Migratory species can experience limiting factors at different locations and during different periods of their annual cycle. In migratory birds, these factors may even occur in different hemispheres. Therefore, identifying the distribution of populations throughout their annual cycle (i.e., migratory connectivity) can reveal the complex ecological and evolutionary relationships that link species and ecosystems across the globe and illuminate where and how limiting factors influence population trends. A growing body of literature continues to identify species that exhibit weak connectivity wherein individuals from distinct breeding areas co-occur during the nonbreeding period. A detailed account of a broadly distributed species exhibiting strong migratory connectivity in which nonbreeding isolation of populations is associated with differential population trends remains undescribed. Here, we present a range-wide assessment of the nonbreeding distribution and migratory connectivity of two broadly dispersed Nearctic-Neotropical migratory songbirds. We used geolocators to track the movements of 70 Vermivora warblers from sites spanning their breeding distribution in eastern North America and identified links between breeding populations and nonbreeding areas. Unlike blue-winged warblers (Vermivora cyanoptera), breeding populations of golden-winged warblers (Vermivora chrysoptera) exhibited strong migratory connectivity, which was associated with historical trends in breeding populations: stable for populations that winter in Central America and declining for those that winter in northern South America.
","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.1718985115","usgsCitation":"Kramer, G.R., Andersen, D.E., Buehler, D.A., Wood, P.B., Peterson, S.M., Lehman, J.A., Aldinger, K.R., Bulluck, L.P., Harding, S.R., Jones, J.A., Loegering, J.P., Smalling, C.G., Vallender, R., and Streby, H.M., 2018, Population trends in Vermivora warblers are linked to strong migratory connectivity: Proceedings of the National Academy of Sciences of the United States of America, v. 115, no. 14, p. E3192-E3200, https://doi.org/10.1073/pnas.1718985115.","productDescription":"9 p.","startPage":"E3192","endPage":"E3200","ipdsId":"IP-092348","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468754,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1073/pnas.1718985115","text":"External Repository"},{"id":354256,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"115","issue":"14","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-26","publicationStatus":"PW","scienceBaseUri":"5afee6b6e4b0da30c1bfbd56","contributors":{"authors":[{"text":"Kramer, Gunnar R.","contributorId":94184,"corporation":false,"usgs":false,"family":"Kramer","given":"Gunnar","email":"","middleInitial":"R.","affiliations":[{"id":34539,"text":"Minnesota Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":735655,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andersen, David E. 0000-0001-9535-3404 dea@usgs.gov","orcid":"https://orcid.org/0000-0001-9535-3404","contributorId":199408,"corporation":false,"usgs":true,"family":"Andersen","given":"David","email":"dea@usgs.gov","middleInitial":"E.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":735619,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buehler, David A.","contributorId":176238,"corporation":false,"usgs":false,"family":"Buehler","given":"David","email":"","middleInitial":"A.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":735656,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wood, Petra B. 0000-0002-8575-1705 pbwood@usgs.gov","orcid":"https://orcid.org/0000-0002-8575-1705","contributorId":199090,"corporation":false,"usgs":true,"family":"Wood","given":"Petra","email":"pbwood@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":735620,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Peterson, Sean M.","contributorId":9354,"corporation":false,"usgs":false,"family":"Peterson","given":"Sean","email":"","middleInitial":"M.","affiliations":[{"id":13013,"text":"Department of Environmental Science, Policy and Management, University of California, Berkeley","active":true,"usgs":false},{"id":34539,"text":"Minnesota Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":735657,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lehman, Justin A.","contributorId":166944,"corporation":false,"usgs":false,"family":"Lehman","given":"Justin","email":"","middleInitial":"A.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":735658,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Aldinger, Kyle R.","contributorId":171892,"corporation":false,"usgs":false,"family":"Aldinger","given":"Kyle","email":"","middleInitial":"R.","affiliations":[{"id":34541,"text":"West Virginia Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false},{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":735659,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bulluck, Lesley P.","contributorId":204987,"corporation":false,"usgs":false,"family":"Bulluck","given":"Lesley","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":735660,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Harding, Sergio R.","contributorId":198906,"corporation":false,"usgs":false,"family":"Harding","given":"Sergio","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":735661,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jones, John A.","contributorId":200310,"corporation":false,"usgs":false,"family":"Jones","given":"John","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":735662,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Loegering, John P.","contributorId":166933,"corporation":false,"usgs":false,"family":"Loegering","given":"John","email":"","middleInitial":"P.","affiliations":[{"id":33353,"text":"University of Minnesota, Crookston","active":true,"usgs":false}],"preferred":false,"id":735663,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Smalling, Curtis G.","contributorId":191724,"corporation":false,"usgs":false,"family":"Smalling","given":"Curtis","email":"","middleInitial":"G.","affiliations":[{"id":33352,"text":"Audubon North Carolina","active":true,"usgs":false}],"preferred":false,"id":735664,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Vallender, Rachel","contributorId":194966,"corporation":false,"usgs":false,"family":"Vallender","given":"Rachel","email":"","affiliations":[{"id":34540,"text":"Canadian Museum of Nature","active":true,"usgs":false},{"id":27312,"text":"Canadian Wildlife Service, Environment and Climate Change Canada, 6 Bruce Street, Mount","active":true,"usgs":false}],"preferred":false,"id":735665,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Streby, Henry M.","contributorId":11024,"corporation":false,"usgs":false,"family":"Streby","given":"Henry","email":"","middleInitial":"M.","affiliations":[{"id":12455,"text":"University of Toledo","active":true,"usgs":false}],"preferred":false,"id":735666,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70196979,"text":"70196979 - 2018 - Probabilistic measures of climate change vulnerability, adaptation action benefits, and related uncertainty from maximum temperature metric selection","interactions":[],"lastModifiedDate":"2018-05-21T13:01:51","indexId":"70196979","displayToPublicDate":"2018-05-15T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Probabilistic measures of climate change vulnerability, adaptation action benefits, and related uncertainty from maximum temperature metric selection","docAbstract":"Predictions of the projected changes in species distributions and potential adaptation action benefits can help guide conservation actions. There is substantial uncertainty in projecting species distributions into an unknown future, however, which can undermine confidence in predictions or misdirect conservation actions if not properly considered. Recent studies have shown that the selection of alternative climate metrics describing very different climatic aspects (e.g., mean air temperature vs. mean precipitation) can be a substantial source of projection uncertainty. It is unclear, however, how much projection uncertainty might stem from selecting among highly correlated, ecologically similar climate metrics (e.g., maximum temperature in July, maximum 30‐day temperature) describing the same climatic aspect (e.g., maximum temperatures) known to limit a species’ distribution. It is also unclear how projection uncertainty might propagate into predictions of the potential benefits of adaptation actions that might lessen climate change effects. We provide probabilistic measures of climate change vulnerability, adaptation action benefits, and related uncertainty stemming from the selection of four maximum temperature metrics for brook trout (Salvelinus fontinalis), a cold‐water salmonid of conservation concern in the eastern United States. Projected losses in suitable stream length varied by as much as 20% among alternative maximum temperature metrics for mid‐century climate projections, which was similar to variation among three climate models. Similarly, the regional average predicted increase in brook trout occurrence probability under an adaptation action scenario of full riparian forest restoration varied by as much as .2 among metrics. Our use of Bayesian inference provides probabilistic measures of vulnerability and adaptation action benefits for individual stream reaches that properly address statistical uncertainty and can help guide conservation actions. Our study demonstrates that even relatively small differences in the definitions of climate metrics can result in very different projections and reveal high uncertainty in predicted climate change effects.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.14101","usgsCitation":"DeWeber, J.T., and Wagner, T., 2018, Probabilistic measures of climate change vulnerability, adaptation action benefits, and related uncertainty from maximum temperature metric selection: Global Change Biology, v. 24, no. 6, p. 2735-2748, https://doi.org/10.1111/gcb.14101.","productDescription":"14 p.","startPage":"2735","endPage":"2748","ipdsId":"IP-090617","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468761,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcb.14101","text":"Publisher Index Page"},{"id":354199,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"24","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-27","publicationStatus":"PW","scienceBaseUri":"5afee6bce4b0da30c1bfbd88","contributors":{"authors":[{"text":"DeWeber, Jefferson T.","contributorId":199675,"corporation":false,"usgs":false,"family":"DeWeber","given":"Jefferson","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":735454,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":735167,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70196975,"text":"sim3388 - 2018 - Surficial geologic map of the Dillingham quadrangle, southwestern Alaska","interactions":[],"lastModifiedDate":"2018-05-16T10:06:12","indexId":"sim3388","displayToPublicDate":"2018-05-14T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3388","title":"Surficial geologic map of the Dillingham quadrangle, southwestern Alaska","docAbstract":"Director,
Alaska Science Center
U.S. Geological Survey
4230 University Drive
Anchorage, Alaska 99508
Bacterial pneumonia is a threat to bighorn sheep (Ovis canadensis) populations. Bighorn sheep in the East Humboldt Mountain Range (EHR), Nevada, USA, experienced a pneumonia epizootic in 2009–2010. Testing of mountain goats (Oreamnos americanus) that were captured or found dead on this range during and after the epizootic detected bacteria commonly associated with bighorn sheep pneumonia die‐offs. Additionally, in years subsequent to the bighorn sheep epizootic, the mountain goat population had low kid:adult ratios, a common outcome for bighorn sheep populations that have experienced a pneumonia epizootic. We hypothesized that pneumonia was present and negatively affecting mountain goat kids in the EHR. From June–August 2013–2015, we attempted to observe mountain goat kids with marked adult females in the EHR at least once per week to document signs of respiratory disease; identify associations between respiratory disease, activity levels, and subsequent disappearance (i.e., death); and estimate weekly survival. Each time we observed a kid with a marked adult female, we recorded any signs of respiratory disease and collected behavior data that we fit to a 3‐state discrete hidden Markov model (HMM) to predict a kid's state (active vs. sedentary) and its probability of disappearing. We first observed clinical signs of respiratory disease in kids in late July–early August each summer. We observed 8 of 31 kids with marked adult females with signs of respiratory disease on 13 occasions. On 11 of these occasions, the HMM predicted that kids were in the sedentary state, which was associated with increased probability of subsequent death. We estimated overall probability of kid survival from June–August to be 0.19 (95% CI = 0.08–0.38), which was lower than has been reported in other mountain goat populations. We concluded that respiratory disease was present in the mountain goat kids in the EHR and negatively affected their activity levels and survival. Our results raise concerns about potential effects of pneumonia to mountain goat populations and the potential for disease transmission between mountain goats and bighorn sheep where the species are sympatric.
","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21470","usgsCitation":"Blanchong, J.A., Anderson, C.A., Clark, N.J., Klaver, R.W., Plummer, P.J., Cox, M., Mcadoo, C., and Wolff, P.L., 2018, Respiratory disease, behavior, and survival of mountain goat kids: Journal of Wildlife Management, v. 82, no. 6, p. 1243-1251, https://doi.org/10.1002/jwmg.21470.","productDescription":"9 p.","startPage":"1243","endPage":"1251","ipdsId":"IP-094396","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":487211,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://lib.dr.iastate.edu/nrem_pubs/276","text":"External Repository"},{"id":354147,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"82","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-25","publicationStatus":"PW","scienceBaseUri":"5afee6bee4b0da30c1bfbd96","contributors":{"authors":[{"text":"Blanchong, Julie A.","contributorId":6030,"corporation":false,"usgs":false,"family":"Blanchong","given":"Julie","email":"","middleInitial":"A.","affiliations":[{"id":13018,"text":"Department of Forest and Wildlife Ecology, University of Wisconsin, Madison","active":true,"usgs":false}],"preferred":false,"id":735235,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Christopher A.","contributorId":204866,"corporation":false,"usgs":false,"family":"Anderson","given":"Christopher","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":735236,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clark, Nicholas J.","contributorId":204867,"corporation":false,"usgs":false,"family":"Clark","given":"Nicholas","email":"","middleInitial":"J.","affiliations":[{"id":16755,"text":"University of Queensland, Australia","active":true,"usgs":false}],"preferred":false,"id":735237,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Klaver, Robert W. 0000-0002-3263-9701 bklaver@usgs.gov","orcid":"https://orcid.org/0000-0002-3263-9701","contributorId":3285,"corporation":false,"usgs":true,"family":"Klaver","given":"Robert","email":"bklaver@usgs.gov","middleInitial":"W.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":734914,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Plummer, Paul J.","contributorId":204868,"corporation":false,"usgs":false,"family":"Plummer","given":"Paul","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":735238,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cox, Mike","contributorId":198457,"corporation":false,"usgs":false,"family":"Cox","given":"Mike","email":"","affiliations":[],"preferred":false,"id":735239,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mcadoo, Caleb","contributorId":204869,"corporation":false,"usgs":false,"family":"Mcadoo","given":"Caleb","email":"","affiliations":[],"preferred":false,"id":735240,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wolff, Peregrine L.","contributorId":69865,"corporation":false,"usgs":true,"family":"Wolff","given":"Peregrine","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":735241,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70196638,"text":"ds1085 - 2018 - Groundwater-quality data from the eastern Snake River Plain Aquifer, Jerome and Gooding Counties, south-central Idaho, 2017","interactions":[],"lastModifiedDate":"2018-05-14T11:15:38","indexId":"ds1085","displayToPublicDate":"2018-05-11T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1085","title":"Groundwater-quality data from the eastern Snake River Plain Aquifer, Jerome and Gooding Counties, south-central Idaho, 2017","docAbstract":"Groundwater-quality samples and water-level data were collected from 36 wells in the Jerome/Gooding County area of the eastern Snake River Plain aquifer during June 2017. The wells included 30 wells sampled for the U.S. Geological Survey’s National Water-Quality Assessment project, plus an additional 6 wells were selected to increase spatial distribution. The data provide water managers with the ability for an improved understanding of groundwater quality and flow directions in the area. Groundwater-quality samples were analyzed for nutrients, major ions, trace elements, and stable isotopes of water. Quality-assurance and quality-control measures consisted of multiple blank samples and a sequential replicate sample. All data are available online at the USGS National Water Information System.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1085","collaboration":"Prepared in cooperation with the Idaho Department of Water Resources and Idaho Power Company","usgsCitation":"Skinner, K.D., 2018, Groundwater-quality data from the eastern Snake River Plain aquifer, Jerome and Gooding Counties, south-central Idaho, 2017: U.S. Geological Survey Data Series 1085, 20 p., https://doi.org/10.3133/ds1085.","productDescription":"iv, 20 p.","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-093930","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":354092,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1085/ds1085.pdf","text":"Report","size":"1.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1085"},{"id":354091,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1085/coverthb.jpg"}],"country":"United States","state":"Idaho","county":"Gooding County, Jerome County","otherGeospatial":"Snake River Plain Aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.33,\n 42.56218435232186\n ],\n [\n -114.33,\n 42.917212160086194\n ],\n [\n -115,\n 42.917212160086194\n ],\n [\n -115,\n 42.56218435232186\n ],\n [\n -114.33,\n 42.56218435232186\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
Submarine groundwater fluxes across the seafloor facilitate important hydrological and biogeochemical exchanges between oceans and seabed sediment, yet few studies have investigated spatially distributed groundwater fluxes in deep‐ocean environments such as continental slopes. Heat has been previously applied as a submarine groundwater tracer using an analytical solution to a heat flow equation assuming steady state conditions and homogeneous thermal conductivity. These assumptions are often violated in shallow seabeds due to ocean bottom temperature changes or sediment property variations. Here heat tracing analysis techniques recently developed for terrestrial settings are applied in concert to examine the influences of groundwater flow, ocean temperature changes, and seabed thermal conductivity variations on deep‐ocean sediment temperature profiles. Temperature observations from the sediment and bottom ocean water on the Scotian Slope off eastern Canada are used to demonstrate how simple thermal methods for tracing groundwater can be employed if more comprehensive techniques indicate that the simplifying assumptions are valid. The spatial distribution of the inferred groundwater fluxes on the slope suggests a downward groundwater flow system with recharge occurring over the upper‐middle slope and discharge on the lower slope. We speculate that the downward groundwater flow inferred on the Scotian Slope is due to density‐driven processes arising from underlying salt domes, in contrast with upward slope systems driven by geothermal convection. Improvements in the design of future submarine hydrogeological studies are proposed for thermal data collection and groundwater flow analysis, including new equations that quantify the minimum detectable flux magnitude for a given sensor accuracy and profile length.
","language":"English","publisher":"Wiley","doi":"10.1029/2017WR022353","usgsCitation":"Kurylyk, B.L., Irvine, D.J., Mohammed, A., Bense, V.F., Briggs, M.A., Loder, J., and Geshelin, Y., 2018, Rethinking the use of seabed sediment temperature profiles to trace submarine groundwater flow: Water Resources Research, v. 54, no. 7, p. 4595-4614, https://doi.org/10.1029/2017WR022353.","productDescription":"20 p.","startPage":"4595","endPage":"4614","ipdsId":"IP-095613","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":468770,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2017wr022353","text":"Publisher Index Page"},{"id":360328,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Scotian Slope","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -63,\n 41\n ],\n [\n -60,\n 41\n ],\n [\n -60,\n 43\n ],\n [\n -63,\n 43\n ],\n [\n -63,\n 41\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"54","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-07","publicationStatus":"PW","scienceBaseUri":"5c14cfb8e4b006c4f8545d3f","contributors":{"authors":[{"text":"Kurylyk, Barret L.","contributorId":176296,"corporation":false,"usgs":false,"family":"Kurylyk","given":"Barret","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":754277,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Irvine, Dylan J.","contributorId":190404,"corporation":false,"usgs":false,"family":"Irvine","given":"Dylan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":754278,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mohammed, A.A.","contributorId":211492,"corporation":false,"usgs":false,"family":"Mohammed","given":"A.A.","email":"","affiliations":[{"id":16660,"text":"University of Calgary","active":true,"usgs":false}],"preferred":false,"id":754279,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bense, V. F.","contributorId":211493,"corporation":false,"usgs":false,"family":"Bense","given":"V.","email":"","middleInitial":"F.","affiliations":[{"id":37803,"text":"Wageningen University","active":true,"usgs":false}],"preferred":false,"id":754280,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Briggs, Martin A. 0000-0003-3206-4132 mbriggs@usgs.gov","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":4114,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","email":"mbriggs@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":754276,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Loder, J.W.","contributorId":211494,"corporation":false,"usgs":false,"family":"Loder","given":"J.W.","email":"","affiliations":[{"id":38259,"text":"Bedford Institute of Oceanography, Dartmouth, Canada","active":true,"usgs":false}],"preferred":false,"id":754281,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Geshelin, Y.","contributorId":211495,"corporation":false,"usgs":false,"family":"Geshelin","given":"Y.","email":"","affiliations":[{"id":38259,"text":"Bedford Institute of Oceanography, Dartmouth, Canada","active":true,"usgs":false}],"preferred":false,"id":754282,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70195537,"text":"sir20185030 - 2018 - Hydrogeologic setting, conceptual groundwater flow system, and hydrologic conditions 1995–2010 in Florida and parts of Georgia, Alabama, and South Carolina","interactions":[],"lastModifiedDate":"2018-09-25T06:19:59","indexId":"sir20185030","displayToPublicDate":"2018-05-04T14:00:00","publicationYear":"2018","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":"2018-5030","title":"Hydrogeologic setting, conceptual groundwater flow system, and hydrologic conditions 1995–2010 in Florida and parts of Georgia, Alabama, and South Carolina","docAbstract":"The hydrogeologic setting and groundwater flow system in Florida and parts of Georgia, Alabama, and South Carolina is dominated by the highly transmissive Floridan aquifer system. This principal aquifer is a vital source of freshwater for public and domestic supply, as well as for industrial and agricultural uses throughout the southeastern United States. Population growth, increased tourism, and increased agricultural production have led to increased demand on groundwater from the Floridan aquifer system, particularly since 1950. The response of the Floridan aquifer system to these stresses often poses regional challenges for water-resource management that commonly transcend political or jurisdictional boundaries. To help water-resource managers address these regional challenges, the U.S. Geological Survey (USGS) Water Availability and Use Science Program began assessing groundwater availability of the Floridan aquifer system in 2009.
The current conceptual groundwater flow system was developed for the Floridan aquifer system and adjacent systems partly on the basis of previously published USGS Regional Aquifer-System Analysis (RASA) studies, specifically many of the potentiometric maps and the modeling efforts in these studies. The Floridan aquifer system extent was divided into eight hydrogeologically distinct subregional groundwater basins delineated on the basis of the estimated predevelopment (circa 1880s) potentiometric surface: (1) Panhandle, (2) Dougherty Plain-Apalachicola, (3) Thomasville-Tallahassee, (4) Southeast Georgia-Northeast Florida-South South Carolina, (5) Suwannee, (6) West-central Florida, (7) East-central Florida, and (8) South Florida. The use of these subregions allows for a more detailed analysis of the individual basins and the groundwater flow system as a whole.
The hydrologic conditions and associated groundwater budget were updated relative to previous RASA studies to include additional data collected since the 1980s and to reflect the entire groundwater flow system, including the surficial, intermediate, and Floridan aquifer systems for a contemporary period (1995–2010). Inflow to the groundwater flow system of 33,700 million gallons per day (Mgal/d) was assumed to be exclusively from net recharge (precipitation minus evapotranspiration and surface runoff). Outflow from the groundwater flow system included spring discharge (7,700 Mgal/d) and groundwater withdrawals (5,200 Mgal/d). Estimates for all components of the groundwater system were not possible because of large uncertainties associated with internal leakage, coastal discharge, and discharge to streams and lakes. A numerical modeling analysis is required to improve this hydrologic budget calculation and to forecast future changes in groundwater levels and aquifer storage caused by groundwater withdrawals, land-use change, and the effects of climate variability and change.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185030","collaboration":"Water Availability and Use Science Program","usgsCitation":"Bellino, J.C., Kuniansky, E.L., O’Reilly, A.M., and Dixon, J.F., 2018, Hydrogeologic setting, conceptual groundwater flow system, and hydrologic conditions 1995–2010 in Florida and parts of Georgia, Alabama, and South Carolina: U.S. Geological Survey Scientific Investigations Report 2018–5030, 103 p., https://doi.org/10.3133/sir20185030.","productDescription":"Report: viii, 103 p.; Plate: 36.0 x 49.0 inches; Data Releases","numberOfPages":"115","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-056534","costCenters":[{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"links":[{"id":353934,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2018/5030/sir20185030_plate.pdf","text":"Plate 1","size":"3.02 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5030 Plate 1"},{"id":353936,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7CJ8BMS","text":"USGS data release","description":"USGS Data Release","linkHelpText":" Soil-Water-Balance model datasets used to estimate mean groundwater recharge in Florida and parts of Georgia, Alabama, and South Carolina, 1995–2010"},{"id":353933,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5030/sir20185030.pdf","text":"Report","size":"46.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5030"},{"id":353932,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5030/coverthb2.jpg"},{"id":353937,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75Q4TZD","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Potentiometric Surface Contours, Wells, and Groundwater Basin Divides for the Upper Floridan Aquifer in Florida and Parts of Georgia, South Carolina, and Alabama, May–June 2010—Updated"},{"id":353935,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78K7749","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Groundwater Withdrawals in Florida and parts of Georgia, Alabama, and South Carolina, 1995–2010"}],"country":"United States","state":"Alabama, Florida, Georgia, South Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.17626953125,\n 24.467150664739002\n ],\n [\n -79.6728515625,\n 24.467150664739002\n ],\n [\n -79.6728515625,\n 32.85190345738802\n ],\n [\n -88.17626953125,\n 32.85190345738802\n ],\n [\n -88.17626953125,\n 24.467150664739002\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane
Lutz, FL 33559
Painted Buntings (Passerina ciris) have been declining in the southeastern United States since the 1970s. A recent demographic assessment highlighted the importance of estimating demographic parameters, which have received little attention to date. The dearth of information is troublesome because attempts to reverse declining trends require a better understanding of the relationship between habitat quality and age- and sex-specific survival and recruitment rates. We used capture–mark–recapture data collected from 2007 to 2015 on Bald Head Island (BHI) and at Hammocks Beach State Park (HBSP) in North Carolina, USA, to estimate local age- and sex-specific annual survival rates and local population size and recruitment rates using programs MARK and LOLASURVIV. Juveniles had lower local survival rates than adults (HBSP: 0.28 ± 0.14 vs. 0.67 ± 0.06; BHI: 0.28 ± 0.04 vs. 0.57 ± 0.02). Local annual survival rates for males on BHI (0.50 ± 0.03) were lower than those for females (0.57 ± 0.02). Age-specific differences were consistent with known differential age-dependent survival skills, and sex-specific differences were consistent with the potential influence of sexual dichromism. Conservative estimates of population size on BHI averaged 101 juveniles and 263 adults annually. Annual in situ reproductive recruitment averaged 28 individuals plus an additional 120 new immigrants, indicating successful reproduction and connectivity with neighboring coastal populations. Local adult survival estimates from our 2 North Carolinian study populations were similar to high-end estimates from across the eastern and western range of the species (∼0.60). Finite observed population growth rate estimates between the BHI population (λ = 1.10) and a South Carolinian population (λ = 0.87) underscore the potential role of differential habitat quality and the importance of information from multiple sites, including nonbreeding grounds, for proper inferences about the status of the species. Reported vital rates provide a stronger foundation on which to base habitat quality as assessed with demographic parameters and to guide Painted Bunting conservation regionally.
","language":"English","publisher":"American Ornithological Society","doi":"10.1650/CONDOR-17-74.1","usgsCitation":"Yirka, L.M., Collazo, J., O’Shea, B.J., Gerwin, J., Rotenberg, J.A., and Cobb, D.T., 2018, Demographic rates of two southeastern populations of Painted Bunting, 2007–2015: The Condor, v. 120, no. 2, p. 319-329, https://doi.org/10.1650/CONDOR-17-74.1.","productDescription":"11 p.","startPage":"319","endPage":"329","ipdsId":"IP-083696","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":488790,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1650/condor-17-74.1","text":"Publisher Index Page"},{"id":356150,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"Bald Head Island, Hammocks Beach State Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.5577392578125,\n 33.792843773631844\n ],\n [\n -76.17919921875,\n 33.792843773631844\n ],\n [\n -76.17919921875,\n 34.95574425733423\n ],\n [\n -78.5577392578125,\n 34.95574425733423\n ],\n [\n -78.5577392578125,\n 33.792843773631844\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"120","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc451e4b0f5d57878ea55","contributors":{"authors":[{"text":"Yirka, Liani M.","contributorId":206731,"corporation":false,"usgs":false,"family":"Yirka","given":"Liani","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":741571,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collazo, Jaime A. 0000-0002-1816-7744 jaime_collazo@usgs.gov","orcid":"https://orcid.org/0000-0002-1816-7744","contributorId":173448,"corporation":false,"usgs":true,"family":"Collazo","given":"Jaime A.","email":"jaime_collazo@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":741375,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Shea, Brian J.","contributorId":206732,"corporation":false,"usgs":false,"family":"O’Shea","given":"Brian","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":741572,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gerwin, J.A.","contributorId":88149,"corporation":false,"usgs":true,"family":"Gerwin","given":"J.A.","email":"","affiliations":[],"preferred":false,"id":741573,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rotenberg, James A.","contributorId":206733,"corporation":false,"usgs":false,"family":"Rotenberg","given":"James","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":741574,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cobb, David T.","contributorId":176235,"corporation":false,"usgs":false,"family":"Cobb","given":"David","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":741575,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70196951,"text":"70196951 - 2018 - A multiscale investigation of habitat use and within-river distribution of sympatric sand darter species","interactions":[],"lastModifiedDate":"2018-05-17T15:50:26","indexId":"70196951","displayToPublicDate":"2018-05-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5689,"text":"Journal of Geospatial Applications in Natural Resources","active":true,"publicationSubtype":{"id":10}},"title":"A multiscale investigation of habitat use and within-river distribution of sympatric sand darter species","docAbstract":"The western sand darter Ammocrypta clara, and eastern sand darter Ammocrypta pellucida, are sand-dwelling fishes of conservation concern. Past research has emphasized the importance of studying individual populations of conservation concern, while recent research has revealed the importance of incorporating landscape scale processes that structure habitat mosaics and local populations. We examined habitat use and distributions of western and eastern sand darters in the lower Elk River of West Virginia. At the sandbar habitat use scale, western sand darters were detected in sandbars with greater area, higher proportions of coarse grain sand and faster bottom current velocity, while the eastern sand darter used a wider range of sandbar habitats. The landscape scale analysis revealed that contributing drainage area was an important predictor for both species, while sinuosity, which presumably represents valley type, also contributed to the western sand darter’s habitat suitability. Sandbar quality (area, grain size, and velocity) and fluvial geomorphic variables (drainage area and valley type) are likely key driving factors structuring sand darter distributions in the Elk River. This multiscale study of within-river species distribution and habitat use is unique, given that only a few sympatric populations are known of western and eastern sand darters.
","language":"English","publisher":"SFA ScholarWorks","usgsCitation":"Thompson, P.A., Welsh, S., Strager, M.P., and Rizzo, A.A., 2018, A multiscale investigation of habitat use and within-river distribution of sympatric sand darter species: Journal of Geospatial Applications in Natural Resources, v. 2, no. 1, p. 1-22.","productDescription":"Article 1; 22 p.","startPage":"1","endPage":"22","ipdsId":"IP-086297","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":354289,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":354109,"type":{"id":15,"text":"Index Page"},"url":"https://scholarworks.sfasu.edu/j_of_geospatial_applications_in_natural_resources/vol2/iss1/1/"}],"country":"United States","state":"West Virginia","otherGeospatial":"Elk River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.6668701171875,\n 38.3384247989913\n ],\n [\n -80.68634033203125,\n 38.3384247989913\n ],\n [\n -80.68634033203125,\n 38.68122173079789\n ],\n [\n -81.6668701171875,\n 38.68122173079789\n ],\n [\n -81.6668701171875,\n 38.3384247989913\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"2","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6c4e4b0da30c1bfbdf8","contributors":{"authors":[{"text":"Thompson, Patricia A. pathompson@usgs.gov","contributorId":139753,"corporation":false,"usgs":false,"family":"Thompson","given":"Patricia","email":"pathompson@usgs.gov","middleInitial":"A.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":735754,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Welsh, Stuart A. 0000-0003-0362-054X swelsh@usgs.gov","orcid":"https://orcid.org/0000-0003-0362-054X","contributorId":152088,"corporation":false,"usgs":true,"family":"Welsh","given":"Stuart A.","email":"swelsh@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":735119,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Strager, Michael P.","contributorId":169817,"corporation":false,"usgs":false,"family":"Strager","given":"Michael","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":735755,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rizzo, Austin A.","contributorId":191439,"corporation":false,"usgs":false,"family":"Rizzo","given":"Austin","email":"","middleInitial":"A.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":735756,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196770,"text":"70196770 - 2018 - Irrigated agriculture and future climate change effects on groundwater recharge, northern High Plains aquifer, USA","interactions":[],"lastModifiedDate":"2018-05-01T13:25:49","indexId":"70196770","displayToPublicDate":"2018-05-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":680,"text":"Agricultural Water Management","active":true,"publicationSubtype":{"id":10}},"title":"Irrigated agriculture and future climate change effects on groundwater recharge, northern High Plains aquifer, USA","docAbstract":"Understanding the controls of agriculture and climate change on recharge rates is critically important to develop appropriate sustainable management plans for groundwater resources and coupled irrigated agricultural systems. In this study, several physical (total potential (ψT) time series) and chemical tracer and dating (3H, Cl−, Br−, CFCs, SF6, and 3H/3He) methods were used to quantify diffuse recharge rates beneath two rangeland sites and irrigation recharge rates beneath two irrigated corn sites along an east-west (wet-dry) transect of the northern High Plains aquifer, Platte River Basin, central Nebraska. The field-based recharge estimates and historical climate were used to calibrate site-specific Hydrus-1D models, and irrigation requirements were estimated using the Crops Simulation Model (CROPSIM). Future model simulations were driven by an ensemble of 16 global climate models and two global warming scenarios to project a 2050 climate relative to the historical baseline 1990 climate, and simulate changes in precipitation, irrigation, evapotranspiration, and diffuse and irrigation recharge rates. Although results indicate statistical differences between the historical variables at the eastern and western sites and rangeland and irrigated sites, the low warming scenario (+1.0 °C) simulations indicate no statistical differences between 2050 and 1990. However, the high warming scenarios (+2.4 °C) indicate a 25% and 15% increase in median annual evapotranspiration and irrigation demand, and decreases in future diffuse recharge by 53% and 98% and irrigation recharge by 47% and 29% at the eastern and western sites, respectively. These results indicate an important threshold between the low and high warming scenarios that if exceeded could trigger a significant bidirectional shift in 2050 hydroclimatology and recharge gradients. The bidirectional shift is that future northern High Plains temperatures will resemble present central High Plains temperatures and future recharge rates in the east will resemble present recharge rates in the western part of the northern High Plains aquifer. The reductions in recharge rates could accelerate declining water levels if irrigation demand and other management strategies are not implemented. Findings here have important implications for future management of irrigation practices and to slow groundwater depletion in this important agricultural region.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.agwat.2018.03.022","usgsCitation":"Lauffenburger, Z.H., Gurdak, J., Hobza, C.M., Woodward, D., and Wolf, C., 2018, Irrigated agriculture and future climate change effects on groundwater recharge, northern High Plains aquifer, USA: Agricultural Water Management, v. 204, p. 69-80, https://doi.org/10.1016/j.agwat.2018.03.022.","productDescription":"12 p.","startPage":"69","endPage":"80","ipdsId":"IP-095074","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":468796,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.agwat.2018.03.022","text":"Publisher Index Page"},{"id":353879,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Northern High Plains Aquifer","volume":"204","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6cce4b0da30c1bfbe18","contributors":{"authors":[{"text":"Lauffenburger, Zachary H.","contributorId":204545,"corporation":false,"usgs":false,"family":"Lauffenburger","given":"Zachary","email":"","middleInitial":"H.","affiliations":[{"id":6690,"text":"San Francisco State University","active":true,"usgs":false}],"preferred":false,"id":734307,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gurdak, Jason J.","contributorId":189822,"corporation":false,"usgs":false,"family":"Gurdak","given":"Jason J.","affiliations":[],"preferred":false,"id":734308,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hobza, Christopher M. 0000-0002-6239-934X cmhobza@usgs.gov","orcid":"https://orcid.org/0000-0002-6239-934X","contributorId":2393,"corporation":false,"usgs":true,"family":"Hobza","given":"Christopher","email":"cmhobza@usgs.gov","middleInitial":"M.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":734306,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Woodward, Duane","contributorId":204547,"corporation":false,"usgs":false,"family":"Woodward","given":"Duane","affiliations":[{"id":36954,"text":"Central Platte Natural Resources District","active":true,"usgs":false}],"preferred":false,"id":734310,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wolf, Cassandra","contributorId":204546,"corporation":false,"usgs":false,"family":"Wolf","given":"Cassandra","email":"","affiliations":[{"id":6690,"text":"San Francisco State University","active":true,"usgs":false}],"preferred":false,"id":734309,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196457,"text":"sir20185050 - 2018 - Discharge, sediment, and water chemistry in Clear Creek, western Nevada, water years 2013–16","interactions":[],"lastModifiedDate":"2018-05-02T10:35:24","indexId":"sir20185050","displayToPublicDate":"2018-05-01T00:00:00","publicationYear":"2018","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":"2018-5050","title":"Discharge, sediment, and water chemistry in Clear Creek, western Nevada, water years 2013–16","docAbstract":"Clear Creek is a small stream that drains the eastern Carson Range near Lake Tahoe, flows roughly parallel to the Highway 50 corridor, and discharges to the Carson River near Carson City, Nevada. Historical and ongoing development in the drainage basin is thought to be affecting Clear Creek and its sediment-transport characteristics. Previous studies from water years (WYs) 2004 to 2007 and from 2010 to 2012 evaluated discharge, selected water-quality parameters, and suspended-sediment concentrations, loads, and yields at three Clear Creek sampling sites. This report serves as a continuation of the data collection and analyses of the Clear Creek discharge regime and associated water-chemistry and sediment concentrations and loads during WYs 2013–16.
Total annual sediment loads ranged from 870 to 5,300 tons during WYs 2004–07, from 320 to 1,770 tons during WYs 2010–12, and from 50 to 200 tons during WYs 2013–16. Ranges in annual loads during the three study periods were not significantly different; however, total loads were greater during 2004–07 than they were during 2013–16. Annual suspended-sediment loads in WYs 2013–16 showed no significant change since WYs 2010–12 at sites 1 (U.S. Geological Survey reference site 10310485; Clear Creek above Highway 50, near Spooner Summit, Nevada) or 2 (U.S. Geological Survey streamgage 10310500; Clear Creek above Highway 50, near Spooner Summit, Nevada), but significantly lower loads at site 3 (U.S. Geological Survey site 10310518; Clear Creek at Fuji Park, at Carson City, Nevada), supporting the theory of sediment deposition between sites 2 and 3 where the stream gradient becomes more gradual. Currently, a threshold discharge of about 3.3 cubic feet per second is required to mobilize streambed sediment (bedload) from site 2 in Clear Creek. Mean daily discharge was significantly lower in 2010–12 than in 2004–07 and also significantly lower in 2013–16 than in 2010–12. During this study, lower bedload, and therefore lower total sediment load in Clear Creek was primarily due to significantly lower discharge and cannot be directly attributed to sediment mitigation work in the basin.
Water chemistry in Clear Creek shows that the general water type of the creek under base-flow conditions in autumn is a dilute calcium bicarbonate. During winter and spring, the chemistry shifts toward a slightly more sodium and chloride character. Though the chemical characteristics show seasonal change, the water chemistries examined as part of this investigation remain within ecological criteria as adopted by the Nevada Division of Environmental Protection. There was no evidence of aqueous polynuclear aromatic hydrocarbons (PAHs) present in Clear Creek water during this study. Concentrations of PAHs, as determined in one bed-sediment sample and multiple semi-permeable membrane device extracts, were either less than quantifiable limits of analysis or were found at similar concentrations as blank samples.
In July 2014, a 250–300-acre fire burned in the Clear Creek drainage basin. One day after the fire was extinguished, a thunderstorm washed sediment into the creek. A water chemistry sample collected as part of the post-fire storm event showed that the stormwater entering the creek had increased the concentrations of ammonium and organic nitrogen, phosphorus, manganese, and potassium; a similar finding of many other studies evaluating the effects of fires in small drainage basins. Subsequent chemical analyses of Clear Creek water in August 2014 (one month later) showed that these constituents had returned to pre-fire concentrations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185050","collaboration":"Prepared in cooperation with the Nevada Department of Transportation","usgsCitation":"Huntington, J.M., Riddle, D.J., and Paul, A.P., 2018, Discharge, sediment, and water chemistry in Clear Creek, western Nevada, water years 2013–16: U.S. Geological Survey Scientific-Investigations Report 2018–5050, 55 p., https://doi.org/10.3133/sir20185050.","productDescription":"vii, 55 p.","onlineOnly":"Y","ipdsId":"IP-067971","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":353895,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5050/sir20185050.pdf","text":"Report","size":"6.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5050"},{"id":353894,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5050/coverthb.jpg"}],"country":"United States","state":"Nevada","city":"Carson City","otherGeospatial":"Clear Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.9,\n 39.19\n ],\n [\n -119.7,\n 39.19\n ],\n [\n -119.7,\n 39.06\n ],\n [\n -119.9,\n 39.06\n ],\n [\n -119.9,\n 39.19\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Rd.
Carson City, Nevada 89701
The U.S. Geological Survey, in cooperation with the International Joint Commission, compiled historical data on regulated streamflows and lake levels and estimated unregulated streamflows and lake levels on Forest City Stream at Forest City, Maine, and East Grand Lake on the United States-Canada border between Maine and New Brunswick to study the effects on streamflows and lake levels if two or all three dam gates are left open. Historical regulated monthly mean streamflows in Forest City Stream at the outlet of East Grand Lake (referred to as Grand Lake by Environment Canada) fluctuated between 114 cubic feet per second (ft3 /s) (3.23 cubic meters per second [m3 /s]) in November and 318 ft3 /s (9.01 m3 /s) in September from 1975 to 2015 according to Environment Canada streamgaging data. Unregulated monthly mean streamflows at this location estimated from regression equations for unregulated sites range from 59.2 ft3 /s (1.68 m3 /s) in September to 653 ft3 /s (18.5 m3 /s) in April. Historical lake levels in East Grand Lake fluctuated between 431.3 feet (ft) (131.5 meters [m]) in October and 434.0 ft (132.3 m) in May from 1969 to 2016 according to Environment Canada lake level data for East Grand Lake. Average monthly lake levels modeled by using the estimated hydrology for unregulated flows, and an outflow rating built from a hydraulic model with all gates at the dam open, range from 427.7 ft (130.4 m) in September to 431.1 ft (131.4 m) in April. Average monthly lake levels would likely be from 1.8 to 5.4 ft (0.55 to 1.6 m) lower with the gates at the dam opened than they have been historically. The greatest lake level changes would be from June through September.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185044","collaboration":"Prepared in cooperation with the International Joint Commission","usgsCitation":"Lombard, P.J., 2018, Estimation of unregulated monthly, annual, and peak streamflows in Forest City Stream and lake levels in East Grand Lake, United States-Canada border between Maine and New Brunswick: U.S. Geological Survey Scientific Investigations Report 2018–5044, 8 p., https://doi.org/10.3133/sir20185044.","productDescription":"Report: iv, 8 p.; Data release","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-092951","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":353763,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7PN94VN","text":"USGS data release","description":"USGS data release","linkHelpText":"Bathymetric data for St. Croix River at outlet to East Grand Lake and Forest City Dam Survey, United States-Canadian border between Maine and New Brunswick"},{"id":353745,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5044/sir20185044.pdf","text":"Report","size":"873 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5044"},{"id":353744,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5044/coverthb.jpg"}],"country":"Canada, United States","state":"Maine, New Brunswick","otherGeospatial":"East Grand Lake, Forest City Stream","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.884521484375,\n 45.60587170876381\n ],\n [\n -67.68951416015625,\n 45.60587170876381\n ],\n [\n -67.68951416015625,\n 45.82066487514085\n ],\n [\n -67.884521484375,\n 45.82066487514085\n ],\n [\n -67.884521484375,\n 45.60587170876381\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
196 Whitten Road
Augusta, ME 04330
Hurricane Sandy was a large and intense storm with high winds that caused total water levels from combined tides and storm surge to reach 4.0 m in the Atlantic Ocean and 2.5 m in Great South Bay (GSB), a back-barrier bay between Fire Island and Long Island, New York. In this study the impact of the hurricane winds and waves are examined in order to understand the flow of ocean water into the back-barrier bay and water level variations within the bay. To accomplish this goal, a high resolution hurricane wind field is used to drive the coupled Delft3D-SWAN hydrodynamic and wave models over a series of grids with the finest resolution in GSB. The processes that control water levels in the back-barrier bay are investigated by comparing the results of four cases that include: (i) tides only; (ii) tides, winds and waves with no overwash over Fire Island allowed; (iii) tides, winds, waves and limited overwash at the east end of the island; (iv) tides, winds, waves and extensive overwash along the island. The results indicate that strong local wind-driven storm surge along the bay axis had the largest influence on the total water level fluctuations during the hurricane. However, the simulations allowing for overwash have higher correlation with water level observations in GSB and suggest that island overwash provided a significant contribution of ocean water to eastern GSB during the storm. The computations indicate that overwash of 7500–10,000 m3s−1 was approximately the same as the inflow from the ocean through the major existing inlet. Overall, the model results indicate the complex variability in total water levels driven by tides, ocean storm surge, surge from local winds, and overwash that had a significant impact on the circulation in Great South Bay during Hurricane Sandy.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.csr.2018.04.003","usgsCitation":"Bennett, V.C., Mulligan, R.P., and Hapke, C.J., 2018, A numerical model investigation of the impacts of Hurricane Sandy on water level variability in Great South Bay, New York: Continental Shelf Research, v. 161, p. 1-11, https://doi.org/10.1016/j.csr.2018.04.003.","productDescription":"11 p.","startPage":"1","endPage":"11","ipdsId":"IP-082328","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468811,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.csr.2018.04.003","text":"Publisher Index Page"},{"id":353706,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Great South Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.7,\n 40.55\n ],\n [\n -72.7,\n 40.55\n ],\n [\n -72.7,\n 40.8\n ],\n [\n -73.7,\n 40.8\n ],\n [\n -73.7,\n 40.55\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"161","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6d0e4b0da30c1bfbe52","contributors":{"authors":[{"text":"Bennett, Vanessa C. C.","contributorId":204457,"corporation":false,"usgs":false,"family":"Bennett","given":"Vanessa","email":"","middleInitial":"C. C.","affiliations":[{"id":36943,"text":"Queens University","active":true,"usgs":false}],"preferred":false,"id":734015,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mulligan, Ryan P.","contributorId":194423,"corporation":false,"usgs":false,"family":"Mulligan","given":"Ryan","email":"","middleInitial":"P.","affiliations":[{"id":35723,"text":"Queen's University - Kingston, Ontario","active":true,"usgs":false}],"preferred":false,"id":734016,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hapke, Cheryl J. 0000-0002-2753-4075 chapke@usgs.gov","orcid":"https://orcid.org/0000-0002-2753-4075","contributorId":2981,"corporation":false,"usgs":true,"family":"Hapke","given":"Cheryl","email":"chapke@usgs.gov","middleInitial":"J.","affiliations":[{"id":6676,"text":"USGS (retired)","active":true,"usgs":false}],"preferred":true,"id":734014,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196520,"text":"ofr20181064 - 2018 - Status and trends of adult Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) sucker populations in Upper Klamath Lake, Oregon, 2017","interactions":[],"lastModifiedDate":"2018-04-25T10:18:41","indexId":"ofr20181064","displayToPublicDate":"2018-04-24T00:00:00","publicationYear":"2018","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":"2018-1064","displayTitle":"Status and trends of adult Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) sucker populations in Upper Klamath Lake, Oregon, 2017","title":"Status and trends of adult Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) sucker populations in Upper Klamath Lake, Oregon, 2017","docAbstract":"Data from a long-term capture-recapture program were used to assess the status and dynamics of populations of two long-lived, federally endangered catostomids in Upper Klamath Lake, Oregon. Lost River suckers (LRS; Deltistes luxatus) and shortnose suckers (SNS; Chasmistes brevirostris) have been captured and tagged with passive integrated transponder (PIT) tags during their spawning migrations in each year since 1995. In addition, beginning in 2005, individuals that had been previously PIT-tagged were re-encountered on remote underwater antennas deployed throughout sucker spawning areas. Captures and remote encounters during the spawning season in spring 2016 were incorporated into capture-recapture analyses of population dynamics.
Cormack-Jolly-Seber (CJS) open population capture-recapture models were used to estimate annual survival probabilities, and a reverse-time analog of the CJS model was used to estimate recruitment of new individuals into the spawning populations. In addition, data on the size composition of captured fish were examined to provide corroborating evidence of recruitment. Model estimates of survival and recruitment were used to derive estimates of changes in population size over time and to determine the status of the populations through 2015. Separate analyses were done for each species and also for each subpopulation of LRS. Shortnose suckers and one subpopulation of LRS migrate into tributary rivers to spawn, whereas the other LRS subpopulation spawns at groundwater upwelling areas along the eastern shoreline of the lake.
Capture-recapture analyses indicated that with a few exceptions, the survival of males and females in both Lost River sucker subpopulations was high (greater than 0.88) from 1999 to 2015. Survival was notably lower for males from the river in 2000, 2006, and 2012, and for the shoreline areas in 2002. From 2001 to 2015, the abundance of males in the lakeshore spawning subpopulation decreased by at least 64 percent and the abundance of females decreased by at least 56 percent. Capture-recapture models suggested that the abundance of both sexes in the river spawning subpopulation of LRS had increased substantially since 2006; increases were mostly due to large estimated recruitment events in 2006 and 2008. We know that the estimates in 2006 are substantially biased in favor of recruitment because of a sampling issue. We are skeptical of the magnitude of recruitment indicated by the 2008 estimates as well because (1) few small individuals that would indicate the presence of new recruits were captured in that year, and (2) recapture probabilities in recruitment models based on just physical recaptures of fish were lower than desired for robust inferences from capture-recapture models. If we assume instead that little or no recruitment occurred for this subpopulation, the abundance of both sexes in the river spawning subpopulation likely has decreased at rates similar to the rates for the lakeshore spawning subpopulation from 2002 to 2015.
Shortnose suckers experienced lower and more variable annual survival than either LRS subpopulation. Annual survival of both sexes was relatively low in 2003, 2004, 2010, and 2012. In addition, female survival was low in 1999 and 2000 while male survival was low in 2002. Survival estimate precision in early years of the study; however, are poor. Capture-recapture models and size composition data indicate that recruitment of new individuals into the SNS spawning population was trivial from 2001 to 2005. Models indicate that more than 10 percent of the population was new recruits in a number of more recent years. As a result, capture-recapture modeling suggests that the abundance of adult spawning SNS was relatively stable from 2006 to 2010. We are skeptical of the estimated recruitment in 2006 because of the known sampling issue. We also are skeptical of the estimated recruitment in other recent years because few small individuals that would indicate the presence of new recruits were captured in any of those years, and recapture probabilities in recruitment models were low. The best-case scenario for SNS, based on capture-recapture recruitment modeling, indicates that the abundance of males in the spawning population decreased by 78 percent and the abundance of females decreased by 77 percent from 2001 to 2015. Decreases in abundance for both sexes are likely greater than these estimates indicate.
Despite relatively high survival in most years, we conclude that both species have experienced substantial decreases in the abundance of spawning adults because losses from mortality have not been balanced by recruitment of new individuals. Although capture-recapture data indicate substantial recruitment of new individuals into the spawning populations for SNS and river spawning LRS in some years, size data do not corroborate these estimates. As a result, the status of the endangered sucker populations in Upper Klamath Lake remains distressed, especially for SNS. Our monitoring program provides a robust platform for estimating vital population parameters, evaluating the status of the populations, and assessing the effectiveness of conservation and recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181064","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Hewitt, D.A., Janney, E.C., Hayes, B.S., and Harris, A.C., 2018, Status and trends of adult Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) sucker populations in Upper Klamath Lake, Oregon, 2017: U.S. Geological Survey Open-File Report 2018-1064, 31 p., https://doi.org/10.3133/ofr20181064.","productDescription":"iv, 31 p.","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-096959","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":437938,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97K04NO","text":"USGS data release","linkHelpText":"Status and trends of adult Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) sucker populations in Upper Klamath Lake, Oregon, 2023"},{"id":353417,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1064/coverthb.jpg"},{"id":353418,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1064/ofr20181064.pdf","text":"Report","size":"905 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1064"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.10067749023438,\n 42.21936476344714\n ],\n [\n -121.79992675781249,\n 42.21936476344714\n ],\n [\n -121.79992675781249,\n 42.61981257367216\n ],\n [\n -122.10067749023438,\n 42.61981257367216\n ],\n [\n -122.10067749023438,\n 42.21936476344714\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within the 3-nautical-mile limit of California’s State Waters. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data, acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow subsurface geology.
The Offshore of Point Conception map area is in the westernmost part of the Western Transverse Ranges geologic province, which is north of the California Continental Borderland. Significant clockwise rotation—at least 90°—since the early Miocene has been proposed for the Western Transverse Ranges province, and this region is presently undergoing north-south shortening. The offshore part of the map area lies south of the steep south and west flanks of the Santa Ynez Mountains. The crest of the range, which has a maximum elevation of about 340 m in the map area, lies about 5 km north and east of the arcuate shoreline.
The onland part of the coastal zone is remote and sparsely populated. The road to Jalama Beach County Park provides the only public coastal access in the entire map area. North of this county park, the coastal zone is part of Vandenberg Air Force Base. South of Jalama Beach County Park, most of the coastal zone is part of the Cojo-Jalama Ranch, purchased by the Nature Conservancy in December 2017. A relatively small part of the coastal zone in the eastern part of the map area lies within the privately owned Hollister Ranch. The nearest significant commercial centers are Lompoc (population, about 42,000), about 10 km north of the map area, and Goleta (population, about 30,000), about 50 km east of the map area. The Union Pacific railroad tracks run west and northwest along the coast through the entire map area, within a few hundred meters of the shoreline. The map area has a long history of petroleum exploration, and the seafloor notably includes large asphalt mounds and pockmarks that result from petroleum seepage. Several offshore gas and oil fields were discovered, and some were developed, in and on the margin of California’s State Waters.
Much of the shoreline in the Offshore of Point Conception map area is characterized by narrow beaches that have thin sediment cover above bedrock platforms, backed by low (10- to 20-m-high) cliffs that are capped by a coastal terrace. Beaches are subject to wave erosion during winter storms, followed by gradual sediment recovery or accretion in the late spring, summer, and fall months during the gentler wave climate. The map area lies in the west-central part of the Santa Barbara littoral cell, which is characterized by west-to-east transport of sediment from Point Arguello on the northwest to Hueneme and Mugu Canyons on the southeast. Sediment supply to the map area is mainly from relatively small coastal watersheds, including the Jalama Creek–Espada Creek drainage basin (about 63 km2), as well as Cañada del Jolloru, Black Canyon, Wood Canyon, Cañada del Cojo, and Barranca Honda. Coastal-watershed discharge and sediment load are highly variable, characterized by brief large events during major winter storms and long periods of low (or no) flow and minimal sediment load between storms. In recent (recorded) history, the majority of high-discharge, high-sediment-flux events have been associated with El Niño phases of the El Niño–Southern Oscillation climatic pattern.
Following the coastline, the shelf bends to the north and northwest around Point Conception, and the trend of the shelf break changes from about 298° to 241° azimuth. Shelf width ranges from about 5 km south of Point Conception to about 11 km northwest of it; the slope ranges from about 1.0° to 1.2° to about 0.7° south and northwest of Point Conception, respectively. Southwest of Point Conception, the shelf break and upper slope are incised by a 600-m-wide, 20- to 30-m-deep, south-facing trough, one of five heads of the informally named Arguello submarine canyon.
The map area is located at a major biogeographic transition zone between the east-west-trending Santa Barbara Channel region of the Southern California Bight and the northwest-trending central California coast. North of Point Conception, the coast is subjected to high wave exposure from the north, west, and south, as well as consistently strong upwelling that brings cold, nutrient-rich waters to the surface. Southeast of Point Conception, the Santa Barbara Channel is largely protected from strong north swells by Point Conception and from south swells by the Channel Islands; surface waters are warmer, and upwelling is weak and seasonal.
Seafloor habitats in the broad Santa Barbara Channel region consist of significant amounts of soft, unconsolidated sediment interspersed with isolated areas of rocky habitat that support kelp-forest communities in the nearshore and rocky-reef communities in deeper water. The potential marine benthic habitat types mapped in the Offshore of Point Conception map area are directly related to its Quaternary geologic history, geomorphology, and active sedimentary processes. These potential habitats lie primarily within the Shelf (continental shelf) but also partly within the Flank (basin flank or continental slope) megahabitats. The fairly homogeneous seafloor of sediment and low-relief bedrock provides characteristic habitat for rockfish, groundfish, crabs, shrimp, and other marine benthic organisms. Several areas of smooth sediment form nearshore terraces that have relatively steep, smooth fronts, which are attractive to groundfish. Below the steep shelf break, soft, unconsolidated sediment is interrupted by the heads of several submarine canyons, gullies, and rills, also good potential habitat for rockfish. The map area includes the large (58.3 km2) Point Conception State Marine Reserve.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181024","usgsCitation":"Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series— Offshore of Point Conception, California: U.S. Geological Survey Open-File Report 2018–1024, pamphlet 36 p., 9 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20181024.","productDescription":"Pamphlet: iv, 36 p.; 9 Sheets: 55.0 x 36.0 inches or smaller; Dataset; Metadata","additionalOnlineFiles":"Y","ipdsId":"IP-082855","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":437940,"rank":23,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7QN64XQ","text":"USGS data release","linkHelpText":"California State Waters Map Series Data Catalog--Offshore of Point Conception, California"},{"id":353525,"rank":9,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1024/ofr20181024_sheet8.pdf","text":"Sheet 8","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1024 Sheet 8","linkHelpText":"Local (Offshore of Point Conception Map Area) and Regional (Offshore from Point Conception to Hueneme Canyon) Shallow-Subsurface Geology and Structure, Santa Barbara Channel, California By Samuel Y. Johnson and Stephen R. Hartwell"},{"id":353524,"rank":8,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1024/ofr20181024_sheet7.pdf","text":"Sheet 7","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1024 Sheet 7","linkHelpText":"Seismic-Reflection Profiles, Offshore of Point Conception Map Area, California By Samuel Y. Johnson and Stephen R. Hartwell"},{"id":353532,"rank":16,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sim3302","text":"Scientific Investigations Map 3302","description":"Scientific Investigations Map 3302","linkHelpText":"California State Waters Map Series—Offshore of Coal Oil Point, California, by Sam Y. Johnson and others."},{"id":353531,"rank":15,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sim3319","text":"Scientific Investigations Map 3319","description":"Scientific Investigations Map 3319","linkHelpText":"California State Waters Map Series—Offshore of Refugio Beach, California, by Sam Y. Johnson and others."},{"id":353530,"rank":14,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20181023","text":"Open-File Report 2018–1023","description":"Open-File Report 2018–1023","linkHelpText":"California State Waters Map Series—Offshore of Gaviota, California, by Sam Y. Johnson and others."},{"id":353528,"rank":12,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7QN64XQ","text":"Data Catalog","linkFileType":{"id":5,"text":"html"},"description":"OFR 2018-1024 Data Catalog","linkHelpText":"The GIS data layers for this map are accessible from “California State Waters Map Series—Offshore of Point Conception, California” which is part of California State Waters Map Series Data Catalog. Each GIS data file is listed with a brief description, a small image, and links to the metadata files and the downloadable data files."},{"id":353526,"rank":10,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1024/ofr20181024_sheet9.pdf","text":"Sheet 9","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1024 Sheet 9","linkHelpText":"Offshore and Onshore Geology and Geomorphology, Offshore of Point Conception Map Area, California By Samuel Y. Johnson, Stephen R. Hartwell, and Clifton W. Davenport"},{"id":353529,"rank":13,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/781/","text":"Data Series 781","description":"Data Series 781","linkHelpText":"California State Waters Map Series Data Catalog"},{"id":353523,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1024/ofr20181024_sheet6.pdf","text":"Sheet 6","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1024 Sheet 6","linkHelpText":"Marine Benthic Habitats from the Coastal and Marine Ecological Classification Standard, Offshore of Point Conception Map Area, California By Guy R. Cochrane, Stephen R. Hartwell, and Samuel Y. Johnson"},{"id":353535,"rank":19,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/sim/3254/","text":"Scientific Investigations Map 3254","description":"Scientific Investigations Map 3254","linkHelpText":"California State Waters Map Series—Offshore of Ventura, California, by Sam Y. Johnson and others."},{"id":353534,"rank":18,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/sim/3261/","text":"Scientific Investigations Map 3261","description":"Scientific Investigations Map 3261","linkHelpText":"California State Waters Map Series—Offshore of Carpinteria, California, by Sam Y. Johnson and others."},{"id":353533,"rank":17,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sim3281","text":"Scientific Investigations Map 3281","description":"Scientific Investigations Map 3281","linkHelpText":"California State Waters Map Series—Offshore of Santa Barbara, California, by Sam Y. Johnson and others."},{"id":399118,"rank":22,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_107162.htm"},{"id":353555,"rank":21,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2018/1024/ofr20181024_metadata.html","text":"Metadata","description":"OFR 2018-1024 Metadata"},{"id":353536,"rank":20,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/sim/3225/","text":"Scientific Investigations Map 3225","description":"Scientific Investigations Map 3225","linkHelpText":"California State Waters Map Series—Hueneme Canyon and Vicinity, California, by Sam Y. Johnson and others."},{"id":353527,"rank":11,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1024/ofr20181024_pamphlet.pdf","text":"Pamphlet","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1024 Pamphlet"},{"id":353522,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1024/ofr20181024_sheet5.pdf","text":"Sheet 5","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1024 Sheet 5","linkHelpText":"Seafloor Character, Offshore of Point Conception Map Area, California By Stephen R. Hartwell and Guy R. Cochrane"},{"id":353521,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1024/ofr20181024_sheet4.pdf","text":"Sheet 4","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1024 Sheet 4","linkHelpText":"Data Integration and Visualization, Offshore of Point Conception Map Area, California By Peter Dartnell"},{"id":353520,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1024/ofr20181024_sheet3.pdf","text":"Sheet 3","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1024 Sheet 3","linkHelpText":"Acoustic Backscatter, Offshore of Point Conception Map Area, California By Peter Dartnell and Rikk G. 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Kvitek"},{"id":353517,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1024/coverthb.jpg"}],"scale":"24000","country":"United States","state":"California","otherGeospatial":"Point Conception","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.5636,\n 34.3917\n ],\n [\n -120.3717,\n 34.3917\n ],\n [\n -120.3717,\n 34.5422\n ],\n [\n -120.5636,\n 34.5422\n ],\n [\n -120.5636,\n 34.3917\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information
Pacific Coastal & Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
http://walrus.wr.usgs.gov/
In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within the 3-nautical-mile limit of California’s State Waters. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data, acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow subsurface geology.
The map area is in the southern part of the Western Transverse Ranges geologic province, which is north of the California Continental Borderland. Significant clockwise rotation—at least 90°—since the early Miocene has been proposed for the Western Transverse Ranges province, and the region is presently undergoing north-south shortening. The offshore part of the map area lies south of the steep south flank of the Santa Ynez Mountains. The crest of the range, which has a maximum elevation of about 760 m in the map area, lies about 4 km north of the shoreline.
Gaviota is an unincorporated community that has a sparse population (less than 100), and the coastal zone is largely open space that is locally used for cattle grazing. The Union Pacific railroad tracks extend westward along the coast through the entire map area, within a few hundred meters of the shoreline. Highway 101 crosses the eastern part of the map area, also along the coast, then turns north (inland) and travels through Cañada de la Gaviota and Gaviota Pass en route to Buellton. Gaviota State Park lies at the mouth of Cañada de la Gaviota. West of Gaviota, the onland coastal zone is occupied by the Hollister Ranch, a privately owned, gated community that has no public access.
The map area has a long history of petroleum exploration and development. Several offshore gas fields were discovered and were developed by onshore directional drilling in the 1950s and 1960s. Three offshore petroleum platforms were installed in adjacent federal waters in 1976 (platform “Honda”) and 1989 (platforms “Heritage” and “Harmony”). Local offshore and onshore operations were serviced for more than a century by the Gaviota marine terminal, which is currently being decommissioned and will be abandoned in an intended transition to public open space.
The Offshore of Gaviota map area lies within the western Santa Barbara Channel region of the Southern California Bight, and it is somewhat protected from large Pacific swells from the north and northwest by Point Conception and from south and southwest swells by offshore islands and banks. Much of the shoreline in the map area is characterized by narrow beaches that have thin sediment cover, backed by low (10- to 20-m-high) cliffs that are capped by a narrow coastal terrace. Beaches are subject to wave erosion during winter storms, followed by gradual sediment recovery or accretion in the late spring, summer, and fall months during the gentler wave climate.
The map area lies in the western-central part of the Santa Barbara littoral cell, which is characterized by west-to-east transport of sediment from Point Arguello on the northwest to Hueneme and Mugu Canyons on the southeast. Sediment supply to the western and central part of the littoral cell is mainly from relatively small coastal watersheds. In the map area, sediment sources include Cañada de la Gaviota (52 km2), as well as Cañada de la Llegua, Arroyo el Bulito, Cañada de Santa Anita, Cañada de Alegria, Cañada del Agua Caliente, Cañada del Barro, Cañada del Leon, Cañada San Onofre, and many others. Coastal-watershed discharge and sediment load are highly variable, characterized by brief large events during major winter storms and long periods of low (or no) flow and minimal sediment load between storms. In recent (recorded) history, the majority of high-discharge, high-sediment-flux events have been associated with El Niño phases of the El Niño–Southern Oscillation climatic pattern.
Shelf width in the Offshore of Gaviota map area ranges from about 4.3 to 4.7 km, and shelf slopes average about 1.0° to 1.2° but are highly variable because of the presence of the large Gaviota sediment bar. This bar extends southwestward for about 9 km from the mouth of Cañada de la Gaviota to the shelf break, is as wide as 2 km, and is by far the largest shore-attached sediment bar in the Santa Barbara Channel. The shelf is underlain by bedrock and variable amounts (0 to as much as 36 m in the Gaviota bar) of upper Quaternary sediments deposited as sea level fluctuated in the late Pleistocene. The trend of the shelf break changes from about 276° to 236° azimuth over a distance of about 12 km, and it ranges in depth from about 91 m to as shallow as 62 to 73 m where significant shelf-break and upper-slope failure and landsliding has apparently occurred. The shelf break in the western part of the map area is notably embayed by the heads of three large (150- to 300-m-wide) channels that have been referred to as “the Gaviota Canyons” or as “Drake Canyon,” “Sacate Canyon,” and “Alegria Canyon.”
Seafloor habitats in the broad Santa Barbara Channel region consist of significant amounts of soft, unconsolidated sediment interspersed with isolated areas of rocky habitat that support kelp-forest communities in the nearshore and rocky-reef communities in deeper water. The potential marine benthic habitat types mapped in the Offshore of Gaviota map area are directly related to its Quaternary geologic history, geomorphology, and active sedimentary processes. These potential habitats lie primarily within the Shelf (continental shelf) but also partly within the Flank (basin flank or continental slope) megahabitats. The fairly homogeneous seafloor of sediment and low-relief bedrock provides characteristic habitat for rockfish, groundfish, crabs, shrimp, and other marine benthic organisms. Several areas of smooth sediment form nearshore terraces that have relatively steep, smooth fronts, which may be attractive to groundfish. Below the steep shelf break, soft, unconsolidated sediment is interrupted by the heads of several submarine canyons and rills, some bedrock exposures, and small carbonate mounds associated with asphalt mounds and pockmarks, also good potential habitat for rockfish. The map area includes the relatively small (5.2 km2) Kashtayit State Marine Conservation Area, which largely occupies the inner part of the Gaviota sediment bar.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181023","usgsCitation":"Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series— Offshore of Gaviota, California: U.S. Geological Survey Open-File Report 2018–1023, pamphlet 41 p., 9 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20181023.","productDescription":"Pamphlet: iv, 41 p.; 9 Sheets: 52.0 x 36.0 inches or smaller; Dataset; Metadata","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-082722","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":437941,"rank":23,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TH8JWJ","text":"USGS data release","linkHelpText":"California State Waters Map Series Data Catalog--Offshore of Gaviota, California"},{"id":399119,"rank":22,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_107161.htm"},{"id":353556,"rank":21,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2018/1023/ofr20181023_metadata.html","text":"Metadata","description":"OFR 2018-1023 Metadata"},{"id":353516,"rank":20,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1023/ofr20181023_pamphlet.pdf","text":"Pamphlet","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1023 Pamphlet"},{"id":353515,"rank":19,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7TH8JWJ","text":"Data Catalog","linkFileType":{"id":5,"text":"html"},"description":"OFR 2018-1023 Data Catalog","linkHelpText":"The GIS data layers for this map are accessible from “California State Waters Map Series—Offshore of Gaviota, California” which is part of California State Waters Map Series Data Catalog. 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Davenport"},{"id":353504,"rank":8,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1023/ofr20181023_sheet8.pdf","text":"Sheet 8","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1023 Sheet 8","linkHelpText":"Local (Offshore of Gaviota Map Area) and Regional (Offshore from Point Conception to Hueneme Canyon) Shallow-Subsurface Geology and Structure, Santa Barbara Channel, California By Samuel Y. Johnson and Stephen R. Hartwell"},{"id":353503,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1023/ofr20181023_sheet7.pdf","text":"Sheet 7","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1023 Sheet 7","linkHelpText":"Seismic-Reflection Profiles, Offshore of Gaviota Map Area, California By Samuel Y. Johnson and Stephen R. Hartwell"},{"id":353502,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1023/ofr20181023_sheet6.pdf","text":"Sheet 6","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1023 Sheet 6","linkHelpText":"Marine Benthic Habitats from the Coastal and Marine Ecological Classification Standard, Offshore of Gaviota Map Area, California By Guy R. Cochrane, Stephen R. Hartwell, and Samuel Y. Johnson"},{"id":353506,"rank":10,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1023/coverthb.jpg"}],"scale":"24000","country":"United States","state":"California","city":"Gaviota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.3753,\n 34.4056\n ],\n [\n -120.1833,\n 34.4056\n ],\n [\n -120.1833,\n 34.5425\n ],\n [\n -120.3753,\n 34.5425\n ],\n [\n -120.3753,\n 34.4056\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information
Pacific Coastal & Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
http://walrus.wr.usgs.gov/
The bedrock geologic map of the Miles Pond and Concord quadrangles covers an area of approximately 107 square miles (276 square kilometers) in east-central Vermont and adjacent New Hampshire, north of and along the Connecticut River. This map was created as part of a larger effort to produce a new bedrock geologic map of Vermont through the collection of field data at a scale of 1:24,000. The majority of the map area consists of the Bronson Hill anticlinorium, a post-Early Devonian structure that is cored by metamorphosed Cambrian to Silurian sedimentary, volcanic, and plutonic rocks. A major feature on the map is the Monroe fault, interpreted to be a west-directed, steeply dipping Late Devonian (Acadian) thrust fault. To the west of the Monroe fault, rocks of the Connecticut Valley-Gaspé trough dominate and consist primarily of metamorphosed Silurian and Devonian sedimentary rocks. To the north, the Victory pluton intrudes the Bronson Hill anticlinorium. The Bronson Hill anticlinorium consists of the metamorphosed Albee Formation, the Ammonoosuc Volcanics, the Comerford Intrusive Complex, the Highlandcroft Granodiorite, and the Joselin Turn tonalite. The Albee Formation is an interlayered, feldspathic metasandstone and pelite that is locally sulfidic. Much of the deformed metasandstone is tectonically pinstriped. In places, one can see compositional layering that was transposed by a steeply southeast-dipping foliation. The Ammonoosuc Volcanics are lithologically complex and predominantly include interlayered and interfingered rhyolitic to basaltic volcanic and volcaniclastic rocks, as well as lesser amounts of siltstone, phyllite, graywacke, and grit. The Comerford Intrusive Complex crops out east of the Monroe fault and consists of metamorphosed gabbro, diorite, tonalite, aplitic tonalite, and crosscutting diabase dikes. Abundant mafic dikes from the Comerford Intrusive Complex intruded the Albee Formation and Ammonoosuc Volcanics east of the Monroe fault. The Highlandcroft Granodiorite and Joslin Turn tonalite plutons intruded during the Middle to Late Ordovician.
West of the Monroe fault, the Connecticut Valley-Gaspé trough consists of the Silurian and Devonian Waits River and Gile Mountain Formations. The Waits River Formation is a carbonaceous muscovite-biotite-quartz (±garnet) phyllite containing abundant beds of micaceous quartz-rich limestone. The Gile Mountain Formation consists of interlayered metasandstone and graphitic (and commonly sulfidic) slate, along with minor calcareous metasandstone and ironstone. Graded bedding is common in the Gile Mountain Formation. Rocks of the Devonian New Hampshire Plutonic Suite intruded as plutons, dikes, and sills. The largest of these is the Victory pluton, which consists of weakly foliated, biotite granite and granodiorite. The Victory pluton also intruded a large part of the Albee Formation to the north.
This report consists of a geologic map and an online geographic information systems database that includes contacts of bedrock geologic units, faults, outcrops, and structural geologic information. The geologic map is intended to serve as a foundation for applying geologic information to problems involving land use decisions, groundwater availability and quality, earth resources such as natural aggregate for construction, assessment of natural hazards, and engineering and environmental studies for waste disposal sites and construction projects.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181025","collaboration":"Prepared in cooperation with the State of Vermont, Vermont Agency of Natural Resources, Vermont Geological Survey, and the State of New Hampshire, Department of Environmental Services, New Hampshire Geological Survey","usgsCitation":"Rankin, D.W., 2018, Bedrock geologic map of the Miles Pond and Concord quadrangles, Essex and Caledonia Counties, Vermont, and Grafton County, New Hampshire: U.S. Geological Survey Open-File Report 2018–1025, 1 sheet, scale 1:24,000, https://doi.org/10.3133/ofr20181025.","productDescription":"1 Sheet: 34.47 x 40.58 inches; Databases; Metadata; Spatial Data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-081110","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":353546,"rank":3,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2018/1025/metadata/ofr20181025_milespond-concordnh-geologicmap.mxd","text":"Geologic Map (ArcGIS 10.5)","linkHelpText":"- Miles Pond and Concord, Vermont, and New Hampshire, Geologic Map"},{"id":353538,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1025/ofr20181025_concord-miles-pond-geologicmap10.pdf","text":"Geologic Map","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1025"},{"id":399116,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_107158.htm"},{"id":353547,"rank":6,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2018/1025/metadata/ofr20181025_milespond-concordnh-metadata.zip","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Miles Pond and Concord, Vermont, and New Hampshire, Metadata"},{"id":353545,"rank":5,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2018/1025/metadata/ofr20181025_milespond-concordnh.gdb.zip","text":"Database","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Miles Pond and Concord, Vermont, and New Hampshire, Geodatabase"},{"id":353544,"rank":4,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2018/1025/metadata/ofr20181025_milespond-concordnh-basemap.zip","text":"Base Map","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Miles Pond and Concord, Vermont, and New Hampshire, Base Map"},{"id":353537,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1025/coverthb3.jpg"}],"scale":"24000","country":"United States","state":"New Hampshire, Vermont","county":"Caledonia County, Essex County, Grafton County","otherGeospatial":"Miles Pond and Concord quadrangles","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72,\n 44.375\n ],\n [\n -71.75,\n 44.375\n ],\n [\n -71.75,\n 44.5\n ],\n [\n -72,\n 44.5\n ],\n [\n -72,\n 44.375\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Eastern Geology and Paleoclimate
Science Center
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192
The bedrock geologic map of the Lisbon quadrangle, and parts of the Sugar Hill and East Haverhill quadrangles, Grafton County, New Hampshire, covers an area of approximately 73 square miles (189 square kilometers) in west-central New Hampshire. This map was created as part of a larger effort to produce a new bedrock geologic map of Vermont through the collection of field data at a scale of 1:24,000. A large part of the map area consists of the Bronson Hill anticlinorium, a post-Early Devonian structure that is cored by metamorphosed Cambrian to Devonian sedimentary, volcanic, and plutonic rocks.
The Bronson Hill anticlinorium is the apex of the Middle Ordovician to earliest-Silurian Bronson Hill magmatic arc that contains the Ammonoosuc Volcanics, Partridge Formation, and Oliverian Plutonic Suite, and extends from Maine, through western New Hampshire (down the eastern side of the Connecticut River), through southern New England to Long Island Sound. The deformed and partially eroded arc is locally overlain by a relatively thin Silurian section of metasedimentary rocks (Clough Quartzite and Fitch Formation) that thickens to the east. The Silurian section near Littleton is disconformably overlain by a thicker, Lower Devonian section that includes mostly metasedimentary and minor metavolcanic rocks of the Littleton Formation. The Bronson Hill anticlinorium is bisected by a series of northeast-southwest trending Mesozoic normal faults. Primarily among them is the steeply northwest-dipping Ammonoosuc fault that divides older and younger units (lower and upper sections) of the Ammonoosuc Volcanics. The Ammonoosuc Volcanics are lithologically complex and predominantly include interlayered and interfingered rhyolitic to basaltic volcanic and volcaniclastic rocks, as well as lesser amounts of slate, phyllite, ironstone, chert, sandstone, and pelite. The Albee Formation underlies the Ammonoosuc Volcanics and is predominantly composed of interbedded metamorphosed sandstone, siltstone, and phyllite.
During the Late Ordovician, a series of arc-related plutons intruded the Ammonoosuc Volcanics including the Moody Ledge pluton and the Scrag granite of Billings (1937). Subsequent plutonism related to the Acadian orogeny occurred after volcanism and deposition resulted in the Littleton Formation during the Late Devonian, including the intrusion of the Haverhill pluton and French Pond Granite found in the southern part of the map.
This report consists of a geologic map and an online geographic information systems database that includes contacts of bedrock geologic units, faults, outcrops, and structural geologic information. The geologic map is intended to serve as a foundation for applying geologic information to problems involving land use decisions, groundwater availability and quality, earth resources such as natural aggregate for construction, assessment of natural hazards, and engineering and environmental studies for waste disposal sites and construction projects.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181016","collaboration":"Prepared in cooperation with the State of Vermont, Vermont Agency of Natural Resources, Vermont Geological Survey, and the State of New Hampshire, Department of Environmental Services, New Hampshire Geological Survey","usgsCitation":"Rankin, D.W., 2018, Bedrock geologic map of the Lisbon quadrangle, and parts of the Sugar Hill and East Haverhill quadrangles, Grafton County, New Hampshire: U.S. Geological Survey Open-File Report 2018–1016, 1 sheet, scale 1:24,000, https://doi.org/10.3133/ofr20181016.","productDescription":"1 Sheet: 34.66 x 37.08 inches; Databases; Metadata; Spatial Data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-082431","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":399117,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_107159.htm"},{"id":353552,"rank":6,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2018/1016/metadata/ofr20181016_lisbonnh-metadata.zip","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Lisbon, New Hampshire, Metadata"},{"id":353550,"rank":5,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2018/1016/metadata/ofr20181016_lisbonnh.gdb.zip","text":"Database","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Lisbon, New Hampshire, Geodatabase"},{"id":353549,"rank":4,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2018/1016/metadata/ofr20181016_lisbonnh-basemap.zip","text":"Base Map","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Lisbon, New Hampshire, Base Map"},{"id":353551,"rank":3,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2018/1016/metadata/ofr20181016_lisbonnh-geologicmap.mxd","text":"Geologic Map (ArcGIS 10.5)","linkHelpText":"- Lisbon, New Hampshire, Geologic Map"},{"id":353540,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1016/ofr20181016_lisbon-geologic-map.pdf","text":"Geologic Map","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1016"},{"id":353539,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1016/coverthb2.jpg"}],"scale":"24000","country":"United States","state":"New Hampshire","county":"Grafton County","otherGeospatial":"Lisbon quadrangle, Sugar Hill and East Haverhill quadrangles","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72,\n 44\n ],\n [\n -71.75,\n 44\n ],\n [\n -71.75,\n 44.25\n ],\n [\n -72,\n 44.25\n ],\n [\n -72,\n 44\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Eastern Geology and Paleoclimate
Science Center
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Using a geology-based assessment methodology, the U.S. Geological Survey estimated mean undiscovered, technically recoverable continuous resources of 10.7 trillion cubic feet of natural gas in Upper Devonian shales of the Appalachian Basin Province.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183018","usgsCitation":"Enomoto, C.B., Trippi, M.H., Higley, D.K., Rouse, W.A., Dulong, F.T., Klett, T.R., Mercier, T.J., Brownfield, M.E., Leathers-Miller, H.M., Finn, T.M., Marra, K.R., Le, P.A., Woodall, C.A., and Schenk, C.J., 2018, Assessment of undiscovered continuous gas resources in Upper Devonian Shales of the Appalachian Basin Province, 2017: U.S. Geological Survey Fact Sheet 2018–3018, 2 p., https://doi.org/10.3133/fs20183018.\n","productDescription":"2 p.","onlineOnly":"N","ipdsId":"IP-091695","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":437943,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Z1E62L","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project-Appalachian Basin Province, Upper Devonian Shales Assessment Unit Boundaries and Assessment Input Forms"},{"id":353542,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3018/fs20183018.pdf","text":"Report","size":"1.69 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018-3018"},{"id":360239,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/P9Z1E62L","text":"USGS data release","description":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project-Appalachian Basin Province, Upper Devonian Shales Assessment Unit Boundaries and Assessment Input Forms"},{"id":353541,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3018/coverthb.jpg"},{"id":353543,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20163085","text":"Fact Sheet 2016–3085:","linkHelpText":"Assessment of Undiscovered Oil and Gas Resources of the Mississippian Sunbury Shale and Devonian–Mississippian Chattanooga Shale in the Appalachian Basin Province, 2016"}],"country":"United States","otherGeospatial":"Appalachian Basin Province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86,\n 36\n ],\n [\n -74,\n 36\n ],\n [\n -74,\n 43\n ],\n [\n -86,\n 43\n ],\n [\n -86,\n 36\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Energy Resources Science Center
U.S. Geological Survey
12201 Sunrise Valley Drive, MS-954
Reston, VA 20192
The Whooping Crane (Grus americana) is a federally endangered species in the United States and Canada that relies on wetland, grassland, and cropland habitat during its long migration between wintering grounds in coastal Texas, USA, and breeding sites in Alberta and Northwest Territories, Canada. We combined opportunistic Whooping Crane sightings with landscape data to identify correlates of Whooping Crane occurrence along the migration corridor in North Dakota and South Dakota, USA. Whooping Cranes selected landscapes characterized by diverse wetland communities and upland foraging opportunities. Model performance substantially improved when variables related to detection were included, emphasizing the importance of accounting for biases associated with detection and reporting of birds in opportunistic datasets. We created a predictive map showing relative probability of occurrence across the study region by applying our model to GIS data layers; validation using independent, unbiased locations from birds equipped with platform transmitting terminals indicated that our final model adequately predicted habitat use by migrant Whooping Cranes. The probability map demonstrated that existing conservation efforts have protected much top-tier Whooping Crane habitat, especially in the portions of North Dakota and South Dakota that lie east of the Missouri River. Our results can support species recovery by informing prioritization for acquisition and restoration of landscapes that provide safe roosting and foraging habitats. Our results can also guide the siting of structures such as wind towers and electrical transmission and distribution lines, which pose a strike and mortality risk to migrating Whooping Cranes.
","language":"English","publisher":"American Ornithological Society","doi":"10.1650/CONDOR-17-80.1","usgsCitation":"Niemuth, N.D., Ryba, A.J., Pearse, A.T., Kvas, S.M., Brandt, D.A., Wangler, B., Austin, J.E., and Carlisle, M.J., 2018, Opportunistically collected data reveal habitat selection by migrating Whooping Cranes in the U.S. Northern Plains: The Condor, v. 120, no. 2, p. 343-356, https://doi.org/10.1650/CONDOR-17-80.1.","productDescription":"14 p.","startPage":"343","endPage":"356","ipdsId":"IP-076151","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":468819,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1650/condor-17-80.1","text":"Publisher Index Page"},{"id":353596,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota, South Dakota","volume":"120","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6d9e4b0da30c1bfbe92","contributors":{"authors":[{"text":"Niemuth, Neal D. 0009-0006-9637-5588","orcid":"https://orcid.org/0009-0006-9637-5588","contributorId":204334,"corporation":false,"usgs":false,"family":"Niemuth","given":"Neal","email":"","middleInitial":"D.","affiliations":[{"id":36919,"text":"U.S. Fish and Wildlife Service Habitat and Population Evaluation Team","active":true,"usgs":false}],"preferred":false,"id":733667,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ryba, Adam J.","contributorId":204335,"corporation":false,"usgs":false,"family":"Ryba","given":"Adam","email":"","middleInitial":"J.","affiliations":[{"id":36919,"text":"U.S. Fish and Wildlife Service Habitat and Population Evaluation Team","active":true,"usgs":false}],"preferred":false,"id":733668,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pearse, Aaron T. 0000-0002-6137-1556 apearse@usgs.gov","orcid":"https://orcid.org/0000-0002-6137-1556","contributorId":1772,"corporation":false,"usgs":true,"family":"Pearse","given":"Aaron","email":"apearse@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":733666,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kvas, Susan M.","contributorId":204336,"corporation":false,"usgs":false,"family":"Kvas","given":"Susan","email":"","middleInitial":"M.","affiliations":[{"id":36919,"text":"U.S. Fish and Wildlife Service Habitat and Population Evaluation Team","active":true,"usgs":false}],"preferred":false,"id":733669,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brandt, David A. 0000-0001-9786-307X dbrandt@usgs.gov","orcid":"https://orcid.org/0000-0001-9786-307X","contributorId":149929,"corporation":false,"usgs":true,"family":"Brandt","given":"David","email":"dbrandt@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":733670,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wangler, Brian","contributorId":204337,"corporation":false,"usgs":false,"family":"Wangler","given":"Brian","email":"","affiliations":[{"id":36919,"text":"U.S. Fish and Wildlife Service Habitat and Population Evaluation Team","active":true,"usgs":false}],"preferred":false,"id":733671,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Austin, Jane E. 0000-0001-8775-2210 jaustin@usgs.gov","orcid":"https://orcid.org/0000-0001-8775-2210","contributorId":146411,"corporation":false,"usgs":true,"family":"Austin","given":"Jane","email":"jaustin@usgs.gov","middleInitial":"E.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":733672,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Carlisle, Martha J.","contributorId":204338,"corporation":false,"usgs":false,"family":"Carlisle","given":"Martha","email":"","middleInitial":"J.","affiliations":[{"id":36920,"text":"U.S. Fish and Wildlife Service Ecological Serv, NE field office","active":true,"usgs":false}],"preferred":false,"id":733673,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70199362,"text":"70199362 - 2018 - Proximity of Precambrian basement affects the likelihood of induced seismicity in the Appalachian, Illinois, and Williston Basins, central and eastern United States","interactions":[],"lastModifiedDate":"2019-05-17T10:15:30","indexId":"70199362","displayToPublicDate":"2018-04-17T12:46:24","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Proximity of Precambrian basement affects the likelihood of induced seismicity in the Appalachian, Illinois, and Williston Basins, central and eastern United States","docAbstract":"A dramatic seismicity rate increase in the central and eastern United States (CEUS) over the past decade has been largely associated with the increase in enhanced oil and gas recovery operations and change in industry practices. However, certain areas of the CEUS that have experienced large increases in oil and gas operations, such as the Bakken and Marcellus Shale plays (Williston and Appalachian Basins, respectively), have very little (if any) induced seismicity. No prior study has adequately explained the occurrence or absence of induced seismicity on a regional, basin-to-basin scale in the CEUS. In this study, we improve the basement depth characterization and induced seismicity detection for the Appalachian, Illinois, and Williston Basins to determine whether the proximity of wastewater disposal and/or hydraulic fracturing to the crystalline basement increases the likelihood of induced seismicity. We also investigate the lithologic characteristics of sedimentary strata situated between injection intervals and the crystalline basement to evaluate the role they may play in diminishing the transmission of pore pressure during well stimulations. We find that wastewater disposal in basal sediments or hydraulic fracturing operations <1 km from the Precambrian basement raise the likelihood of induced seismicity, an observation that is consistent with the apparent absence of induced seismicity related to production from the Bakken and Marcellus Shale plays.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES01542.1","usgsCitation":"Skoumal, R.J., Brudzinski, M.R., and Currie, B.S., 2018, Proximity of Precambrian basement affects the likelihood of induced seismicity in the Appalachian, Illinois, and Williston Basins, central and eastern United States: Geosphere, v. 14, no. 3, p. 1365-1379, https://doi.org/10.1130/GES01542.1.","productDescription":"15 p.","startPage":"1365","endPage":"1379","ipdsId":"IP-084031","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":468821,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges01542.1","text":"Publisher Index Page"},{"id":357340,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Appalachian Basin, Illinois Basin, Williston Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109,\n 45.5\n ],\n [\n -100,\n 45.5\n ],\n [\n -100,\n 49\n ],\n [\n -109,\n 49\n ],\n [\n -109,\n 45.5\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92,\n 36.5\n ],\n [\n -75,\n 36.5\n ],\n [\n -75,\n 42\n ],\n [\n -92,\n 42\n ],\n [\n -92,\n 36.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-17","publicationStatus":"PW","scienceBaseUri":"5bc03002e4b0fc368eb539c3","contributors":{"authors":[{"text":"Skoumal, Robert J. 0000-0002-5627-6239 rskoumal@usgs.gov","orcid":"https://orcid.org/0000-0002-5627-6239","contributorId":191213,"corporation":false,"usgs":true,"family":"Skoumal","given":"Robert","email":"rskoumal@usgs.gov","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":745037,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brudzinski, Michael R. 0000-0003-1869-0700","orcid":"https://orcid.org/0000-0003-1869-0700","contributorId":207880,"corporation":false,"usgs":false,"family":"Brudzinski","given":"Michael","email":"","middleInitial":"R.","affiliations":[{"id":16608,"text":"Miami University","active":true,"usgs":false}],"preferred":false,"id":745038,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Currie, Brian S.","contributorId":207881,"corporation":false,"usgs":false,"family":"Currie","given":"Brian","email":"","middleInitial":"S.","affiliations":[{"id":16608,"text":"Miami University","active":true,"usgs":false}],"preferred":false,"id":745039,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196536,"text":"ofr20181069 - 2018 - Brown trout in the Lees Ferry reach of the Colorado River—Evaluation of causal hypotheses and potential interventions","interactions":[],"lastModifiedDate":"2024-03-04T18:53:45.200748","indexId":"ofr20181069","displayToPublicDate":"2018-04-17T00:00:00","publicationYear":"2018","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":"2018-1069","title":"Brown trout in the Lees Ferry reach of the Colorado River—Evaluation of causal hypotheses and potential interventions","docAbstract":"Over the period 2014–2016, the number of nonnative brown trout (Salmo trutta) captured during routine monitoring in the Lees Ferry reach of the Colorado River, downstream of Glen Canyon Dam, began increasing. Management agencies and stakeholders have questioned whether the increase in brown trout in the Lees Ferry reach represents a threat to the endangered humpback chub (Gila cypha), to the rainbow trout (Oncorhynchus mykiss) sport fishery, or to other resources of concern. In this report, we evaluate the evidence for the expansion of brown trout in the Lees Ferry reach, consider a range of causal hypotheses for this expansion, examine the likely efficacy of several potential management interventions to reduce brown trout, and analyze the effects of those interventions on other resources of concern.
The brown trout population at Lees Ferry historically consisted of a small number of large fish supported by low levels of immigration from downstream reaches. This population is now showing signs of sustained successful reproduction and is on the cusp of recruiting locally hatched fish into the spawning class, based on analysis with a new integrated population model. The proximate causes of this change in status are a large pulse of immigration in the fall of 2014 and higher reproductive rates in 2015–2017. The ultimate causes of this change are not clear. The pulse of immigrants from downstream reaches in fall 2014 may have been induced by three sequential high-flow releases from the dam in November of 2012–2014, but may also have been the result of a unique set of circumstances unrelated to dam operations. The increase in reproduction may have been the result of any number of changes, including an Allee effect, warmer water temperatures, a decrease in competition from rainbow trout, or fall high-flow releases. Correlations over space and time among predictor variables do not allow us to make a clear inference about the cause of the changes. Under a null causal model, and without any changes to management, we predict there is a 36-percent chance the brown trout population at Lees Ferry will not show sustained growth, and will remain around a mean size of 5,800 adults, near its current size; in contrast, we predict there is a 64-percent chance that the population has a positive intrinsic growth rate and will increase 3–10 fold over the next 20 years. A humpback chub population model linked to the brown trout model suggests an increase of brown trout of this magnitude could lead to declines in the minimum adult humpback chub population over the same time period. Forecasts of rainbow trout abundance, however, suggest that increased abundance of brown trout in the Lees Ferry reach does not pose a threat to the rainbow trout fishery there.
There are interventions that may be effective in moderating the growth of the brown trout population in the Lees Ferry reach of the Colorado River. Across causal hypotheses, we predict that removal strategies (for example, a concerted electrofishing effort or an incentivized take program targeted at large brown trout) could reduce brown trout abundance by approximately 50 percent relative to status quo management. Reductions in the frequency or a change in the seasonal timing of high-flow releases from Glen Canyon Dam could be even more effective, but only under the causal hypotheses that involve effects of such releases on immigration or reproduction. Brown trout management flows— dam releases designed to strand young fish at a vulnerable stage—may be able to reduce brown trout abundance to some degree, but are not forecast to be the most effective strategy under any causal hypothesis.
We predict that the alternative management interventions would have effects on other resource goals as well, and the pattern of these effects differs across causal hypotheses. The removal strategies would incur direct costs (on the order of $7 million over 20 years) and the mechanical removal strategy is unethical from the perspective of several tribes. The strategies that involve reducing the frequency of high-flow releases from Glen Canyon Dam would decrease the ability to transport and store sediment in the ecosystem, potentially undermining goals associated with sandbar building, recreation, and riparian vegetation, but would increase hydropower revenue. Trout management flows would reduce hydropower revenue. From the standpoint of humpback chub, the alternative strategies largely follow the effect on brown trout; when brown trout abundance is reduced, predation pressure decreases, and humpback chub viability is predicted to increase, but the variation in predicted chub viability is not large across strategies or causal hypotheses.
To design a response to brown trout, management agencies will need to navigate both the tradeoffs among resources goals and the uncertainty in the causes of the brown trout expansion. Continued monitoring, possibly coupled with new research or experimental management actions that better inform demographic and ecological dynamics, can help to reduce the causal uncertainty.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181069","collaboration":"Prepared in cooperation with the National Park Service, U.S. Fish and Wildlife Service, Arizona Game and Fish Department, and the Western Area Power Administration","usgsCitation":"Runge, M.C., Yackulic, C.B., Bair, L.S., Kennedy, T.A., Valdez, R.A., Ellsworth, C., Kershner J.L., Rogers, R.S., Trammell, M.A., and Young, K.L., 2018, Brown trout in the Lees Ferry reach of the Colorado River—Evaluation of causal hypotheses and potential interventions: U.S. Geological Survey Open-File Report 2018–1069, 83 p.,\nhttps://doi.org/10.3133/ofr20181069.","productDescription":"ix, 83 p.","numberOfPages":"94","onlineOnly":"Y","ipdsId":"IP-095595","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":353922,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7FN15HC","linkHelpText":"Population dynamics of humpback chub, rainbow trout and brown trout in the Colorado River in its Grand Canyon Reach: modelling code and input data"},{"id":353488,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1069/ofr20181069.pdf","text":"Report","size":"2.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1069"},{"id":353487,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1069/coverthb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.59500122070312,\n 36.834843899148495\n ],\n [\n -111.47209167480469,\n 36.834843899148495\n ],\n [\n -111.47209167480469,\n 36.946599271636295\n ],\n [\n -111.59500122070312,\n 36.946599271636295\n ],\n [\n -111.59500122070312,\n 36.834843899148495\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
12100 Beech Forest Road, Ste 4039
Laurel, MD 20708-4039
The HayWired earthquake scenario, led by the U.S. Geological Survey (USGS), anticipates the impacts of a hypothetical magnitude-7.0 earthquake on the Hayward Fault. The fault is along the east side of California’s San Francisco Bay and is among the most active and dangerous in the United States, because it runs through a densely urbanized and interconnected region. One way to learn about a large earthquake without experiencing it is to conduct a scientifically realistic scenario. The USGS and its partners in the HayWired Coalition and the HayWired Campaign are working to energize residents and businesses to engage in ongoing and new efforts to prepare the region for such a future earthquake.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183016","collaboration":"Prepared in cooperation with the Haywired Coalition","usgsCitation":"Hudnut, K.W., Wein, A.M., Cox, D.A., Porter, K.A., Johnson, L.A., Perry, S.C., Bruce, J.L., and LaPointe, D., 2018, The HayWired earthquake scenario—We can outsmart disaster: U.S. Geological Survey Fact Sheet 2018–3016, 6 p., https://doi.org/10.3133/fs20183016.","productDescription":"6 p.","onlineOnly":"Y","ipdsId":"IP-096004","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":353493,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175013","text":"Scientific Investigations Report 2017-5013","description":"SIR 2018-5013","linkHelpText":"– The HayWired Earthquake Scenario"},{"id":353427,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3016/fs20183016_.pdf","text":"Report","size":"7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018-3016"},{"id":353426,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3016/coverthb.jpg"},{"id":392913,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20213054","text":"Fact Sheet 2021-3054","linkHelpText":"– The HayWired Earthquake Scenario—Societal Consequences"},{"id":392929,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175013V3","text":"Scientific Investigations Report 2017-5013","linkHelpText":"– The HayWired Earthquake Scenario—Societal Consequences"},{"id":392928,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175013v2","text":"Scientific Investigations Report 2017-5013","linkHelpText":"– The HayWired Earthquake Scenario—Engineering Implications"},{"id":392927,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175013v1","text":"Scientific Investigations Report 2017-5013","linkHelpText":"– The HayWired Earthquake Scenario—Earthquake Hazards"}],"country":"United States","state":"California","otherGeospatial":"Hayward Fault, San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.78594970703126,\n 37.10119357072203\n ],\n [\n -121.63787841796875,\n 37.10119357072203\n ],\n [\n -121.63787841796875,\n 38.274844767832825\n ],\n [\n -122.78594970703126,\n 38.274844767832825\n ],\n [\n -122.78594970703126,\n 37.10119357072203\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Menlo Park, Calif.
Office—Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025
https://earthquake.usgs.gov/
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center, in cooperation with the U.S. Army Corps of Engineers, Mobile District, conducted bathymetric surveys of the nearshore waters surrounding Ship and Horn Islands, Gulf Islands National Seashore, Mississippi. The objective of this study was to establish base-level elevation conditions around West Ship, East Ship, and Horn Islands and their associated active littoral system prior to restoration activities. These activities include the closure of Camille Cut and the placement of sediment in the littoral zone of East Ship Island. These surveys can be compared with future surveys to monitor sediment migration patterns post-restoration and can also be measured against historic bathymetric datasets to further our understanding of island evolution.
The USGS collected 667 line-kilometers (km) of single-beam bathymetry data and 844 line-km of interferometric swath bathymetry data in July 2016 under Field Activity Number 2016-347-FA. Data are provided in three datums: (1) the International Terrestrial Reference Frame of 2000 (ellipsoid height); (2) the North American Datum of 1983 (NAD83) CORS96 realization and the North American Vertical Datum of 1988 with respect to the GEOID12B model (orthometric height); and (3) NAD83 (CORS96) and Mean Lower Low Water (tidal datum). Data products, including x,y,zpoint datasets, trackline shapefiles, digital and handwritten Field Activity Collection Systems logs, 50-meter digital elevation model, and formal Federal Geographic Data Committee metadata, are available for download.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1081","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Mobile District","usgsCitation":"DeWitt, N.T., Stalk, C.A., Fredericks, J.J., Flocks, J.G., Kelso, K.W., Farmer, A.S., Tuten, T.M., and Buster, N.A., 2018, Nearshore coastal bathymetry data collected in 2016 from West Ship Island to Horn Island, Gulf Islands National Seashore, Mississippi: U.S. Geological Survey Data Series 1081, https://doi.org/10.3133/ds1081.","productDescription":"HTML Document; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-092109","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":353362,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1081/coverthb.jpg"},{"id":353364,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://coastal.er.usgs.gov/data-release/doi-F7B8571Q/","text":"USGS data release","description":"USGS data release","linkHelpText":"Coastal Bathymetry Data Collected in 2016 nearshore from West Ship Island to Horn Island, Gulf Islands National Seashore, Mississippi"},{"id":353363,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1081/","text":"Report HTML","linkFileType":{"id":5,"text":"html"},"description":"DS 1081"}],"country":"United States","state":"Mississippi","otherGeospatial":"Horn Islands, Gulf Islands National Seashore","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.02359008789062,\n 30.173624550358536\n ],\n [\n -88.50311279296875,\n 30.173624550358536\n ],\n [\n -88.50311279296875,\n 30.28634573802957\n ],\n [\n -89.02359008789062,\n 30.28634573802957\n ],\n [\n -89.02359008789062,\n 30.173624550358536\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th St. South
St. Petersburg, FL 33701
In the Colorado River downstream of Glen Canyon Dam in the Grand Canyon, USA, controlled floods are used to resupply sediment to, and rebuild, river sandbars that have eroded severely over the past five decades owing to dam-induced changes in river flow and sediment supply. In this study, we examine whether controlled floods, can in turn resupply aeolian sediment to some of the large source-bordering aeolian dunefields (SBDs) along the margins of the river. Using a legacy of high-resolution lidar remote-sensing and meteorological data, we characterize the response of four SBDs (a subset of 117 SBDs and other aeolian-sand-dominated areas in the canyon) during four sediment-laden controlled floods of the Colorado River in 2012, 2013, 2014, and 2016. We find that aeolian sediment resupply unambiguously occurred in 8 of the 16 instances of controlled flooding adjacent to SBDs. Resupply attributed to individual floods varied substantially among sites, and occurred with four, three, one, and zero floods at the four sites, respectively. We infer that the relative success of controlled floods as a regulated-river management tool for resupplying sediment to SBDs is analogous to the frequency of resupply observed for fluvial sandbars in this setting, in that sediment resupply was estimated to have occurred for roughly half of the instances of recent controlled flooding at sandbars monitored separately from this study. We find the methods developed in this, and a companion study, are effective tools to quantify geomorphic changes in sediment storage, along linked fluvial and aeolian pathways of sedimentary systems.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.aeolia.2018.02.004","usgsCitation":"Sankey, J.B., Caster, J., Kasprak, A., and East, A.E., 2018, The response of source-bordering aeolian dunefields to sediment-supply changes 2: Controlled floods of the Colorado River in Grand Canyon, Arizona, USA: Aeolian Research, v. 32, p. 154-169, https://doi.org/10.1016/j.aeolia.2018.02.004.","productDescription":"16 p.","startPage":"154","endPage":"169","ipdsId":"IP-092082","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":460953,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.aeolia.2018.02.004","text":"Publisher Index Page"},{"id":353403,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River, Grand Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.04907226562499,\n 35.64390523787731\n ],\n [\n -111.3958740234375,\n 35.64390523787731\n ],\n [\n -111.3958740234375,\n 36.97183825093165\n ],\n [\n -114.04907226562499,\n 36.97183825093165\n ],\n [\n -114.04907226562499,\n 35.64390523787731\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"32","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6dce4b0da30c1bfbece","contributors":{"authors":[{"text":"Sankey, Joel B. 0000-0003-3150-4992 jsankey@usgs.gov","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":3935,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel","email":"jsankey@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":733245,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caster, Joshua 0000-0002-2858-1228 jcaster@usgs.gov","orcid":"https://orcid.org/0000-0002-2858-1228","contributorId":199033,"corporation":false,"usgs":true,"family":"Caster","given":"Joshua","email":"jcaster@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":733247,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kasprak, Alan 0000-0001-8184-6128 akasprak@usgs.gov","orcid":"https://orcid.org/0000-0001-8184-6128","contributorId":190848,"corporation":false,"usgs":true,"family":"Kasprak","given":"Alan","email":"akasprak@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":733246,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"East, Amy E. 0000-0002-9567-9460 aeast@usgs.gov","orcid":"https://orcid.org/0000-0002-9567-9460","contributorId":196364,"corporation":false,"usgs":true,"family":"East","given":"Amy","email":"aeast@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":733248,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}