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
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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":70195991,"text":"fs20183016 - 2018 - The HayWired earthquake scenario—We can outsmart disaster","interactions":[],"lastModifiedDate":"2021-12-14T23:08:54.870782","indexId":"fs20183016","displayToPublicDate":"2018-04-17T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-3016","title":"The HayWired earthquake scenario—We can outsmart disaster","docAbstract":"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/
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 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
Source-bordering dunefields (SBDs), which are primarily built and maintained with river-derived sediment, are found in many large river valleys and are currently impacted by changes in sediment supply due to climate change, land use changes, and river regulation. Despite their importance, a physically based, applied approach for quantifying the response of SBDs to changes in sediment supply does not exist. To address this knowledge gap, here we develop an approach for quantifying the geomorphic responses to sediment-supply alteration based on the interpretation of dunefield morphodynamics from geomorphic change detection and wind characteristics. We use the approach to test hypotheses about the response of individual dunefields to variability in sediment supply at three SBDs along the Colorado River in Grand Canyon, Arizona, USA during the 11 years between 2002 and 2013 when several river floods rebuilt some river sandbars and channel margin deposits that serve as sediment source areas for the SBDs. We demonstrate that resupply of fluvially sourced aeolian sediment occurred at one of the SBDs, but not at the other two, and attribute this differential response to site-specific variability in geomorphology, wind, and sediment source areas. The approach we present is applied in a companion study to shorter time periods with high-resolution topographic data that bracket individual floods in order to infer the resupply of fluvially sourced aeolian sediment to SBDs by managed river flows. Such an applied methodology could also be useful for measuring sediment connectivity and anthropogenic alterations of connectivity in other coupled fluvial-aeolian environments.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.aeolia.2018.02.005","usgsCitation":"Sankey, J.B., Kasprak, A., Caster, J., East, A.E., and Fairley, H.C., 2018, The response of source-bordering aeolian dunefields to sediment-supply changes 1: Effects of wind variability and river-valley morphodynamics: Aeolian Research, v. 32, p. 228-245, https://doi.org/10.1016/j.aeolia.2018.02.005.","productDescription":"18 p.","startPage":"228","endPage":"245","ipdsId":"IP-091253","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":460945,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.aeolia.2018.02.005","text":"Publisher Index Page"},{"id":353401,"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":"5afee6e3e4b0da30c1bfbed0","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":733240,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kasprak, Alan 0000-0001-8184-6128","orcid":"https://orcid.org/0000-0001-8184-6128","contributorId":204162,"corporation":false,"usgs":true,"family":"Kasprak","given":"Alan","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":733241,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":733242,"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":733243,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fairley, Helen C. 0000-0001-6151-4804 hfairley@usgs.gov","orcid":"https://orcid.org/0000-0001-6151-4804","contributorId":3040,"corporation":false,"usgs":true,"family":"Fairley","given":"Helen","email":"hfairley@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":733244,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196496,"text":"70196496 - 2018 - The response of source-bordering aeolian dunefields to sediment-supply changes 2: Controlled floods of the Colorado River in Grand Canyon, Arizona, USA","interactions":[],"lastModifiedDate":"2018-04-13T10:47:24","indexId":"70196496","displayToPublicDate":"2018-04-13T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":666,"text":"Aeolian Research","active":true,"publicationSubtype":{"id":10}},"title":"The response of source-bordering aeolian dunefields to sediment-supply changes 2: Controlled floods of the Colorado River in Grand Canyon, Arizona, USA","docAbstract":"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}]}} ,{"id":70195493,"text":"sim3396 - 2018 - Geologic map of the Weldona 7.5' quadrangle, Morgan County, Colorado","interactions":[],"lastModifiedDate":"2019-05-15T09:28:56","indexId":"sim3396","displayToPublicDate":"2018-04-09T10:30:00","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":"3396","title":"Geologic map of the Weldona 7.5' quadrangle, Morgan County, Colorado","docAbstract":"The Weldona 7.5′ quadrangle is located on the semiarid plains of northeastern Colorado, along the South Platte River corridor where the river has incised into Upper Cretaceous Pierre Shale. The Pierre Shale is largely covered by surficial deposits that formed from alluvial, eolian, and hillslope processes operating in concert with environmental changes from the Pleistocene to the present. The South Platte River, originating high in the Colorado Rocky Mountains, has played a major role in shaping surficial geology in the map area, which is several tens of kilometers downstream from where headwater tributaries join the river. Recurrent glaciation (and deglaciation) of basin headwaters has affected river discharge and sediment supply far downstream, influencing deposition of alluvium and river incision in the Weldona quadrangle. During the Pleistocene the course of the river within the map area shifted progressively southward as it incised, and by late middle Pleistocene the river was south of its present position, cutting and filling deep paleochannels now covered by younger alluvium. The river shifted back to the north during the late Pleistocene. Kiowa and Bijou Creeks are unglaciated tributaries originating in the Colorado Piedmont east of the Front Range that also have played a major role in shaping surficial geology of the map area. Periodically during the late Pleistocene, major flood events on these tributaries deposited large volumes of sediment at their confluences, forming a broad, low-gradient fan of sidestream alluvium that could have occasionally dammed the river for short periods of time. Eolian sand deposits of the Sterling (north of river) and Fort Morgan (south of river) dune fields cover much of the quadrangle and record past episodes of sand mobilization during times of prolonged drought. With the onset of irrigation and damming during historical times, the South Platte River has changed from a broad, shallow, and sandy braided river with highly variable seasonal discharge to a much narrower, deeper river with braided-meandering transition morphology and more uniform discharge.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3396","usgsCitation":"Berry, M.E., Taylor, E.M., Slate, J.L., Paces, J.B., Hanson, P.R., and Brandt, T.R., 2018, Geologic map of the Weldona 7.5′ quadrangle, Morgan County, Colorado: U.S. Geological Survey Scientific Investigations Map 3396, 1 sheet, scale 1:24,000, https://doi.org/10.3133/sim3396.","productDescription":"Map: 54.85 x 37.32 inches; 4 Related Works; 2 Data releases; Read Me","onlineOnly":"Y","ipdsId":"IP-087648","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":352658,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7QN65M3","text":"USGS data release","linkHelpText":"Data release of OSL, 14C, and U-series age data supporting geologic mapping along the South Platte River corridor in northeastern Colorado"},{"id":352657,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sim3344","text":"Scientific Investigations Map 3344 —","linkHelpText":"Geologic map of the Masters 7.5' quadrangle, Weld and Morgan Counties, Colorado"},{"id":352656,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/sim3331","text":"Scientific Investigations Map 3331 —","linkHelpText":"Geologic map of the Orchard 7.5' quadrangle, Morgan County, Colorado"},{"id":352662,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3396/sim3396_geospatial_map.pdf","text":"Georeferenced Map","size":"339 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3336 Georeferenced Map"},{"id":352388,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3396/sim3396_map.pdf","text":"Map","size":"4.26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3336 Map"},{"id":353176,"rank":8,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3396/sim3396_readme.txt","text":"Read Me","size":"8.0kB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3396 Read Me"},{"id":352672,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7610Z63","text":"USGS data release","linkHelpText":"Data release for the geologic map of the Weldona 7.5' quadrangle, Morgan County, Colorado"},{"id":352387,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3396/coverthb.jpg"},{"id":354897,"rank":9,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sim3408","text":"Scientific Investigations Map 3408 —","linkHelpText":"Geologic map of the Fort Morgan 7.5' quadrangle, Morgan County, Colorado"},{"id":363172,"rank":10,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20195020","text":"Scientific Investigations Report 2019-5020 —","linkHelpText":"Pleistocene and Holocene Landscape Development of the South Platte River Corridor, Northeastern Colorado"}],"country":"United States","state":"Colorado","county":"Morgan County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104,\n 40.25\n ],\n [\n -103.875,\n 40.25\n ],\n [\n -103.875,\n 40.375\n ],\n [\n -104,\n 40.375\n ],\n [\n -104,\n 40.25\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geosciences and Environmental Change Science Center
U.S. Geological Survey
Box 25046, Mail Stop 980
Denver, CO 80225
http://gec.cr.usgs.gov/
Kings Bay, Florida, is one of the most important natural winter habitat locations for the federally threatened Trichechus manatus latirostris (Florida manatee). Crystal River National Wildlife Refuge was established in 1983 specifically to provide protection for manatees and their critical habitat. To aid managers at the refuge and other agencies with this task, spatial analyses of local habitat use locations and travel corridors of manatees in Kings Bay during manatee season (November 15–March 31) are presented based on Global Positioning System telemetry of 41 manatees over a 12-year timespan (2006−18). Local habitat use areas and travel corridors differed spatially when Gulf of Mexico water temperatures were cold (less than or equal to 17 degrees Celsius) versus when they were warm (greater than 17 degrees Celsius). During times of cold water, manatees were found in higher concentrations in the main springs and canals throughout the eastern side of the bay, whereas when waters were warm, they were found more generally throughout the bay and into Crystal River, except for the central open part of the bay and the southwest corner.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181051","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service and the Bureau of Ocean Energy Management","usgsCitation":"Slone, D.H., Butler, S.M., and Reid, J.P., 2018, Movements and habitat use locations of manatees within Kings Bay Florida during the Crystal River National Wildlife Refuge winter season (November 15–March 31): U.S. Geological Survey Open-File Report 2018–1051, 11 p., https://doi.org/10.3133/ofr20181051.","productDescription":"iv, 11 p.","numberOfPages":"15","onlineOnly":"Y","ipdsId":"IP-096292","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":353049,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20171146","text":"Open-File Report 2017-1146","linkHelpText":"Timing of warm water refuge use in Crystal River National Wildlife Refuge by manatees—Results and insights from Global Positioning System telemetry data"},{"id":353037,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1051/coverthb2.jpg"},{"id":353038,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1051/ofr20181051.pdf","text":"Report","size":"3.92 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018–1051"}],"country":"United States","state":"Florida","otherGeospatial":"Kings Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.62,\n 28.9\n ],\n [\n -82.58,\n 28.9\n ],\n [\n -82.58,\n 28.875\n ],\n [\n -82.62,\n 28.875\n ],\n [\n -82.62,\n 28.9\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
7920 NW 71 Street
Gainesville, FL 32653
The Lower Valley 7.5-minute quadrangle, located in the core of the Southeast Idaho Phosphate Resource Area, includes Mississippian to Triassic marine sedimentary rocks, Pliocene to Pleistocene basalt, and Tertiary to Holocene surficial deposits. The Mississippian to Triassic marine sedimentary sequence was deposited on a shallow shelf between an emergent craton to the east and the Antler orogenic belt to the west. The Meade Peak Phosphatic Shale Member of the Permian Phosphoria Formation hosts high-grade deposits of phosphate that were the subject of geologic studies through much of the 20th century. Open-pit mining of the phosphate has been underway within and near the Lower Valley quadrangle for several decades.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3215","usgsCitation":"Oberlindacher, H.P., Hovland, R.D., Miller, S.T. , Evans, J.G., and Miller, R.J., 2018, Geologic map of the Lower Valley quadrangle, Caribou County, Idaho: U.S. Geological Survey Scientific Investigations Map 3215, 6 p., 1 sheet, scale 1:24,000, https://doi.org/10.3133/sim3215.","productDescription":"Map: 35.72 x 31.32 inches; Pamphlet: iii, 6 p.; Spatial Data; Metadata; Read Me","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-088533","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":353192,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3215/sim3215_mapsheet.pdf","text":"Geologic Map","size":"8.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3215 Sheet"},{"id":353193,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3215/sim3215_metadata.txt","size":"45 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3215 Metadata"},{"id":353194,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3215/sim3215_geodatabase.zip","text":"Geodatabase","size":"1.7 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3215 Geodatabase"},{"id":353195,"rank":7,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3215/sim3215_shapefiles.zip","text":"Shapefiles","size":"2.2 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3215 Shapefiles"},{"id":353196,"rank":8,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3215/SIM3215_basemap.zip","text":"Base map","size":"7.4 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3215 Base map"},{"id":353189,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3215/coverthb.jpg"},{"id":353190,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3215/sim3215_pamphlet.pdf","text":"Pamphlet","size":"405 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3215 Pamphlet"},{"id":353191,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3215/sim3215_readme.txt","size":"2 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3215 Read Me"}],"country":"United States","state":"Idaho","county":"Caribou County","otherGeospatial":"Lower Valley quadrangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.375,\n 42.875\n ],\n [\n -111.5,\n 42.875\n ],\n [\n -111.5,\n 42.75\n ],\n [\n -111.375,\n 42.75\n ],\n [\n -111.375,\n 42.875\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"The U.S. Geological Survey (USGS) conducted a program of bedrock geologic mapping in much of the central and western Upper Peninsula of Michigan from the 1940s until the late 1990s. Geologic studies in this region are hampered by a scarcity of bedrock exposures because of a nearly continuous blanket of unconsolidated sediments resulting from glaciation of the region during the Pleistocene ice ages. The USGS mapping, done largely at a scale of 1:24,000, routinely recorded the location and extent of exposed bedrock to provide both an indication of where direct observations were made and a guide for future investigations to expedite location of observable rock exposures. The locations of outcrops were generally shown as colored or patterned overlays on printed geologic maps. Although those maps have been scanned and are available as Portable Document Format (PDF) files, no further digital portrayal of the outcrops had been done. We have conducted a prototype study of digitizing and improving locational accuracy of the outcrop locations in parts of Dickinson County, Michigan, to form a data layer that can be used with other data layers in geographic information system applications.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181042","usgsCitation":"Cannon, W.F., Schulte, Ruth, and Bickerstaff, Damon, 2018, Digital representation of exposures of Precambrian bedrock in parts of Dickinson and Iron Counties, Michigan, and Florence and Marinette Counties, Wisconsin: \nU.S. Geological Survey Open-File Report 2018–1042, 3 p., https://doi.org/10.3133/ofr20181042.","productDescription":"Report: 3 p.; Data release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-091916","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":352778,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1042/coverthb.jpg"},{"id":352779,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1042/ofr20181042.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1042"},{"id":352780,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7SJ1JH0","text":"USGS data release","description":"USGS data release"}],"country":"United States","state":"Michigan, Wisconsin","county":"Dickinson County, Florence County, Iron County, Marinette County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.1333,\n 45.75\n ],\n [\n -87.7,\n 45.75\n ],\n [\n -87.7,\n 46.1\n ],\n [\n -88.1333,\n 46.1\n ],\n [\n -88.1333,\n 45.75\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Mineral and Environmental Resources
12201 Sunrise Valley Drive
Mail Stop 954
Reston, VA 20192
ebra mussels (Dreissena polymorpha) and quagga mussels (Dreissena bugensis) were likely introduced from Ponto-Caspian Eurasia to the Laurentian Great Lakes inadvertently via ballast water release in the 1980s and have since spread across the US, including Texas. Their spread into the state, including reservoirs in both Brazos River and Colorado River basins, has resulted in a need to delimit suitable dreissenid habitat and dispersal potential in Texas. The objective of our research was to assess invasion risk in Texas by 1) predicting distribution of suitable habitat of zebra and quagga mussels using Maxent models; 2) refining lake-specific predictions for present zebra mussels via collection of physicochemical data; and 3) assessing the potential for downstream spread of zebra mussels by applying environmental DNA (eDNA) methods in the Leon and Lampasas Rivers downstream from the invaded Lakes Belton and Stillhouse Hollow, respectively.
Maxent models did not predict the occurrence of suitable habitat for quagga mussels within Texas. However, our models accurately identified global zebra mussel habitat (AUC = 0.919), and Bioclim layers representing temperature and precipitation data both strongly influenced predictions. Predicted “hotspots” of suitable zebra mussel habitat in Texas occurred along the Red and Sabine Rivers of north and east Texas, as well as patches of suitable habitat in central Texas between the Colorado and Brazos Rivers and extending inland along the Gulf Coast. Most of the Texas panhandle, west Texas extending toward El Paso, and the Rio Grande valley were predicted to provide poor habitat suitability.
Collection of physicochemical data (dissolved oxygen, pH, specific conductance, and temperature on-site as well as laboratory analysis for Ca, N, and P) from zebra mussel invaded lakes and a subset of identified high-risk lakes of North and Central Texas, did not aid predictions. Visual inspection of biplots of the first three components of a principle component analysis, which together accounted for ~80% of data variability, did not reveal separation between invaded and uninvaded lakes, and logistic regression analysis also failed to identify predictive relationships between measured variables and invasion status.
Using eDNA analysis, we detected the presence of zebra mussel eDNA at 11 of 12 sites and up to at least 90.7 river km downstream from a pair of infested reservoirs. Rate of positive detection among water samples at each site ranged from 1/5 to 5/5, and within positive water samples, rate of detection among technical replicates ranged from 1/8 to 8/8, suggesting considerable heterogeneity in the zebra mussel eDNA signal in both rivers. Furthermore, no clear spatial pattern in detection rate occurred.
Thus, a monitoring strategy that combines traditional sampling (e.g. settlement substrate samplers and microscopy) at sites immediately below a dam, and transitioning to more sensitive eDNA analysis at distances further from the dam may represent the most successful strategy for detection of dreissenid mussel downstream dispersal. Overall, we have demonstrated that while quagga mussels do not appear to represent an invasive threat in Texas, suitable habitat for continuing zebra mussel invasion exists within Texas, and stream and river connections may contribute to their spread. The threat of continued expansion of this poster-child for negative invasive species impacts warrants further prevention efforts, management, and research.
","language":"English","publisher":"Texas Tech University","usgsCitation":"Barnes, M., and Patino, R., 2018, Assessing the risk of dreissenid mussel invasion in Texas based on lake physical characteristics and potential for downstream dispersal, 28 p.","productDescription":"28 p.","ipdsId":"IP-093396","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":426898,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":426897,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://tpwd.texas.gov/landwater/water/aquatic-invasives/research2.phtml","linkFileType":{"id":5,"text":"html"}}],"country":"United States","otherGeospatial":"continental United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n ],\n 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Atlanta","active":true,"usgs":true}],"preferred":true,"id":832423,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70197082,"text":"70197082 - 2018 - Bat activity following restoration prescribed burning in the central Appalachian Upland and riparian habitats","interactions":[],"lastModifiedDate":"2018-05-16T12:47:32","indexId":"70197082","displayToPublicDate":"2018-04-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2821,"text":"Natural Areas Journal","active":true,"publicationSubtype":{"id":10}},"title":"Bat activity following restoration prescribed burning in the central Appalachian Upland and riparian habitats","docAbstract":"After decades of fire suppression in eastern North America, land managers now are prioritizing prescribed fire as a management tool to restore or maintain fire-adapted vegetation communities. However, in long—fire-suppressed landscapes, such as the central and southern Appalachians, it is unknown how bats will respond to prescribed fire in both riparian and upland forest habitats. To address these concerns, we conducted zero-crossing acoustic surveys of bat activity in burned, unburned, riparian, and non-riparian areas in the central Appalachians, Virginia, USA. Burn and riparian variables had model support (ΔAICc < 4) to explain activity of all bat species. Nonetheless, parameter estimates for these conditions were small and confidence intervals overlapped zero for all species, indicating effect sizes were marginal. Our results suggest that bats respond to fire differently between upland and riparian forest habitats, but overall, large landscape-level prescribed fire has a slightly positive to neutral impact on all bats species identified at our study site post—fire application.
","language":"English","publisher":"Natural Areas Association","doi":"10.3375/043.038.0208","usgsCitation":"Austin, L.V., Silvis, A., Ford, W., Muthersbaugh, M., and Powers, K.E., 2018, Bat activity following restoration prescribed burning in the central Appalachian Upland and riparian habitats: Natural Areas Journal, v. 38, no. 2, p. 183-195, https://doi.org/10.3375/043.038.0208.","productDescription":"13 p.","startPage":"183","endPage":"195","ipdsId":"IP-090018","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468869,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10919/99326","text":"External Repository"},{"id":354216,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","county":"Bath County","otherGeospatial":"George Washington National Forest","volume":"38","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6ebe4b0da30c1bfbf6f","contributors":{"authors":[{"text":"Austin, Lauren V.","contributorId":204944,"corporation":false,"usgs":false,"family":"Austin","given":"Lauren","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":735519,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Silvis, Alexander","contributorId":171585,"corporation":false,"usgs":false,"family":"Silvis","given":"Alexander","email":"","affiliations":[{"id":26923,"text":"Virginia Polytechnic Institute, Blacksburg, VA","active":true,"usgs":false}],"preferred":false,"id":735520,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":735504,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muthersbaugh, Michael","contributorId":204945,"corporation":false,"usgs":false,"family":"Muthersbaugh","given":"Michael","affiliations":[],"preferred":false,"id":735521,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Powers, Karen E.","contributorId":171456,"corporation":false,"usgs":false,"family":"Powers","given":"Karen","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":735522,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70197880,"text":"70197880 - 2018 - 2018 one‐year seismic hazard forecast for the central and eastern United States from induced and natural earthquakes","interactions":[],"lastModifiedDate":"2018-06-25T11:02:24","indexId":"70197880","displayToPublicDate":"2018-04-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"2018 one‐year seismic hazard forecast for the central and eastern United States from induced and natural earthquakes","docAbstract":"This article describes the U.S. Geological Survey (USGS) 2018 one‐year probabilistic seismic hazard forecast for the central and eastern United States from induced and natural earthquakes. For consistency, the updated 2018 forecast is developed using the same probabilistic seismicity‐based methodology as applied in the two previous forecasts. Rates of earthquakes across the United States
Atoll and island coastal communities are highly exposed to sea-level rise, tsunamis, storm surges, rogue waves, king tides, and the occasional combination of multiple factors, such as high regional sea levels, extreme high local tides, and unusually strong wave set-up. The elevation of most of these atolls averages just under 3 meters (m), with many areas roughly at sea level. The lack of high-resolution topographic data has been identified as a critical data gap for hazard vulnerability and adaptation efforts and for high-resolution inundation modeling for atoll nations. Modern topographic survey equipment and airborne lidar surveys can be very difficult and costly to deploy. Therefore, unmanned aircraft systems (UAS) were investigated for collecting overlapping imagery to generate topographic digital elevation models (DEMs). Medium- and high-resolution satellite imagery (Landsat 8 and WorldView-3) was investigated to derive nearshore bathymetry.
The Republic of the Marshall Islands is associated with the United States through a Compact of Free Association, and Majuro Atoll is home to the capital city of Majuro and the largest population of the Republic of the Marshall Islands. The only elevation datasets currently available for the entire Majuro Atoll are the Shuttle Radar Topography Mission and the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model Version 2 elevation data, which have a 30-m grid-cell spacing and a 8-m vertical root mean square error (RMSE). Both these datasets have inadequate spatial resolution and vertical accuracy for inundation modeling.
The final topobathymetric DEM (TBDEM) developed for Majuro Atoll is derived from various data sources including charts, soundings, acoustic sonar, and UAS and satellite imagery spanning over 70 years of data collection (1944 to 2016) on different sections of the atoll. The RMSE of the TBDEM over the land area is 0.197 m using over 70,000 Global Navigation Satellite System real-time kinematic survey points for validation, and 1.066 m for Landsat 8 and 1.112 m for WorldView-3 derived bathymetry using over 16,000 and 9,000 lidar bathymetry points, respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185047","usgsCitation":"Palaseanu-Lovejoy, M., Poppenga, S.K., Danielson, J.J., Tyler, D.J., Gesch, D.B., Kottermair, M., Jalandoni, A., Carlson, E., Thatcher, C.A., and Barbee, M.M., 2018, One-meter topobathymetric digital elevation model for Majuro Atoll, Republic of the Marshall Islands, 1944 to 2016: U.S. Geological Survey Scientific Investigations Report 2018–5047, 16 p., https://doi.org/10.3133/sir20185047.","productDescription":"vii, 16 p.","numberOfPages":"27","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-090429","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":352868,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5047/sir20185047.pdf","text":"Report","size":"2.59 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5047"},{"id":352867,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5047/coverthb.jpg"}],"country":"Republic of the Marshall Islands","otherGeospatial":"Majuro Atoll","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 170.96923828125,\n 7.009578865370235\n ],\n [\n 171.42654418945312,\n 7.009578865370235\n ],\n [\n 171.42654418945312,\n 7.261669781279355\n ],\n [\n 170.96923828125,\n 7.261669781279355\n ],\n [\n 170.96923828125,\n 7.009578865370235\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Eastern Geographic Science Center
U.S. Geological Survey
Mail Stop 521
12201 Sunrise Valley Drive
Reston, VA 20192
The practice of fire suppression across the western United States over the past century has led to dense forests, and when coupled with drought has contributed to an increase in large and destructive wildfires. Forest management efforts aimed at reducing flammable fuels through various fuel treatments can help to restore frequent fire regimes and increase forest resilience. Our research examines how different fuel treatments influenced burn severity and post-fire vegetative stand dynamics on the San Carlos Apache Reservation, in east-central Arizona, U.S.A. Our methods included the use of multitemporal remote sensing data and cloud computing to evaluate burn severity and post-fire vegetation conditions as well as statistical analyses. We investigated how forest thinning, commercial harvesting, prescribed burning, and resource benefit burning (managed wildfire) related to satellite measured burn severity (the difference Normalized Burn Ratio – dNBR) following the 2013 Creek Fire and used spectral measures of post-fire stand dynamics to track changes in land surface characteristics (i.e., brightness, greenness and wetness). We found strong negative relationships between dNBR and post-fire greenness and wetness, and a positive non-linear relationship between dNBR and brightness, with greater variability at higher severities. Fire severity and post-fire surface changes also differed by treatment type. Our results showed harvested and thinned sites that were not treated with prescribed fire had the highest severity fire. When harvesting was followed by a prescribed burn, the sites experienced lower burn severity and reduced post-fire changes in vegetation greenness and wetness. Areas that had previously experienced resource benefit burns had the lowest burn severities and the highest post-fire greenness measurements compared to all other treatments, except for where the prescribed burn had occurred. These results suggest that fire treatments may be most effective at reducing the probability of hazardous fire and increasing post-fire recovery. This research demonstrates the utility of remote sensing and spatial data to inform forest management, and how various fuel treatments can influence burn severity and post-fire vegetation response within ponderosa pine forests across the southwestern U.S.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2018.01.036","usgsCitation":"Petrakis, R., Villarreal, M.L., Wu, Z., Hetzler, R., Middleton, B.R., and Norman, L., 2018, Evaluating and monitoring forest fuel treatments using remote sensing applications in Arizona, U.S.A.: Forest Ecology and Management, v. 413, p. 48-61, https://doi.org/10.1016/j.foreco.2018.01.036.","productDescription":"14 p.","startPage":"48","endPage":"61","ipdsId":"IP-083699","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":468881,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2018.01.036","text":"Publisher Index Page"},{"id":437976,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7Z31WW4","text":"USGS data release","linkHelpText":"Dataset for 2013 Creek Fire Research Points, Pre- and Post-Fire Data"},{"id":352992,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.75,\n 33\n ],\n [\n -109.5,\n 33\n ],\n [\n -109.5,\n 33.8\n ],\n [\n -110.75,\n 33.8\n ],\n [\n -110.75,\n 33\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"413","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6f5e4b0da30c1bfbfaf","contributors":{"authors":[{"text":"Petrakis, Roy E. 0000-0001-8932-077X rpetrakis@usgs.gov","orcid":"https://orcid.org/0000-0001-8932-077X","contributorId":174623,"corporation":false,"usgs":true,"family":"Petrakis","given":"Roy","email":"rpetrakis@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":732009,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":1424,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":732010,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wu, Zhuoting 0000-0001-7393-1832 zwu@usgs.gov","orcid":"https://orcid.org/0000-0001-7393-1832","contributorId":4953,"corporation":false,"usgs":true,"family":"Wu","given":"Zhuoting","email":"zwu@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":498,"text":"Office of Land Remote Sensing (Geography)","active":true,"usgs":true}],"preferred":true,"id":732014,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hetzler, Robert","contributorId":203299,"corporation":false,"usgs":false,"family":"Hetzler","given":"Robert","email":"","affiliations":[{"id":36595,"text":"BIA","active":true,"usgs":false}],"preferred":false,"id":732011,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Middleton, Barry R. 0000-0001-8924-4121 bmiddleton@usgs.gov","orcid":"https://orcid.org/0000-0001-8924-4121","contributorId":3947,"corporation":false,"usgs":true,"family":"Middleton","given":"Barry","email":"bmiddleton@usgs.gov","middleInitial":"R.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":732012,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Norman, Laura M. 0000-0002-3696-8406","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":203300,"corporation":false,"usgs":true,"family":"Norman","given":"Laura M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":732013,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70216337,"text":"70216337 - 2018 - Hierarchical modeling assessment of the influence of watershed stressors on fish and invertebrate species in Gulf of Mexico estuaries","interactions":[],"lastModifiedDate":"2020-11-12T15:39:40.108738","indexId":"70216337","displayToPublicDate":"2018-03-28T09:35:38","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Hierarchical modeling assessment of the influence of watershed stressors on fish and invertebrate species in Gulf of Mexico estuaries","docAbstract":"The northern Gulf of Mexico (GoM) spans five U.S. states and encompasses estuaries that vary greatly in size, shape, upstream river input, eutrophication status, and biotic communities. Given the variability among these estuaries, assessing their biological condition relative to anthropogenic stressors is challenging, but important to regional fisheries management and habitat conservation initiatives. Here, a hierarchical generalized linear modeling approach was developed to predict species presence in bottom trawl samples, using data from 33 estuaries over a nineteen-year study period. This is the first GoM estuary assessment to leverage Gulf-wide trawl data to develop species-level indicators and a quantitative index of estuary disturbance. After controlling for sources of variability at the sampling event, estuary, state, and sampling program levels, our approach screened for statistically significant relationships between watershed-level anthropogenic stressors and fish and invertebrate species presence. Modeling results indicate species level indicators with sensitivities to landscape stressor gradients. The most influential stressors include total anthropogenic land use, crop land use, and the number of toxic release sites in upstream watersheds, as well as agriculture in the shoreline buffer, each of which was significantly related to between 21% and 39% of the 57 species studied. Averaging the effects of these influential stressors across species, we develop a quantitative estuary stress index that can be compared against benchmark conditions. In general, disturbance levels were greatest in estuaries west of the Mississippi delta and in highly developed estuaries in southwest Florida. Estuaries from the Florida panhandle to the eastern Mississippi delta had less anthropogenic stress.
The volcanic processes that have shaped the Long Valley Caldera in eastern California have also created an abundant supply of natural hot water. This natural resource provides benefits to many users, including power generation at the Casa Diablo Geothermal Plant, warm water for a state fish hatchery, and beautiful scenic areas such as Hot Creek gorge for visitors. However, some features can be dangerous because of sudden and unpredictable changes in the location and flow rate of boiling water. The U.S. Geological Survey monitors several aspects of the hydrothermal system in the Long Valley Caldera including temperature, flow rate, and water chemistry.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183009","collaboration":"Prepared in cooperation with the U.S. Forest Service","usgsCitation":"Evans, W.C., Hurwitz, S., Bergfeld, D., and Howle, J.F., 2018, Hot water in the Long Valley Caldera—The benefits and hazards of this large natural resource: U.S. Geological Survey Fact Sheet 2018–3009, 4 p., https://doi.org/10.3133/fs20183009.","productDescription":"4 p.","ipdsId":"IP-092280","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":352768,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3009/fs2018_3009.pdf","text":"Report","size":"4.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018-3009"},{"id":352767,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3009/cover_thb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Long Valley Caldera","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.0694808959961,\n 37.591383348725785\n ],\n [\n -118.68667602539062,\n 37.591383348725785\n ],\n [\n -118.68667602539062,\n 37.765286825037926\n ],\n [\n -119.0694808959961,\n 37.765286825037926\n ],\n [\n -119.0694808959961,\n 37.591383348725785\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information
Volcano Science Center - Menlo Park
U.S. Geological Survey
345 Middlefield Road, MS 910
Menlo Park, CA 94025
The Edwin B. Forsythe National Wildlife Refuge (hereafter Forsythe refuge or the refuge) is situated along the central New Jersey coast and provides a mixture of freshwater and saltwater habitats for numerous bird, wildlife, and plant species. Little data and information were previously available regarding the freshwater dynamics that support the refuge’s ecosystems. In cooperation with the U.S. Fish and Wildlife Service, the U.S. Geological Survey conducted an assessment of the hydrologic resources and processes in the refuge and surrounding areas to provide baseline information for evaluating restoration projects and future changes in the hydrologic system associated with climate change and other anthropogenic stressors.
During spring 2015, water levels were measured at groundwater and surface-water sites in and near the Forsythe refuge. These water-level measurements, along with surface-water elevations obtained from digital elevation models, were used to construct water-table-elevation and depth-to-water maps of the refuge and surrounding areas. Water-table elevations in the refuge ranged from sea level to approximately 65 feet above sea level; in most of the refuge, the water-table elevation was within 3 feet of sea level. The water-table-elevation map indicates that the direction of shallow groundwater flow at the regional scale is generally from west to east (much of it from the northwest to the southeast), and groundwater moves downgradient from the uplands toward major groundwater discharge areas consisting of coastal streams and wetlands. The depth to water is estimated to be less than 2 feet for approximately 86 percent of the refuge, which coincides closely with the percentage of wetland area in the refuge. Depth to water in excess of 20 feet below land surface is limited to higher elevation areas of the refuge.
Streamflow data collected at continuous-record streamgages and partial-record stations within the Mullica-Toms Basin were summarized. Hydrograph separation of streamflow data for eight streamgages (2004–13) reveals that base flow accounts for 68–94 percent of streamflow in basins upstream from the refuge. The high base-flow inputs underscore the importance of groundwater as a source of freshwater that supports both the streams that flow into the refuge and the hydroecology of the contributing basins. Mean annual flow typically ranged from 1.7 to 2.1 cubic feet per second per square mile at the streamgages (2004–13) and between 1.2 and 2.3 cubic feet per second per square mile at the partial-record stations (1965–2015) but was notably greater or lower than these ranges at several stations.
Mean annual water budgets were estimated for multiple regions of the refuge for 2004–13 using data compiled from nearby meteorological stations and groundwater flows derived from previously calibrated groundwater-flow models. Precipitation, groundwater recharge, and evapotranspiration were estimated from available data; direct runoff was calculated as the residual component of the water balance. Groundwater recharge rates were greatest in the upland-dominated areas of the refuge with estimates of 14.4 to 18.9 inches per year, which are equivalent to 30 to 40 percent of precipitation. Groundwater recharge rates were nearly zero in the central coastal areas because these areas are major groundwater discharge zones, the water table is near land surface, the subsurface is close to saturation and cannot accept much recharge, and much of the area is underlain by thick marsh deposits likely with low permeability. Estimates of evapotranspiration varied from about 26 inches per year in the upland-dominated areas to more than 35 inches per year in the coastal wetlands, equivalent to 55–79 percent of mean annual precipitation, indicating that it is a major component of the hydrodynamics of the Forsythe refuge.
On the basis of output from previously calibrated groundwater-flow models, nearly all of the groundwater exiting the surficial aquifer system in the central coastal areas of the refuge is discharged to wetlands, which highlights the importance of groundwater discharge in supporting the ecosystems of the Forsythe refuge. In the central coastal areas, horizontal flow contributes more than 90 percent of the groundwater flow to the surficial system, indicating that the upbasin areas are a substantial source of water that ultimately discharges to streams and wetlands in the refuge.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175088","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Wieben, C.M., and Chepiga, M.M., 2018, Hydrologic assessment of the Edwin B. Forsythe National Wildlife Refuge, New Jersey: U.S. Geological Survey Scientific Investigations Report 2017–5088, 38 p., https://doi.org/10.3133/sir20175088.\n","productDescription":"Report: viii, 38 p.; 2 Plates: 24.0 x 36.0 inches; Data release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-079840","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":352411,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5088/sir20175088.pdf","text":"Report","size":"25.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5088"},{"id":352410,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5088/coverthb.jpg"},{"id":352412,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78G8JMN","text":"USGS data release","description":"USGS data release","linkHelpText":"Water-table elevation contours and depth-to-water grid for the Edwin B. Forsythe National Wildlife Refuge, New Jersey, and vicinity, spring 2015"},{"id":352535,"rank":6,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5088/sir20175088_plate02.pdf","text":"Plate 2","size":"4.15 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Water-Table Elevation in and near the Southern Part of the Edwin B. Forsythe National Wildlife Refuge, New Jersey, Spring 2015"},{"id":352426,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://doi.org/10.3133/sir20175135","text":"Scientific Investigations Report 2017–5135","linkHelpText":"- Hydrogeology of, Simulation of Groundwater Flow in, and Potential Effects of Sea-Level Rise on the Kirkwood-Cohansey Aquifer System in the Vicinity of Edwin B. Forsythe National Wildlife Refuge, New Jersey"},{"id":352534,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5088/sir20175088_plate01.pdf","text":"Plate 1 ","size":"12.1 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Water-Table Elevation in and near the Northern Part of the Edwin B. Forsythe National Wildlife Refuge, New Jersey, Spring 2015"}],"country":"United States","state":"New Jersey","otherGeospatial":"Edwin B. Forsythe National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74,\n 39.4167\n ],\n [\n -74,\n 40.07807142745009\n ],\n [\n -74.5,\n 40.07807142745009\n ],\n [\n -74.5,\n 39.4167\n ],\n [\n -74,\n 39.4167\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
Fort Pulaski National Monument is located on Cockspur Island in Chatham County, Georgia, within the Atlantic Coastal Plain province. The island lies near the mouth of the Savannah River, and consists of small mounds (hummocks), salt marshes, and sediment dredged from the river. A 1,017-foot (ft) (310-meter [m])-deep core drilled at Cockspur Island in 2010 by the U.S. Geological Survey revealed several sedimentary units ranging in age from 43 million years old to present. Sand and mud are present at drilling depths from 0 to 182 ft (56 m), limestone is present at depths from 182 ft (56 m) to 965 ft (295 m), and glauconitic sand is present at depths from 965 ft (295 m) to 1,017 ft (310 m). The limestone and the water within the limestone are referred to collectively as the Floridan aquifer system, which is the primary source of drinking water for the City of Savannah and surrounding communities. In addition to details of the subsurface geology, this fact sheet identifies the following geologic materials used in the construction of Fort Pulaski: (1) granite, (2) bricks, (3) sandstone, and (4) lime mud with oyster shells.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183011","usgsCitation":"Swezey, C.S., Seefelt, E.L., and Parker, M., 2018, A brief geological history of Cockspur Island at Fort Pulaski National Monument, Chatham County, Georgia: U.S. Geological Survey Fact Sheet 2018‒3011, 4 p., https://doi.org/10.3133/fs20183011.","productDescription":"4 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":" IP-082254","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":352324,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3011/fs20183011.pdf","text":"Report","size":"6.05 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018-3011"},{"id":352323,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3011/coverthb.jpg"}],"country":"United States","state":"Georgia","county":"Chatham County","otherGeospatial":"Fort Pulaski National Monument","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.92349052429198,\n 32.021321351629176\n ],\n [\n -80.87533950805664,\n 32.021321351629176\n ],\n [\n -80.87533950805664,\n 32.03696591411931\n ],\n [\n -80.92349052429198,\n 32.03696591411931\n ],\n [\n -80.92349052429198,\n 32.021321351629176\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Geology Paleoclimate Science Center
U.S. Geological Survey
Mail Stop 926A
12201 Sunrise Valley Drive
Reston, VA 20192
How well seabirds compensate for variability in prey abundance and composition near their breeding colonies influences their distribution and reproductive success. We used tufted puffins (Fratercula cirrhata) as forage fish samplers to study marine food webs from the western Aleutian Islands (53°N, 173°E) to Kodiak Island (57°N, 153°W), Alaska, during August 2012–2014. Around each colony we obtained data on: environmental characteristics (sea surface temperature and salinity, seafloor depth and slope, tidal range, and chlorophyll-a), relative forage fish biomass (hydroacoustic backscatter), and seabird community composition and density at-sea. On colonies, we collected puffin chick-meals to characterize forage communities and determine meal energy density, and measured chicks to obtain a body condition index. There were distinct environmental gradients from west to east, and environmental variables differed by ecoregions: the (1) Western-Central Aleutians, (2) Eastern Aleutians, and, (3) Alaska Peninsula. Forage fish biomass, species richness, and community composition all differed markedly between ecoregions. Forage biomass was strongly correlated with environmental gradients, and environmental gradients and forage biomass accounted for ~ 50% of the variability in at-sea density of tufted puffins and all seabird taxa combined. Despite the local and regional variability in marine environments and forage, the mean biomass of prey delivered to puffin chicks did not differ significantly between ecoregions, nor did chick condition or puffin density at-sea. We conclude that puffins can adjust their foraging behavior to produce healthy chicks across a wide range of environmental conditions. This extraordinary flexibility enables their overall success and wide distribution across the North Pacific Ocean.
","language":"English","publisher":"Springer","doi":"10.1007/s00227-018-3304-4","usgsCitation":"Schoen, S.K., Piatt, J.F., Arimitsu, M.L., Heflin, B., Madison, E.N., Drew, G.S., Renner, M., Rojek, N.A., Douglas, D.C., and DeGange, A.R., 2018, Avian predator buffers against variability in marine habitats with flexible foraging behavior: Marine Biology, v. 165, p. 1-14, https://doi.org/10.1007/s00227-018-3304-4.","productDescription":"Article 47; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-090458","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":437987,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TQ60GV","text":"USGS data release","linkHelpText":"Marine ecology near Tufted Puffin colonies across the Aleutian Archipelago and Alaska Peninsula, 2012-2014"},{"id":352355,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Aleutian Islands, Gulf of Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -188.525390625,\n 50.84757295365389\n ],\n [\n -151.6552734375,\n 50.84757295365389\n ],\n [\n -151.6552734375,\n 57.657157596582984\n ],\n [\n -188.525390625,\n 57.657157596582984\n ],\n [\n -188.525390625,\n 50.84757295365389\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"165","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-15","publicationStatus":"PW","scienceBaseUri":"5afee701e4b0da30c1bfc050","contributors":{"authors":[{"text":"Schoen, Sarah K. 0000-0002-5685-5185 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0000-0001-6982-2238 marimitsu@usgs.gov","orcid":"https://orcid.org/0000-0001-6982-2238","contributorId":140501,"corporation":false,"usgs":true,"family":"Arimitsu","given":"Mayumi","email":"marimitsu@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":730653,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Heflin, Brielle 0000-0002-4836-9187 bheflin@usgs.gov","orcid":"https://orcid.org/0000-0002-4836-9187","contributorId":198164,"corporation":false,"usgs":true,"family":"Heflin","given":"Brielle","email":"bheflin@usgs.gov","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":730654,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Madison, Erica N. emadison@usgs.gov","contributorId":3409,"corporation":false,"usgs":true,"family":"Madison","given":"Erica","email":"emadison@usgs.gov","middleInitial":"N.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":730655,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Drew, Gary S. 0000-0002-6789-0891 gdrew@usgs.gov","orcid":"https://orcid.org/0000-0002-6789-0891","contributorId":3311,"corporation":false,"usgs":true,"family":"Drew","given":"Gary","email":"gdrew@usgs.gov","middleInitial":"S.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":730656,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Renner, Martin","contributorId":198248,"corporation":false,"usgs":false,"family":"Renner","given":"Martin","email":"","affiliations":[],"preferred":false,"id":730657,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rojek, Nora A.","contributorId":201046,"corporation":false,"usgs":false,"family":"Rojek","given":"Nora","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":730658,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":2388,"corporation":false,"usgs":true,"family":"Douglas","given":"David","email":"ddouglas@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":730659,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"DeGange, Anthony R. tdegange@usgs.gov","contributorId":203210,"corporation":false,"usgs":false,"family":"DeGange","given":"Anthony","email":"tdegange@usgs.gov","middleInitial":"R.","affiliations":[{"id":36582,"text":"Former USGS ASC employee","active":true,"usgs":false}],"preferred":false,"id":730660,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70194963,"text":"ofr20181004 - 2018 - Flooding in the southern Midwestern United States, April–May 2017","interactions":[],"lastModifiedDate":"2018-09-25T06:37:49","indexId":"ofr20181004","displayToPublicDate":"2018-03-09T00:00:00","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":"2018-1004","title":"Flooding in the southern Midwestern United States, April–May 2017","docAbstract":"Excessive rainfall resulted in flooding on numerous rivers throughout the southern Midwestern United States (southern Midwest) in late April and early May of 2017. The heaviest rainfall, between April 28 and 30, resulted in extensive flooding from eastern Oklahoma to southern Indiana including parts of Missouri, Arkansas, and Illinois.
Peak-of-record streamflows were set at 21 U.S. Geological Survey (USGS) streamgages in the southern Midwest during the resulting April–May 2017 flooding and each of the five States included in the study area had at least one streamgage with a peak of record during the flood. The annual exceedance probability (AEP) estimates for the April–May 2017 peak streamflows indicate that peaks at 5 USGS streamgages had AEPs of 0.2 percent or less (500-year recurrence interval or greater), and peak streamflows at 15 USGS streamgages had AEPs in the range from greater than 0.2 to 1 percent (500- to 100-year recurrence intervals).
Examination of the magnitude of the temporal changes in median annual peak streamflows indicated positive increases, in general, throughout the study area for each of the 1930–2017, 1956–2017, 1975–2017, and 1989–2017 analysis periods. The median increase in peak streamflows was greatest in 1975–2017 and 1989–2017 with maximum increases of 8 to 10 percent per year. No stations in the 1975–2017 or 1989–2017 analysis period had median negative changes in peak streamflows.
","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181004","usgsCitation":"Heimann, D.C., Holmes, R.R., Jr., and Harris, T.E., 2018, Flooding in the southern Midwestern United States, April–May 2017: U.S. Geological Survey Open-File Report 2018–1004, 36 p., https://doi.org/10.3133/ofr20181004.","productDescription":"Report: v, 36 p.; 7 Films","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-091177","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":352359,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/of/2018/1004/downloads/Films/Film1.mp4","text":"Film 1—","size":"15.6 MB","description":"OFR 2018–1004 Film 1","linkHelpText":"April 28, 2017–May 10, 2017, Daily streamflow magnitude in study area compared to long-term median streamflows"},{"id":352364,"rank":8,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/of/2018/1004/downloads/Films/Film6_NFK_MO_HWYPP.mp4","text":"Film 6—(film courtesy of Aerial Ozarks)","size":"172 MB","description":"OFR 2018–1004 Film 6","linkHelpText":"James Bridge on MO-PP, North Fork River, Ozark County, Mo."},{"id":352361,"rank":5,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/of/2018/1004/downloads/Films/Film3_NFK_SpringCK.mp4","text":"Film 3—(film courtesy of Aerial Ozarks)","size":"159 MB","description":"OFR 2018–1004 Film 3","linkHelpText":"Twin Bridges in Douglas County, Mo., North Fork River and Spring Creek"},{"id":352363,"rank":7,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/of/2018/1004/downloads/Films/Film5_BryantCK_Hwy181.mp4","text":"Film 5—(film courtesy of Aerial Ozarks)","size":"137 MB","description":"OFR 2018–1004 Film 5","linkHelpText":"Hodgson Mill on Hwy. 181, Bryant Creek, Ozark County, Mo."},{"id":352341,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1004/coverthb2.jpg"},{"id":352362,"rank":6,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/of/2018/1004/downloads/Films/Film4_NFK_MO_HWY_CC(HammondMillBrdge).mp4","text":"Film 4—(film courtesy of Aerial Ozarks)","size":"126 MB","description":"OFR 2018–1004 Film 4","linkHelpText":"Hammond Mill Bridge on MO-CC, North Fork River, Ozark County, Mo."},{"id":352365,"rank":9,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/of/2018/1004/downloads/Films/Film7_DryCK_MO_HwyAP.mp4","text":"Film 7—(film courtesy of Aerial Ozarks)","size":"70.0 MB","description":"OFR 2018–1004 Film 7","linkHelpText":"Dry Creek Bridge on MO-AP, Dry Creek, Howell County, Mo."},{"id":352342,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1004/ofr20181004.pdf","text":"Report","size":"8.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018–1004"},{"id":352394,"rank":10,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2018/1004/downloads/Films/Films.zip","text":"Films","size":"746 MB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2018–1004 Films"},{"id":352360,"rank":4,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/of/2018/1004/downloads/Films/Film2_SpringCK_HwyAP.mp4","text":"Film 2—(film courtesy of Aerial Ozarks)","size":"75.4 MB","description":"OFR 2018–1004 Film 2","linkHelpText":"Spring Creek Bridge on MO-AP"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.20751953125,\n 33.706062655101206\n ],\n [\n -87.36328125,\n 33.706062655101206\n ],\n [\n -87.36328125,\n 39.38526381099774\n ],\n [\n -95.20751953125,\n 39.38526381099774\n ],\n [\n -95.20751953125,\n 33.706062655101206\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Missouri Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
A mass balance is formulated to evaluate the mobilization of chlorinated ethene compounds (CE) from the rock matrix of a fractured mudstone aquifer under pre- and postbioremediation conditions. The analysis relies on a sparse number of monitoring locations and is constrained by a detailed description of the groundwater flow regime. Groundwater flow modeling developed under the site characterization identified groundwater fluxes to formulate the CE mass balance in the rock volume exposed to the injected remediation amendments. Differences in the CE fluxes into and out of the rock volume identify the total CE mobilized from diffusion, desorption, and nonaqueous phase liquid dissolution under pre- and postinjection conditions. The initial CE mass in the rock matrix prior to remediation is estimated using analyses of CE in rock core. The CE mass mobilized per year under preinjection conditions is small relative to the total CE mass in the rock, indicating that current pump-and-treat and natural attenuation conditions are likely to require hundreds of years to achieve groundwater concentrations that meet regulatory guidelines. The postinjection CE mobilization rate increased by approximately an order of magnitude over the 5 years of monitoring after the amendment injection. This rate is likely to decrease and additional remediation applications over several decades would still be needed to reduce CE mass in the rock matrix to levels where groundwater concentrations in fractures achieve regulatory standards.
","language":"English","publisher":"Wiley","doi":"10.1111/gwat.12586","usgsCitation":"Shapiro, A.M., Tiedeman, C.R., Imbrigiotta, T.E., Goode, D.J., Hsieh, P.A., Lacombe, P., DeFlaun, M.F., Drew, S.R., and Curtis, G.P., 2018, Bioremediation in fractured rock: 2. Mobilization of chloroethene compounds from the rock matrix: Groundwater, v. 56, no. 2, p. 317-336, https://doi.org/10.1111/gwat.12586.","productDescription":"20 p.","startPage":"317","endPage":"336","ipdsId":"IP-088890","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":352329,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey","city":"West Trenton","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.81480240821838,\n 40.26764815781309\n ],\n [\n -74.8107898235321,\n 40.26764815781309\n ],\n [\n -74.8107898235321,\n 40.27047242769165\n ],\n [\n -74.81480240821838,\n 40.27047242769165\n ],\n [\n -74.81480240821838,\n 40.26764815781309\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"56","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-05","publicationStatus":"PW","scienceBaseUri":"5afee701e4b0da30c1bfc05a","contributors":{"authors":[{"text":"Shapiro, Allen M. 0000-0002-6425-9607 ashapiro@usgs.gov","orcid":"https://orcid.org/0000-0002-6425-9607","contributorId":2164,"corporation":false,"usgs":true,"family":"Shapiro","given":"Allen","email":"ashapiro@usgs.gov","middleInitial":"M.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":730558,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tiedeman, Claire R. 0000-0002-0128-3685 tiedeman@usgs.gov","orcid":"https://orcid.org/0000-0002-0128-3685","contributorId":196777,"corporation":false,"usgs":true,"family":"Tiedeman","given":"Claire","email":"tiedeman@usgs.gov","middleInitial":"R.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":730559,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Imbrigiotta, Thomas E. 0000-0003-1716-4768 timbrig@usgs.gov","orcid":"https://orcid.org/0000-0003-1716-4768","contributorId":152114,"corporation":false,"usgs":true,"family":"Imbrigiotta","given":"Thomas","email":"timbrig@usgs.gov","middleInitial":"E.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":730560,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goode, Daniel J. 0000-0002-8527-2456 djgoode@usgs.gov","orcid":"https://orcid.org/0000-0002-8527-2456","contributorId":193394,"corporation":false,"usgs":true,"family":"Goode","given":"Daniel","email":"djgoode@usgs.gov","middleInitial":"J.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":false,"id":730561,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hsieh, Paul A. 0000-0003-4873-4874 pahsieh@usgs.gov","orcid":"https://orcid.org/0000-0003-4873-4874","contributorId":1634,"corporation":false,"usgs":true,"family":"Hsieh","given":"Paul","email":"pahsieh@usgs.gov","middleInitial":"A.","affiliations":[{"id":39113,"text":"WMA - Office of Quality Assurance","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":730562,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lacombe, Pierre 0000-0002-9596-7622 placombe@usgs.gov","orcid":"https://orcid.org/0000-0002-9596-7622","contributorId":152113,"corporation":false,"usgs":true,"family":"Lacombe","given":"Pierre","email":"placombe@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":730563,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"DeFlaun, Mary F.","contributorId":203177,"corporation":false,"usgs":false,"family":"DeFlaun","given":"Mary","email":"","middleInitial":"F.","affiliations":[{"id":36571,"text":"Geosyntec Consultants","active":true,"usgs":false}],"preferred":false,"id":730564,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Drew, Scott R.","contributorId":203178,"corporation":false,"usgs":false,"family":"Drew","given":"Scott","email":"","middleInitial":"R.","affiliations":[{"id":36571,"text":"Geosyntec Consultants","active":true,"usgs":false}],"preferred":false,"id":730565,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Curtis, Gary P. 0000-0003-3975-8882 gpcurtis@usgs.gov","orcid":"https://orcid.org/0000-0003-3975-8882","contributorId":2346,"corporation":false,"usgs":true,"family":"Curtis","given":"Gary","email":"gpcurtis@usgs.gov","middleInitial":"P.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":730566,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70195883,"text":"70195883 - 2018 - Changes in freshwater mussel communities linked to legacy pollution in the Lower Delaware River","interactions":[],"lastModifiedDate":"2018-03-07T15:03:47","indexId":"70195883","displayToPublicDate":"2018-03-07T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2898,"text":"Northeastern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Changes in freshwater mussel communities linked to legacy pollution in the Lower Delaware River","docAbstract":"Freshwater mussels are among the most-imperiled organisms worldwide, although they provide a variety of important functions in the streams and rivers they inhabit. Among Atlantic-slope rivers, the Delaware River is known for its freshwater mussel diversity and biomass; however, limited data are available on the freshwater mussel fauna in the lower, non-tidal portion of the river. This section of the Delaware River has experienced decades of water-quality degradation from both industrial and municipal sources, primarily as a function of one of its major tributaries, the Lehigh River. We completed semi-quantitative snorkel surveys in 53.5 of the 121 km of the river to document mussel community composition and the continued impacts from pollution (particularly inputs from the Lehigh River) on mussel fauna. We detected changes in mussel catch per unit effort (CPUE) below the confluence of the Lehigh River, with significant declines in the dominant species Elliptio complanata (Eastern Elliptio) as we moved downstream from its confluence—CPUE dropped from 179 to 21 mussels/h. Patterns in mussel distribution around the Lehigh confluence matched chemical signatures of Lehigh water input. Specifically, Eastern Elliptio CPUE declined more quickly moving downstream on the Pennsylvania bank, where Lehigh River water input was more concentrated compared to the New Jersey bank. A definitive causal link remains to be established between the Lehigh River and the dramatic shifts in mussel community composition, warranting continued investigation as it relates to mussel conservation and restoration in the basin.
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