Water temperature influences most physical and biological processes in streams, and along with streamflows is a major driver of ecosystem processes. Collecting data to measure water temperature is therefore imperative, and relatively straightforward. Several protocols exist for collecting stream temperature data, but these are frequently directed towards specialists. This document was developed to address the need for a protocol intended for non-specialists (non-aquatic) staff. It provides specific step-by-step procedures on (1) how to launch data loggers, (2) check the factory calibration of data loggers prior to field use, (3) how to install data loggers in streams for year-round monitoring, (4) how to download and retrieve data loggers from the field, and (5) how to input project data into organizational databases.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section A: Surface-water techniques in Book 3: Applications of hydraulics","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm3A25","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Heck, M.P., Schultz, L.D., Hockman-Wert, D., Dinger, E.C., and Dunham, J.B., 2018, Monitoring stream temperatures—A guide for non-specialists: U.S. Geological Survey Techniques and Methods, book 3, chap. A25, 76 p., https://doi.org/10.3133/tm3A25.","productDescription":"iv, 76 p.","numberOfPages":"84","onlineOnly":"Y","ipdsId":"IP-090007","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":353592,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/03/a25/coverthb.jpg"},{"id":353593,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/03/a25/tm3a25.pdf","text":"Report","size":"45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 3A25"}],"publicComments":"This report is Chapter 25 of Section A: Surface-water techniques in Book 3: Applications of hydraulics.","contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
We have conducted a gravity survey of the Coso geothermal field to continue the time-lapse gravity study of the area initiated in 1991. In this report, we outline a method of processing the gravity data that minimizes the random errors and instrument bias introduced into the data by the Scintrex CG-5 relative gravimeters that were used. After processing, the standard deviation of the data was estimated to be ±13 microGals. These data reveal that the negative gravity anomaly over the Coso geothermal field, centered on gravity station CER1, is continuing to increase in magnitude over time. Preliminary modeling indicates that water-table drawdown at the location of CER1 is between 65 and 326 meters over the last two decades. We note, however, that several assumptions on which the model results depend, such as constant elevation and free-water level over the study period, still require verification.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181053","collaboration":"Prepared in cooperation with the U.S. Department of the Navy Geothermal Program Office","usgsCitation":"Phelps, G., Cronkite-Ratcliff, C., and Blake, K., 2018, A time-lapse gravity survey of the Coso geothermal field, China Lake Naval Air Weapons Station, California: U.S. Geological Survey Open-File Report 2018–1053, 25 p., https://doi.org/10.3133/ofr20181053.","productDescription":"Report: v, 25 p.; Table","numberOfPages":"31","onlineOnly":"Y","ipdsId":"IP-082096","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":353589,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1053/coverthb.jpg"},{"id":353590,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1053/ofr20181053.pdf","text":"Report","size":"9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1053"},{"id":353607,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2018/1053/ofr20181053_table1.xlsx","text":"Table 1","size":"22 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2018-1053"}],"country":"United States","state":"California","otherGeospatial":"Coso Geothermal Field, China Lake Naval Air Weapons Station","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118,\n 35.88682489453265\n ],\n [\n -117.625,\n 35.88682489453265\n ],\n [\n -117.625,\n 36.25\n ],\n [\n -118,\n 36.25\n ],\n [\n -118,\n 35.88682489453265\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Environmental DNA (eDNA) detection is a technique used to non-invasively detect cryptic, low density, or logistically difficult-to-study species, such as imperiled manatees. For eDNA measurement, genetic material shed into the environment is concentrated from water samples and analyzed for the presence of target species. Cytochrome bquantitative PCR and droplet digital PCR eDNA assays were developed for the 3 Vulnerable manatee species: African, Amazonian, and both subspecies of the West Indian (Florida and Antillean) manatee. Environmental DNA assays can help to delineate manatee habitat ranges, high use areas, and seasonal population changes. To validate the assay, water was analyzed from Florida’s east coast containing a high-density manatee population and produced 31564 DNA molecules l-1on average and high occurrence (ψ) and detection (p) estimates (ψ = 0.84 [0.40-0.99]; p = 0.99 [0.95-1.00]; limit of detection 3 copies µl-1). Similar occupancy estimates were produced in the Florida Panhandle (ψ = 0.79 [0.54-0.97]) and Cuba (ψ = 0.89 [0.54-1.00]), while occupancy estimates in Cameroon were lower (ψ = 0.49 [0.09-0.95]). The eDNA-derived detection estimates were higher than those generated using aerial survey data on the west coast of Florida and may be effective for population monitoring. Subsequent eDNA studies could be particularly useful in locations where manatees are (1) difficult to identify visually (e.g. the Amazon River and Africa), (2) are present in patchy distributions or are on the verge of extinction (e.g. Jamaica, Haiti), and (3) where repatriation efforts are proposed (e.g. Brazil, Guadeloupe). Extension of these eDNA techniques could be applied to other imperiled marine mammal populations such as African and Asian dugongs.
","language":"English","publisher":"Inter-Research","doi":"10.3354/esr00880","usgsCitation":"Hunter, M., Meigs-Friend, G., Ferrante, J.A., Takoukam Kamla, A., Dorazio, R., Keith Diagne, L., Luna, F., Lanyon, J.M., and Reid, J.P., 2018, Surveys of environmental DNA (eDNA): a new approach to estimate occurrence in Vulnerable manatee populations: Endangered Species Research, v. 35, p. 101-111, https://doi.org/10.3354/esr00880.","productDescription":"12 p.","startPage":"101","endPage":"111","ipdsId":"IP-087696","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":468820,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr00880","text":"Publisher Index Page"},{"id":353606,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6d9e4b0da30c1bfbe8e","contributors":{"authors":[{"text":"Hunter, Margaret 0000-0002-4760-9302 mhunter@usgs.gov","orcid":"https://orcid.org/0000-0002-4760-9302","contributorId":140627,"corporation":false,"usgs":true,"family":"Hunter","given":"Margaret","email":"mhunter@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":733728,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meigs-Friend, Gaia 0000-0001-5181-7510 gmeigs-friend@usgs.gov","orcid":"https://orcid.org/0000-0001-5181-7510","contributorId":4688,"corporation":false,"usgs":true,"family":"Meigs-Friend","given":"Gaia","email":"gmeigs-friend@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":733729,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ferrante, Jason A. 0000-0003-3453-4636 jferrante@usgs.gov","orcid":"https://orcid.org/0000-0003-3453-4636","contributorId":201638,"corporation":false,"usgs":true,"family":"Ferrante","given":"Jason","email":"jferrante@usgs.gov","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":733730,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Takoukam Kamla, Aristide","contributorId":204221,"corporation":false,"usgs":false,"family":"Takoukam Kamla","given":"Aristide","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":733731,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dorazio, Robert 0000-0003-2663-0468 bob_dorazio@usgs.gov","orcid":"https://orcid.org/0000-0003-2663-0468","contributorId":172151,"corporation":false,"usgs":true,"family":"Dorazio","given":"Robert","email":"bob_dorazio@usgs.gov","affiliations":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":733732,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Keith Diagne, Lucy","contributorId":204222,"corporation":false,"usgs":false,"family":"Keith Diagne","given":"Lucy","affiliations":[{"id":36882,"text":"African Aquatic Conservation Fund","active":true,"usgs":false}],"preferred":false,"id":733733,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Luna, Fabia","contributorId":204223,"corporation":false,"usgs":false,"family":"Luna","given":"Fabia","affiliations":[{"id":36883,"text":"The National Center for Research and Conservation of Aquatic Mammals","active":true,"usgs":false}],"preferred":false,"id":733734,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lanyon, Janet M.","contributorId":204224,"corporation":false,"usgs":false,"family":"Lanyon","given":"Janet","email":"","middleInitial":"M.","affiliations":[{"id":13335,"text":"The University of Queensland","active":true,"usgs":false}],"preferred":false,"id":733735,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Reid, James P. 0000-0002-8497-1132 jreid@usgs.gov","orcid":"https://orcid.org/0000-0002-8497-1132","contributorId":3460,"corporation":false,"usgs":true,"family":"Reid","given":"James","email":"jreid@usgs.gov","middleInitial":"P.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":733736,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70196575,"text":"70196575 - 2018 - Opportunistically collected data reveal habitat selection by migrating Whooping Cranes in the U.S. Northern Plains","interactions":[],"lastModifiedDate":"2018-04-19T09:26:58","indexId":"70196575","displayToPublicDate":"2018-04-19T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3551,"text":"The Condor","active":true,"publicationSubtype":{"id":10}},"title":"Opportunistically collected data reveal habitat selection by migrating Whooping Cranes in the U.S. Northern Plains","docAbstract":"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":70195757,"text":"sim3401 - 2018 - Uranium concentrations in groundwater, northeastern Washington","interactions":[],"lastModifiedDate":"2018-04-19T10:02:37","indexId":"sim3401","displayToPublicDate":"2018-04-18T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3401","title":"Uranium concentrations in groundwater, northeastern Washington","docAbstract":"A study of uranium in groundwater in northeastern Washington was conducted to make a preliminary assessment of naturally occurring uranium in groundwater relying on existing information and limited reconnaissance sampling. Naturally occurring uranium is associated with granitic and metasedimentary rocks, as well as younger sedimentary deposits, that occur in this region. The occurrence and distribution of uranium in groundwater is poorly understood. U.S. Environmental Protection Agency (EPA) regulates uranium in Group A community water systems at a maximum contaminant level (MCL) of 30 μg/L in order to reduce uranium exposure, protect from toxic kidney effects of uranium, and reduce the risk of cancer. However, most existing private wells in the study area, generally for single family use, have not been sampled for uranium. This document presents available uranium concentration data from throughout a multi-county region, identifies data gaps, and suggests further study aimed at understanding the occurrence of uranium in groundwater.
The study encompasses about 13,000 square miles (mi2) in the northeastern part of Washington with a 2010 population of about 563,000. Other than the City of Spokane, most of the study area is rural with small towns interspersed throughout the region. The study area also includes three Indian Reservations with small towns and scattered population. The area has a history of uranium exploration and mining, with two inactive uranium mines on the Spokane Indian Reservation and one smaller inactive mine on the outskirts of Spokane. Historical (1977–2016) uranium in groundwater concentration data were used to describe and illustrate the general occurrence and distribution of uranium in groundwater, as well as to identify data deficiencies. Uranium concentrations were detected at greater than 1 microgram per liter (μg/L) in 60 percent of the 2,382 historical samples (from wells and springs). Uranium concentrations ranged from less than 1 to 88,600 μg/L, and the median concentration of uranium in groundwater for all sites was 1.4 μg/L.
New (2017) uranium in groundwater concentration data were obtained by sampling 13 private domestic wells for uranium in areas without recent (2000s) water-quality data. Uranium was detected in all 13 wells sampled for this study; concentrations ranged from 1.03 to 1,180 μg/L with a median of 22 μg/L. Uranium concentrations of groundwater samples from 6 of the 13 wells exceeded the MCL for uranium. Uranium concentrations in water samples from two wells were 1,130 and 1,180 μg/L, respectively; nearly 40 times the MCL.
Additional data collection and analysis are needed in rural areas where self-supplied groundwater withdrawals are the primary source of water for human consumption. Of the roughly 43,000 existing water wells in the study area, only 1,755 wells, as summarized in this document, have available uranium concentration data, and some of those data are decades old. Furthermore, analysis of area groundwater quality would benefit from a more extensive chemical-analysis suite including general chemistry in order to better understand local geochemical conditions that largely govern the mobility of uranium. Although the focus of the present study is uranium, it also is important to recognize that there are other radionuclides of concern that may be present in area groundwater.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3401","usgsCitation":"Kahle, S.C., Welch, W.B., Tecca, A.E., and Eliason, D.M., 2018, Uranium concentrations in groundwater, northeastern Washington: U.S. Geological Survey Scientific Investigations Map 3401, 1 sheet, https://doi.org/10.3133/sim3401.","productDescription":"Map: 44.0 x 34.0 inches; Table; 3 Figures","additionalOnlineFiles":"Y","ipdsId":"IP-091739","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":353579,"rank":5,"type":{"id":13,"text":"Illustration"},"url":"https://pubs.usgs.gov/sim/3401/sim3401_figure05.pdf","text":"Figure 5","size":"4.5 MB layered","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3401 Figure 5","linkHelpText":"Locations of wells with associated uranium concentrations showing generalized geologic material of open interval, Ferry, Pend Oreille, and Stevens Counties, Washington. Wells with groundwater samples with uranium concentrations greater than or equal to 30 micrograms per liter are labeled."},{"id":353574,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3401/coverthb2.jpg"},{"id":353575,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3401/sim3401.pdf","text":"Map","size":"13.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3401"},{"id":353577,"rank":3,"type":{"id":13,"text":"Illustration"},"url":"https://pubs.usgs.gov/sim/3401/sim3401_figure03.pdf","text":"Figure 3","size":"8.3 MB layered","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3401 Figure 3","linkHelpText":"Geology, locations of uranium assay sites or mines, and locations of wells and springs with historical uranium concentrations in groundwater of greater than or equal to 10 micrograms per liter (μg/L), northeastern Washington, 1977–2016."},{"id":353581,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sim/3401/sim3401_table01.xlsx","text":"Table 1","size":"210 KB xlsx","description":"SIM 3401 Table 1"},{"id":353578,"rank":4,"type":{"id":13,"text":"Illustration"},"url":"https://pubs.usgs.gov/sim/3401/sim3401_figure04.pdf","text":"Figure 4","size":"6.1 MB layered","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3401 Figure 4","linkHelpText":"Magnitude and distribution of historical uranium concentrations in groundwater samples, northeastern Washington, 1977–2016."}],"country":"United States","state":"Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120,\n 47.5\n ],\n [\n -117,\n 47.5\n ],\n [\n -117,\n 49\n ],\n [\n -120,\n 49\n ],\n [\n -120,\n 47.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
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":70198740,"text":"70198740 - 2018 - Does what go up also come down? Using a recruitment model to balance alewife nutrient import and export","interactions":[],"lastModifiedDate":"2018-08-24T12:13:56","indexId":"70198740","displayToPublicDate":"2018-04-17T08:18:16","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2680,"text":"Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science","active":true,"publicationSubtype":{"id":10}},"title":"Does what go up also come down? Using a recruitment model to balance alewife nutrient import and export","docAbstract":"Migrating adult Alewives Alosa pseudoharengus are a source of marine-derived nutrients on the East Coast of North America, importing nitrogen and phosphorus into freshwater habitats. Juvenile migrants subsequently transport freshwater-derived nutrients into the ocean. We developed a deterministic model to explore the theoretical nutrient dynamics of Alewife migrations at differing spawner abundances. Net nutrient balance was calculated relative to these abundances along the spawner–recruit curve. The ecological consequences of these subsidies in a particular watershed depend on the magnitude of adult escapement relative to the habitat’s carrying capacity for juveniles. At low escapement levels and assuming complete habitat access, the number of recruits produced per spawner was high and juvenile nutrient export dominated. At high escapement levels, fewer recruits were produced per spawner because recruitment is density dependent. As a result, adult nutrient import dominated. At varying levels of freshwater productivity and fisheries mortality for upstream spawners, this trend remained the same while the magnitude of the endpoints changed. Productivity level was the major determinant of export, while fisheries mortality had the strongest effect on adult import. The dynamics of this nutrient trade-off are important for managers to consider as a recovering population will likely shift from net export to net import as escapement increases. This transition will be sensitive to both harvest rates and to fish passage efficacy at dams and other barriers.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/mcf2.10021","usgsCitation":"Barber, B.L., Gibson, A.J., O’Malley, A., and Zydlewski, J.D., 2018, Does what go up also come down? Using a recruitment model to balance alewife nutrient import and export: Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science, v. 10, no. 2, p. 236-254, https://doi.org/10.1002/mcf2.10021.","productDescription":"19 p.","startPage":"236","endPage":"254","ipdsId":"IP-088585","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468822,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/mcf2.10021","text":"Publisher Index Page"},{"id":356605,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-17","publicationStatus":"PW","scienceBaseUri":"5b98a2d9e4b0702d0e842ff9","contributors":{"authors":[{"text":"Barber, Betsy L.","contributorId":207173,"corporation":false,"usgs":false,"family":"Barber","given":"Betsy","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":743026,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gibson, A. Jamie","contributorId":207172,"corporation":false,"usgs":false,"family":"Gibson","given":"A.","email":"","middleInitial":"Jamie","affiliations":[],"preferred":false,"id":743027,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Malley, Andrew","contributorId":169716,"corporation":false,"usgs":false,"family":"O’Malley","given":"Andrew","email":"","affiliations":[],"preferred":false,"id":743028,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zydlewski, Joseph D. 0000-0002-2255-2303 jzydlewski@usgs.gov","orcid":"https://orcid.org/0000-0002-2255-2303","contributorId":2004,"corporation":false,"usgs":true,"family":"Zydlewski","given":"Joseph","email":"jzydlewski@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":742809,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"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
Lake Hayward is one of only about 30 hypersaline lakes worldwide that is meromictic and heliothermal and as such behaves as a natural salt gradient solar pond. Lake Hayward acts as a local groundwater sink, resulting in seasonally variable hypersaline lake water with total dissolved solids (TDS) in the upper layer (mixolimnion) ranging between 56 kg m−3 and 207 kg m−3 and the deeper layer (monimolimnion) from 153 kg m−3 to 211 kg m−3. This is up to six times the salinity of seawater and thus has the highest salinity of all eleven lakes in the Yalgorup National Park lake system. A program of continuously recorded water temperature profiles has shown that salinity stratification initiated by direct rainfall onto the lake’s surface and local runoff into the lake results in the onset of heliothermal conditions within hours of rainfall onset.
The lake alternates between being fully mixed and becoming thermally and chemically stratified several times during the annual cycle, with the longest extended periods of heliothermal behaviour lasting 23 and 22 weeks in the winters of 1992 and 1993 respectively. The objective was to quantify the heat budgets of the cyclical heliothermal behaviour of Lake Hayward.
During the period of temperature profile logging, the maximum recorded temperature of the monimolimnion was 42.6 °C at which time the temperature of the mixolimnion was 29.4 °C.
The heat budget of two closed heliothermal cycles initiated by two rainfall events of 50 mm and 52 mm in 1993 were analysed. The cycles prevailed for 11 and 20 days respectively and the heat budget showed net heat accumulations of 34.2 MJ m−3 and 15.4 MJ m−3, respectively. The corresponding efficiencies of lake heat gain to incident solar energy were 0.17 and 0.18 respectively. Typically, artificial salinity gradient solar ponds (SGSP) have a solar radiation capture efficiencies ranging from 0.10 up to 0.30. Results from Lake Hayward have implications for comparative biogeochemistry and its characteristics should aid in identification of other hitherto unknown heliothermal lakes.
There is a growing interest toward the use of autonomous recording units (ARUs) for acoustic surveying of secretive marsh bird populations. However, there is little information on how ARUs compare to human surveyors or how best to use ARU data that can be collected continuously throughout the day. We used ARUs to conduct 2 acoustic surveys for king (Rallus elegans) and clapper rails (R. crepitans) within a tidal marsh complex along the Pamunkey River, Virginia, USA, during May–July 2015. To determine the effectiveness of an ARU in replacing human personnel, we compared results of callback point‐count surveys with concurrent acoustic recordings and calculated estimates of detection probability for both rail species combined. The success of ARUs at detecting rails that human observers recorded decreased with distance (P ≤ 0.001), such that at <25 m, 90.3% of human‐recorded rails also were detected by the ARU, but at >75 m, only 34.0% of human‐detected rails were detected by the ARU. To determine a subsampling scheme for continuous ARU data that allows for effective surveying of presence and call rates of rails, we used ARUs to conduct 15 continuous 48‐hr passive surveys, generating 720 hr of recordings. We established 5 subsampling periods of 5, 10, 15, 30, and 45 min to evaluate ARU‐based presence and vocalization detections of rails compared with each of the full 60‐min sampling of ARU‐based detection of rails. All subsampling periods resulted in different (P ≤ 0.001) detection rates and unstandardized vocalization rates compared with the hourly sampling period. However, standardized vocalization counts from the 30‐min subsampling period were not different from vocalization counts of the full hourly sampling period. When surveying rail species in estuarine environments, species‐, habitat‐, and ARU‐specific limitations to ARU sampling should be considered when making inferences about abundances and distributions from ARU data.
","language":"English","publisher":"Wiley","doi":"10.1002/wsb.860","usgsCitation":"Stiffler, L.L., Anderson, J.T., and Katzner, T., 2018, Evaluating autonomous acoustic surveying techniques for rails in tidal marshes: Wildlife Society Bulletin, v. 42, no. 1, p. 78-83, https://doi.org/10.1002/wsb.860.","productDescription":"6 p.","startPage":"78","endPage":"83","ipdsId":"IP-088311","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":499995,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/3d927e4f83cc4c23b0ab3649c9fefe3e","text":"External Repository"},{"id":353484,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"42","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-08","publicationStatus":"PW","scienceBaseUri":"5afee6dae4b0da30c1bfbea0","contributors":{"authors":[{"text":"Stiffler, Lydia L.","contributorId":198904,"corporation":false,"usgs":false,"family":"Stiffler","given":"Lydia","email":"","middleInitial":"L.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false},{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":733623,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, James T.","contributorId":28071,"corporation":false,"usgs":false,"family":"Anderson","given":"James","email":"","middleInitial":"T.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":733624,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":733622,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196568,"text":"70196568 - 2018 - Decision support frameworks and tools for conservation","interactions":[],"lastModifiedDate":"2018-04-17T13:58:05","indexId":"70196568","displayToPublicDate":"2018-04-17T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1326,"text":"Conservation Letters","active":true,"publicationSubtype":{"id":10}},"title":"Decision support frameworks and tools for conservation","docAbstract":"The practice of conservation occurs within complex socioecological systems fraught with challenges that require transparent, defensible, and often socially engaged project planning and management. Planning and decision support frameworks are designed to help conservation practitioners increase planning rigor, project accountability, stakeholder participation, transparency in decisions, and learning. We describe and contrast five common frameworks within the context of six fundamental questions (why, who, what, where, when, how) at each of three planning stages of adaptive management (project scoping, operational planning, learning). We demonstrate that decision support frameworks provide varied and extensive tools for conservation planning and management. However, using any framework in isolation risks diminishing potential benefits since no one framework covers the full spectrum of potential conservation planning and decision challenges. We describe two case studies that have effectively deployed tools from across conservation frameworks to improve conservation actions and outcomes. Attention to the critical questions for conservation project planning should allow practitioners to operate within any framework and adapt tools to suit their specific management context. We call on conservation researchers and practitioners to regularly use decision support tools as standard practice for framing both practice and research.
","language":"English","publisher":"Wiley","doi":"10.1111/conl.12385","usgsCitation":"Schwartz, M.W., Cook, C.N., Pressey, R.L., Pullin, A.S., Runge, M.C., Salafsky, N., Sutherland, W.J., and Williamson, M.A., 2018, Decision support frameworks and tools for conservation: Conservation Letters, v. 11, no. 2, p. 1-12, https://doi.org/10.1111/conl.12385.","productDescription":"e12385; 12 p.","startPage":"1","endPage":"12","ipdsId":"IP-070227","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":468824,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/conl.12385","text":"Publisher Index Page"},{"id":353490,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-23","publicationStatus":"PW","scienceBaseUri":"5afee6dae4b0da30c1bfbe9e","contributors":{"authors":[{"text":"Schwartz, Mark W.","contributorId":145938,"corporation":false,"usgs":false,"family":"Schwartz","given":"Mark","email":"","middleInitial":"W.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":733627,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cook, Carly N.","contributorId":204315,"corporation":false,"usgs":false,"family":"Cook","given":"Carly","email":"","middleInitial":"N.","affiliations":[{"id":36914,"text":"School of Biological Sciences, Monash University, Clayton, Victoria 3800, Australia","active":true,"usgs":false}],"preferred":false,"id":733628,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pressey, Robert L.","contributorId":204316,"corporation":false,"usgs":false,"family":"Pressey","given":"Robert","email":"","middleInitial":"L.","affiliations":[{"id":36915,"text":"Australian Research Council Centre of Excellence for Coral Reef Studies, James Cook University, Townsville, Queensland, Australia","active":true,"usgs":false}],"preferred":false,"id":733629,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pullin, Andrew S.","contributorId":204317,"corporation":false,"usgs":false,"family":"Pullin","given":"Andrew","email":"","middleInitial":"S.","affiliations":[{"id":36916,"text":"Centre for Evidence-Based Conservation, Bangor University, Bangor, Gwynedd, LL57 2UW, UK","active":true,"usgs":false}],"preferred":false,"id":733630,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":733626,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Salafsky, Nick","contributorId":204318,"corporation":false,"usgs":false,"family":"Salafsky","given":"Nick","email":"","affiliations":[{"id":36917,"text":"Foundations of Success, Bethesda, MD 20816, USA","active":true,"usgs":false}],"preferred":false,"id":733631,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sutherland, William J.","contributorId":204319,"corporation":false,"usgs":false,"family":"Sutherland","given":"William","email":"","middleInitial":"J.","affiliations":[{"id":36918,"text":"Conservation Science Group, Department of Zoology, University of Cambridge, Cambridge CB2 3QZ, UK","active":true,"usgs":false}],"preferred":false,"id":733632,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Williamson, Matthew A.","contributorId":201232,"corporation":false,"usgs":false,"family":"Williamson","given":"Matthew","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":733633,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70196569,"text":"70196569 - 2018 - Thinning, tree-growth, and resistance to multi-year drought in a mixed-conifer forest of northern California","interactions":[],"lastModifiedDate":"2018-04-17T13:56:00","indexId":"70196569","displayToPublicDate":"2018-04-17T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Thinning, tree-growth, and resistance to multi-year drought in a mixed-conifer forest of northern California","docAbstract":"Drought is an important stressor in forest ecosystems that can influence tree vigor and survival. In the U.S., forest managers use two primary management techniques to promote resistance and resilience to drought: prescribed fire and mechanical thinning. Generally applied to reduce fuels and fire hazard, treatments may also reduce competition for resources that may improve tree-growth and reduce mortality during drought. A recent severe and prolonged drought in California provided a natural experiment to investigate tree-growth responses to fuel treatments and climatic stress. We assessed tree-growth from 299 ponderosa pine (Pinus ponderosa) and Douglas-fir (Pseudotsuga menziesii) in treated and untreated stands during severe drought from 2012 to 2015 in the mixed-conifer forests of Whiskeytown National Recreation Area (WNRA) in northern California. The treatment implemented at WNRA removed 34% of live basal area through mechanical thinning with a subsequent pile burning of residual fuels. Tree-growth was positively associated with crown ratio and negatively associated with competition and a 1-year lag of climate water deficit, an index of drought. Douglas-fir generally had higher annual growth than ponderosa pine, although factors affecting growth were the same for both species. Drought resistance, expressed as the ratio between mean growth during drought and mean growth pre-drought, was higher in treated stands compared to untreated stands during both years of severe drought (2014 and 2015) for ponderosa pine but only one year (2014) for Douglas-fir. Thinning improved drought resistance, but tree size, competition and species influenced this response. On-going thinning treatments focused on fuels and fire hazard reduction are likely to be effective at promoting growth and greater drought resistance in dry mixed-conifer forests. Given the likelihood of future droughts, land managers may choose to implement similar treatments to reduce potential impacts.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2018.03.043","usgsCitation":"Vernon, M.J., Sherriff, R.L., van Mantgem, P., and Kane, J.M., 2018, Thinning, tree-growth, and resistance to multi-year drought in a mixed-conifer forest of northern California: Forest Ecology and Management, v. 422, p. 190-198, https://doi.org/10.1016/j.foreco.2018.03.043.","productDescription":"9 p.","startPage":"190","endPage":"198","ipdsId":"IP-093097","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":468823,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2018.03.043","text":"Publisher Index Page"},{"id":353489,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"422","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6dae4b0da30c1bfbe9c","contributors":{"authors":[{"text":"Vernon, Michael J.","contributorId":204321,"corporation":false,"usgs":false,"family":"Vernon","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":7067,"text":"Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":733635,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sherriff, Rosemary L.","contributorId":204199,"corporation":false,"usgs":false,"family":"Sherriff","given":"Rosemary","email":"","middleInitial":"L.","affiliations":[{"id":7067,"text":"Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":733636,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Mantgem, Phillip J. 0000-0002-3068-9422","orcid":"https://orcid.org/0000-0002-3068-9422","contributorId":204320,"corporation":false,"usgs":true,"family":"van Mantgem","given":"Phillip J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":733634,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kane, Jeffrey M.","contributorId":181978,"corporation":false,"usgs":false,"family":"Kane","given":"Jeffrey","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":733637,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70195863,"text":"ds1080 - 2018 - Compilation of new and previously published geochemical and modal data for Mesoproterozoic igneous rocks of the St. Francois Mountains, southeast Missouri","interactions":[],"lastModifiedDate":"2018-04-17T10:57:08","indexId":"ds1080","displayToPublicDate":"2018-04-16T13:50:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1080","title":"Compilation of new and previously published geochemical and modal data for Mesoproterozoic igneous rocks of the St. Francois Mountains, southeast Missouri","docAbstract":"The purpose of this report is to present recently acquired as well as previously published geochemical and modal petrographic data for igneous rocks in the St. Francois Mountains, southeast Missouri, as part of an ongoing effort to understand the regional geology and ore deposits of the Mesoproterozoic basement rocks of southeast Missouri, USA. The report includes geochemical data that is (1) newly acquired by the U.S. Geological Survey and (2) compiled from numerous sources published during the last fifty-five years. These data are required for ongoing petrogenetic investigations of these rocks. Voluminous Mesoproterozoic igneous rocks in the St. Francois Mountains of southeast Missouri constitute the basement buried beneath Paleozoic sedimentary rock that is over 600 meters thick in places. The Mesoproterozoic rocks of southeast Missouri represent a significant component of approximately 1.4 billion-year-old (Ga) igneous rocks that crop out extensively in North America along the southeast margin of Laurentia and subsequent researchers suggested that iron oxide-copper deposits in the St. Francois Mountains are genetically associated with ca. 1.4 Ga magmatism in this region. The geochemical and modal data sets described herein were compiled to support investigations concerning the tectonic setting and petrologic processes responsible for the associated magmatism.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1080","usgsCitation":"du Bray, E.A. Day, W.C., and Meighan, C.J., 2018,Compilation of new and previously published geochemical and modal data for Mesoproterozoic igneous rocks of the St. Francois Mountains, southeast Missouri: U.S. Geological Survey Data Series 1080, 10 p., https://doi.org/10.3133/ds1080.","productDescription":"Report: iv, 10 p.; Appendixes; Data Release; Read Me","onlineOnly":"Y","ipdsId":"IP-090393","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":353360,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F79W0DSN","text":"USGS data release","linkHelpText":"Data release supporting compilation of new and previously published geochemical and modal data for Mesoproterozoic igneous rocks of the St. Francois Mountains, southeast Missouri"},{"id":353322,"rank":8,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/1080/ds1080_ReadMe.txt","text":"Read Me","size":"8.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"DS 1080 Read Me"},{"id":353316,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1080/ds1080.pdf","text":"Report","size":"48.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1080"},{"id":353317,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1080/ds1080_appendix1_MO15_17_Field_Notes.txt","text":"Appendix 1. Field Notes","size":"16.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"DS 1080 Field Notes, Text File","linkHelpText":"Definition and characterization of data fields for field notes for igneous rocks of the St. Francois Mountains, southeast Missouri collected between 2015 and 2017 (text file)"},{"id":353320,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1080/ds1080_appendix2_SE_MO_ChemData_AlteredMineralized.txt","text":"Appendix 2. Chemical Data, Altered Mineralized","size":"348 kB","linkFileType":{"id":2,"text":"txt"},"description":"DS 1080 Chemical Data, Altered Mineralized","linkHelpText":"Definition and characterization of data fields for geochemical and modal data for igneous rocks in the St. Francois Mountains, southeast Missouri (text file)"},{"id":353315,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1080/coverthb.jpg"},{"id":353321,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1080/ds1080_appendix2_SE_MO_ChemData_FreshUnaltered.txt","text":"Appendix 2. Chemical Data, Fresh Unaltered","size":"256 kB","linkFileType":{"id":2,"text":"txt"},"description":"DS 1080 Chemical Data, Fresh Unaltered","linkHelpText":"Definition and characterization of data fields for geochemical and modal data for igneous rocks in the St. Francois Mountains, southeast Missouri (text file)"},{"id":353319,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1080/ds1080_appendix2_SE_MO_ChemData.xlsx","text":"Appendix 2. Chemical Data","size":"692 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 1080 Chemical Data","linkHelpText":"Definition and characterization of data fields for geochemical and modal data for igneous rocks in the St. Francois Mountains, southeast Missouri (Excel file)"},{"id":353318,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1080/ds1080_appendix1_MO15_17_Field_Notes.xlsx","text":"Appendix 1. Field Notes","size":"28.0 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 1080 Field Notes, Excel File","linkHelpText":"Definition and characterization of data fields for field notes for igneous rocks of the St. Francois Mountains, southeast Missouri collected between 2015 and 2017 (Excel file)"}],"country":"United States","state":"Missouri","otherGeospatial":"St. Francois Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.603759765625,\n 36.848856608486905\n ],\n [\n -89.98901367187499,\n 36.848856608486905\n ],\n [\n -89.98901367187499,\n 38.496593518947584\n ],\n [\n -92.603759765625,\n 38.496593518947584\n ],\n [\n -92.603759765625,\n 36.848856608486905\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geology, Geophysics and Geochemistry Science Center
U.S. Geological Survey
Box 25046, MS-973
Denver, CO 80225-0046
This study examined titanium distribution in the Atlantic Coastal Plain of the southeastern United States; the titanium is found in heavy-mineral sands that include the minerals ilmenite (Fe2+TiO3), rutile (TiO2), or leucoxene (an alteration product of ilmenite). Deposits of heavy-mineral sands in ancient and modern coastal plains are a significant feedstock source for the titanium dioxide pigments industry. Currently, two heavy-mineral sands mining and processing operations are active in the southeast United States producing concentrates of ilmenite-leucoxene, rutile, and zircon. The results of this study indicate the potential for similar deposits in many areas of the Atlantic Coastal Plain.
This study used the titanium analyses of 3,457 stream sediment samples that were analyzed as part of the U.S. Geological Survey’s National Geochemical Survey program. This data set was analyzed by an integrated spatial modeling technique known as Bayesian hierarchical modeling to map the regional-scale, spatial distribution of titanium concentrations. In particular, clusters of anomalous concentrations of titanium occur: (1) along the Fall Zone, from Virginia to Alabama, where metamorphic and igneous rocks of the Piedmont region contact younger sediments of the Coastal Plain; (2) a paleovalley near the South Carolina and North Carolina border; (3) the upper and middle Atlantic Coastal Plain of North Carolina; (4) the majority of the Atlantic Coastal Plain of Virginia; and (5) barrier islands and stretches of the modern shoreline from South Carolina to northeast Florida. The areas mapped by this study could help mining companies delimit areas for exploration.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185045","usgsCitation":"Van Gosen, B.S, and Ellefsen, K.J., 2018, Titanium mineral resources in heavy-mineral sands in the Atlantic coastal plain of the southeastern United States: U.S. Geological Survey Scientific Investigations Report 2018–5045, 32 p., https://doi.org/10.3133/sir20185045.","productDescription":"Report: v, 32 p.; Read Me; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-092420","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":353350,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7J38R16","text":"USGS data release","linkHelpText":"Titanium concentrations in stream sediments from the Atlantic Coastal Plain of the southeastern U.S. (1975-1999)"},{"id":353348,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5045/coverthb.jpg"},{"id":353349,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5045/sir20185045.pdf","text":"Report","size":"19.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5045"},{"id":353352,"rank":4,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sir/2018/5045/sir20185045_Readme.txt","text":"Read Me","size":"8.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2018–5045 Read Me"}],"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 -88.3552303599749,\n 29.6305\n ],\n [\n -76.0284,\n 29.6305\n ],\n [\n -76.0284,\n 38.4013255312409\n ],\n [\n -88.3552303599749,\n 38.4013255312409\n ],\n [\n -88.3552303599749,\n 29.6305\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geology, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
Box 25046, MS 973
Denver, CO 80225
Major and trace element and radiogenic isotopic characteristics of primitive mafic Pleistocene and Holocene lavas from Newberry Volcano, Oregon, define two groups. The first consists of dry tholeiitic high-alumina olivine basalts that are slightly enriched in highly incompatible elements. The second group consists of calc-alkaline basalts that contained 2–4 wt % H2O prior to eruption and shows strong enrichment in the light rare earth elements, Ba, and Sr, and deficits in Nb, Ta, Hf, and Zr. The tholeiitic basalts reflect 6–11% anhydrous adiabatic decompression melting of spinel peridotite. The calc-alkaline basalts derived from compositionally distinct sources with strong LIL enrichment and relative depletion in HFSE, but with Sr, Nd, Hf, and Pb isotopic composition only slightly distinct from the sources of the tholeiitic magmas. Radiogenic Os correlates with LREE enrichment in the calc-alkaline magmas, which indicates that their source materials include a contribution from a mafic component that was melted in the garnet stability field. The calc-alkaline magmas were derived by melting of peridotite metasomatized by a fluid/melt that originated by melting of a mixture of the sediment plus MORB basalt/mantle in the underlying subducting oceanic plate. While the trace element characteristics of the calc-alkaline magmas were determined by the subduction component, their isotopic characteristics were modified during transit through the mantle by interaction with the highly magmatically processed mantle wedge beneath Newberry Volcano that, without the slab component, serves as the source of the tholeiitic magmas.
Healthy streams and the fish and other organisms that live in them contribute to our quality of life. Extensive modification of the landscape in the Midwestern United States, however, has profoundly affected the condition of streams. Row crops and pavement have replaced grasslands and woodlands, streams have been straightened, and wetlands and fields have been drained. Runoff from agricultural and urban land brings sediment and chemicals to streams. What is the chemical, physical, and biological condition of Midwestern streams? Which physical and chemical stressors are adversely affecting biological communities, what are their origins, and how might we lessen or avoid their adverse effects?
In 2013, the U.S. Geological Survey (USGS) conducted the Midwest Stream Quality Assessment to evaluate how human activities affect the biological condition of Midwestern streams. In collaboration with the U.S. Environmental Protection Agency National Rivers and Streams Assessment, the USGS sampled 100 streams, chosen to be representative of the different types of watersheds in the region. Biological condition was evaluated based on the number and diversity of fish, algae, and invertebrates in the streams. Changes to the physical habitat and chemical characteristics of the streams—“stressors”—were assessed, and their relation to landscape factors and biological condition was explored by using mathematical models. The data and models help us to better understand how the human activities on the landscape are affecting streams in the region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173087","usgsCitation":"Van Metre, P.C., Mahler, B.J., Carlisle, Daren, and Coles, James, 2018, The Midwest Stream Quality Assessment—Influences of human activities on streams: U.S. Geological Survey Fact Sheet 2017–3087, 6 p., https://doi.org/10.3133/fs20173087.","productDescription":"6 p.","onlineOnly":"N","ipdsId":"IP-087878","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":350638,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3087/coverthb2.jpg"},{"id":350639,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3087/fs20173087.pdf","text":"Report","size":"2.53 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017–3087"},{"id":350640,"rank":3,"type":{"id":18,"text":"Project Site"},"url":"https://water.usgs.gov/nawqa/","text":"National Water-Quality Assessment (NAWQA) Project"}],"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 -98.525390625,\n 36.756490329505176\n ],\n [\n -81.93603515625,\n 36.756490329505176\n ],\n [\n -81.93603515625,\n 45.166547157856016\n ],\n [\n -98.525390625,\n 45.166547157856016\n ],\n [\n -98.525390625,\n 36.756490329505176\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"National Water-Quality Assessment (NAWQA) Project
U.S. Geological Survey
413 National Center
12201 Sunrise Valley Drive
Reston, Virginia 20192
Beginning in 2014, the U.S. Geological Survey, in collaboration with Bloom Biological, Inc., began telemetry research on golden eagles (Aquila chrysaetos) captured in the San Diego, Orange, and western Riverside Counties of southern California. This work was supported by the San Diego Association of Governments, California Department of Fish and Wildlife, the U.S. Fish and Wildlife Service, the Bureau of Land Management, and the U.S. Geological Survey. Since 2014, we have tracked more than 40 eagles, although this report focuses only on San Diego County eagles.
An important objective of this research is to develop habitat selection models for golden eagles. Here we provide predictions of population-level habitat selection for golden eagles in San Diego County based on environmental covariates related to land use and terrain.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181067","collaboration":"Prepared in cooperation with San Diego Association of Governments, U.S. Fish and Wildlife Service, Bureau of Land Management, California Department of Fish and Wildlife","usgsCitation":"Tracey, J.A., Madden, M.C., Bloom, P.H., Katzner, T.E., and Fisher, R.N., 2018, Golden eagle (Aquila chrysaetos) habitat selection as a function of land use and terrain, San Diego County, California: U.S. Geological Survey Open-File Report 2018–1067, 13 p., https://doi.org/10.3133/ofr20181067.","productDescription":"Report: iv, 13 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-096732","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":353465,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OZVGEG","text":"USGS data release","description":"USGS Data 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Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive
Sacramento, California 95819
After nearly a century of producing power, two large hydroelectric dams on the Elwha River in Washington State were removed during 2011 to 2014 to restore the river ecosystem and recover imperiled salmon populations. Roughly two-thirds of the 21 million cubic meters of sediment—enough to fill nearly 2 million dump trucks—contained behind the dams was released downstream, which restored natural processes and initiated important changes to the river, estuarine, and marine ecosystems. A multidisciplinary team of scientists from the Lower Elwha Klallam Tribe, academia, non-governmental organizations, Federal and state agencies, and the U.S. Geological Survey collected key data before, during, and after dam removal to understand the outcomes of this historic project on the Elwha River ecosystem.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183025","usgsCitation":"Duda, J.J., Beirne, M.M., Warrick, J.A., and Magirl, C.S., 2018, Science partnership between U.S. Geological Survey and the Lower Elwha Klallam Tribe—Understanding the Elwha River Dam Removal Project: U.S. Geological Survey Fact Sheet 2018–3025, 4 p., https://doi.org/10.3133/fs20183025.","productDescription":"4 p.","ipdsId":"IP-095968","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":353441,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3025/fs20183025.pdf","text":"Report","size":"1.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018-3025"},{"id":353440,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3025/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Elwha River Dam ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.58434677124025,\n 48.13504826529439\n ],\n [\n -123.53628158569335,\n 48.13504826529439\n ],\n [\n -123.53628158569335,\n 48.16036041905986\n ],\n [\n -123.58434677124025,\n 48.16036041905986\n ],\n [\n -123.58434677124025,\n 48.13504826529439\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Regional Executive
U.S. Geological Survey Northwest Area
909 First Ave., Suite 800, Seattle, WA 98104
nwa_dropbox@usgs.gov/northwest
Biodegradation of contaminants can increase the temperature in the subsurface due to heat generated from exothermic reactions, making temperature observations a potentially low-cost approach for determining microbial activity. For this technique to gain more widespread acceptance, it is necessary to better understand all the factors affecting the measured temperatures. Biodegradation has been occurring at a crude oil-contaminated site near Bemidji, Minnesota for 39 years, creating a quasi-steady-state plume of contaminants and degradation products. A model of subsurface heat generation and transport helps elucidate the contribution of microbial and infrastructure heating to observed temperature increases at this site. We created a steady-state, two-dimensional, heat transport model using previous-published parameter values for physical, chemical and biodegradation properties. Simulated temperature distributions closely match the observed average annual temperatures measured in the contaminated area at the site within less than 0.2 °C in the unsaturated zone and 0.4 °C in the saturated zone. The model results confirm that the observed subsurface heat from microbial activity is due primarily to methane oxidation in the unsaturated zone resulting in a 3.6 °C increase in average annual temperature. Another important source of subsurface heat is from the active, crude-oil pipelines crossing the site. The pipelines impact temperatures for a distance of 200 m and contribute half the heat. Model results show that not accounting for the heat from the pipelines leads to overestimating the degradation rates by a factor of 1.7, demonstrating the importance of identifying and quantifying all heat sources. The model results also highlighted a zone where previously unknown microbial activity is occurring at the site.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jconhyd.2018.03.011","usgsCitation":"Warren, E., and Bekins, B.A., 2018, Relative contributions of microbial and infrastructure heat at a crude oil-contaminated site: Journal of Contaminant Hydrology, v. 211, p. 94-103, https://doi.org/10.1016/j.jconhyd.2018.03.011.","productDescription":"10 p.","startPage":"94","endPage":"103","ipdsId":"IP-091056","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":355636,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","county":"Beltrami County","city":"Bemidji","volume":"211","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e598e4b060350a15d1e2","contributors":{"authors":[{"text":"Warren, Ean 0000-0002-2634-8289 ewarren@usgs.gov","orcid":"https://orcid.org/0000-0002-2634-8289","contributorId":206234,"corporation":false,"usgs":true,"family":"Warren","given":"Ean","email":"ewarren@usgs.gov","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":739851,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bekins, Barbara A. 0000-0002-1411-6018 babekins@usgs.gov","orcid":"https://orcid.org/0000-0002-1411-6018","contributorId":1348,"corporation":false,"usgs":true,"family":"Bekins","given":"Barbara","email":"babekins@usgs.gov","middleInitial":"A.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":739852,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70198045,"text":"70198045 - 2018 - Relative importance of water-quality stressors in predicting fish community responses in midwestern streams","interactions":[],"lastModifiedDate":"2018-07-12T22:49:34","indexId":"70198045","displayToPublicDate":"2018-04-16T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Relative importance of water-quality stressors in predicting fish community responses in midwestern streams","docAbstract":"Fish, habitat, and water chemistry data were collected from 98 streams in the midwestern United States, an area dominated by intense cultivation of row crops, in order to identify important water‐quality stressors to fish communities. We focused on 10 stressors including riparian disturbance, riparian vegetative cover, instream fish cover, streambed sedimentation, streamflow variability, total nitrogen, total phosphorus, minimum dissolved oxygen, pesticides, and bed sediment contaminants. Fish community response variables included a measure of observed/expected taxonomic completeness; species‐specific tolerances to nitrogen, phosphorus, dissolved oxygen, and water temperature; the percent of species classified as macrohabitat generalists; and an index of pesticide toxicity to fish. Multivariate analysis indicated that total nitrogen was the most important stressor, signifying that fish communities were responding to total nitrogen despite relatively high levels common to an agricultural setting. Individually, fish taxonomic completeness decreased with increasing streambed sedimentation, whereas fish community tolerance to total phosphorus increased with increasing streambed sedimentation, riparian disturbance, and total nitrogen. These findings underscore the importance of multiple biological response metrics to better understand the effects of water‐quality stressors on fish communities and highlight the complex relations between total phosphorus and fish communities.
","language":"English","publisher":"American Water Resources Association","doi":"10.1111/1752-1688.12646","usgsCitation":"Meador, M.R., and Frey, J.W., 2018, Relative importance of water-quality stressors in predicting fish community responses in midwestern streams: Journal of the American Water Resources Association, v. 54, no. 3, p. 708-723, https://doi.org/10.1111/1752-1688.12646.","productDescription":"16 p.","startPage":"708","endPage":"723","ipdsId":"IP-072326","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":355614,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Midwest","volume":"54","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-12","publicationStatus":"PW","scienceBaseUri":"5b46e598e4b060350a15d1e4","contributors":{"authors":[{"text":"Meador, Michael R. 0000-0001-5956-3340 mrmeador@usgs.gov","orcid":"https://orcid.org/0000-0001-5956-3340","contributorId":195592,"corporation":false,"usgs":true,"family":"Meador","given":"Michael","email":"mrmeador@usgs.gov","middleInitial":"R.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":false,"id":739756,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Frey, Jeffrey W. 0000-0002-3453-5009 jwfrey@usgs.gov","orcid":"https://orcid.org/0000-0002-3453-5009","contributorId":487,"corporation":false,"usgs":true,"family":"Frey","given":"Jeffrey","email":"jwfrey@usgs.gov","middleInitial":"W.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":739757,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70195023,"text":"sir20185024 - 2018 - Evaluating the potential for near-shore bathymetry on the Majuro Atoll, Republic of the Marshall Islands, using Landsat 8 and WorldView-3 imagery","interactions":[],"lastModifiedDate":"2019-12-30T11:31:34","indexId":"sir20185024","displayToPublicDate":"2018-04-16T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5024","title":"Evaluating the potential for near-shore bathymetry on the Majuro Atoll, Republic of the Marshall Islands, using Landsat 8 and WorldView-3 imagery","docAbstract":"Satellite-derived near-shore bathymetry (SDB) is becoming an increasingly important method for assessing vulnerability to climate change and natural hazards in low-lying atolls of the northern tropical Pacific Ocean. Satellite imagery has become a cost-effective means for mapping near-shore bathymetry because ships cannot collect soundings safely while operating close to the shore. Also, green laser light detection and ranging (lidar) acquisitions are expensive in remote locations. Previous research has demonstrated that spectral band ratio-based techniques, commonly called the natural logarithm approach, may lead to more precise measurements and modeling of bathymetry because of the phenomenon that different substrates at the same depth have approximately equal ratio values. The goal of this research was to apply the band ratio technique to Landsat 8 at-sensor radiance imagery and WorldView-3 atmospherically corrected imagery in the coastal waters surrounding the Majuro Atoll, Republic of the Marshall Islands, to derive near-shore bathymetry that could be incorporated into a seamless topobathymetric digital elevation model of Majuro. Attenuation of light within the water column was characterized by measuring at-sensor radiance and reflectance at different depths and calculating an attenuation coefficient. Bathymetric lidar data, collected by the U.S. Naval Oceanographic Office in 2006, were used to calibrate the SDB results. The bathymetric lidar yielded a strong linear relation with water depths. The Landsat 8-derived SDB estimates derived from the blue/green band ratio exhibited a water attenuation extinction depth of 6 meters with a coefficient of determination R2=0.9324. Estimates derived from the coastal/red band ratio had an R2=0.9597. At the same extinction depth, SDB estimates derived from WorldView-3 imagery exhibited an R2=0.9574. Because highly dynamic coastal shorelines can be affected by erosion, wetland loss, hurricanes, sea-level rise, urban development, and population growth, consistent bathymetric data are needed to better understand sensitive coastal land/water interfaces in areas subject to coastal disasters.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185024","usgsCitation":"Poppenga, S.K., Palaseanu-Lovejoy, M., Gesch, D.B., Danielson, J.J., and Tyler, D.J., 2018, Evaluating the potential for near-shore bathymetry on the Majuro Atoll, Republic of the Marshall Islands, using Landsat 8 and WorldView-3 imagery: U.S. Geological Survey Scientific Investigations Report 2018–5024, 14 p., https://doi.org/10.3133/sir20185024.","productDescription":"Report: vii, 14 p.; Data Release","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-092726","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":353367,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7416VXX","text":"USGS data release","description":"USGS Data Release","linkHelpText":"One Meter Topobathymetric Digital Elevation Model for Majuro Atoll, Republic of the Marshall Islands, 1944 to 2016"},{"id":353365,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5024/coverthb2.jpg"},{"id":353366,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5024/sir20185024.pdf","text":"Report","size":"3.28 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5024"}],"country":"Republic of the Marshall Islands","otherGeospatial":"Majuro Atoll","contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD
Springs at La Soufrière of Guadeloupe have been monitored for nearly four decades since the phreatic eruption and associated seismic activity in 1976. We conceptualize degassing vapor/gas mixtures as square‐wave sources of chloride and heat and apply a new semianalytic solution to demonstrate that chloride and heat pulses with the same timing and duration result in good matches between measured and simulated spring temperatures and concentrations. While the concentration of chloride pulses is variable, the local boiling temperature of 96°C was assigned to all thermal pulses. Because chloride is a conservative tracer, chloride breakthrough is only affected by one‐dimensional advection and dispersion. The thermal tracer is damped and lagged relative to chloride due to conductive heat exchange with the overlying and underlying strata. Joint analysis of temperature and chloride allows estimation of the onset and duration of degassing pulses, refining the chronology of recent magmatic intrusion.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017GL076449","usgsCitation":"Chen, K., Zhan, H., Burns, E.R., Ingebritsen, S.E., and Agrinier, P., 2018, The influence of episodic shallow magma degassing on heat and chemical transport in volcanic hydrothermal systems: Geophysical Research Letters, v. 45, no. 7, p. 3068-3076, https://doi.org/10.1002/2017GL076449.","productDescription":"9 p.","startPage":"3068","endPage":"3076","ipdsId":"IP-092662","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":468825,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017gl076449","text":"Publisher Index Page"},{"id":353470,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"45","issue":"7","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-13","publicationStatus":"PW","scienceBaseUri":"5afee6dbe4b0da30c1bfbeb2","contributors":{"authors":[{"text":"Chen, Kewei 0000-0002-0444-9724","orcid":"https://orcid.org/0000-0002-0444-9724","contributorId":204253,"corporation":false,"usgs":false,"family":"Chen","given":"Kewei","email":"","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":733501,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhan, Hongbin 0000-0003-2060-4904","orcid":"https://orcid.org/0000-0003-2060-4904","contributorId":192156,"corporation":false,"usgs":false,"family":"Zhan","given":"Hongbin","email":"","affiliations":[],"preferred":false,"id":733502,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burns, Erick R. 0000-0002-1747-0506 eburns@usgs.gov","orcid":"https://orcid.org/0000-0002-1747-0506","contributorId":192154,"corporation":false,"usgs":true,"family":"Burns","given":"Erick","email":"eburns@usgs.gov","middleInitial":"R.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":733500,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ingebritsen, Steven E. 0000-0001-6917-9369 seingebr@usgs.gov","orcid":"https://orcid.org/0000-0001-6917-9369","contributorId":818,"corporation":false,"usgs":true,"family":"Ingebritsen","given":"Steven","email":"seingebr@usgs.gov","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":733503,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Agrinier, Pierre","contributorId":204254,"corporation":false,"usgs":false,"family":"Agrinier","given":"Pierre","email":"","affiliations":[{"id":30776,"text":"Institut de Physique du Globe de Paris","active":true,"usgs":false}],"preferred":false,"id":733504,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196557,"text":"70196557 - 2018 - Landscape connectivity for bobcat (Lynx rufus) and lynx (Lynx canadensis) in the Northeastern United States","interactions":[],"lastModifiedDate":"2018-04-16T17:15:30","indexId":"70196557","displayToPublicDate":"2018-04-16T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Landscape connectivity for bobcat (Lynx rufus) and lynx (Lynx canadensis) in the northeastern United States","title":"Landscape connectivity for bobcat (Lynx rufus) and lynx (Lynx canadensis) in the Northeastern United States","docAbstract":"Landscape connectivity is integral to the persistence of metapopulations of wide ranging carnivores and other terrestrial species. The objectives of this research were to investigate the landscape characteristics essential to use of areas by lynx and bobcats in northern New England, map a habitat availability model for each species, and explore connectivity across areas of the region likely to experience future development pressure. A Mahalanobis distance analysis was conducted on location data collected between 2005 and 2010 from 16 bobcats in western Vermont and 31 lynx in northern Maine to determine which variables were most consistent across all locations for each species using three scales based on average 1) local (15 minute) movement, 2) linear distance between daily locations, and 3) female home range size. The bobcat model providing the widest separation between used locations and random study area locations suggests that they cue into landscape features such as edge, availability of cover, and development density at different scales. The lynx model with the widest separation between random and used locations contained five variables including natural habitat, cover, and elevation—all at different scales. Shrub scrub habitat—where lynx’s preferred prey is most abundant—was represented at the daily distance moved scale. Cross validation indicated that outliers had little effect on models for either species. A habitat suitability value was calculated for each 30 m2 pixel across Vermont, New Hampshire, and Maine for each species and used to map connectivity between conserved lands within selected areas across the region. Projections of future landscape change illustrated potential impacts of anthropogenic development on areas lynx and bobcat may use, and indicated where connectivity for bobcats and lynx may be lost. These projections provided a guide for conservation of landscape permeability for lynx, bobcat, and species relying on similar habitats in the region.
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Jennifer","contributorId":204306,"corporation":false,"usgs":false,"family":"Vashon","given":"Jennifer","email":"","affiliations":[],"preferred":false,"id":733602,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Freeman, Mark","contributorId":171650,"corporation":false,"usgs":false,"family":"Freeman","given":"Mark","email":"","affiliations":[],"preferred":false,"id":733603,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Royar, Kim","contributorId":9886,"corporation":false,"usgs":true,"family":"Royar","given":"Kim","affiliations":[],"preferred":false,"id":733604,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kilpatrick, C. William","contributorId":204307,"corporation":false,"usgs":false,"family":"Kilpatrick","given":"C.","email":"","middleInitial":"William","affiliations":[],"preferred":false,"id":733605,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70208022,"text":"70208022 - 2018 - Are prey remains accurate indicators of chick diet? A comparison of diet quantification techniques for Black Oystercatchers","interactions":[],"lastModifiedDate":"2020-01-27T12:38:06","indexId":"70208022","displayToPublicDate":"2018-04-15T06:30:16","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5557,"text":"Wader Study","active":true,"publicationSubtype":{"id":10}},"title":"Are prey remains accurate indicators of chick diet? A comparison of diet quantification techniques for Black Oystercatchers","docAbstract":"The quantification of prey remains is a common method for estimating the diet of a variety of birds. However, these estimates may be subject to biases based on prey body type, nesting habitat, and collection date. To better understand biases and limitations associated with this method, we compared it with two others commonly used to characterize diet: direct observation of parents feeding young and diet reconstruction by stable isotope analysis. In 2013-14, we monitored the diet of 20 Black Oystercatcher broods in south-central Alaska using all three methods, having collected 2126 prey remains, observed 1979 prey items fed to chicks, and obtained stable isotopes values of 39 blood samples from 22 chicks. Direct observations and stable isotope techniques similarly characterized diet composition but these approaches yielded different results from those obtained using prey remains. Soft-bodied prey, such as worms, were not detected in prey remains, and filter-feeders were under-represented. For example, mussels and barnacles, which have flesh that can be removed without having to detach the shell from the substrate, were underestimated using prey remains (mussels: 33% for prey remains vs. 44%, 43% for observations and stable isotopes, respectively; barnacles: 2% vs. 9%, 8%, respectively). On rocky islands, where chicks are confined to a small area around the nest, there were significantly greater quantities of prey remains constituting different diets than on gravel beaches, where chicks leave the nest site within days of hatching. For researchers using prey remains to monitor diet, we suggest that they combine this method with direct observations or stable isotope analysis to understand what prey items may be missed or under-represented.","language":"English","publisher":"International Wader Study Group","doi":"10.18194/ws.00105","usgsCitation":"Robinson, B., Coletti, H., Phillips, L., and Powell, A., 2018, Are prey remains accurate indicators of chick diet? A comparison of diet quantification techniques for Black Oystercatchers: Wader Study, v. 125, no. 1, p. 20-32, https://doi.org/10.18194/ws.00105.","productDescription":"13 p.","startPage":"20","endPage":"32","ipdsId":"IP-069549","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":437945,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7WH2N5Q","text":"USGS data release","linkHelpText":"Black Oystercatcher Nest and Diet Data from Kachemak Bay, Katmai National Park and Preserve, Kenai Fjords National Park, and Prince William Sound"},{"id":371508,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -158.115234375,\n 59.130863097255904\n ],\n [\n -144.140625,\n 59.130863097255904\n ],\n [\n -144.140625,\n 65.94647177615738\n ],\n [\n -158.115234375,\n 65.94647177615738\n ],\n [\n -158.115234375,\n 59.130863097255904\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"125","issue":"1","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Robinson, B.H. 0000-0001-8588-7162","orcid":"https://orcid.org/0000-0001-8588-7162","contributorId":221774,"corporation":false,"usgs":false,"family":"Robinson","given":"B.H.","affiliations":[{"id":36971,"text":"University of Alaska","active":true,"usgs":false}],"preferred":false,"id":780174,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coletti, H.A.","contributorId":221776,"corporation":false,"usgs":false,"family":"Coletti","given":"H.A.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":780175,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Phillips, L.M.","contributorId":221775,"corporation":false,"usgs":false,"family":"Phillips","given":"L.M.","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":780176,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Powell, Abby 0000-0002-9783-134X abby_powell@usgs.gov","orcid":"https://orcid.org/0000-0002-9783-134X","contributorId":176843,"corporation":false,"usgs":true,"family":"Powell","given":"Abby","email":"abby_powell@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":780173,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}