Paleomagnetic and GPS data indicate that Washington and Oregon have rotated clockwise for the past 16 Myr. Late Cenozoic and Quaternary fault geometries, seismicity lineaments, and focal mechanisms provide evidence that this rotation is accommodated by north directed thrusting and right-lateral strike-slip faulting in Washington, and SW to W directed normal faulting and right-lateral strike-slip faulting to the east. Several curvilinear NW to NNW trending high-angle strike-slip faults and seismicity lineaments in Washington and NW Oregon define a geologic pole (117.7°W, 47.9°N) of rotation relative to North America. Many faults and focal mechanisms throughout northwestern U.S. and southwestern British Columbia have orientations consistent with this geologic pole as do GPS surface velocities corrected for elastic Cascadia subduction zone coupling. Large Quaternary normal faults radial to the geologic pole, which appear to accommodate crustal rotation via crustal extension, are widespread and can be found along the Lewis and Clark zone in Montana, within the Centennial fault system north of the Snake River Plain in Idaho and Montana, to the west of the Wasatch Front in Utah, and within the northern Basin and Range in Oregon and Nevada. Distributed strike-slip faults are most prominent in western Washington and Oregon and may serve to transfer slip between faults throughout the northwestern U.S.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2016TC004223","usgsCitation":"Brocher, T.M., Wells, R.E., Lamb, A.P., and Weaver, C.S., 2017, Evidence for distributed clockwise rotation of the crust in the northwestern United States from fault geometries and focal mechanisms: Tectonics, v. 36, no. 5, p. 787-818, https://doi.org/10.1002/2016TC004223.","productDescription":"32 p.","startPage":"787","endPage":"818","ipdsId":"IP-068687","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":469865,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016tc004223","text":"Publisher Index Page"},{"id":340937,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"British Columbia, Oregon, Washington","otherGeospatial":"Vancouver Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125,\n 42\n ],\n [\n -118,\n 42\n ],\n [\n -118,\n 49\n ],\n [\n -125,\n 49\n ],\n [\n -125,\n 42\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-05","publicationStatus":"PW","scienceBaseUri":"591183afe4b0e541a03c1a46","contributors":{"authors":[{"text":"Brocher, Thomas M. 0000-0002-9740-839X brocher@usgs.gov","orcid":"https://orcid.org/0000-0002-9740-839X","contributorId":262,"corporation":false,"usgs":true,"family":"Brocher","given":"Thomas","email":"brocher@usgs.gov","middleInitial":"M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":694440,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wells, Ray E. 0000-0002-7796-0160 rwells@usgs.gov","orcid":"https://orcid.org/0000-0002-7796-0160","contributorId":141072,"corporation":false,"usgs":true,"family":"Wells","given":"Ray","email":"rwells@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":694441,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lamb, Andrew P. alamb@usgs.gov","contributorId":5720,"corporation":false,"usgs":true,"family":"Lamb","given":"Andrew","email":"alamb@usgs.gov","middleInitial":"P.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":694442,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weaver, Craig S. craig@usgs.gov","contributorId":2690,"corporation":false,"usgs":true,"family":"Weaver","given":"Craig","email":"craig@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":694443,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70187541,"text":"70187541 - 2017 - Unconventional oil and gas spills: Risks, mitigation priorities, and state reporting requirements","interactions":[],"lastModifiedDate":"2017-07-12T16:02:48","indexId":"70187541","displayToPublicDate":"2017-05-08T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Unconventional oil and gas spills: Risks, mitigation priorities, and state reporting requirements","docAbstract":"Rapid growth in unconventional oil and gas (UOG) has produced jobs, revenue, and energy, but also concerns over spills and environmental risks. We assessed spill data from 2005 to 2014 at 31 481 UOG wells in Colorado, New Mexico, North Dakota, and Pennsylvania. We found 2–16% of wells reported a spill each year. Median spill volumes ranged from 0.5 m3 in Pennsylvania to 4.9 m3 in New Mexico; the largest spills exceeded 100 m3. Seventy-five to 94% of spills occurred within the first three years of well life when wells were drilled, completed, and had their largest production volumes. Across all four states, 50% of spills were related to storage and moving fluids via flowlines. Reporting rates varied by state, affecting spill rates and requiring extensive time and effort getting data into a usable format. Enhanced and standardized regulatory requirements for reporting spills could improve the accuracy and speed of analyses to identify and prevent spill risks and mitigate potential environmental damage. Transparency for data sharing and analysis will be increasingly important as UOG development expands. We designed an interactive spills data visualization tool (http://snappartnership.net/groups/hydraulic-fracturing/webapp/spills.html) to illustrate the value of having standardized, public data.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.6b05749","usgsCitation":"Patterson, L.A., Konschnik, K.E., Wiseman, H., Fargione, J., Maloney, K.O., Kiesecker, J.M., Nicot, J., Baruch-Mordo, S., Entrekin, S., Trainor, A., and Saiers, J., 2017, Unconventional oil and gas spills: Risks, mitigation priorities, and state reporting requirements: Environmental Science & Technology, v. 51, no. 5, p. 2563-2573, https://doi.org/10.1021/acs.est.6b05749.","productDescription":"11 p.","startPage":"2563","endPage":"2573","ipdsId":"IP-076744","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":469868,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.6b05749","text":"Publisher Index Page"},{"id":340919,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"5","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-21","publicationStatus":"PW","scienceBaseUri":"591183b0e4b0e541a03c1a4a","contributors":{"authors":[{"text":"Patterson, Lauren A.","contributorId":177289,"corporation":false,"usgs":false,"family":"Patterson","given":"Lauren","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":694403,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Konschnik, Katherine E.","contributorId":191826,"corporation":false,"usgs":false,"family":"Konschnik","given":"Katherine","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":694404,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wiseman, Hannah","contributorId":191827,"corporation":false,"usgs":false,"family":"Wiseman","given":"Hannah","affiliations":[],"preferred":false,"id":694405,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fargione, Joseph","contributorId":191828,"corporation":false,"usgs":false,"family":"Fargione","given":"Joseph","affiliations":[],"preferred":false,"id":694406,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Maloney, Kelly O. 0000-0003-2304-0745 kmaloney@usgs.gov","orcid":"https://orcid.org/0000-0003-2304-0745","contributorId":4636,"corporation":false,"usgs":true,"family":"Maloney","given":"Kelly","email":"kmaloney@usgs.gov","middleInitial":"O.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":694402,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kiesecker, Joseph M.","contributorId":146679,"corporation":false,"usgs":false,"family":"Kiesecker","given":"Joseph","email":"","middleInitial":"M.","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":694407,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nicot, Jean-Philippe","contributorId":175575,"corporation":false,"usgs":false,"family":"Nicot","given":"Jean-Philippe","email":"","affiliations":[],"preferred":false,"id":694408,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Baruch-Mordo, Sharon","contributorId":191830,"corporation":false,"usgs":false,"family":"Baruch-Mordo","given":"Sharon","email":"","affiliations":[],"preferred":false,"id":694409,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Entrekin, Sally","contributorId":147949,"corporation":false,"usgs":false,"family":"Entrekin","given":"Sally","affiliations":[{"id":16964,"text":"University of Central Arkansas","active":true,"usgs":false}],"preferred":false,"id":694410,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Trainor, Anne","contributorId":191831,"corporation":false,"usgs":false,"family":"Trainor","given":"Anne","affiliations":[],"preferred":false,"id":694411,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Saiers, James","contributorId":191832,"corporation":false,"usgs":false,"family":"Saiers","given":"James","affiliations":[],"preferred":false,"id":694412,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70187551,"text":"70187551 - 2017 - Historical analysis of riparian vegetation change in response to shifting management objectives on the Middle Rio Grande","interactions":[],"lastModifiedDate":"2017-05-08T15:44:02","indexId":"70187551","displayToPublicDate":"2017-05-08T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2596,"text":"Land","active":true,"publicationSubtype":{"id":10}},"title":"Historical analysis of riparian vegetation change in response to shifting management objectives on the Middle Rio Grande","docAbstract":"Riparian ecosystems are valuable to the ecological and human communities that depend on them. Over the past century, they have been subject to shifting management practices to maximize human use and ecosystem services, creating a complex relationship between water policy, management, and the natural ecosystem. This has necessitated research on the spatial and temporal dynamics of riparian vegetation change. The San Acacia Reach of the Middle Rio Grande has experienced multiple management and river flow fluctuations, resulting in threats to its riparian and aquatic ecosystems. This research uses remote sensing data, GIS, a review of management decisions, and an assessment of climate to both quantify how riparian vegetation has been altered over time and provide interpretations of the relationships between riparian change and shifting climate and management objectives. This research focused on four management phases from 1935 to 2014, each highlighting different management practices and climate-driven river patterns, providing unique opportunities to observe a direct relationship between river management, climate, and riparian response. Overall, we believe that management practices coupled with reduced surface river-flows with limited overbank flooding influenced the compositional and spatial patterns of vegetation, including possibly increasing non-native vegetation coverage. However, recent restoration efforts have begun to reduce non-native vegetation coverage.
","language":"English","publisher":"MDPI","doi":"10.3390/land6020029","usgsCitation":"Petrakis, R., van Leeuwen, W., Villarreal, M.L., Tashjian, P., Dello Russo, R., and Scott, C.A., 2017, Historical analysis of riparian vegetation change in response to shifting management objectives on the Middle Rio Grande: Land, v. 6, no. 2, p. 1-23, https://doi.org/10.3390/land6020029.","productDescription":"Article 29; 23 p.","startPage":"1","endPage":"23","ipdsId":"IP-079082","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":469864,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/land6020029","text":"Publisher Index Page"},{"id":438351,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7154F84","text":"USGS data release","linkHelpText":"Middle Rio Grande Multitemporal Land Cover Classifications - 1935, 1962, 1987, 1999, and 2014"},{"id":340957,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Middle Rio Grande","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.03979492187499,\n 33.61919376817004\n ],\n [\n -106.75140380859374,\n 33.61919376817004\n ],\n [\n -106.75140380859374,\n 34.27197081112463\n ],\n [\n -107.03979492187499,\n 34.27197081112463\n ],\n [\n -107.03979492187499,\n 33.61919376817004\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-22","publicationStatus":"PW","scienceBaseUri":"591183afe4b0e541a03c1a44","contributors":{"authors":[{"text":"Petrakis, Roy E. 0000-0001-8932-077X rpetrakis@usgs.gov","orcid":"https://orcid.org/0000-0001-8932-077X","contributorId":174623,"corporation":false,"usgs":true,"family":"Petrakis","given":"Roy","email":"rpetrakis@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":694506,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Leeuwen, Willem","contributorId":148978,"corporation":false,"usgs":false,"family":"van Leeuwen","given":"Willem","email":"","affiliations":[],"preferred":false,"id":694507,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":1424,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":694505,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tashjian, Paul","contributorId":191857,"corporation":false,"usgs":false,"family":"Tashjian","given":"Paul","email":"","affiliations":[],"preferred":false,"id":694508,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dello Russo, Regina","contributorId":191858,"corporation":false,"usgs":false,"family":"Dello Russo","given":"Regina","email":"","affiliations":[],"preferred":false,"id":694509,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Scott, Christopher A.","contributorId":31664,"corporation":false,"usgs":true,"family":"Scott","given":"Christopher","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":694510,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70187542,"text":"70187542 - 2017 - Unconventional oil and gas spills: Materials, volumes, and risks to surface waters in four states of the U.S.","interactions":[],"lastModifiedDate":"2018-04-02T16:48:30","indexId":"70187542","displayToPublicDate":"2017-05-08T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Unconventional oil and gas spills: Materials, volumes, and risks to surface waters in four states of the U.S.","docAbstract":"Extraction of oil and gas from unconventional sources, such as shale, has dramatically increased over the past ten years, raising the potential for spills or releases of chemicals, waste materials, and oil and gas. We analyzed spill data associated with unconventional wells from Colorado, New Mexico, North Dakota and Pennsylvania from 2005 to 2014, where we defined unconventional wells as horizontally drilled into an unconventional formation. We identified materials spilled by state and for each material we summarized frequency, volumes and spill rates. We evaluated the environmental risk of spills by calculating distance to the nearest stream and compared these distances to existing setback regulations. Finally, we summarized relative importance to drinking water in watersheds where spills occurred. Across all four states, we identified 21,300 unconventional wells and 6622 reported spills. The number of horizontal well bores increased sharply beginning in the late 2000s; spill rates also increased for all states except PA where the rate initially increased, reached a maximum in 2009 and then decreased. Wastewater, crude oil, drilling waste, and hydraulic fracturing fluid were the materials most often spilled; spilled volumes of these materials largely ranged from 100 to 10,000 L. Across all states, the average distance of spills to a stream was highest in New Mexico (1379 m), followed by Colorado (747 m), North Dakota (598 m) and then Pennsylvania (268 m), and 7.0, 13.3, and 20.4% of spills occurred within existing surface water setback regulations of 30.5, 61.0, and 91.4 m, respectively. Pennsylvania spills occurred in watersheds with a higher relative importance to drinking water than the other three states. Results from this study can inform risk assessments by providing improved input parameters on volume and rates of materials spilled, and guide regulations and the management policy of spills.
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Geological Survey Washington Water Science Center","interactions":[],"lastModifiedDate":"2017-05-09T10:19:44","indexId":"ofr20171044","displayToPublicDate":"2017-05-08T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1044","title":"Quality-assurance plan for water-quality activities in the U.S. Geological Survey Washington Water Science Center","docAbstract":"In accordance with guidelines set forth by the Office of Water Quality in the Water Mission Area of the U.S. Geological Survey, a quality-assurance plan has been created for use by the Washington Water Science Center (WAWSC) in conducting water-quality activities. This qualityassurance plan documents the standards, policies, and procedures used by the WAWSC for activities related to the collection, processing, storage, analysis, and publication of water-quality data. The policies and procedures documented in this quality-assurance plan for water-quality activities complement the quality-assurance plans for surface-water and groundwater activities at the WAWSC.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171044","usgsCitation":"Conn, K.E., Huffman, R.L., and Barton, Cynthia, 2017, Quality-assurance plan for water-quality activities in the U.S. Geological Survey Washington Water Science Center: U.S. Geological Survey Open-File Report 2017–1044, 66 p., https://doi.org/10.3133/ofr20171044.","productDescription":"vi, 66 p.","numberOfPages":"76","onlineOnly":"Y","ipdsId":"IP-083785","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":340969,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1044/ofr20171044.pdf","text":"Report","size":"1.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1044"},{"id":340968,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1044/coverthb.jpg"}],"contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
Concern over declining pollinators has led to multiple conservation initiatives for improving forage for bees in agroecosystems. Using data available through the Pollinator Library (npwrc.usgs.gov/pollinator/), we summarize plant–pollinator interaction data collected from 2012–2015 on lands managed by the U.S. Fish and Wildlife Service and private lands enrolled in U.S. Department of Agriculture conservation programs in eastern North Dakota (ND). Furthermore, we demonstrate how plant–pollinator interaction data from the Pollinator Library and seed cost information can be used to evaluate hypothetical seeding mixes for pollinator habitat enhancements. We summarize records of 314 wild bee and 849 honey bee (Apis mellifera L.) interactions detected on 63 different plant species. The wild bee observations consisted of 46 species, 15 genera, and 5 families. Over 54% of all wild bee observations were represented by three genera―Bombus, Lassioglossum, and Melissodes. The most commonly visited forbs by wild bees were Monarda fistulosa, Sonchus arvensis, and Zizia aurea. The most commonly visited forbs by A. mellifera were Cirsium arvense, Melilotus officinalis, and Medicago sativa. Among all interactions, 13% of A. mellifera and 77% of wild bee observations were made on plants native to ND. Our seed mix evaluation shows that mixes may often need to be tailored to meet the unique needs of wild bees and managed honey bees in agricultural landscapes. Our evaluation also demonstrates the importance of incorporating both biologic and economic information when attempting to design cost-effective seeding mixes for supporting pollinators in a critically important part of the United States.
","language":"English","publisher":"Entomological Society of America","doi":"10.1093/ee/nvx070","usgsCitation":"Otto, C., O’Dell, S., Bryant, R.B., Euliss, N., Bush, R., and Smart, M., 2017, Using publicly available data to quantify plant–pollinator interactions and evaluate conservation seeding mixes in the Northern Great Plains: Environmental Entomology, v. 46, no. 3, p. 565-578, https://doi.org/10.1093/ee/nvx070.","productDescription":"14 p.","startPage":"565","endPage":"578","ipdsId":"IP-081790","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":340909,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"46","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-02","publicationStatus":"PW","scienceBaseUri":"591183b1e4b0e541a03c1a50","contributors":{"authors":[{"text":"Otto, Clint 0000-0002-7582-3525 cotto@usgs.gov","orcid":"https://orcid.org/0000-0002-7582-3525","contributorId":5426,"corporation":false,"usgs":true,"family":"Otto","given":"Clint","email":"cotto@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":694286,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Dell, Samuel sodell@usgs.gov","contributorId":152473,"corporation":false,"usgs":true,"family":"O’Dell","given":"Samuel","email":"sodell@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":694397,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bryant, R. B.","contributorId":191824,"corporation":false,"usgs":false,"family":"Bryant","given":"R.","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":694287,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Euliss, Ned H. Jr.","contributorId":178233,"corporation":false,"usgs":false,"family":"Euliss","given":"Ned H. Jr.","affiliations":[],"preferred":false,"id":694288,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bush, Rachel","contributorId":191796,"corporation":false,"usgs":false,"family":"Bush","given":"Rachel","email":"","affiliations":[],"preferred":false,"id":694289,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smart, Matthew 0000-0003-0711-3035 msmart@usgs.gov","orcid":"https://orcid.org/0000-0003-0711-3035","contributorId":174424,"corporation":false,"usgs":true,"family":"Smart","given":"Matthew","email":"msmart@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":694290,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70187521,"text":"70187521 - 2017 - Large wood and in-stream habitat for juvenile coho salmon and larval lampreys in a Pacific Northwest stream","interactions":[],"lastModifiedDate":"2017-11-22T16:57:10","indexId":"70187521","displayToPublicDate":"2017-05-06T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Large wood and in-stream habitat for juvenile coho salmon and larval lampreys in a Pacific Northwest stream","docAbstract":"The influences of large wood on Pacific salmon are well-studied, but studies of nonsalmonid species such as lampreys are uncommon. To address this need, we evaluated the potential effects of large wood on larval lampreys (Pacific Lamprey, Entosphenus tridentatus; and potentially Western Brook Lamprey Lampetra richardsoni), as well as juvenile Coho Salmon Oncorhynchus kisutch, in a small coastal Oregon stream. Our objectives were to 1) identify in-stream habitat characteristics associated with the presence of larval lampreys and abundance of juvenile Coho Salmon; and 2) evaluate how these characteristics were associated with in-stream wood. To address habitat use, we quantified presence of larval lampreys in 92 pools and abundance of juvenile Coho Salmon in 44 pools during summer low flows. We focused on a study reach where large wood was introduced into the stream between 2008 and 2009. Results indicated that presence of larval lampreys was significantly associated with availability of fine sediment and deeper substrate. The abundance of juvenile Coho Salmon (fish/pool) was strongly associated with pool surface area and to a weaker extent with the proportion of cobble and boulder substrates in pools. Pools with wood, regardless of whether they were formed by wood, had significantly greater coverage of fine sediment, deeper substrate, and greater pool surface area. Taken together, these results suggest that in-stream wood can provide habitat associated with presence of larval lampreys and greater abundance of juvenile Coho Salmon.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/02755947.2017.1313794","usgsCitation":"Gonzalez, R., Dunham, J.B., Lightcap, S.W., and McEnroe, J.R., 2017, Large wood and in-stream habitat for juvenile coho salmon and larval lampreys in a Pacific Northwest stream: North American Journal of Fisheries Management, v. 37, no. 4, p. 683-699, https://doi.org/10.1080/02755947.2017.1313794.","productDescription":"17 p.","startPage":"683","endPage":"699","ipdsId":"IP-085351","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":340874,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","volume":"37","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-02","publicationStatus":"PW","scienceBaseUri":"590ee0b3e4b0e541a03a8492","contributors":{"authors":[{"text":"Gonzalez, Rosalinda","contributorId":174889,"corporation":false,"usgs":false,"family":"Gonzalez","given":"Rosalinda","email":"","affiliations":[],"preferred":false,"id":694305,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":694304,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lightcap, Scott W.","contributorId":139991,"corporation":false,"usgs":false,"family":"Lightcap","given":"Scott","email":"","middleInitial":"W.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":694306,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McEnroe, Jeffery R.","contributorId":139990,"corporation":false,"usgs":false,"family":"McEnroe","given":"Jeffery","email":"","middleInitial":"R.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":694307,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70187326,"text":"ofr20171047 - 2017 - Characterization of peak streamflows and flood inundation at selected areas in North Carolina following Hurricane Matthew, October 2016","interactions":[],"lastModifiedDate":"2017-08-29T15:36:32","indexId":"ofr20171047","displayToPublicDate":"2017-05-05T12:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1047","title":"Characterization of peak streamflows and flood inundation at selected areas in North Carolina following Hurricane Matthew, October 2016","docAbstract":"The passage of Hurricane Matthew through central and eastern North Carolina during October 7–9, 2016, brought heavy rainfall, which resulted in major flooding. More than 15 inches of rain was recorded in some areas. More than 600 roads were closed, including Interstates 95 and 40, and nearly 99,000 structures were affected by floodwaters. Immediately following the flooding, the U.S. Geological Survey documented 267 high-water marks, of which 254 were surveyed. North Carolina Emergency Management documented and surveyed 353 high-water marks. Using a subset of these highwater marks, six flood-inundation maps were created for hard-hit communities. Digital datasets of the inundation areas, study reach boundary, and water-depth rasters are available for download. In addition, peak gage-height data, peak streamflow data, and annual exceedance probabilities (in percent) were determined for 24 U.S. Geological Survey streamgages located near the heavily flooded communities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171047","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Musser, J.W., Watson, K.M., and Gotvald, A.J., 2017, Characterization of peak streamflows and flood inundation at selected areas in North Carolina following Hurricane Matthew, October 2016 (ver. 2.0, August 2017): U.S. Geological Survey Open-File Report 2017–1047, 23 p., https://doi.org/10.3133/ofr20171047.","productDescription":"Report: v, 23 p.; Data Release, Version History","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-085645","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":340658,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75X276T","text":"USGS data release","description":"USGS data release","linkHelpText":"Flood inundation, flood depth, and high-water marks for selected areas in North Carolina from the October 2016 flood"},{"id":340659,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1047/ofr20171047.pdf","text":"Report","size":"4.02 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1047"},{"id":340657,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1047/coverthb3.jpg"},{"id":342197,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2017/1047/versionHist.txt","size":"2.31 MB","linkFileType":{"id":2,"text":"txt"}}],"country":"United States","state":"North Carolina, South Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.75,\n 34\n ],\n [\n -76.75,\n 34\n ],\n [\n -76.75,\n 36.116667\n ],\n [\n -79.75,\n 36.116667\n ],\n [\n -79.75,\n 34\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: October 2016; Version 1.1: June 2017; Version 2.0: August 2017","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
Congress directed the Federal Government to work with States to restore the Nation’s largest estuary.
Chesapeake Bay restoration provides important economic and ecological benefits:
Chesapeake Bay Coordinator
MD-DE-DC Water Science Center
U.S. Geological Survey
5522 Research Park Drive
Baltimore, MD 21228
Over the last decade, publications on deep-sea corals have tripled. Most attention has been paid to Lophelia pertusa, a globally distributed scleractinian coral that creates critical three-dimensional habitat in the deep ocean. The bacterial community associated with L. pertusa has been previously described by a number of studies at sites in the Mediterranean Sea, Norwegian fjords, off Great Britain, and in the Gulf of Mexico (GOM). However, use of different methodologies prevents direct comparisons in most cases. Our objectives were to address intra-regional variation and to identify any conserved bacterial core community. We collected samples from three distinct colonies of L. pertusa at each of four locations within the western Atlantic: three sites within the GOM and one off the east coast of the United States. Amplicon libraries of 16S rRNA genes were generated using primers targeting the V4–V5 hypervariable region and 454 pyrosequencing. The dominant phylum was Proteobacteria (75–96%). At the family level, 80–95% of each sample was comprised of five groups: Pirellulaceae, Pseudonocardiaceae, Rhodobacteraceae, Sphingomonadaceae, and unclassified Oceanospirillales. Principal coordinate analysis based on weighted UniFrac distances showed a clear distinction between the GOM and Atlantic samples. Interestingly, the replicate samples from each location did not always cluster together, indicating there is not a strong site-specific influence. The core bacterial community, conserved in 100% of the samples, was dominated by the operational taxonomic units of genera Novosphingobium and Pseudonocardia, both known degraders of aromatic hydrocarbons. The sequence of another core member, Propionibacterium, was also found in prior studies of L. pertusa from Norway and Great Britain, suggesting a role as a conserved symbiont. By examining more than 40,000 sequences per sample, we found that GOM samples were dominated by the identified conserved core sequences, whereas open Atlantic samples had a much higher proportion of locally consistent bacteria. Further, predictive functional profiling highlights the potential for the L. pertusa microbiome to contribute to chemoautotrophy, nutrient cycling, and antibiotic production.
","language":"English","publisher":"Frontiers Research Foundation","publisherLocation":"Lausanne","doi":"10.3389/fmicb.2017.00796","usgsCitation":"Kellogg, C.A., Goldsmith, D.B., and Gray, M.A., 2017, Biogeographic comparison of Lophelia-associated bacterial communities in the Western Atlantic reveals conserved core microbiome: Frontiers in Microbiology, v. 8, Article 796: 15 p., https://doi.org/10.3389/fmicb.2017.00796.","productDescription":"Article 796: 15 p.","ipdsId":"IP-083194","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469869,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmicb.2017.00796","text":"Publisher Index Page"},{"id":340853,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89,\n 24\n ],\n [\n -79,\n 24\n ],\n [\n -79,\n 31\n ],\n [\n -89,\n 31\n ],\n [\n -89,\n 24\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-04","publicationStatus":"PW","scienceBaseUri":"590d8f2fe4b0e541a03a834e","contributors":{"authors":[{"text":"Kellogg, Christina A. 0000-0002-6492-9455 ckellogg@usgs.gov","orcid":"https://orcid.org/0000-0002-6492-9455","contributorId":391,"corporation":false,"usgs":true,"family":"Kellogg","given":"Christina","email":"ckellogg@usgs.gov","middleInitial":"A.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":694256,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goldsmith, Dawn B. 0000-0003-0080-5346 dgoldsmith@usgs.gov","orcid":"https://orcid.org/0000-0003-0080-5346","contributorId":191764,"corporation":false,"usgs":true,"family":"Goldsmith","given":"Dawn","email":"dgoldsmith@usgs.gov","middleInitial":"B.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":694257,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gray, Michael A. 0000-0002-3856-5037 mgray@usgs.gov","orcid":"https://orcid.org/0000-0002-3856-5037","contributorId":3532,"corporation":false,"usgs":true,"family":"Gray","given":"Michael","email":"mgray@usgs.gov","middleInitial":"A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":694258,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70189766,"text":"70189766 - 2017 - Conservation challenges and research needs for Pacific lamprey in the Columbia River Basin","interactions":[],"lastModifiedDate":"2018-02-28T14:30:23","indexId":"70189766","displayToPublicDate":"2017-05-05T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1657,"text":"Fisheries","onlineIssn":"1548-8446","printIssn":"0363-2415","active":true,"publicationSubtype":{"id":10}},"title":"Conservation challenges and research needs for Pacific lamprey in the Columbia River Basin","docAbstract":"The Pacific Lamprey Entosphenus tridentatus, an anadromous fish native to the northern Pacific Ocean and bordering freshwater habitats, has recently experienced steep declines in abundance and range contractions along the West Coast of North America. During the early 1990s, Native American tribes recognized the declining numbers of lamprey and championed their importance. In 2012, 26 entities signed a conservation agreement to coordinate and implement restoration and research for Pacific Lamprey. Regional plans have identified numerous threats, monitoring needs, and strategies to conserve and restore Pacific Lamprey during their freshwater life stages. Prime among these are needs to improve lamprey passage, restore freshwater habitats, educate stakeholders, and implement lamprey-specific research and management protocols. Key unknowns include range-wide trends in status, population dynamics, population delineation, limiting factors, and marine influences. We synthesize these key unknowns, with a focus on the freshwater life stages of lamprey in the Columbia River basin.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/03632415.2017.1305857","usgsCitation":"Clemens, B.J., Beamish, R.J., Coates, K.C., Docker, M.F., Dunham, J.B., Gray, A.E., Hess, J.E., Jolley, J.C., Lampman, R., McIlraith, B.J., Moser, M.L., Murauskas, J.G., Noakes, D.L., Schaller, H.A., Schreck, C.B., Starcevich, S.J., Streif, B., van de Wetering, S.J., Wade, J., Weitkamp, L.A., and Wyss, L.A., 2017, Conservation challenges and research needs for Pacific lamprey in the Columbia River Basin: Fisheries, v. 42, no. 5, p. 268-280, https://doi.org/10.1080/03632415.2017.1305857.","productDescription":"14 p. 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Here we used public land records to characterize livestock grazing across Wyoming, USA, and we used Greater Sage-grouse (Centrocercus urophasianus) as a model organism to evaluate responses to livestock management. With annual counts of male Sage-grouse from 743 leks (breeding display sites) during 2004–2014, we modeled population trends in response to grazing level (represented by a relative grazing index) and timing across a gradient in vegetation productivity as measured by the Normalized Vegetation Difference Index (NDVI). We found grazing can have both positive and negative effects on Sage-grouse populations depending on the timing and level of grazing. Sage-grouse populations responded positively to higher grazing levels after peak vegetation productivity, but populations declined when similar grazing levels occurred earlier, likely reflecting the sensitivity of cool-season grasses to grazing during peak growth periods. We also found support for the hypothesis that effects of grazing management vary with local vegetation productivity. These results illustrate the importance of broad-scale analyses by revealing patterns in Sage-grouse population trends that may not be inferred from studies at finer scales, and could inform sustainable grazing management in these ecosystems.
","language":"English","publisher":"Ecological Society of America","publisherLocation":"Washington, D.C.","doi":"10.1002/eap.1512","usgsCitation":"Monroe, A., Aldridge, C.L., Assal, T.J., Veblen, K.E., Pyke, D.A., and Casazza, M.L., 2017, Patterns in Greater Sage-grouse population dynamics correspond with public grazing records at broad scales: Ecological Applications, v. 27, no. 4, p. 1096-1107, https://doi.org/10.1002/eap.1512.","productDescription":"12 p.","startPage":"1096","endPage":"1107","ipdsId":"IP-073681","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":37273,"text":"Advanced Research Computing (ARC)","active":true,"usgs":true}],"links":[{"id":438352,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F70K26RK","text":"USGS data release","linkHelpText":"Evaluating population responses of Greater sage-grouse to 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\"}}]}","volume":"27","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-22","publicationStatus":"PW","scienceBaseUri":"590d8f2fe4b0e541a03a8350","contributors":{"authors":[{"text":"Monroe, Adrian P. 0000-0003-0934-8225 amonroe@usgs.gov","orcid":"https://orcid.org/0000-0003-0934-8225","contributorId":152209,"corporation":false,"usgs":true,"family":"Monroe","given":"Adrian P.","email":"amonroe@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":694230,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":694235,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Assal, Timothy J. 0000-0001-6342-2954 assalt@usgs.gov","orcid":"https://orcid.org/0000-0001-6342-2954","contributorId":2203,"corporation":false,"usgs":true,"family":"Assal","given":"Timothy","email":"assalt@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":694231,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Veblen, Kari E.","contributorId":76872,"corporation":false,"usgs":false,"family":"Veblen","given":"Kari","email":"","middleInitial":"E.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":694232,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pyke, David A. 0000-0002-4578-8335 david_a_pyke@usgs.gov","orcid":"https://orcid.org/0000-0002-4578-8335","contributorId":3118,"corporation":false,"usgs":true,"family":"Pyke","given":"David","email":"david_a_pyke@usgs.gov","middleInitial":"A.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":694233,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":694234,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70187494,"text":"70187494 - 2017 - Using strain rates to forecast seismic hazards","interactions":[],"lastModifiedDate":"2017-05-05T11:33:06","indexId":"70187494","displayToPublicDate":"2017-05-05T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3879,"text":"Eos, Earth and Space Science News","active":true,"publicationSubtype":{"id":10}},"title":"Using strain rates to forecast seismic hazards","docAbstract":"One essential component in forecasting seismic hazards is observing the gradual accumulation of tectonic strain accumulation along faults before this strain is suddenly released as earthquakes. Typically, seismic hazard models are based on geologic estimates of slip rates along faults and historical records of seismic activity, neither of which records actively accumulating strain. But this strain can be estimated by geodesy: the precise measurement of tiny position changes of Earth’s surface, obtained from GPS, interferometric synthetic aperture radar (InSAR), or a variety of other instruments.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1029/2017EO067343","usgsCitation":"Evans, E., 2017, Using strain rates to forecast seismic hazards: Eos, Earth and Space Science News, v. 98, HTML Document, https://doi.org/10.1029/2017EO067343.","productDescription":"HTML Document","ipdsId":"IP-080754","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":469870,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2017eo067343","text":"Publisher Index Page"},{"id":340856,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"98","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"590d8f30e4b0e541a03a8354","contributors":{"authors":[{"text":"Evans, Eileen 0000-0002-7290-5269 eevans@usgs.gov","orcid":"https://orcid.org/0000-0002-7290-5269","contributorId":167021,"corporation":false,"usgs":true,"family":"Evans","given":"Eileen","email":"eevans@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":694186,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70187495,"text":"70187495 - 2017 - Oil and gas development influences big-game hunting in Wyoming","interactions":[],"lastModifiedDate":"2017-05-05T11:05:27","indexId":"70187495","displayToPublicDate":"2017-05-05T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Oil and gas development influences big-game hunting in Wyoming","docAbstract":"Development from extracting oil and gas resources can have unintended effects on multiple ecosystem functions, with cascading effects on wildlife, ecosystem services, and local economies. Big-game hunting opportunities may be closely related to these effects, but empirical analyses of impacts of energy development on hunting are limited. We examined the influence of oil and gas development density on harvest efficiency, or harvest per unit of hunter effort, within all hunt areas in Wyoming, USA, from 2008 to 2014 for 3 big-game species: elk (Cervus canadensis), mule deer (Odocoileus hemionus), and pronghorn (Antilocapra americana). Using harvest/hunter day as the response variable, we compared linear mixed-effects models for each species that included total well density (i.e., all wells constructed up to the year of record), active well density (i.e., only those wells currently producing oil or gas in that year), or neither as a predictor variable. We used well densities as indicators of development in the absence of data specifying the locations of other oil and gas infrastructure (e.g., roads, well pads). Models also accounted for the fixed effects of road density, hunter density, proportion of the area that is public land with unrestricted hunter access, proportion of the area that is forested, year of observation, and random effects of variation among hunt areas nested within associated game herd units. Presence of oil and gas wells had a positive influence on harvest efficiency for elk and mule deer. Although there was no overall effect to pronghorn, there was a negative influence of wells on juvenile pronghorn harvest efficiency. Changes in harvest efficiency due to expanding oil and gas development could alter the time spent hunting by hunters and their chances of harvesting an animal. This could have subsequent impacts on hunter satisfaction, game populations, and economic revenue generated from recreational hunters.
","language":"English","publisher":"The Wildlife Society","publisherLocation":"Hoboken, NJ","doi":"10.1002/jwmg.21205","usgsCitation":"Dorning, M., Garman, S.L., Diffendorfer, J., Semmens, D.J., Hawbaker, T., and Bagstad, K.J., 2017, Oil and gas development influences big-game hunting in Wyoming: Journal of Wildlife Management, v. 81, no. 3, p. 379-392, https://doi.org/10.1002/jwmg.21205.","productDescription":"14 p.","startPage":"379","endPage":"392","ipdsId":"IP-075405","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":340855,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"81","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-18","publicationStatus":"PW","scienceBaseUri":"590d8f30e4b0e541a03a8352","contributors":{"authors":[{"text":"Dorning, Monica 0000-0002-7576-1256 mdorning@usgs.gov","orcid":"https://orcid.org/0000-0002-7576-1256","contributorId":191772,"corporation":false,"usgs":true,"family":"Dorning","given":"Monica","email":"mdorning@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":694187,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garman, Steven L. 0000-0002-9032-9074 slgarman@usgs.gov","orcid":"https://orcid.org/0000-0002-9032-9074","contributorId":3741,"corporation":false,"usgs":true,"family":"Garman","given":"Steven","email":"slgarman@usgs.gov","middleInitial":"L.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":694188,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":694189,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Semmens, Darius J. 0000-0001-7924-6529 dsemmens@usgs.gov","orcid":"https://orcid.org/0000-0001-7924-6529","contributorId":1714,"corporation":false,"usgs":true,"family":"Semmens","given":"Darius","email":"dsemmens@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":694190,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":568,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":694191,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":694192,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70187523,"text":"70187523 - 2017 - The relationship between female brooding and male nestling provisioning: does climate underlie geographic variation in sex roles?","interactions":[],"lastModifiedDate":"2017-05-08T11:30:44","indexId":"70187523","displayToPublicDate":"2017-05-05T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2190,"text":"Journal of Avian Biology","active":true,"publicationSubtype":{"id":10}},"title":"The relationship between female brooding and male nestling provisioning: does climate underlie geographic variation in sex roles?","docAbstract":"Comparative studies of populations occupying different environments can provide insights into the ecological conditions affecting differences in parental strategies, including the relative contributions of males and females. Male and female parental strategies reflect the interplay between ecological conditions, the contributions of the social mate, and the needs of offspring. Climate is expected to underlie geographic variation in incubation and brooding behavior, and can thereby affect both the absolute and relative contributions of each sex to other aspects of parental care such as offspring provisioning. However, geographic variation in brooding behavior has received much less attention than variation in incubation attentiveness or provisioning rates. We compared parental behavior during the nestling period in populations of orange-crowned warblers Oreothlypis celata near the northern (64°N) and southern (33°N) boundaries of the breeding range. In Alaska, we found that males were responsible for the majority of food delivery whereas the sexes contributed equally to provisioning in California. Higher male provisioning in Alaska appeared to facilitate a higher proportion of time females spent brooding the nestlings. Surprisingly, differences in brooding between populations could not be explained by variation in ambient temperature, which was similar between populations during the nestling period. While these results represent a single population contrast, they suggest additional hypotheses for the ecological correlates and evolutionary drivers of geographic variation in brooding behavior, and the factors that shape the contributions of each sex.
","language":"English","publisher":"Wiley","doi":"10.1111/jav.00890","usgsCitation":"Yoon, J., Sofaer, H., Sillett, T., Morrison, S.A., and Ghalambor, C.K., 2017, The relationship between female brooding and male nestling provisioning: does climate underlie geographic variation in sex roles?: Journal of Avian Biology, v. 48, no. 2, p. 220-228, https://doi.org/10.1111/jav.00890.","productDescription":"9 p. ","startPage":"220","endPage":"228","ipdsId":"IP-070914","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":340920,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"48","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-27","publicationStatus":"PW","scienceBaseUri":"591183b3e4b0e541a03c1a58","contributors":{"authors":[{"text":"Yoon, Jongmin","contributorId":191808,"corporation":false,"usgs":false,"family":"Yoon","given":"Jongmin","email":"","affiliations":[],"preferred":false,"id":694316,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sofaer, Helen 0000-0002-9450-5223 hsofaer@usgs.gov","orcid":"https://orcid.org/0000-0002-9450-5223","contributorId":169118,"corporation":false,"usgs":true,"family":"Sofaer","given":"Helen","email":"hsofaer@usgs.gov","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":false,"id":694315,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sillett, T. Scott","contributorId":80788,"corporation":false,"usgs":false,"family":"Sillett","given":"T. Scott","affiliations":[{"id":7035,"text":"Smithsonian Conservation Biology Institute, National Zoological Park","active":true,"usgs":false}],"preferred":false,"id":694317,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morrison, Scott A.","contributorId":83780,"corporation":false,"usgs":false,"family":"Morrison","given":"Scott","email":"","middleInitial":"A.","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":694318,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ghalambor, Cameron K.","contributorId":93722,"corporation":false,"usgs":false,"family":"Ghalambor","given":"Cameron","email":"","middleInitial":"K.","affiliations":[{"id":6998,"text":"Department of Biology, Colorado State University","active":true,"usgs":false}],"preferred":false,"id":694319,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70182142,"text":"sir20175010 - 2017 - Simulation of groundwater flow in the glacial aquifer system of northeastern Wisconsin with variable model complexity","interactions":[],"lastModifiedDate":"2017-05-04T15:33:55","indexId":"sir20175010","displayToPublicDate":"2017-05-04T12:30:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5010","title":"Simulation of groundwater flow in the glacial aquifer system of northeastern Wisconsin with variable model complexity","docAbstract":"The U.S. Geological Survey, National Water-Quality Assessment seeks to map estimated intrinsic susceptibility of the glacial aquifer system of the conterminous United States. Improved understanding of the hydrogeologic characteristics that explain spatial patterns of intrinsic susceptibility, commonly inferred from estimates of groundwater age distributions, is sought so that methods used for the estimation process are properly equipped. An important step beyond identifying relevant hydrogeologic datasets, such as glacial geology maps, is to evaluate how incorporation of these resources into process-based models using differing levels of detail could affect resulting simulations of groundwater age distributions and, thus, estimates of intrinsic susceptibility.
This report describes the construction and calibration of three groundwater-flow models of northeastern Wisconsin that were developed with differing levels of complexity to provide a framework for subsequent evaluations of the effects of process-based model complexity on estimations of groundwater age distributions for withdrawal wells and streams. Preliminary assessments, which focused on the effects of model complexity on simulated water levels and base flows in the glacial aquifer system, illustrate that simulation of vertical gradients using multiple model layers improves simulated heads more in low-permeability units than in high-permeability units. Moreover, simulation of heterogeneous hydraulic conductivity fields in coarse-grained and some fine-grained glacial materials produced a larger improvement in simulated water levels in the glacial aquifer system compared with simulation of uniform hydraulic conductivity within zones. The relation between base flows and model complexity was less clear; however, the relation generally seemed to follow a similar pattern as water levels. Although increased model complexity resulted in improved calibrations, future application of the models using simulated particle tracking is anticipated to evaluate if these model design considerations are similarly important for understanding the primary modeling objective - to simulate reasonable groundwater age distributions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175010","usgsCitation":"Juckem, P.F., Clark, B.R., and Feinstein, D.T., 2017, Simulation of groundwater flow in the glacial aquifer system of northeastern Wisconsin with variable model complexity: U.S. Geological Survey Scientific Investigations Report 2017–5010, 52 p., https://doi.org/10.3133/sir20175010.","productDescription":"viii, 52 p.","numberOfPages":"64","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-077195","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":336160,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5010/coverthb.jpg"},{"id":336162,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/sir2017-5010.xml","text":"USGS data release","description":"USGS data 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\"}}]}","publicComments":"National Water-Quality Assessment","contact":"Director, Wisconsin Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562
This assessment was conducted to fulfill the requirements of section 712 of the Energy Independence and Security Act of 2007 and to improve understanding of factors influencing carbon balance in ecosystems of Hawai‘i. Ecosystem carbon storage, carbon fluxes, and carbon balance were examined for major terrestrial ecosystems on the seven main Hawaiian islands in two time periods: baseline (from 2007 through 2012) and future (projections from 2012 through 2061). The assessment incorporated observed data, remote sensing, statistical methods, and simulation models. The national assessment has been completed for the conterminous United States, using methodology described in SIR 2010-5233, with results provided in three regional reports (PP 1804, PP 1797, and PP 1897), and for Alaska, with results provided in PP 1826.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1834","usgsCitation":"Selmants, P.C., Giardina, C.P., Jacobi, J.D., and Zhu, Zhiliang, eds., 2017, Baseline and projected future carbon storage and carbon fluxes in ecosystems of Hawai‘i: U.S. Geological Survey Professional Paper 1834, 134 p., https://doi.org/10.3133/pp1834.","productDescription":"vii, 134 p.","numberOfPages":"146","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-077242","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"links":[{"id":340802,"rank":18,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/pp1787","text":"Professional Paper 1787","linkHelpText":"- Baseline and projected future carbon storage and greenhouse-gas fluxes in the Great Plains Region of the United States"},{"id":340799,"rank":15,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/pp1826","text":"Professional Paper 1826","linkHelpText":"- Baseline and projected future carbon storage and greenhouse-gas fluxes in ecosystems of Alaska"},{"id":340797,"rank":13,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1834/a/pp1834_chapter8.pdf","text":"Chapter 8. Projected Future Carbon Storage and Carbon Fluxes in Terrestrial Ecosystems of Hawai‘i From Changes in Climate, Land Use, and Disturbance","size":"4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1826","linkHelpText":"- By Benjamin M. Sleeter, Jinxun Liu, Colin J. Daniel, Todd J. Hawbaker, Tamara S. Wilson, Lucas B. Fortini, James D. Jacobi, Paul C. Selmants, Christian P. Giardina, Creighton M. Litton, and R. Flint Hughes"},{"id":340796,"rank":12,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1834/a/pp1834_chapter7.pdf","text":"Chapter 7. Baseline and Projected Future Aquatic Carbon Fluxes to Nearshore Waters in Hawai‘i","size":"2.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1826","linkHelpText":"- By Richard A. MacKenzie, Ayron M. Strauch, Tracy N. Wiegner, Steven L. Colbert, Edward G. Stets, and Robert G. Streigl"},{"id":340794,"rank":10,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1834/a/pp1834_chapter5.pdf","text":"Chapter 5. Wildland Fires and Greenhouse Gas Emissions in Hawai‘i","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1826","linkHelpText":"- By Todd J. Hawbaker, Clay Trauernicht, Stephen M. Howard, Creighton M. Litton, Christian P. Giardina, James D. Jacobi, Lucas B. Fortini, R. Flint Hughes, Paul C. Selmants, and Zhiliang Zhu"},{"id":340791,"rank":7,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1834/a/pp1834_chapter2.pdf","text":"Chapter 2. Baseline Land Cover","size":"3.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1826","linkHelpText":"- By James D. Jacobi, Jonathan P. Price, Lucas B. Fortini, Samuel M. Gon III, and Paul Berkowitz"},{"id":340821,"rank":5,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1834/a/pp1834_executive_summary.pdf","text":"Executive Summary","size":"250 KB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1826","linkHelpText":"- By Paul C. Selmants, Christian P. Giardina, James D. Jacobi, Lucas B. Fortini, R. Flint Hughes, Todd J. Hawbaker, Richard A. MacKenzie, Benjamin M. Sleeter, and Zhiliang Zhu"},{"id":340803,"rank":19,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/sir20105233","text":"Scientific Investigations Report 2010-5233","linkHelpText":"- A method for assessing carbon stocks, carbon sequestration, and greenhouse-gas fluxes in ecosystems of the United States under present conditions and future scenarios"},{"id":340798,"rank":14,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1834/a/pp1834_chapter9.pdf","text":"Chapter 9. Hawai‘i Carbon Balance","size":"600 KB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1826","linkHelpText":"- By Paul C. Selmants, Christian P. Giardina, Benjamin M.Sleeter, Jinxun Liu, and Zhiliang Zhu"},{"id":340786,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1834/a/pp1834.pdf","text":"Report","size":"23 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1826"},{"id":340787,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1834/coverthb.jpg"},{"id":340788,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/pp/1834/a/pp1834_cover.pdf","text":"Covers","size":"5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1826"},{"id":340789,"rank":4,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/pp/1834/a/pp1834_front.pdf","text":"Front Matter","size":"241 KB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1826"},{"id":340790,"rank":6,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1834/a/pp1834_chapter1.pdf","text":"Chapter 1. Scope and Methodology","size":"665 KB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1826","linkHelpText":"- By Christian P. Giardina, Paul C. Selmants, and James D. Jacobi"},{"id":340792,"rank":8,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1834/a/pp1834_chapter3.pdf","text":"Chapter 3. Projecting End-of-Century Shifts in the Spatial Pattern of Plant-Available Water Across Hawai‘i to Assess Implications to Vegetation Shifts","size":"5.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1826","linkHelpText":"- By Lucas B. Fortini, James D. Jacobi, and Jonathan P. Price"},{"id":340793,"rank":9,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1834/a/pp1834_chapter4.pdf","text":"Chapter 4. Influence of Invasive Species on Carbon Storage in Hawai‘i’s Ecosystems","size":"620 KB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1826","linkHelpText":"- By R. Flint Hughes, Gregory P. Asner, Creighton M. Litton, Paul C. Selmants, Todd J. Hawbaker, James D. Jacobi, Christian P. Giardina, and Benjamin M. Sleeter"},{"id":340795,"rank":11,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1834/a/pp1834_chapter6.pdf","text":"Chapter 6. Baseline Carbon Storage and Carbon Fluxes in Terrestrial Ecosystems of Hawai‘i","size":"2.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1826","linkHelpText":"- By Paul C. Selmants, Christian P. Giardina, Sinan Sousan, David E. Knapp, Heather L. Kimball, Todd J. Hawbaker, Alvaro Moreno, Jami Seirer, Steve W. Running, Tomoaki Miura, Rafael Bergstrom, R. Flint Hughes, Creighton M. Litton, and Gregory P. Asner"},{"id":342057,"rank":20,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7DB80B9","text":"Hawaii Land Cover and Habitat Status","linkHelpText":"(Chapter 2)"},{"id":340800,"rank":16,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/pp1804","text":"Professional Paper 1804","linkHelpText":"- Baseline and projected future carbon storage and greenhouse-gas fluxes in ecosystems of the Eastern United States"},{"id":340801,"rank":17,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/pp1797","text":"Professional Paper 1797","linkHelpText":"- Baseline and projected future carbon storage and greenhouse-gas fluxes in ecosystems of the Western United States"}],"country":"United 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\"}}]}","contact":"Land Change Science Program
U.S. Geological Survey
12201 Sunrise Valley Drive
MS 519A National Center
Reston, VA 20192
Infectious hematopoietic necrosis virus (IHNV) is an important pathogen of salmonid fishes. A validated universal reverse transcriptase quantitative PCR (RT-qPCR) assay that can quantify levels of IHNV in fish tissues has been previously reported. In the present study, we adapted the published set of IHNV primers and probe for use in a reverse-transcriptase droplet digital PCR (RT-ddPCR) assay for quantification of the virus in fish tissue samples. The RT-ddPCR and RT-qPCR assays detected 13 phylogenetically diverse IHNV strains, but neither assay produced detectable amplification when RNA from other fish viruses was used. The RT-ddPCR assay had a limit of detection (LOD) equating to 2.2 plaque forming units (PFU)/μl while the LOD for the RT-qPCR was 0.2 PFU/μl. Good agreement (69.4–100%) between assays was observed when used to detect IHNV RNA in cell culture supernatant and tissues from IHNV infected rainbow trout (Oncorhynchus mykiss) and arctic char (Salvelinus alpinus). Estimates of RNA copy number produced by the two assays were significantly correlated but the RT-qPCR consistently produced higher estimates than the RT-ddPCR. The analytical properties of the N gene RT-ddPCR test indicated that this method may be useful to assess IHNV RNA copy number for research and diagnostic purposes. Future work is needed to establish the within and between laboratory diagnostic performance of the RT-ddPCR assay.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jviromet.2017.03.010","usgsCitation":"Jia, P., Purcell, M.K., Pan, G., Wang, J., Kan, S., Liu, Y., Zheng, X., SHi, X., He, J., Yu, L., Hua, Q., Lu, T., Lan, W., Winton, J., Jin, N., and Liu, H., 2017, Analytical validation of a reverse transcriptase droplet digital PCR (RT-ddPCR) for quantitative detection of infectious hematopoietic necrosis virus: Journal of Virological Methods, v. 245, p. 73-80, https://doi.org/10.1016/j.jviromet.2017.03.010.","productDescription":"8 p.","startPage":"73","endPage":"80","ipdsId":"IP-080805","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":340846,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"245","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"590c3dc8e4b0e541a038dd21","contributors":{"authors":[{"text":"Jia, Peng","contributorId":191750,"corporation":false,"usgs":false,"family":"Jia","given":"Peng","email":"","affiliations":[],"preferred":false,"id":694141,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Purcell, Maureen K. 0000-0003-0154-8433 mpurcell@usgs.gov","orcid":"https://orcid.org/0000-0003-0154-8433","contributorId":168475,"corporation":false,"usgs":true,"family":"Purcell","given":"Maureen","email":"mpurcell@usgs.gov","middleInitial":"K.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":694140,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pan, Guang","contributorId":191751,"corporation":false,"usgs":false,"family":"Pan","given":"Guang","email":"","affiliations":[],"preferred":false,"id":694142,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wang, Jinjin","contributorId":191752,"corporation":false,"usgs":false,"family":"Wang","given":"Jinjin","email":"","affiliations":[],"preferred":false,"id":694143,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kan, Shifu","contributorId":191753,"corporation":false,"usgs":false,"family":"Kan","given":"Shifu","email":"","affiliations":[],"preferred":false,"id":694144,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Liu, Yin","contributorId":191754,"corporation":false,"usgs":false,"family":"Liu","given":"Yin","email":"","affiliations":[],"preferred":false,"id":694145,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zheng, Xiaocong","contributorId":191755,"corporation":false,"usgs":false,"family":"Zheng","given":"Xiaocong","email":"","affiliations":[],"preferred":false,"id":694146,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"SHi, Xiujie","contributorId":191756,"corporation":false,"usgs":false,"family":"SHi","given":"Xiujie","email":"","affiliations":[],"preferred":false,"id":694147,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"He, Junqiang","contributorId":191757,"corporation":false,"usgs":false,"family":"He","given":"Junqiang","email":"","affiliations":[],"preferred":false,"id":694148,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Yu, Li","contributorId":191758,"corporation":false,"usgs":false,"family":"Yu","given":"Li","email":"","affiliations":[],"preferred":false,"id":694149,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Hua, Qunyi","contributorId":191759,"corporation":false,"usgs":false,"family":"Hua","given":"Qunyi","email":"","affiliations":[],"preferred":false,"id":694150,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lu, Tikang","contributorId":191760,"corporation":false,"usgs":false,"family":"Lu","given":"Tikang","email":"","affiliations":[],"preferred":false,"id":694151,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Lan, Wensheng","contributorId":191761,"corporation":false,"usgs":false,"family":"Lan","given":"Wensheng","email":"","affiliations":[],"preferred":false,"id":694152,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Winton, James 0000-0002-3505-5509 jwinton@usgs.gov","orcid":"https://orcid.org/0000-0002-3505-5509","contributorId":179330,"corporation":false,"usgs":true,"family":"Winton","given":"James","email":"jwinton@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":694153,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Jin, Ningyi","contributorId":191762,"corporation":false,"usgs":false,"family":"Jin","given":"Ningyi","email":"","affiliations":[],"preferred":false,"id":694154,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Liu, Hong","contributorId":191763,"corporation":false,"usgs":false,"family":"Liu","given":"Hong","email":"","affiliations":[],"preferred":false,"id":694155,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70187506,"text":"70187506 - 2017 - Evaluation of laser ablation double-focusing SC-ICPMS for “common” lead isotopic measurements in silicate glasses and mineral","interactions":[],"lastModifiedDate":"2017-06-07T14:02:44","indexId":"70187506","displayToPublicDate":"2017-05-04T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2155,"text":"Journal of Analytical Atomic Spectrometry","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of laser ablation double-focusing SC-ICPMS for “common” lead isotopic measurements in silicate glasses and mineral","docAbstract":"An analytical method for the in situ measurement of “common” Pb isotope ratios in silicate glasses and minerals using a 193-nm excimer laser ablation (LA) system with a double-focusing single-collector (SC)-ICPMS is presented and evaluated as a possible alternative to multiple-collector (MC)-ICPMS. This LA-SC-ICPMS technique employs fast-scanning ion deflectors to sequentially place a series of flat-topped isotope peaks into a single ion-counting detector at a fixed accelerating voltage and magnetic field strength. Reference materials (including NIST, MPI-DING, and USGS glasses) are used to identify two analytical artifacts on the Pb isotope ratios (expressed here as heavier/lighter isotopes) when corrected for mass bias relative to NIST SRM610. The first artifact is characterized by anomalously low Pb isotope ratios (~0.1%/AMU) when SRM610 is analyzed in raster mode as an unknown at small spot sizes (<25 µm), which may indicate that (1) SRM610 is isotopically heterogeneous on a small length scale and/or (2) there is a non-spectral matrix effect on the Pb isotope ratios related to differences in spot size. The second artifact is characterized by anomalously high Pb isotope ratios (<0.1%/AMU) for NIST SRM612 (in raster mode) and some Fe-rich glass reference materials (BCR-2G, GOR132-G, and T1-G). These offsets are thought to be caused by one or more non-spectral matrix effects related to differences in the ablation behavior, composition, or physical properties of these reference materials compared to the bracketing SRM610 standard. The precision (±2SD) of our LA-SC-ICPMS Pb isotopic measurements is similar to (207Pb/206Pb and 208Pb/206Pb, or 20XPb/206Pb) or better than (206Pb/204Pb,207Pb/204Pb, and 208Pb/204Pb, or 20XPb/204Pb) a series of published studies that used a different type of SC-ICPMS and obtained a factor of ~3-4 higher sensitivity for Pb. An increase in the sensitivity of our LA-SC-ICPMS would likely improve the precision of the 20XPb/206Pb and 20XPb/204Pb ratios for low-Pb materials (<5 ppm), possibly making the technique broadly similar to LA-MC-ICPMS (particularly compared to methods that rely upon at least one ion-counting detector). Further improvement in the precision of the 20XPb/206Pb and 20XPb/204Pb ratios for high-Pb materials (>5 ppm) by LA-SC-ICPMS is unlikely, and in this case, LA-MC-ICPMS remains the preferable analytical technique.
","language":"English","publisher":"Royal Society of Chemistry","doi":"10.1039/c7ja00005g","usgsCitation":"Pietruszka, A.J., and Neymark, L., 2017, Evaluation of laser ablation double-focusing SC-ICPMS for “common” lead isotopic measurements in silicate glasses and mineral: Journal of Analytical Atomic Spectrometry, v. 32, no. 6, p. 1135-1154, https://doi.org/10.1039/c7ja00005g.","productDescription":"20 p.","startPage":"1135","endPage":"1154","ipdsId":"IP-082736","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":340845,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"590c3dc8e4b0e541a038dd1f","contributors":{"authors":[{"text":"Pietruszka, Aaron J. 0000-0002-2826-9509 apietruszka@usgs.gov","orcid":"https://orcid.org/0000-0002-2826-9509","contributorId":4552,"corporation":false,"usgs":true,"family":"Pietruszka","given":"Aaron","email":"apietruszka@usgs.gov","middleInitial":"J.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":694220,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Neymark, Leonid A. 0000-0003-4190-0278 lneymark@usgs.gov","orcid":"https://orcid.org/0000-0003-4190-0278","contributorId":140338,"corporation":false,"usgs":true,"family":"Neymark","given":"Leonid A.","email":"lneymark@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":694221,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70187355,"text":"ofr20171049 - 2017 - Eastern Denali Fault surface trace map, eastern Alaska and Yukon, Canada","interactions":[],"lastModifiedDate":"2023-11-03T16:52:08.991249","indexId":"ofr20171049","displayToPublicDate":"2017-05-04T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1049","title":"Eastern Denali Fault surface trace map, eastern Alaska and Yukon, Canada","docAbstract":"We map the 385-kilometer (km) long surface trace of the right-lateral, strike-slip Denali Fault between the Totschunda-Denali Fault intersection in Alaska, United States and the village of Haines Junction, Yukon, Canada. In Alaska, digital elevation models based on light detection and ranging and interferometric synthetic aperture radar data enabled our fault mapping at scales of 1:2,000 and 1:10,000, respectively. Lacking such resources in Yukon, we developed new structure-from-motion digital photogrammetry products from legacy aerial photos to map the fault surface trace at a scale of 1:10,000 east of the international border. The section of the fault that we map, referred to as the Eastern Denali Fault, did not rupture during the 2002 Denali Fault earthquake (moment magnitude 7.9). Seismologic, geodetic, and geomorphic evidence, along with a paleoseismic record of past ground-rupturing earthquakes, demonstrate Holocene and contemporary activity on the fault, however. This map of the Eastern Denali Fault surface trace complements other data sets by providing an openly accessible digital interpretation of the location, length, and continuity of the fault’s surface trace based on the accompanying digital topography dataset. Additionally, the digitized fault trace may provide geometric constraints useful for modeling earthquake scenarios and related seismic hazard.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171049","usgsCitation":"Bender, A.M., and Haeussler, P.J., 2017, Eastern Denali Fault surface trace map, eastern Alaska and Yukon, Canada: U.S. Geological Survey Open-File Report 2017–1049, 10 p., https://doi.org/10.3133/ofr20171049.","productDescription":"iii, 10 p.","numberOfPages":"13","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-084514","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":438353,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7T151WC","text":"USGS data release","linkHelpText":"Eastern Denali Fault Surface Trace Map, Eastern Alaska and Adjacent Canada, 1978-2008"},{"id":422373,"rank":3,"type":{"id":15,"text":"Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_105646.htm","linkFileType":{"id":5,"text":"html"}},{"id":340824,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1049/coverthb.jpg"},{"id":340825,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1049/ofr20171049.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1049"}],"country":"Canada, United States","state":"Alaska, Yukon","otherGeospatial":"Denali Fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -147,\n 60\n ],\n [\n -135,\n 60\n ],\n [\n -135,\n 64\n ],\n [\n -147,\n 64\n ],\n [\n -147,\n 60\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Alaska Science Center
U.S. Geological Survey
4210 University Dr.
Anchorage, AK 99508
The U.S. Geological Survey Monthly Water Balance Model Futures Portal (https://my.usgs.gov/mows/) is a user-friendly interface that summarizes monthly historical and simulated future conditions for seven hydrologic and meteorological variables (actual evapotranspiration, potential evapotranspiration, precipitation, runoff, snow water equivalent, atmospheric temperature, and streamflow) at locations across the conterminous United States (CONUS).
The estimates of these hydrologic and meteorological variables were derived using a Monthly Water Balance Model (MWBM), a modular system that simulates monthly estimates of components of the hydrologic cycle using monthly precipitation and atmospheric temperature inputs. Precipitation and atmospheric temperature from 222 climate datasets spanning historical conditions (1952 through 2005) and simulated future conditions (2020 through 2099) were summarized for hydrographic features and used to drive the MWBM for the CONUS. The MWBM input and output variables were organized into an open-access database. An Open Geospatial Consortium, Inc., Web Feature Service allows the querying and identification of hydrographic features across the CONUS. To connect the Web Feature Service to the open-access database, a user interface—the Monthly Water Balance Model Futures Portal—was developed to allow the dynamic generation of summary files and plots based on plot type, geographic location, specific climate datasets, period of record, MWBM variable, and other options. Both the plots and the data files are made available to the user for download
Director, USGS Colorado Water Science Center
U.S. Geological Survey
Box 25046, Mail Stop 415
Denver, CO 80225
The occurrence of arsenic and uranium in groundwater at concentrations that exceed drinking-water standards is a concern because of the potential adverse effects on human health. Some early studies of arsenic occurrence in groundwater considered anthropogenic causes, but more recent studies have focused on sources of naturally occurring arsenic to groundwater, such as minerals within aquifer materials that are in contact with groundwater. Arsenic and uranium in groundwater in New England have been shown to have a strong association to the geologic setting and nearby streambed sediment concentrations. In New Hampshire and Massachusetts, arsenic and uranium concentrations greater than human-health benchmarks have shown distinct spatial patterns when related to the bedrock units mapped at the local scale.
The Connecticut Department of Public Health (DPH) reported that there are about 322,600 private wells in Connecticut serving approximately 823,000 people, or 23 percent of the State’s population. The State does not require that existing private wells be routinely tested for arsenic, uranium, or other contaminants; consequently, private wells are only sampled at the well owner’s discretion or when they are newly constructed. The U.S. Geological Survey (USGS), in cooperation with the DPH, completed an assessment in 2016 on the distribution of concentrations of arsenic and uranium in groundwater from bedrock in Connecticut. This report presents the major findings for arsenic and uranium concentrations from water samples collected from 2013 to 2015 from private wells.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171046","issn":"2331-1258","collaboration":"Prepared in cooperation with the Connecticut Department of Public Health","usgsCitation":"Flanagan, S.M., and Brown, C.J., 2017, Arsenic and uranium in private wells in Connecticut, 2013–15: U.S. Geological Survey Open-File Report 2017–1046; 8 p., https://doi.org/10.3133/ofr20171046.","productDescription":"Report: 8 p; Data Release","numberOfPages":"8","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-076719","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":340583,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7K935P5","text":"USGS data release","description":"USGS data release","linkHelpText":"Inventory of water-quality and geologic-setting data from 674 private wells in Connecticut, 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U.S. Geological Survey
331 Commerce Way, Suite 2
Pembroke, NH 03275
Aim
The distributions of exotic species reflect patterns of human-mediated dispersal, species climatic tolerances and a suite of other biotic and abiotic factors. The relative importance of each of these factors will shape how the spread of exotic species is affected by ongoing economic globalization and climate change. However, patterns of trade may be correlated with variation in scientific sampling effort globally, potentially confounding studies that do not account for sampling patterns.
Location
Global.
Time period
Museum records, generally from the 1800s up to 2015.
Major taxa studied
Plant species exotic to the United States.
Methods
We used data from the Global Biodiversity Information Facility (GBIF) to summarize the number of plant species with exotic occurrences in the United States that also occur in each other country world-wide. We assessed the relative importance of trade and climatic similarity for explaining variation in the number of shared species while evaluating several methods to account for variation in sampling effort among countries.
Results
Accounting for variation in sampling effort reversed the relative importance of trade and climate for explaining numbers of shared species. Trade was strongly correlated with numbers of shared U.S. exotic plants between the United States and other countries before, but not after, accounting for sampling variation among countries. Conversely, accounting for sampling effort strengthened the relationship between climatic similarity and species sharing. Using the number of records as a measure of sampling effort provided a straightforward approach for the analysis of occurrence data, whereas species richness estimators and rarefaction were less effective at removing sampling bias.
Main conclusions
Our work provides support for broad-scale climatic limitation on the distributions of exotic species, illustrates the need to account for variation in sampling effort in large biodiversity databases, and highlights the difficulty in inferring causal links between the economic drivers of invasion and global patterns of exotic species occurrence.
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At the same time, ecosystems in the GOM are changing rapidly, with unknown consequences for migratory landbird populations, many of which are experiencing population declines. In general, the extent to which events encountered en route limit migratory bird populations is not well understood. At the same time, information from weather surveillance radar, stable isotopes, tracking, eBird, and genetic datasets is increasingly available to address many of the unanswered questions about bird populations that migrate through stopover and airspace habitats in the GOM. We review the state of the science and identify key research needs to understand the impacts of en route events around the GOM region on populations of intercontinental landbird migrants that breed in North America, including: (1) distribution, timing, and habitat associations; (2) habitat characteristics and quality; (3) migratory connectivity; and (4) threats to and current conservation status of airspace and stopover habitats. 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