions the field samples for the entire survey area into two clusters. The field samples in each cluster are partitioned again to create two subclusters, and so on. This manual procedure generates a hierarchy of clusters, and the different levels of the hierarchy show geochemical and geological processes occurring at different spatial scales. Although there are many different clustering methods, we use Bayesian finite mixture modeling with two probability distributions, which yields two clusters. The model parameters are estimated with Hamiltonian Monte Carlo sampling of the posterior probability density function, which usually has multiple modes. Each mode has its own set of model parameters; each set is checked to ensure that it is consistent both with the data and with independent geologic knowledge. The set of model parameters that is most consistent with the independent geologic knowledge is selected for detailed interpretation and partitioning of the field samples.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2016.05.016","usgsCitation":"Ellefsen, K.J., and Smith, D., 2016, Manual hierarchical clustering of regional geochemical data using a Bayesian finite mixture model: Applied Geochemistry, v. 75, p. 200-210, https://doi.org/10.1016/j.apgeochem.2016.05.016.","productDescription":"11 p.","startPage":"200","endPage":"210","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073180","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":324600,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":470811,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2016.05.016","text":"Publisher Index Page"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107,\n 37\n ],\n [\n -107,\n 41\n ],\n [\n -102,\n 41\n ],\n [\n -102,\n 37\n ],\n [\n -107,\n 37\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"75","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5774e345e4b07dd077c5fcab","contributors":{"authors":[{"text":"Ellefsen, Karl J. 0000-0003-3075-4703 ellefsen@usgs.gov","orcid":"https://orcid.org/0000-0003-3075-4703","contributorId":789,"corporation":false,"usgs":true,"family":"Ellefsen","given":"Karl","email":"ellefsen@usgs.gov","middleInitial":"J.","affiliations":[{"id":82803,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":false}],"preferred":true,"id":629166,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, David 0000-0002-9543-800X","orcid":"https://orcid.org/0000-0002-9543-800X","contributorId":169280,"corporation":false,"usgs":true,"family":"Smith","given":"David","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":629167,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70174210,"text":"70174210 - 2016 - Year-round monitoring of contaminants in Neal and Rogers Creeks, Hood River Basin, Oregon, 2011-12, and assessment of risks to salmonids","interactions":[],"lastModifiedDate":"2016-06-29T15:30:05","indexId":"70174210","displayToPublicDate":"2016-06-29T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Year-round monitoring of contaminants in Neal and Rogers Creeks, Hood River Basin, Oregon, 2011-12, and assessment of risks to salmonids","docAbstract":"Pesticide presence in streams is a potential threat to Endangered Species Act listed salmonids in the Hood River basin, Oregon, a primarily forested and agricultural basin. Two types of passive samplers, polar organic chemical integrative samplers (POCIS) and semipermeable membrane devices (SPMDs), were simultaneously deployed at four sites in the basin during Mar. 2011–Mar. 2012 to measure the presence of pesticides, polybrominated diphenyl ethers (PBDEs), and polychlorinated biphenyls (PCBs). The year-round use of passive samplers is a novel approach and offers several new insights. Currently used pesticides and legacy contaminants, including many chlorinated pesticides and PBDEs, were present throughout the year in the basin’s streams. PCBs were not detected. Time-weighted average water concentrations for the 2-month deployment periods were estimated from concentrations of chemicals measured in the passive samplers. Currently used pesticide concentrations peaked during spring and were detected beyond their seasons of expected use. Summed concentrations of legacy contaminants in Neal Creek were highest during July–Sept., the period with the lowest streamflows. Endosulfan was the only pesticide detected in passive samplers at concentrations exceeding Oregon or U.S. Environmental Protection Agency water-quality thresholds. A Sensitive Pesticide Toxicity Index (SPTI) was used to estimate the relative acute potential toxicity among sample mixtures. The acute potential toxicity of the detected mixtures was likely greater for invertebrates than for fish and for all samples in Neal Creek compared to Rogers Creek, but the indices appear to be low overall (<0.1). Endosulfans and pyrethroid insecticides were the largest contributors to the SPTIs for both sites. SPTIs of some discrete (grab) samples from the basin that were used for comparison exceeded 0.1 when some insecticides (azinphos methyl, chlorpyrifos, malathion) were detected at concentrations near or exceeding acute water-quality thresholds. Early life stages and adults of several sensitive fish species, including salmonids, are present in surface waters of the basin throughout the year, including during periods of peak estimated potential toxicity. Based on these data, direct toxicity to salmonids from in-stream pesticide exposure is unlikely, but indirect impacts (reduced fitness due to cumulative exposures or negative impacts to invertebrate prey populations) are unknown.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0158175","usgsCitation":"Temple, W.B., Morace, J.L., Nilsen, E.B., Alvarez, D., and Masterson, K., 2016, Year-round monitoring of contaminants in Neal and Rogers Creeks, Hood River Basin, Oregon, 2011-12, and assessment of risks to salmonids: PLoS ONE, v. 11, no. 6, 32 p., https://doi.org/10.1371/journal.pone.0158175.","productDescription":"32 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070114","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":470814,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0158175","text":"Publisher Index Page"},{"id":324651,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Green Point Creek, Hood River basin, Neal Creek, Rogers Creek, West Fork Hood River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121,\n 46\n ],\n [\n -121,\n 45\n ],\n [\n -122,\n 45\n ],\n [\n -122,\n 46\n ],\n [\n -121,\n 46\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-27","publicationStatus":"PW","scienceBaseUri":"5774e35ce4b07dd077c5fd60","contributors":{"authors":[{"text":"Temple, Whitney B. wbtemple@usgs.gov","contributorId":4488,"corporation":false,"usgs":true,"family":"Temple","given":"Whitney","email":"wbtemple@usgs.gov","middleInitial":"B.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":641307,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morace, Jennifer L. 0000-0002-8132-4044 jlmorace@usgs.gov","orcid":"https://orcid.org/0000-0002-8132-4044","contributorId":945,"corporation":false,"usgs":true,"family":"Morace","given":"Jennifer","email":"jlmorace@usgs.gov","middleInitial":"L.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":641308,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nilsen, Elena B. 0000-0002-0104-6321 enilsen@usgs.gov","orcid":"https://orcid.org/0000-0002-0104-6321","contributorId":923,"corporation":false,"usgs":true,"family":"Nilsen","given":"Elena","email":"enilsen@usgs.gov","middleInitial":"B.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":641309,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Alvarez, David 0000-0002-6918-2709 dalvarez@usgs.gov","orcid":"https://orcid.org/0000-0002-6918-2709","contributorId":150499,"corporation":false,"usgs":true,"family":"Alvarez","given":"David","email":"dalvarez@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":641310,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Masterson, Kevin","contributorId":172573,"corporation":false,"usgs":false,"family":"Masterson","given":"Kevin","email":"","affiliations":[{"id":27064,"text":"Oregon Department of Environmental Quality","active":true,"usgs":false}],"preferred":false,"id":641311,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70159581,"text":"70159581 - 2016 - Digestive physiology comparisons of aquatic invertebrates in the Upper Mississippi River Basin","interactions":[],"lastModifiedDate":"2016-09-19T15:44:03","indexId":"70159581","displayToPublicDate":"2016-06-28T17:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2299,"text":"Journal of Freshwater Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Digestive physiology comparisons of aquatic invertebrates in the Upper Mississippi River Basin","docAbstract":"Limited information is available on the composition of digestive enzymes present in unionid mussels and the zebra mussel, Dreissena polymorpha. Available information is nearly exclusive to species used for culture purposes. A commercially available enzyme assay kit was used to examine the effect of habitat within an ecosystem, season, and species on the activities of several digestive enzymes. We used Amblema plicata to represent native unionids, D. polymorpha, and also Hydropsyche orris as an outgroup to compare differences between mussels and other macroinvertebrates. The data indicated that neither location nor time affect the activities of the digestive enzymes tested; species was the only factor to affect the activity. Differences were found mostly between four enzymes: naphthol-AS-BI-phosphohydrolase, acid phosphatase, alkaline phosphatase, and β-galactosidase.
","language":"English","publisher":"Taylor and Francis","doi":"10.1080/02705060.2015.1132485","usgsCitation":"Sauey, B., Amberg, J., Cooper, S.T., Grunwald, S.K., Haro, R.J., and Gaikowski, M., 2016, Digestive physiology comparisons of aquatic invertebrates in the Upper Mississippi River Basin: Journal of Freshwater Ecology, v. 31, no. 3, p. 303-314, https://doi.org/10.1080/02705060.2015.1132485.","productDescription":"12 p.","startPage":"303","endPage":"314","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064819","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":470817,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/02705060.2015.1132485","text":"Publisher Index Page"},{"id":324567,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Upper Mississippi River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.3837890625,\n 37.10776507118514\n ],\n [\n -93.3837890625,\n 45.66012730272194\n ],\n [\n -89.07714843749999,\n 45.66012730272194\n ],\n [\n -89.07714843749999,\n 37.10776507118514\n ],\n [\n -93.3837890625,\n 37.10776507118514\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"31","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-01-11","publicationStatus":"PW","scienceBaseUri":"577391a3e4b07657d1a88bc2","contributors":{"authors":[{"text":"Sauey, Blake W. bsauey@usgs.gov","contributorId":4748,"corporation":false,"usgs":true,"family":"Sauey","given":"Blake W.","email":"bsauey@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":579560,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Amberg, Jon 0000-0002-8351-4861 jamberg@usgs.gov","orcid":"https://orcid.org/0000-0002-8351-4861","contributorId":149785,"corporation":false,"usgs":true,"family":"Amberg","given":"Jon","email":"jamberg@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":579561,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cooper, Scott T.","contributorId":147777,"corporation":false,"usgs":false,"family":"Cooper","given":"Scott","email":"","middleInitial":"T.","affiliations":[{"id":16932,"text":"University of Wisconsin–La Crosse, Biology Department","active":true,"usgs":false}],"preferred":false,"id":579562,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grunwald, Sandra K.","contributorId":147778,"corporation":false,"usgs":false,"family":"Grunwald","given":"Sandra","email":"","middleInitial":"K.","affiliations":[{"id":16933,"text":"University of Wisconsin–La Crosse, Chemistry & Biochemistry Department","active":true,"usgs":false}],"preferred":false,"id":579563,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haro, Roger J.","contributorId":139538,"corporation":false,"usgs":false,"family":"Haro","given":"Roger","email":"","middleInitial":"J.","affiliations":[{"id":12793,"text":"University of Wisconsin-La Crosse","active":true,"usgs":false}],"preferred":false,"id":579564,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gaikowski, Mark P. 0000-0002-6507-9341 mgaikowski@usgs.gov","orcid":"https://orcid.org/0000-0002-6507-9341","contributorId":149357,"corporation":false,"usgs":true,"family":"Gaikowski","given":"Mark P.","email":"mgaikowski@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":579565,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70171119,"text":"70171119 - 2016 - An assessment of mercury in estuarine sediment and tissue in Southern New Jersey using public domain data","interactions":[],"lastModifiedDate":"2016-06-28T15:09:16","indexId":"70171119","displayToPublicDate":"2016-06-28T16:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2676,"text":"Marine Pollution Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"An assessment of mercury in estuarine sediment and tissue in Southern New Jersey using public domain data","docAbstract":"Mercury (Hg) is considered a contaminant of global concern for coastal environments due to its toxicity, widespread occurrence in sediment, and bioaccumulation in tissue. Coastal New Jersey, USA, is characterized by shallow bays and wetlands that provide critical habitat for wildlife but share space with expanding urban landscapes. This study was designed as an assessment of the magnitude and distribution of Hg in coastal New Jersey sediments and critical species using publicly available data to highlight potential data gaps. Mercury concentrations in estuary sediments can exceed 2 μg/g and correlate with concentrations of other metals. Based on existing data, the concentrations of Hg in mussels in southern New Jersey are comparable to those observed in other urbanized Atlantic Coast estuaries. Lack of methylmercury data for sediments, other media, and tissues are data gaps needing to be filled for a clearer understanding of the impacts of Hg inputs to the ecosystem.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpolbul.2016.04.027","usgsCitation":"Ng, K., Szabo, Z., Reilly, P.A., Barringer, J., and Smalling, K., 2016, An assessment of mercury in estuarine sediment and tissue in Southern New Jersey using public domain data: Marine Pollution Bulletin, v. 107, no. 1, p. 22-35, https://doi.org/10.1016/j.marpolbul.2016.04.027.","productDescription":"14 p.","startPage":"22","endPage":"35","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069013","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":470819,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.marpolbul.2016.04.027","text":"Publisher Index Page"},{"id":324536,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.7015380859375,\n 39.24714385893248\n ],\n [\n -74.7015380859375,\n 40.12009038025332\n ],\n [\n -74.00665283203124,\n 40.12009038025332\n ],\n [\n -74.00665283203124,\n 39.24714385893248\n ],\n [\n -74.7015380859375,\n 39.24714385893248\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"107","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"577391a2e4b07657d1a88bbe","contributors":{"authors":[{"text":"Ng, Kara","contributorId":169541,"corporation":false,"usgs":false,"family":"Ng","given":"Kara","email":"","affiliations":[{"id":25560,"text":"The City College of New York, Division of Science","active":true,"usgs":false}],"preferred":false,"id":629961,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Szabo, Zoltan 0000-0002-0760-9607 zszabo@usgs.gov","orcid":"https://orcid.org/0000-0002-0760-9607","contributorId":138827,"corporation":false,"usgs":true,"family":"Szabo","given":"Zoltan","email":"zszabo@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629960,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reilly, Pamela A. 0000-0002-2937-4490 jankowsk@usgs.gov","orcid":"https://orcid.org/0000-0002-2937-4490","contributorId":653,"corporation":false,"usgs":true,"family":"Reilly","given":"Pamela","email":"jankowsk@usgs.gov","middleInitial":"A.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629962,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barringer, Julia jbarring@usgs.gov","contributorId":169542,"corporation":false,"usgs":true,"family":"Barringer","given":"Julia","email":"jbarring@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629963,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smalling, Kelly L. 0000-0002-1214-4920 ksmall@usgs.gov","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":149769,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L. 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Fluid exchange within these lowhydraulic-gradient systems can occur across broad spatial and temporal scales, with variable contributions to material transport and transformation. Identifying and assessing the scales at which these processes operate is essential for accurate evaluations of how these systems contribute to global biogeochemical cycles. The distribution of 222Rn and 223,224,226Ra have complex spatial patterns along the Shark River Slough estuary (SRSE), Everglades, FL. High-resolution time-series measurements of 222Rn activity, salinity, and water level were used to quantify processes affecting radon fluxes out of the mangrove forest over a tidal cycle. Based on field data, tidal pumping through an extensive network of crab burrows in the lower FCE provides the best explanation for the high radon and fluid fluxes. Burrows are irrigated during rising tides when radon and other dissolved constituents are released from the mangrove soil. Flushing efficiency of the burrows—defined as the tidal volume divided by the volume of burrows— estimated for the creek drainage area vary seasonally from 25 (wet season) to 100 % (dry season) in this study. The tidal pumping of the mangrove forest soil acts as a significant vector for exchange between the forest and the estuary. Processes that enhance exchange of O2 and other materials across the sediment-water interface could have a profound impact on the environmental response to larger scale processes such as sea level rise and climate change. Compounding the material budgets of the SRSE are additional inputs from groundwater from the Biscayne Aquifer, which were identified using radium isotopes. Quantification of the deep groundwater component is not obtainable, but isotopic data suggest a more prevalent signal in the dry season. These findings highlight the important role that both tidal- and seasonal-scale forcings play on groundwater movement in low-gradient hydrologic systems.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-016-0079-z","usgsCitation":"Smith, C.G., Price, R.M., Swarzenski, P.W., and Stalker, J.C., 2016, The role of ocean tides on groundwater-surface water exchange in a mangrove-dominated estuary: Shark River Slough, Florida Coastal Everglades, USA: Estuaries and Coasts, v. 39, no. 6, p. 1600-1616, https://doi.org/10.1007/s12237-016-0079-z.","productDescription":"17 p.","startPage":"1600","endPage":"1616","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067122","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":324525,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.3482666015625,\n 25.175116531621764\n ],\n [\n -81.3482666015625,\n 25.76526690492097\n ],\n [\n -80.4364013671875,\n 25.76526690492097\n ],\n [\n -80.4364013671875,\n 25.175116531621764\n ],\n [\n -81.3482666015625,\n 25.175116531621764\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"39","issue":"6","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-26","publicationStatus":"PW","scienceBaseUri":"577391a8e4b07657d1a88bdc","contributors":{"authors":[{"text":"Smith, Christopher G. 0000-0002-8075-4763 cgsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-8075-4763","contributorId":3410,"corporation":false,"usgs":true,"family":"Smith","given":"Christopher","email":"cgsmith@usgs.gov","middleInitial":"G.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":622616,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Price, Rene M.","contributorId":52880,"corporation":false,"usgs":true,"family":"Price","given":"Rene","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":622617,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swarzenski, Peter W. 0000-0003-0116-0578 pswarzen@usgs.gov","orcid":"https://orcid.org/0000-0003-0116-0578","contributorId":1070,"corporation":false,"usgs":true,"family":"Swarzenski","given":"Peter","email":"pswarzen@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":622618,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stalker, Jeremy C.","contributorId":167541,"corporation":false,"usgs":false,"family":"Stalker","given":"Jeremy","email":"","middleInitial":"C.","affiliations":[{"id":24739,"text":"Jacksonville State University","active":true,"usgs":false}],"preferred":false,"id":622619,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70174171,"text":"70174171 - 2016 - Loss of genetic diversity and increased subdivision in an endemic Alpine Stonefly threatened by climate change","interactions":[],"lastModifiedDate":"2016-11-15T13:59:21","indexId":"70174171","displayToPublicDate":"2016-06-28T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Loss of genetic diversity and increased subdivision in an endemic Alpine Stonefly threatened by climate change","docAbstract":"Much remains unknown about the genetic status and population connectivity of high-elevation and high-latitude freshwater invertebrates, which often persist near snow and ice masses that are disappearing due to climate change. Here we report on the conservation genetics of the meltwater stonefly Lednia tumana (Ricker) of Montana, USA, a cold-water obligate species. We sequenced 1530 bp of mtDNA from 116 L. tumana individuals representing “historic” (>10 yr old) and 2010 populations. The dominant haplotype was common in both time periods, while the second-most-common haplotype was found only in historic samples, having been lost in the interim. The 2010 populations also showed reduced gene and nucleotide diversity and increased genetic isolation. We found lower genetic diversity in L. tumana compared to two other North American stonefly species, Amphinemura linda (Ricker) and Pteronarcys californica Newport. Our results imply small effective sizes, increased fragmentation, limited gene flow, and loss of genetic variation among contemporary L. tumana populations, which can lead to reduced adaptive capacity and increased extinction risk. This study reinforces concerns that ongoing glacier loss threatens the persistence of L. tumana, and provides baseline data and analysis of how future environmental change could impact populations of similar organisms.
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Joseph 0000-0001-7818-3941 jgiersch@usgs.gov","orcid":"https://orcid.org/0000-0001-7818-3941","contributorId":4022,"corporation":false,"usgs":true,"family":"Giersch","given":"J. 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In recorded history, the jaguars range has extended from the Southern United States, throughout Mexico, to Central and South America, and they occupy a wide variety of habitats. A previous jaguar genetic study found high historical levels of gene flow among jaguar populations over broad areas but did not include any samples of jaguar from the States of Arizona, United States, or Sonora, Mexico. Arizona and Sonora have been part of the historical distribution of jaguars; however, poaching and habitat fragmentation have limited their distribution until they were declared extinct in the United States and endangered in Sonora. Therefore, a need was apparent to have this northernmost (Arizona/Sonora) jaguar population included in an overall jaguar molecular taxonomy and genetic diversity analyses. In this study, we used molecular genetic markers to examine diversity and taxonomy for jaguars in the Northwestern Jaguar Recovery Unit (NJRU; Sonora, Sinaloa, and Jalisco, Mexico; and southern Arizona and New Mexico, United States) relative to jaguars in other parts of the jaguar range (Central and South America). The objectives of this study were to:
Leader, Arizona Cooperative Fish and Wildlife Research Unit
U.S. Geological Survey
325 Biosciences East
Tucson, Arizona 85721
http://www.coopunits.org/Arizona/