The National Climate Change and Wildlife Science Center (NCCWSC) and the Department of the Interior (DOI) Climate Science Centers (CSCs) had another exciting year in 2014. The NCCWSC moved toward focusing their science funding on several high priority areas and, along with the CSCs, gained new agency partners; contributed to various workshops, meetings, publications, student activities, and Tribal/indigenous activities; increased outreach; and more.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1415","usgsCitation":"Varela Minder, Elda, and Padgett, Holly A. 2015, The National Climate Change and Wildlife Science Center and Department of the Interior Climate Science Centers annual report for 2014: U.S. Geological Survey Circular 1415, 32 p., https://dx.doi.org/10.3133/cir1415.","productDescription":"v, 18 p.","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-064590","costCenters":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":310576,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1415/circ1415.pdf","text":"Report","size":"4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"CIR 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U.S. Geological Survey
MS 516 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
https://nccwsc.usgs.gov/
Physiological constraints dictate animals’ ability to exploit habitats. For marine mammals, it is important to quantify physiological limits that influence diving and their ability to alter foraging behaviors. We characterized age-specific dive limits of walruses by measuring anaerobic (acid-buffering capacity) and aerobic (myoglobin content) capacities of the muscles that power hind (longissimus dorsi) and fore (supraspinatus) flipper propulsion. Mean buffering capacities were similar across muscles and age classes (a fetus, five neonatal calves, a 3 month old and 20 adults), ranging from 41.31 to 54.14 slykes and 42.00 to 46.93 slykes in the longissimus and supraspinatus, respectively. Mean myoglobin in the fetus and neonatal calves fell within a narrow range (longissimus: 0.92–1.68 g 100 g−1 wet muscle mass; supraspinatus: 0.88–1.64 g 100 g−1 wet muscle mass). By 3 months post-partum, myoglobin in the longissimus increased by 79%, but levels in the supraspinatus remained unaltered. From 3 months post-partum to adulthood, myoglobin increased by an additional 26% in the longissimus and increased by 126% in the supraspinatus; myoglobin remained greater in the longissimus compared with the supraspinatus. Walruses are unique among marine mammals because they are born with a mature muscle acid-buffering capacity and attain mature myoglobin content early in life. Despite rapid physiological development, small body size limits the diving capacity of immature walruses and extreme sexual dimorphism reduces the diving capacity of adult females compared with adult males. Thus, free-ranging immature walruses likely exhibit the shortest foraging dives while adult males are capable of the longest foraging dives.
","language":"English","publisher":"The Company of Biologists","doi":"10.1242/jeb.125757","usgsCitation":"Norem, S.R., Jay, C.V., Burns, J.M., and Fischbach, A.S., 2015, Rapid maturation of the muscle biochemistry that supports diving in Pacific walruses (Odobenus rosmarus divergens): Journal of Experimental Biology, v. 218, p. 3319-3329, https://doi.org/10.1242/jeb.125757.","productDescription":"11 p.","startPage":"3319","endPage":"3329","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064440","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":310669,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"218","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"563092bce4b093cee78203d2","contributors":{"authors":[{"text":"Norem, Shawn R.","contributorId":149449,"corporation":false,"usgs":false,"family":"Norem","given":"Shawn","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":578453,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jay, Chadwick V. 0000-0002-9559-2189 cjay@usgs.gov","orcid":"https://orcid.org/0000-0002-9559-2189","contributorId":192736,"corporation":false,"usgs":true,"family":"Jay","given":"Chadwick","email":"cjay@usgs.gov","middleInitial":"V.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":578403,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burns, Jennifer M.","contributorId":98569,"corporation":false,"usgs":false,"family":"Burns","given":"Jennifer","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":578454,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fischbach, Anthony S. 0000-0002-6555-865X afischbach@usgs.gov","orcid":"https://orcid.org/0000-0002-6555-865X","contributorId":2865,"corporation":false,"usgs":true,"family":"Fischbach","given":"Anthony","email":"afischbach@usgs.gov","middleInitial":"S.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":578404,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159405,"text":"70159405 - 2015 - Explained and unexplained tissue loss in corals from the Tropical Eastern Pacific","interactions":[],"lastModifiedDate":"2015-10-27T10:59:09","indexId":"70159405","displayToPublicDate":"2015-10-27T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1396,"text":"Diseases of Aquatic Organisms","active":true,"publicationSubtype":{"id":10}},"title":"Explained and unexplained tissue loss in corals from the Tropical Eastern Pacific","docAbstract":"Coral reefs rival rainforest in biodiversity, but are declining in part because of disease. Tissue loss lesions, a manifestation of disease, are present in dominant Pocillopora along the Pacific coast of Mexico. We characterized tissue loss in 7 species of Pocillopora from 9 locations (44 sites) spanning southern to northern Mexico. Corals were identified to species, and tissue loss lesions were photographed and classified as those explainable by predation and those that were unexplained. A focal predation study was done concurrently at 3 locations to confirm origin of explained lesions. Of 1054 cases of tissue loss in 7 species of corals, 84% were associated with predation (fish, snails, or seastar) and the remainder were unexplained. Types of tissue loss were not related to coral density; however there was significant geographic heterogeneity in type of lesion; one site in particular (Cabo Pulmo) had the highest prevalence of predator-induced tissue loss (mainly pufferfish predation). Crown-of-thorns starfish, pufferfish, and snails were the most common predators and preferred P. verrucosa, P. meandrina, and P. capitata, respectively. Of the 9 locations, 4 had unexplained tissue loss with prevalence ranging from 1 to 3% with no species predilection. Unexplained tissue loss was similar to white syndrome (WS) in morphology, indicating additional study is necessary to clarify the cause(s) of the lesions and the potential impacts to dominant corals along the Pacific coast of Mexico.
","language":"English","publisher":"Inter-Research","doi":"10.3354/dao02914","usgsCitation":"Rodriguez-Villalobos, J.C., Work, T.M., Calderon-Aguilera, L.E., Reyes-Bonilla, H., and Hernandez, L., 2015, Explained and unexplained tissue loss in corals from the Tropical Eastern Pacific: Diseases of Aquatic Organisms, v. 116, p. 121-131, https://doi.org/10.3354/dao02914.","productDescription":"11 p.","startPage":"121","endPage":"131","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066893","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":471704,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/dao02914","text":"Publisher Index Page"},{"id":310668,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico","volume":"116","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"563092b9e4b093cee78203c6","contributors":{"authors":[{"text":"Rodriguez-Villalobos, Jenny Carolina","contributorId":149443,"corporation":false,"usgs":false,"family":"Rodriguez-Villalobos","given":"Jenny","email":"","middleInitial":"Carolina","affiliations":[{"id":17735,"text":"CICESE, Mexico","active":true,"usgs":false}],"preferred":false,"id":578425,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Work, Thierry M. 0000-0002-4426-9090 thierry_work@usgs.gov","orcid":"https://orcid.org/0000-0002-4426-9090","contributorId":1187,"corporation":false,"usgs":true,"family":"Work","given":"Thierry","email":"thierry_work@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":578424,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Calderon-Aguilera, Luis Eduardo","contributorId":149444,"corporation":false,"usgs":false,"family":"Calderon-Aguilera","given":"Luis","email":"","middleInitial":"Eduardo","affiliations":[{"id":17735,"text":"CICESE, Mexico","active":true,"usgs":false}],"preferred":false,"id":578426,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reyes-Bonilla, Hector","contributorId":149445,"corporation":false,"usgs":false,"family":"Reyes-Bonilla","given":"Hector","email":"","affiliations":[{"id":12968,"text":"Departamento de Biologia Marina, Universidad Autonoma de Baja California Sur, La Paz, Baja California Sur, Mexico","active":true,"usgs":false}],"preferred":false,"id":578427,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hernandez, Luis","contributorId":149446,"corporation":false,"usgs":false,"family":"Hernandez","given":"Luis","email":"","affiliations":[{"id":12968,"text":"Departamento de Biologia Marina, Universidad Autonoma de Baja California Sur, La Paz, Baja California Sur, Mexico","active":true,"usgs":false}],"preferred":false,"id":578428,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70148579,"text":"70148579 - 2015 - Using hydrophones as a surrogate monitoring technique to detect temporal and spatial variability in bedload transport","interactions":[],"lastModifiedDate":"2017-06-05T10:40:02","indexId":"70148579","displayToPublicDate":"2015-10-27T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Using hydrophones as a surrogate monitoring technique to detect temporal and spatial variability in bedload transport","docAbstract":"Collecting physical bedload measurements is an expensive and time-consuming endeavor that rarely captures the spatial and temporal variability of sediment transport. Technological advances can improve monitoring of sediment transport by filling in temporal gaps between physical sampling periods. We have developed a low-cost hydrophone recording system designed to record the sediment-generated noise (SGN) resulting from collisions of coarse particles (generally larger than 4 mm) in gravel-bedded rivers. The sound level of the signal recorded by the hydrophone is assumed to be proportional to the magnitude of bedload transport as long as the acoustic frequency of the SGN is known, the grain-size distribution of the bedload is assumed constant, and the frequency band of the ambient noise is known and can be excluded from the analysis. Each system has two hydrophone heads and samples at half-hour intervals. Ten systems were deployed on the San Joaquin River, California, and its tributaries for ten months during water year 2014, and two systems were deployed during a flood event on the Gunnison River, Colorado in 2014. A mobile hydrophone system was also tested at both locations to collect longitudinal profiles of SGN. Physical samples of bedload were not collected in this study. In lieu of physical measurements, several audio recordings from each site were aurally reviewed to confirm the presence or absence of SGN, and hydraulic data were compared to historical measurements of bedload transport or transport capacity estimates to verify if hydraulic conditions during the study would likely produce bedload transport. At one site on the San Joaquin River, the threshold of movement was estimated to have occurred around 30 m 3 /s based on SGN data. During the Gunnison River flood event, continuous data showed clockwise hysteresis, indicating that bedload transport was generally less at any given streamflow discharge during the recession limb of the hydrograph. Spatial variability in transport was also detected in the longitudinal profiles audibly and using signal processing algorithms. These experiments demonstrate the ability of hydrophone technology to capture the temporal and spatial variability of sediment transport, which may be missed when samples are collected using conventional methods.
","conferenceTitle":"3rd Joint Federal Interagency Conference","conferenceDate":"April 19-23, 2015","conferenceLocation":"Reno, NV","language":"English","publisher":"Joint Federal Interagency Conference","usgsCitation":"Marineau, M.D., Minear, J., and Wright, S., 2015, Using hydrophones as a surrogate monitoring technique to detect temporal and spatial variability in bedload transport, 3rd Joint Federal Interagency Conference, Reno, NV, April 19-23, 2015, 12 p.","productDescription":"12 p.","ipdsId":"IP-060794","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":342079,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Colorado","otherGeospatial":"Gunnison River, San Joaquin River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.083333,\n 37.1\n ],\n [\n -120.083333,\n 36.683333\n ],\n [\n -119.683333,\n 36.683333\n ],\n [\n -119.683333,\n 37.1\n ],\n [\n -120.083333,\n 37.1\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.458333,\n 38.925\n ],\n [\n -108.25,\n 38.925\n ],\n [\n -108.25,\n 38.7\n ],\n [\n -108.458333,\n 38.7\n ],\n [\n -108.458333,\n 38.925\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59366daae4b0f6c2d0d7d62e","contributors":{"authors":[{"text":"Marineau, Mathieu D. 0000-0002-6568-0743 mmarineau@usgs.gov","orcid":"https://orcid.org/0000-0002-6568-0743","contributorId":4954,"corporation":false,"usgs":true,"family":"Marineau","given":"Mathieu","email":"mmarineau@usgs.gov","middleInitial":"D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":548731,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Minear, J. Toby","contributorId":9938,"corporation":false,"usgs":true,"family":"Minear","given":"J. Toby","affiliations":[],"preferred":false,"id":548732,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wright, Scott 0000-0002-0387-5713 sawright@usgs.gov","orcid":"https://orcid.org/0000-0002-0387-5713","contributorId":1536,"corporation":false,"usgs":true,"family":"Wright","given":"Scott","email":"sawright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":548733,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70159382,"text":"cir1414 - 2015 - Biodiversity and Habitat Markets—Policy, Economic, and Ecological implications of Market-Based Conservation","interactions":[],"lastModifiedDate":"2016-03-31T16:09:18","indexId":"cir1414","displayToPublicDate":"2015-10-26T17:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1414","title":"Biodiversity and Habitat Markets—Policy, Economic, and Ecological implications of Market-Based Conservation","docAbstract":"This report is a primer on market-like and market-based mechanisms designed to conserve biodiversity and habitat. The types of markets and market-based approaches that were implemented or are emerging to benefit biodiversity and habitat in the United States are examined. The central approaches considered in this report include payments for ecosystem services, conservation banks, habitat exchanges, and eco-labels. Based on literature reviews and input from experts and practitioners, the report characterizes each market-based approach including policy context and structure; the theoretical basis for applying market-based approaches; the ecological effectiveness of practices and tools for measuring performance; and the future outlook for biodiversity and habitat markets. This report draws from previous research and serves as a summary of pertinent information associated with biodiversity and habitat markets while providing references to materials that go into greater detail on specific topics.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1414","collaboration":"Prepared in cooperation with the U.S. Department of Agriculture, Office of Environmental Markets","usgsCitation":"Pindilli, Emily, and Casey, Frank, 2015, Biodiversity and habitat markets—Policy, economic, and ecological implications\nof market-based conservation: U.S. Geological Survey Circular 1414, 60 p., https://dx.doi.org/10.3133/cir1414.","productDescription":"vii, 60 p.","numberOfPages":"72","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065059","costCenters":[],"links":[{"id":310628,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1414/circ1414.pdf","text":"Report","size":"20.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Circular 1414"},{"id":310627,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1414/coverthb2.jpg"}],"contact":"Science and Decisions Center
U.S. Geological Survey
413 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
http://www.usgs.gov/sdc/
This map and cross sections are redrafted modified versions of the Geological map of the Kundelan ore deposit area, scale 1:10,000 (graphical supplement no. 18) and the Geological map of the Kundelan deposits, scale 1:2,000 (graphical supplement no. 3) both contained in an unpublished Soviet report by Litvinenko and others (1971) (report no. 0540). The unpublished Soviet report was prepared in cooperation with the Ministry of Mines and Industries of the Royal Government of Afghanistan in Kabul during 1971. This redrafted map and cross sections illustrate the geology of the main Kundelan copper-gold skarn deposit, located within the Kundelan copper and gold area of interest (AOI), Zabul Province, Afghanistan. Areas of interest (AOIs) of non-fuel mineral resources within Afghanistan were first described and defined by Peters and others (2007) and later by the work of Peters and others (2011a). The location of the main Kundelan copper-gold skarn deposit (area of this map) and the Kundelan copper and gold AOI is shown on the index map provided on this map sheet.
\nThe estimated resources of the Kundelan copper-gold skarn deposit are 21,400 metric tons (t) of copper, 1.6 t of gold, and 133.4 t of molybdenum at an average grade of 1.21 weight percent (wt. %) copper (ranging from 0.66 to 4.03 wt. % copper); 0.9 grams per metric ton (g/t) gold (ranging from 0.3 to 3.1 g/t gold); 0.14 wt. % molybdenum; and as much as 10 g/t silver and 0.03 wt. % bismuth (Peters and others, 2011b).
\nSmall past production of gold and base metals is also reported by Douvgal and others (1971) from many prospects within the Kundelan copper and gold AOI. Outside the skarn areas, argillic hydrothermal alteration is present (Abdullah and others, 1977). Most copper and gold prospects in the Kundelan copper and gold AOI are reported to contain commercial-grade ores of copper and (or) gold, and many prospect areas have potential for these commodities to be discovered in commercial volumes. Future initial mine exploration and later development in many of the prospects, and specifically in the Kundelan copper-gold skarn deposit, could result in near-term small- to medium-sized gold mining operations (Peters and others, 2011b).
\nThe redrafted map and cross sections reproduce the topology of rock units, contacts, faults, and so forth, of the original Soviet map and cross sections, and they include modifications based on our examination of these documents and our observations made during a brief field visit in August of 2010. We have attempted to translate the original Russian terminology and rock classifications into modern English geologic usage as literally as possible without changing any genetic or process-oriented implications in the original descriptions. We also use the age designations from the original Soviet maps, except for the phase I and II intrusive igneous rocks. Phase I and II igneous rocks are reassigned an Early Cretaceous age (from lower Paleogene) based on a uranium-lead (U-Pb) zircon SHRIMP analysis from quartz diorite, which yielded an age of 104±1 Ma (mega-annum). The information provided in the description of map units is from both the source report by Litvinenko and others (1971) and the original 1:10,000 scale map (graphical supplement no. 18), also from Litvinenko and others (1971). Because of the poor quality of the original map, some map features could not be identified and some features may be misinterpreted. The rock unit colors used on the redrafted maps and cross sections differ from the colors shown on the original Soviet version. Colors were selected according to the color and pattern scheme of the Commission for the Geological Map of the World (CGMW) at http://www.ccgm.org.
\nElevations on the cross sections are derived from the original Soviet topography and may not match the Global Digital Elevation Model (GDEM) topography used on the redrafted map of this report. Most hydrography derived from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) has not been included on our redrafted version of the map because of a poor fit with alluvial deposits from the unmodified original Soviet map (graphical supplement no. 18; Litvinenko and others, 1971).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151198","collaboration":"Prepared in cooperation with the Afghan Geological Survey under the auspices of the U.S. Department of Defense","usgsCitation":"Tucker, R.D., Peters, S.G., Stettner, W.R., Masonic, L.M., and Moran, T.W., comps., 2015, Geologic map of Kundelan ore deposits and prospects, Zabul Province, Afghanistan; Modified from the 1971 original map compilations of K.I. Litvinenko and others: U.S. Geological Survey Open-File Report 2015–1198, 1 sheet, scale 1:10,000, https://dx.doi.org/10.3133/ofr20151198.","productDescription":"1 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059646","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":310464,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1198/ofr20151198.pdf","text":"Report","size":"75.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1198"},{"id":310463,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1198/coverthb.jpg"}],"country":"Afghanistan","state":"Zabul Province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 66.884765625,\n 31.59725256170666\n ],\n [\n 69.3896484375,\n 31.59725256170666\n ],\n [\n 69.3896484375,\n 33.32134852669881\n ],\n [\n 66.884765625,\n 33.32134852669881\n ],\n [\n 66.884765625,\n 31.59725256170666\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Office of International Programs
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Reston, VA 20192
http://international.usgs.gov/index.htm
We report chemical data for selected shallow wells and coastal springs that were sampled in 2014 to determine whether geothermal power production in the Puna area over the past two decades has affected the characteristics of regional groundwater. The samples were analyzed for major and minor chemical species, trace metals of environmental concern, stable isotopes of water, and two organic compounds (pentane and isopropanol) that are injected into the deep geothermal reservoir at the power plant. Isopropanol was not detected in any of the groundwaters; confirmed detection of pentane was restricted to one monitoring well near the power plant at a low concentration not indicative of source. Thus, neither organic compound linked geothermal operations to groundwater contamination, though chemical stability and transport velocity questions exist for both tracers. Based on our chemical analysis of geothermal fluid at the power plant and on many similar results from commercially analyzed samples, we could not show that geothermal constituents in the groundwaters we sampled came from the commercially developed reservoir. Our data are consistent with a long-held view that heat moves by conduction from the geothermal reservoir into shallow groundwaters through a zone of low permeability rock that blocks passage of geothermal water. The data do not rule out all impacts of geothermal production on groundwater. Removal of heat during production, for example, may be responsible for minor changes that have occurred in some groundwater over time, such as the decline in temperature of one monitoring well near the power plant. Such indirect impacts are much harder to assess, but point out the need for an ongoing groundwater monitoring program that should include the coastal springs down-gradient from the power plant.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155139","usgsCitation":"Evans, W., Bergfeld, D., Sutton, A., Lee, R., and Lorenson, T., 2015, Groundwater chemistry in the vicinity of the Puna Geothermal Venture Power Plant, Hawai‘i, after two decades of production: U.S. Geological Survey Scientific Investigations Report 2015-5139, v, 26 p., https://doi.org/10.3133/sir20155139.","productDescription":"v, 26 p.","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2014-01-01","temporalEnd":"2014-12-31","ipdsId":"IP-068405","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":310658,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5139/coverthb.jpg"},{"id":310659,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5139/sir20155139.pdf","text":"Report","size":"2.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5139"}],"country":"United States","state":"Hawaii","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -154.98310089111328,\n 19.34289288466279\n ],\n [\n -154.99408721923828,\n 19.51255069063782\n ],\n [\n -154.918212890625,\n 19.581463883128308\n ],\n [\n -154.8028564453125,\n 19.52484721904625\n ],\n [\n -154.81761932373047,\n 19.47533181665073\n ],\n [\n -154.98310089111328,\n 19.34289288466279\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"NRP staff, National Research Program
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345 Middlefield Road, MS-435
Menlo Park, CA 94025
http://water.usgs.gov/nrp
Coastal communities are uniquely vulnerable to sea-level rise (SLR) and severe storms such as hurricanes. These events enhance the dispersion and concentration of natural and anthropogenic chemicals and pathogenic microorganisms that could adversely affect the health and resilience of coastal communities and ecosystems in coming years. The U.S. Geological Survey has developed a strategy to define baseline and post-event sediment-bound environmental health (EH) stressors (hereafter referred to as the Sediment-Bound Contaminant Resiliency and Response [SCoRR] strategy). A tiered, multimetric approach will be used to (1) identify and map contaminant sources and potential exposure pathways for human and ecological receptors, (2) define the baseline mixtures of EH stressors present in sediments and correlations of relevance, (3) document post-event changes in EH stressors present in sediments, and (4) establish and apply metrics to quantify changes in coastal resilience associated with sediment-bound contaminants. Integration of this information provides a means to improve assessment of the baseline status of a complex system and the significance of changes in contaminant hazards due to storm-induced (episodic) and SLR (incremental) disturbances. This report describes the purpose and design of the SCoRR strategy and the methods used to construct a decision support tool to identify candidate sampling stations vulnerable to contaminants that may be mobilized by coastal storms.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151188A","collaboration":"Toxic Substances Hydrology Program","usgsCitation":"Reilly, T.J., Jones, D.K., Focazio, M.J., Aquino, K.C., Carbo, C.L., Kaufhold, E.E., Zinecker, E.K., Benzel, W.M., Fisher, S.C., Griffin, D.W., Iwanowicz, L.R., Loftin, K.A. and Schill, W.B., 2015, Strategy to evaluate persistent contaminant hazards resulting from sea-level rise and storm-derived disturbances—Study design and methodology for station prioritization: U.S. Geological Survey Open-File Report 2015–1188A, 20 p., https://dx.doi.org/10.3133/ofr20151188A.","productDescription":"Report: vi, 20 p.; 3 Appendixes","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-066315","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":438671,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7F47MBM","text":"USGS data release","linkHelpText":"Matrix inhibition PCR and Microtox 81.9% screening assay analytical results for samples collected for the Sediment-Bound Contaminant Resiliency and Response Strategy pilot study, northeastern United States, 2015"},{"id":312421,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/ofr20151188B","text":"Open-File Report 2015-1188B","linkHelpText":"Standard Operating Procedures for Collection of Soil and Sediment Samples for the Sediment-bound Contaminant Resiliency and Response (SCoRR) Strategy Pilot Study"},{"id":310598,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1188/A/ofr2015-1188a_appendixa-ntasdatabase.xlsx","text":"Appendix A","size":"223 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2015-1188 A","linkHelpText":"National Target Analyte Strategy (NTAS) Constituent Database"},{"id":310599,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1188/A/ofr2015-1188a_appendixb-tri-ranks.xlsx","text":"Appendix B","size":"91.6 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2015-1188 A","linkHelpText":"National Target Analyte Strategy (NTAS) Ranked Constituent Database"},{"id":310596,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1188/A/coverthb.jpg"},{"id":310597,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1188/A/ofr20151188a.pdf","text":"Report","size":"5.17 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1188 A"},{"id":310600,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1188/A/ofr2015-1188a_appendixc-frsquestionnaire.xlsx","text":"Appendix C","size":"46.2 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2015-1188 A","linkHelpText":"U.S. Environmental Protection Agency (EPA) Facility Registry Service (FRS) Questionnaire used to Generate Potential Contaminant Hazard Ranks"}],"country":"United States","state":"Connecticut, Delaware, District of Columbia, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.9375,\n 36.66841891894786\n ],\n [\n -75.146484375,\n 38.03078569382294\n ],\n [\n -74.70703125,\n 39.095962936305504\n ],\n [\n -73.6962890625,\n 40.111688665595956\n ],\n [\n -71.9384765625,\n 40.84706035607122\n ],\n [\n -71.103515625,\n 41.21172151054787\n ],\n [\n -69.9169921875,\n 41.60722821271717\n ],\n [\n -69.873046875,\n 42.16340342422401\n ],\n [\n -70.4443359375,\n 42.35854391749705\n ],\n [\n -70.57617187499999,\n 42.97250158602597\n ],\n [\n -70.048828125,\n 43.54854811091288\n ],\n [\n 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37.68382032669382\n ],\n [\n -79.189453125,\n 36.98500309285596\n ],\n [\n -77.6953125,\n 36.949891786813296\n ],\n [\n -76.552734375,\n 36.527294814546245\n ],\n [\n -75.9375,\n 36.66841891894786\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"U.S. Geological Survey
Toxic Substances Hydrology Program
12201 Sunrise Valley Drive
Reston, Virginia 20192
http://www.usgs.gov/envirohealth/
A series of maps that describe the distribution and texture of sea-floor sediments and physiographic zones of Massachusetts State waters from Nahant to Salisbury, Massachusetts, including western Massachusetts Bay, have been produced by using high-resolution geophysical data (interferometric and multibeam swath bathymetry, lidar bathymetry, backscatter intensity, and seismic reflection profiles), sediment samples, and bottom photographs. These interpretations are intended to aid statewide efforts to inventory and manage coastal and marine resources, link with existing data interpretations, and provide information for research focused on coastal evolution and environmental change. Marine geologic mapping of the inner continental shelf of Massachusetts is a statewide cooperative effort of the U.S. Geological Survey and the Massachusetts Office of Coastal Zone Management.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151153","collaboration":"Prepared in cooperation with the Massachusetts Office of Coastal Zone Management","usgsCitation":"Pendleton, E.A., Barnhardt, W.A., Baldwin, W.E., Foster, D.S., Schwab, W.C., Andrews, B.D., and Ackerman, S.D., 2015, Sea-floor texture and physiographic zones of the inner continental shelf from Salisbury to Nahant, Massachusetts, including the Merrimack Embayment and Western Massachusetts Bay: U.S. Geological Survey Open-File Report 2015–1153, 36 p., 1 appendix, https://dx.doi.org/10.3133/ofr20151153.","productDescription":"vi, 36 p.; HTML Documet","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-057824","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":309391,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/of/2015/1153/index.html","text":"Report HTML","description":"OFR 2015-1153"},{"id":308684,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1153/ofr20151153.pdf","text":"Report","size":"2.02 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1153"},{"id":308683,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1153/images/coverthb.jpg"}],"country":"United States","state":"Massachusetts","city":"Nahant, Salisbury","otherGeospatial":"Massachusetts Bay, Merrimack Embayment","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.95794677734374,\n 42.407234661551875\n ],\n [\n -70.95794677734374,\n 42.84777884235988\n ],\n [\n -70.56106567382812,\n 42.84777884235988\n ],\n [\n -70.56106567382812,\n 42.407234661551875\n ],\n [\n -70.95794677734374,\n 42.407234661551875\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 0254
http://woodshole.er.usgs.gov/
Chambers Lake is a manmade reservoir on Birch Run, a tributary to West Branch Brandywine Creek in Chester County, Pennsylvania. The lake was created in 1994 after the completion of Multi-Purpose Dam PA-436F (Hibernia Dam), which was built under the Watershed Protection & Flood Control Prevention Act (U.S. Soil Conservation Service, 1991). Hibernia dam is 1,700 feet upstream from the confluence of Birch Run with West Branch Brandywine Creek. The primary objectives for Hibernia Dam were to provide (1) flood control, (2) a supplemental source of water supply for the greater City of Coatesville public water system, and (3) recreational opportunities. The drainage basin of Chambers Lake encompasses approximately 4.5 square miles, and the lake covers a surface area of about 95 acres at normal pool, which is at an elevation of 579.2 feet above the North American Vertical Datum of 1988 (NAVD 88) [580.0 feet above the National Geodetic Vertical Datum of 1929 (NGVD 29)]. The crest of the auxiliary spillway of the dam is 586.6 feet above NAVD 88. The elevation of the auxiliary spillway is important to this investigation because this elevation defines the flood storage capacity of Chambers Lake. Water levels exceeding this elevation are routed through the auxiliary spillway and flow through adjoining woodland to Birch Run.
\nThe U.S. Geological Survey (USGS), in cooperation with Chester County Water Resources Authority (CCWRA) and the County of Chester, surveyed the bathymetry and selected above-water features of Chambers Lake in September 2014. The purpose of the survey was to develop an accurate representation of the surface of the bottom of Chambers Lake and to determine the stage area and reservoir-storage capacity relation as of September 2014. CCWRA is responsible for operation of the dam and water-supply reservoir. Since construction, CCWRA has used a stage–storage capacity relation developed from the original survey conducted in the 1990s to estimate the volume of water available for water supply and the available flood storage. The bathymetric mapping effort was initiated due to interest in potential changes in current (2014) storage capacity when compared to the stage–storage capacity relation developed during design. The generated bathymetric surface may serve as a baseline to which temporal changes in storage capacity, owing to sedimentation and other factors, can be compared. In addition, these data will improve the overall accuracy of the stage–storage capacity table that CCWRA uses for reservoir and flood management operations.
\nThis report describes the methods used to create a bathymetric map of Chambers Lake for the computation of reservoir storage capacity as of September 2014. The product is a bathymetric map and a table showing the storage capacity of the reservoir at 2-foot increments from minimum usable elevation up to full capacity at the crest of the auxiliary spillway.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3346","collaboration":"Prepared in cooperation with the Chester County Water Resources Authority","usgsCitation":"Gyves, M.C., 2015, Bathymetry and capacity of Chambers Lake, Chester County, Pennsylvania: U.S. Geological Survey Scientific Investigations Map 3346, https://dx.doi.org/10.3133/sim3346.","productDescription":"1 Sheet: 38 x 36 inches ; Spatial Data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-062894","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":310602,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3346/coverthb.jpg"},{"id":310604,"rank":3,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3346/sim3346_spatial_data.zip","text":"Spatial Data","size":"13.1 MB","description":"SIM 3346"},{"id":310603,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3346/sim3346.pdf","text":"Report","size":"1.71 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3346"}],"country":"United States","state":"Pennsylvania","county":"Chester County","otherGeospatial":"Chambers Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.86523056030273,\n 40.02781160777367\n ],\n [\n -75.86523056030273,\n 40.03622367578228\n ],\n [\n -75.84815025329588,\n 40.03622367578228\n ],\n [\n -75.84815025329588,\n 40.02781160777367\n ],\n [\n -75.86523056030273,\n 40.02781160777367\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Pennsylvania Water Science Center
215 Limekiln Road
New Cumberland, PA 17070
http://pa.water.usgs.gov/
Sagebrush steppe ecosystems in the United States currently occur on only about one-half of their historical land area because of changes in land use, urban growth, and degradation of land, including invasions of non-native plants. The existence of many animal species depends on the existence of sagebrush steppe habitat. The greater sage-grouse (Centrocercus urophasianus) is a landscape-dependent bird that requires intact habitat and combinations of sagebrush and perennial grasses to exist. In addition, other sagebrush-obligate animals also have similar requirements and restoration of landscapes for greater sage-grouse also will benefit these animals. Once sagebrush lands are degraded, they may require restoration actions to make those lands viable habitat for supporting sagebrushobligate animals. This restoration handbook is the first in a three-part series on restoration of sagebrush ecosystems. In Part 1, we discuss concepts surrounding landscape and restoration ecology of sagebrush ecosystems and greater sage-grouse that habitat managers and restoration practitioners need to know to make informed decisions regarding where and how to restore specific areas. We will describe the plant dynamics of sagebrush steppe ecosystems and their responses to major disturbances, fire, and defoliation. We will introduce the concepts of ecosystem resilience to disturbances and resistance to invasions of annual grasses within sagebrush steppe. An introduction to soils and ecological site information will provide insights into the specific plants that can be restored in a location. Soil temperature and moisture regimes are described as a tool for determining resilience and resistance and the potential for various restoration actions. Greater sage-grouse are considered landscape birds that require large areas of intact sagebrush steppe; therefore, we describe concepts of landscape ecology that aid our decisions regarding habitat restoration. We provide a brief overview of restoration techniques for sage-grouse habitat restoration. We conclude with a description of the critical nature of monitoring for adaptive management of sagebrush steppe restoration at landscape- and project-specific levels.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1416","isbn":"9781411339682","collaboration":"Prepared in cooperation with U.S. Joint Fire Science Program and National Interagency Fire Center, Bureau of Land Management, Great Northern Landscape Conservation, and Western Association of Fish and Wildlife Agencies","usgsCitation":"Pyke, D.A., Chambers, J.C., Pellant, M., Knick, S.T., Miller, R,F., Beck, J.L., Doescher, P.S., Schupp, E.W., Roundy,\nB.A., Brunson, M., and McIver, J.D., 2015, Restoration handbook for sagebrush steppe ecosystems with emphasis on\ngreater sage-grouse habitat—Part 1. Concepts for understanding and applying restoration: U.S. Geological Survey\nCircular 1416, 44 p., https://dx.doi.org/10.3133/cir1416.","productDescription":"vii, 43 p.","numberOfPages":"56","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061315","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":337388,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/cir1426","text":"Circular 1426 –","linkHelpText":"Restoration handbook for sagebrush steppe ecosystems with emphasis on greater sage-grouse habitat—Part 3. Site level restoration decisions"},{"id":310607,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1416/cir1416.pdf","text":"Report","size":"6.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Circular 1416 PDF"},{"id":310606,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1416/coverthb.jpg"},{"id":337387,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/cir1418","text":"Circular 1418 –","linkHelpText":"Restoration handbook for sagebrush steppe ecosystems with emphasis on greater sage-grouse habitat—Part 2. Landscape level restoration decisions"}],"country":"United States","state":"Arizona, California, Colorado, Idaho, Montana, Nebraska, Nevada, New Mexico, North Dakota, Oregon, South Dakota, Utah, Washington, Wyoming","otherGeospatial":"Colorado Plateau, Columbia Basin, Great Basin, Silver Sagebrush, Snake River Plain, Wyoming Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.720703125,\n 49.55372551347579\n ],\n [\n -104.32617187499999,\n 47.98992166741417\n ],\n [\n -104.19433593749999,\n 47.57652571374621\n ],\n [\n -103.798828125,\n 46.98025235521883\n ],\n [\n -103.71093749999999,\n 46.28622391806708\n ],\n [\n -103.623046875,\n 45.67548217560647\n ],\n [\n -103.9306640625,\n 43.992814500489914\n ],\n [\n -104.4580078125,\n 43.26120612479979\n ],\n [\n -106.083984375,\n 40.54720023441049\n ],\n [\n -106.61132812499999,\n 39.842286020743394\n ],\n [\n -106.61132812499999,\n 37.75334401310656\n ],\n [\n -105.99609375,\n 36.87962060502676\n ],\n [\n -106.6552734375,\n 36.31512514748051\n ],\n [\n -108.67675781249999,\n 36.10237644873644\n ],\n [\n -110.5224609375,\n 36.24427318493909\n ],\n [\n -111.181640625,\n 35.460669951495305\n ],\n [\n -113.203125,\n 35.28150065789119\n ],\n [\n -115.26855468749999,\n 35.99578538642032\n ],\n [\n -117.6416015625,\n 36.421282443649496\n ],\n [\n -119.61914062499999,\n 38.06539235133249\n ],\n [\n -121.11328124999999,\n 39.774769485295465\n ],\n [\n -121.904296875,\n 41.27780646738183\n ],\n [\n -122.29980468749999,\n 41.934976500546604\n ],\n [\n -122.3876953125,\n 44.465151013519616\n ],\n [\n -121.4208984375,\n 47.39834920035926\n ],\n [\n -120.234375,\n 47.78363463526376\n ],\n [\n -118.740234375,\n 47.60616304386874\n ],\n [\n -117.94921874999999,\n 46.58906908309182\n ],\n [\n -118.6083984375,\n 45.85941212790755\n ],\n [\n -118.740234375,\n 44.77793589631623\n ],\n [\n -115.04882812499999,\n 44.37098696297173\n ],\n [\n -113.99414062499999,\n 45.55252525134013\n ],\n [\n -112.236328125,\n 46.22545288226939\n ],\n [\n -110.8740234375,\n 47.487513008956554\n ],\n [\n -112.5,\n 48.69096039092549\n ],\n [\n -112.587890625,\n 49.35375571830993\n ],\n [\n -110.7861328125,\n 49.724479188713005\n ],\n [\n -109.51171875,\n 49.75287993415023\n ],\n [\n -108.720703125,\n 49.55372551347579\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Forest and Rangeland Ecosystem Science Center
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777 NW 9th St., Suite 400
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http://fresc.usgs.gov
Slow slip events (SSEs) are observed worldwide and often coincide with tectonic tremor. Notable examples of SSEs lacking observed tectonic tremor, however, occur beneath Kīlauea Volcano, Hawaii, the Boso Peninsula, Japan, near San Juan Bautista on the San Andreas Fault, California, and recently in Central Ecuador. These SSEs are similar to other worldwide SSEs in many ways (e.g., size or duration), but lack the concurrent tectonic tremor observed elsewhere; instead, they trigger swarms of regular earthquakes. We investigate the physical conditions that may distinguish these non-tremor-genic SSEs from those associated with tectonic tremor, including slip velocity, pressure, temperature, fluids, and fault asperities, although we cannot eliminate the possibility that tectonic tremor may be obscured in highly attenuating regions. Slip velocities of SSEs at Kīlauea Volcano (∼10−6 m/s) and Boso Peninsula (∼10−7 m/s) are among the fastest SSEs worldwide. Kīlauea Volcano, the Boso Peninsula, and Central Ecuador are also among the shallowest SSEs worldwide, and thus have lower confining pressures and cooler temperatures in their respective slow slip zones. Fluids also likely contribute to tremor generation, and no corresponding zone of high vp/vs has been noted at Kīlauea or Boso. We suggest that the relatively faster slip velocities at Kīlauea Volcano and the Boso Peninsula result from specific physical conditions that may also be responsible for triggering swarms of regular earthquakes adjacent to the slow slip, while different conditions produce slower SSE velocities elsewhere and trigger tectonic tremor.
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(SDM) are used to help understand what drives the distribution of various plant and animal species. These models are typically high dimensional scalar functions, where the dimensions of the domain correspond to predictor variables of the model algorithm. Understanding and exploring the differences between models help ecologists understand areas where their data or understanding of the system is incomplete and will help guide further investigation in these regions. These differences can also indicate an important source of model to model uncertainty. However, it is cumbersome and often impractical to perform this analysis using existing tools, which allows for manual exploration of the models usually as 1-dimensional curves. In this paper, we propose a topology-based framework to help ecologists explore the differences in various SDMs directly in the high dimensional domain. In order to accomplish this, we introduce the concept of maximum topology matching that computes a locality-aware correspondence between similar extrema of two scalar functions. The matching is then used to compute the similarity between two functions. We also design a visualization interface that allows ecologists to explore SDMs using their topological features and to study the differences between pairs of models found using maximum topological matching. We demonstrate the utility of the proposed framework through several use cases using different data sets and report the feedback obtained from ecologists.
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Combined analysis of the spatial distribution of earthquakes and regional moment tensor focal mechanisms indicate reactivation of a subsurface unnamed and unmapped left-lateral strike-slip fault. Coulomb failure stress change calculations using the relocated seismicity and slip distribution determined from regional moment tensors, allow for the possibility that the Wilzetta-Whitetail fault zone south of Cushing, Oklahoma, could produce a large, damaging earthquake comparable to the 2011 Prague event. Resultant very strong shaking levels (MMI VII) in the epicentral region present the possibility of this potential earthquake causing moderate to heavy damage to national strategic infrastructure and local communities.
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rherrmann@usgs.gov","contributorId":5609,"corporation":false,"usgs":true,"family":"Herrmann","given":"Robert","email":"rherrmann@usgs.gov","middleInitial":"B.","affiliations":[],"preferred":true,"id":573722,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Briggs, Richard W. 0000-0001-8108-0046 rbriggs@usgs.gov","orcid":"https://orcid.org/0000-0001-8108-0046","contributorId":139002,"corporation":false,"usgs":true,"family":"Briggs","given":"Richard","email":"rbriggs@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":573723,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Smoczyk, Gregory M. 0000-0002-6591-4060 gsmoczyk@usgs.gov","orcid":"https://orcid.org/0000-0002-6591-4060","contributorId":5239,"corporation":false,"usgs":true,"family":"Smoczyk","given":"Gregory","email":"gsmoczyk@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards 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Atlántico","interactions":[],"lastModifiedDate":"2017-06-30T10:09:15","indexId":"fs20153074","displayToPublicDate":"2015-10-23T11:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-3074","title":"Investigación del USGS sobre el ecosistema de arrecifes de coral en el Atlántico","docAbstract":"Los arrecifes de coral son estructuras sólidas, biomineralizadas que protegen comunidades costeras actuando como barreras protectoras de peligros tales como los huracanes y los tsunamis. Estos proveen arena a las playas a través de procesos naturales de erosión, fomentan la industria del turismo, las actividades recreacionales y proveen hábitats pesqueros esenciales. La conti-nua degradación mundial de ecosistemas de arrecifes de coral está bien documentada. Existe la necesidad de enfoque y organización de la ciencia para entender los procesos complejos físicos y biológicos e interacciones que están afectando el estado de los arrecifes coralinos y su capacidad para responder a un entorno cambiante.
","language":"Spanish","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153074","usgsCitation":"Kuffner, I.B., Yates, K.K., Zawada, D.G., Richey, J.N., Kellogg, C.A., Toth, L.T., and Torres-Garcia, L., 2015, Investigación del USGS sobre el ecosistema de arrecifes de coral en el Atlántico: Servicio Geológico de los Estados Unidos Hoja de Información 2015-3074, 2 p., https://dx.doi.org/10.3133/fs20153074.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-069804","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":310582,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/fs20153073","text":"Fact Sheet 2015-3073 (English)","size":"2.48 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2015-3074"},{"id":310581,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2015/3074/coverthb.jpg"},{"id":310568,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3074/fs20153074.pdf","text":"Report","size":"2.22 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2015-3074"}],"country":"United States","state":"Florida","otherGeospatial":"Florida Keys ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.0406494140625,\n 24.8689944482603\n ],\n [\n -81.5625,\n 24.73685348477069\n ],\n [\n -82.2381591796875,\n 24.569606275190566\n ],\n [\n -81.83441162109374,\n 24.44464923209822\n ],\n [\n -80.78247070312499,\n 24.711905448466087\n ],\n [\n -80.35125732421875,\n 25.07316070640961\n ],\n [\n -80.06011962890625,\n 25.485430526043555\n ],\n [\n -80.321044921875,\n 25.51765742999406\n ],\n [\n -81.0406494140625,\n 24.8689944482603\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
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600 4th Street South
St. Petersburg, FL 33701
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Coral reefs are massive, biomineralized structures that protect coastal communities by acting as barriers to hazards such as hurricanes and tsunamis. They provide sand for beaches through the natural process of erosion, support tourism and recreational industries, and provide essential habitat for fisheries. The continuing global degradation of coral reef ecosystems is well documented. There is a need for focused, coordinated science to understand the complex physical and biological processes and interactions that are impacting the condition of coral reefs and their ability to respond to a changing environment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153073","usgsCitation":"Kuffner, I.B., Yates, K.K., Zawada, D.G., Richey, J.N., Kellogg, C.A., and Toth, L.T., 2015, USGS research on Atlantic coral reef ecosystems: U.S. Geological Survey Fact Sheet 2015-3073, 2 p., https://dx.doi.org/10.3133/fs20153073.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-069803","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":310579,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2015/3073/coverthb.jpg"},{"id":310584,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/fs20153074","text":"Fact Sheet 2015-3074 (Spanish)","size":"2.22 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2015-3073"},{"id":310569,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3073/fs20153073.pdf","text":"Report","size":"2.48 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2015-3073"}],"country":"United States","state":"Florida","otherGeospatial":"Florida Keys","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.0406494140625,\n 24.8689944482603\n ],\n [\n -81.5625,\n 24.73685348477069\n ],\n [\n -82.2381591796875,\n 24.569606275190566\n ],\n [\n -81.83441162109374,\n 24.44464923209822\n ],\n [\n -80.78247070312499,\n 24.711905448466087\n ],\n [\n -80.35125732421875,\n 25.07316070640961\n ],\n [\n -80.06011962890625,\n 25.485430526043555\n ],\n [\n -80.321044921875,\n 25.51765742999406\n ],\n [\n -81.0406494140625,\n 24.8689944482603\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
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http://coastal.er.usgs.gov/
Studies of active fault zones have flourished with the availability of high-resolution topographic data, particularly where airborne light detection and ranging (lidar) and structure from motion (SfM) data sets provide a means to remotely analyze submeter-scale fault geomorphology. To determine surface offset at a point along a strike-slip earthquake rupture, geomorphic features (e.g., stream channels) are measured days to centuries after the event. Analysis of these and cumulatively offset features produces offset distributions for successive earthquakes that are used to understand earthquake rupture behavior. As researchers expand studies to more varied terrain types, climates, and vegetation regimes, there is an increasing need to standardize and uniformly validate measurements of tectonically displaced geomorphic features. A recently compiled catalog of nearly 5000 earthquake offsets across a range of measurement and reporting styles provides insight into quality rating and uncertainty trends from which we formulate best-practice and reporting recommendations for remote studies. In addition, a series of public and beginner-level studies validate the remote methodology for a number of tools and emphasize considerations to enhance measurement accuracy and precision for beginners and professionals. Our investigation revealed that (1) standardizing remote measurement methods and reporting quality rating schemes is essential for the utility and repeatability of fault-offset measurements; (2) measurement discrepancies often involve misinterpretation of the offset geomorphic feature and are a function of the investigator’s experience; (3) comparison of measurements made by a single investigator in different climatic regions reveals systematic differences in measurement uncertainties attributable to variation in feature preservation; (4) measuring more components of a displaced geomorphic landform produces more consistently repeatable estimates of offset; and (5) inadequate understanding of pre-event morphology and post-event modifications represents a greater epistemic limitation than the aleatoric limitations of the measurement process.
\n","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geosphere","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Geological Society of America","publisherLocation":"Boulder, CO","doi":"10.1130/GES01197.1","usgsCitation":"Salisbury, B., Haddad, D., Rockwell, T.K., Arrowsmith, R., Madugo, C., Zielke, O., and Scharer, K.M., 2015, Validation of meter-scale surface faulting offset measurements from high-resolution topographic data: Geosphere, v. 6, no. 11, p. 1884-1901, https://doi.org/10.1130/GES01197.1.","productDescription":"18 p.","startPage":"1884","endPage":"1901","numberOfPages":"18","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064820","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":471707,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges01197.1","text":"Publisher Index Page"},{"id":318019,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-23","publicationStatus":"PW","scienceBaseUri":"56c304e0e4b0946c65208823","contributors":{"authors":[{"text":"Salisbury, Barrett","contributorId":166850,"corporation":false,"usgs":false,"family":"Salisbury","given":"Barrett","email":"","affiliations":[{"id":12431,"text":"ASU","active":true,"usgs":false}],"preferred":false,"id":620206,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haddad, D.E.","contributorId":45545,"corporation":false,"usgs":true,"family":"Haddad","given":"D.E.","email":"","affiliations":[],"preferred":false,"id":620207,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rockwell, T. K.","contributorId":34688,"corporation":false,"usgs":false,"family":"Rockwell","given":"T.","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":620208,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arrowsmith, R.","contributorId":166851,"corporation":false,"usgs":false,"family":"Arrowsmith","given":"R.","email":"","affiliations":[{"id":12431,"text":"ASU","active":true,"usgs":false}],"preferred":false,"id":620209,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Madugo, C.","contributorId":166852,"corporation":false,"usgs":false,"family":"Madugo","given":"C.","email":"","affiliations":[{"id":24560,"text":"PGE","active":true,"usgs":false}],"preferred":false,"id":620210,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zielke, O.","contributorId":166853,"corporation":false,"usgs":false,"family":"Zielke","given":"O.","affiliations":[{"id":24561,"text":"KAUST","active":true,"usgs":false}],"preferred":false,"id":620211,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Scharer, Katherine M. 0000-0003-2811-2496 kscharer@usgs.gov","orcid":"https://orcid.org/0000-0003-2811-2496","contributorId":3385,"corporation":false,"usgs":true,"family":"Scharer","given":"Katherine","email":"kscharer@usgs.gov","middleInitial":"M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":620205,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70159638,"text":"70159638 - 2015 - A random-walk algorithm for modeling lithospheric density and the role of body forces in the evolution of the Midcontinent Rift","interactions":[],"lastModifiedDate":"2016-12-14T12:31:31","indexId":"70159638","displayToPublicDate":"2015-10-23T02:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"A random-walk algorithm for modeling lithospheric density and the role of body forces in the evolution of the Midcontinent Rift","docAbstract":"
This paper develops a Monte Carlo algorithm for extracting three-dimensional lithospheric density models from geophysical data. Empirical scaling relationships between velocity and density create a 3D starting density model, which is then iteratively refined until it reproduces observed gravity and topography. This approach permits deviations from uniform crustal velocity-density scaling, which provide insight into crustal lithology and prevent spurious mapping of crustal anomalies into the mantle.
\nWe test this algorithm on the Proterozoic Midcontinent Rift (MCR), north-central U.S. The MCR provides a challenge because it hosts a gravity high overlying low shear-wave velocity crust in a generally flat region. Our initial density estimates are derived from a seismic velocity/crustal thickness model based on joint inversion of surface-wave dispersion and receiver functions. By adjusting these estimates to reproduce gravity and topography, we generate a lithospheric-scale model that reveals dense middle crust and eclogitized lowermost crust within the rift. Mantle lithospheric density beneath the MCR is not anomalous, consistent with geochemical evidence that lithospheric mantle was not the primary source of rift-related magmas and suggesting that extension occurred in response to far-field stress rather than a hot mantle plume. Similarly, the subsequent inversion of normal faults resulted from changing far-field stress that exploited not only warm, recently faulted crust but also a gravitational potential energy low in the MCR. The success of this density modeling algorithm in the face of such apparently contradictory geophysical properties suggests that it may be applicable to a variety of tectonic and geodynamic problems.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2015GC005961","usgsCitation":"Levandowski, W.B., Boyd, O.S., Briggs, R.W., and Gold, R.D., 2015, A random-walk algorithm for modeling lithospheric density and the role of body forces in the evolution of the Midcontinent Rift: Geochemistry, Geophysics, Geosystems, v. 16, no. 12, p. 4084-4107, https://doi.org/10.1002/2015GC005961.","productDescription":"24 p.","startPage":"4084","endPage":"4107","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070530","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":471708,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015gc005961","text":"Publisher Index Page"},{"id":311381,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa, Kansas, Michigan, Minnesota, Nebraska, Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.0009765625,\n 48.545705491847464\n ],\n [\n -87.6708984375,\n 48.864714761802794\n ],\n [\n -89.7802734375,\n 48.40003249610685\n ],\n [\n -92.5048828125,\n 47.27922900257082\n ],\n [\n -93.955078125,\n 45.767522962149904\n ],\n [\n -95.1416015625,\n 44.74673324024678\n ],\n [\n -95.6689453125,\n 43.32517767999296\n ],\n [\n -96.064453125,\n 42.65012181368025\n ],\n [\n -96.6796875,\n 41.11246878918086\n ],\n [\n -97.6904296875,\n 39.232253141714885\n ],\n [\n -97.998046875,\n 37.64903402157866\n ],\n [\n -95.49316406249999,\n 37.43997405227057\n ],\n [\n -94.3505859375,\n 38.95940879245423\n ],\n [\n -91.97753906249999,\n 41.178653972331695\n ],\n [\n -91.4501953125,\n 42.19596877629178\n ],\n [\n -91.0546875,\n 43.58039085560786\n ],\n [\n -90.791015625,\n 44.96479793033104\n ],\n [\n -89.69238281249999,\n 45.89000815866184\n ],\n [\n -87.4951171875,\n 46.49839225859763\n ],\n [\n -86.0009765625,\n 48.545705491847464\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"12","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-12","publicationStatus":"PW","scienceBaseUri":"564b0c3de4b0ebfbef0d3128","contributors":{"authors":[{"text":"Levandowski, William Brower 0000-0003-4903-5012 wlevandowski@usgs.gov","orcid":"https://orcid.org/0000-0003-4903-5012","contributorId":5729,"corporation":false,"usgs":true,"family":"Levandowski","given":"William","email":"wlevandowski@usgs.gov","middleInitial":"Brower","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":579838,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boyd, Oliver S. 0000-0001-9457-0407 olboyd@usgs.gov","orcid":"https://orcid.org/0000-0001-9457-0407","contributorId":140739,"corporation":false,"usgs":true,"family":"Boyd","given":"Oliver","email":"olboyd@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":579839,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Briggs, Richard W. 0000-0001-8108-0046 rbriggs@usgs.gov","orcid":"https://orcid.org/0000-0001-8108-0046","contributorId":139002,"corporation":false,"usgs":true,"family":"Briggs","given":"Richard","email":"rbriggs@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":579840,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gold, Ryan D. 0000-0002-4464-6394 rgold@usgs.gov","orcid":"https://orcid.org/0000-0002-4464-6394","contributorId":3883,"corporation":false,"usgs":true,"family":"Gold","given":"Ryan","email":"rgold@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":579841,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70160379,"text":"70160379 - 2015 - Declining acidic deposition begins reversal of forest-soil acidification in the northeastern U.S. and eastern Canada","interactions":[],"lastModifiedDate":"2015-12-18T14:45:15","indexId":"70160379","displayToPublicDate":"2015-10-23T00:00:00","publicationYear":"2015","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":"Declining acidic deposition begins reversal of forest-soil acidification in the northeastern U.S. and eastern Canada","docAbstract":"Decreasing trends in acidic deposition levels over the past several decades have led to partial chemical recovery of surface waters. However, depletion of soil Ca from acidic deposition has slowed surface water recovery and led to the impairment of both aquatic and terrestrial ecosystems. Nevertheless, documentation of acidic deposition effects on soils has been limited, and little is known regarding soil responses to ongoing acidic deposition decreases. In this study, resampling of soils in eastern Canada and the northeastern U.S. was done at 27 sites exposed to reductions in wet SO42– deposition of 5.7–76%, over intervals of 8–24 y. Decreases of exchangeable Al in the O horizon and increases in pH in the O and B horizons were seen at most sites. Among all sites, reductions in SO42– deposition were positively correlated with ratios (final sampling/initial sampling) of base saturation (P < 0.01) and negatively correlated with exchangeable Al ratios (P < 0.05) in the O horizon. However, base saturation in the B horizon decreased at one-third of the sites, with no increases. These results are unique in showing that the effects of acidic deposition on North American soils have begun to reverse.
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group.","interactions":[],"lastModifiedDate":"2017-09-08T10:20:59","indexId":"70159571","displayToPublicDate":"2015-10-23T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5015,"text":"Canadian Wildlife Biology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Gray Wolf (Canis lupus) dyad monthly association rates by demographic group.","docAbstract":"Preliminary data from GPS-collared wolves (Canis lupus) in the Superior National Forest of northeastern Minnesota indicated wolves had low association rates with packmates during summer. However, aerial-telemetry locations of very high frequency (VHF)-radioed wolves in this same area showed high associations among packmates during winter. We analyzed aerial-telemetry-location data from VHF-collared wolves in several packs (n=18 dyads) in this same area from 1994-2012 by month, and found lowest association rates occurred during June. While other studies have found low association among wolf packmates during summer, information on differences in association patterns depending on the wolf associates’ demographics is sparse. During May-July, association rates were greatest for breeding pairs, followed by sibling dyads, and lowest for parent– offspring dyads. Our findings improve our understanding of how individual wolf relationships affect monthly association rates. We highlight some important remaining questions regarding wolf packmate associations.
","language":"English","publisher":"Canadian Wildlife Biology and Management","usgsCitation":"Barber-Meyer, S., and Mech, L.D., 2015, Gray Wolf (Canis lupus) dyad monthly association rates by demographic group.: Canadian Wildlife Biology and Management, v. 4, no. 2, p. 163-168.","productDescription":"6 p.","startPage":"163","endPage":"168","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065091","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":323864,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":311109,"type":{"id":15,"text":"Index Page"},"url":"https://cwbm.name/gray-wolf-canis-lupus-dyad-monthly-association-rates-by-demographic-group/"}],"country":"United States","state":"Minnesota","otherGeospatial":"Superior National Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.845703125,\n 47.89148526708789\n ],\n [\n -91.845703125,\n 47.954064687296885\n ],\n [\n -91.73652648925781,\n 47.954064687296885\n ],\n [\n -91.73652648925781,\n 47.89148526708789\n ],\n [\n -91.845703125,\n 47.89148526708789\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"4","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57651f35e4b07657d19c78a5","contributors":{"authors":[{"text":"Barber-Meyer, Shannon M. 0000-0002-3048-2616 sbarber-meyer@usgs.gov","orcid":"https://orcid.org/0000-0002-3048-2616","contributorId":147904,"corporation":false,"usgs":true,"family":"Barber-Meyer","given":"Shannon M.","email":"sbarber-meyer@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":579521,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mech, L. David 0000-0003-3944-7769 david_mech@usgs.gov","orcid":"https://orcid.org/0000-0003-3944-7769","contributorId":2518,"corporation":false,"usgs":true,"family":"Mech","given":"L.","email":"david_mech@usgs.gov","middleInitial":"David","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":579522,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70159480,"text":"70159480 - 2015 - Green turtles (Chelonia mydas) have novel asymmetrical antibodies","interactions":[],"lastModifiedDate":"2015-11-23T13:18:12","indexId":"70159480","displayToPublicDate":"2015-10-23T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2350,"text":"Journal of Immunology","active":true,"publicationSubtype":{"id":10}},"title":"Green turtles (Chelonia mydas) have novel asymmetrical antibodies","docAbstract":"Igs in vertebrates comprise equally sized H and L chains, with exceptions such as H chain–only Abs in camels or natural Ag receptors in sharks. In Reptilia, Igs are known as IgYs. Using immunoassays with isotype-specific mAbs, in this study we show that green turtles (Chelonia mydas) have a 5.7S 120-kDa IgY comprising two equally sized H/L chains with truncated Fc and a 7S 200-kDa IgY comprised of two differently sized H chains bound to L chains and apparently often noncovalently associated with an antigenically related 90-kDa moiety. Both the 200- and 90-kDa 7S molecules are made in response to specific Ag, although the 90-kDa molecule appears more prominent after chronic Ag stimulation. Despite no molecular evidence of a hinge, electron microscopy reveals marked flexibility of Fab arms of 7S and 5.7S IgY. Both IgY can be captured with protein G or melon gel, but less so with protein A. Thus, turtle IgY share some characteristics with mammalian IgG. However, the asymmetrical structure of some turtle Ig and the discovery of an Ig class indicative of chronic antigenic stimulation represent striking advances in our understanding of immunology.
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A marked decline in pronghorn numbers on the\nCPNM (from approximately 200 to <30 individuals from 1989 to 2011)\nprompted a study of fawn habitat use and fawn survival from 2009 to\n2011. Only 45 fawns were born during this period. We attached GPS\ncollars to 44% of these fawns (<5 days-of-age). We then used the locations\nof collared fawns to develop two separate binary logistic regression\nmodels to explore the best combination of micro- and macrohabitat-scale\nenvironmental variables for predicting (1) fawn habitat selection and\n(2) fawn survival. Model results for habitat selection showed that fawn\nlocations were associated with increased concealment at close distances (5\nm and 50 m) and decreased concealment at far distances (100 m). Fawn\nlocations were on lower sloped terrain and closer to available drinking\nwater and saltbush (Atriplex spp.). Model results for fawn survival showed\nthat increased survival time was associated with higher sloped terrain,\nproximity to available drinking water and saltbush, and increased distance\nfrom high-use roads. Collectively, these results demonstrate that fawn\nhabitat selection is scale-dependent and likely influenced by the combined\nspatio-temporal needs of both females and their young. 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Center","active":true,"usgs":true}],"preferred":true,"id":638594,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Longshore, Kathleen M. 0000-0001-6621-1271 longshore@usgs.gov","orcid":"https://orcid.org/0000-0001-6621-1271","contributorId":2677,"corporation":false,"usgs":true,"family":"Longshore","given":"Kathleen","email":"longshore@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":638593,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lowrey, Chris E. 0000-0001-5084-7275 clowrey@usgs.gov","orcid":"https://orcid.org/0000-0001-5084-7275","contributorId":3225,"corporation":false,"usgs":true,"family":"Lowrey","given":"Chris","email":"clowrey@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":638595,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, Daniel B.","contributorId":97829,"corporation":false,"usgs":true,"family":"Thompson","given":"Daniel B.","affiliations":[],"preferred":false,"id":638596,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70157183,"text":"sir20155127 - 2015 - Characteristics of sediment transport at selected sites along the Missouri River, 2011–12","interactions":[],"lastModifiedDate":"2015-10-22T15:08:55","indexId":"sir20155127","displayToPublicDate":"2015-10-22T15:00:00","publicationYear":"2015","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":"2015-5127","title":"Characteristics of sediment transport at selected sites along the Missouri River, 2011–12","docAbstract":"Extreme flooding in the Missouri River in 2011, followed by a year of more typical streamflows in 2012, allowed the sediment-transport regime to be compared between the unprecedented conditions of 2011 and the year immediately following the flooding. As part of a cooperative effort between the U.S. Geological Survey and the U.S. Army Corps of Engineers, this report follows up U.S. Geological Survey Scientific Investigations Report 2013–5006 by comparing sediment transport between years and among sampling sites spanning the Garrison Segment in North Dakota, the Gavins Point Segment downstream from Lewis and Clark Lake, and a part of the Channelized Segment along the Nebraska-Iowa border. Suspended sediment, bed material, bedload, and streamflow data from June 2011 through November 2012 were designated as “measured” total loads, wash loads, and bed-material loads; and, alternatively, were applied to the Modified-Einstein Procedure to compute sediment loads that were designated as “estimated” total loads.
\nBeyond the expected result that sediment loads were much lower during typical streamflows than those measured during the flooding, the measured data indicated some localized sediment-transport processes for further examination. Extreme and prolonged flooding can temporarily deplete sediment supplies locally, and evidence indicating such depletion was present at some sites. Unexpectedly high bed-material loads in the Gavins Point Segment may reflect episodic bar erosion just upstream from the sampling site. The relative contribution of bedload was typically 10 percent or less of the total load during the flooding. Following the flooding, this relative amount increased at some sites but not others, the reasons for which are possibly related to differences in stream velocity. Ultimately, the bedload decreased as it entered the Channelized Segment because of increased velocity and the turbulent mixing ability of the river as compared to the Gavins Point Segment. This turbulent mixing may also convert bed-material load into wash load, thereby rendering those sediments unavailable for creating sandbars and other bedforms. Though some of the sampling data support this premise, it was not consistently manifested by differences between the sediment load of the two segments during typical-streamflow conditions.
\nThe Modified-Einstein Procedure tended to predict greater total-sediment loads when compared to measured values. These differences may be the result of sediment deficits in the Missouri River that lead to an overprediction by the Modified-Einstein Procedure, the unsampled zone above the streambed that leads to an underprediction by the suspended sampler, or general uncertainty in the sampling approach. The differences between total-sediment load obtained through measurements and that estimated from applied theoretical procedures such as the Modified-Einstein Procedure pose a challenge for reliably characterizing total-sediment transport. Though it is not clear which of the two techniques is more accurate, the general tendency of the two to be within an order of magnitude of one another may be adequate for many sediment studies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155127","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Omaha District","usgsCitation":"Rus, D.L., Galloway, J.M., and Alexander, J.S., 2015, Characteristics of sediment transport at selected sites along the Missouri River, 2011–12: U.S. Geological Survey Scientific Investigations Report 2015–5127, 34 p., https://dx.doi.org/10.3133/sir20155127.","productDescription":"v, 34 p.","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2011-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-055952","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":310206,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5127/coverthb.jpg"},{"id":310207,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5127/sir20155127.pdf","text":"Report","size":"1.34 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5127"}],"country":"United States","state":"Iowa, Kansas, Missouri, Nebraska, North Dakota, South Dakota","otherGeospatial":"Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.087890625,\n 38.685509760012\n ],\n [\n -93.42773437499999,\n 40.613952441166596\n ],\n [\n -95.2734375,\n 43.51668853502909\n ],\n [\n -97.18505859374999,\n 45.90529985724796\n ],\n [\n -101.162109375,\n 47.90161354142077\n ],\n [\n -102.9638671875,\n 47.79839667295524\n ],\n [\n -101.62353515625,\n 43.992814500489914\n ],\n [\n -97.53662109375,\n 41.77131167976407\n ],\n [\n -94.9658203125,\n 38.5825261593533\n ],\n [\n -92.08740234375,\n 38.16911413556086\n ],\n [\n -90,\n 38.444984668894705\n ],\n [\n -90.087890625,\n 38.685509760012\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, Nebraska 68512
http://ne.water.usgs.gov/
The availability of land cover data at local scales is an important component in forest management and monitoring efforts. Regional land cover data seldom provide detailed information needed to support local management needs. Here we present a transferable framework to model forest cover by major plant functional type using aerial photos, multi-date Système Pour l’Observation de la Terre (SPOT) imagery, and topographic variables. We developed probability of occurrence models for deciduous broad-leaved forest and needle-leaved evergreen forest using logistic regression in the southern portion of the Wyoming Basin Ecoregion. The model outputs were combined into a synthesis map depicting deciduous and coniferous forest cover type. We evaluated the models and synthesis map using a field-validated, independent data source. Results showed strong relationships between forest cover and model variables, and the synthesis map was accurate with an overall correct classification rate of 0.87 and Cohen’s kappa value of 0.81. The results suggest our method adequately captures the functional type, size, and distribution pattern of forest cover in a spatially heterogeneous landscape.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/2150704X.2015.1072289","usgsCitation":"Assal, T.J., Anderson, P.J., and Sibold, J., 2015, Mapping forest functional type in a forest-shrubland ecotone using SPOT imagery and predictive habitat distribution modelling: Remote Sensing Letters, v. 6, no. 10, p. 755-764, https://doi.org/10.1080/2150704X.2015.1072289.","productDescription":"10 p.","startPage":"755","endPage":"764","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066673","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":310373,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Utah, Wyoming","otherGeospatial":"Wyoming Basin Ecoregion","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.8740234375,\n 40.052847601823984\n ],\n [\n -110.8740234375,\n 41.9921602333763\n ],\n [\n -107.830810546875,\n 41.9921602333763\n ],\n [\n -107.830810546875,\n 40.052847601823984\n ],\n [\n -110.8740234375,\n 40.052847601823984\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","issue":"10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-21","publicationStatus":"PW","scienceBaseUri":"5629faa5e4b011227bf1fd18","contributors":{"authors":[{"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":577979,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Patrick J. 0000-0003-2281-389X andersonpj@usgs.gov","orcid":"https://orcid.org/0000-0003-2281-389X","contributorId":3590,"corporation":false,"usgs":true,"family":"Anderson","given":"Patrick","email":"andersonpj@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":577980,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sibold, Jason","contributorId":10724,"corporation":false,"usgs":false,"family":"Sibold","given":"Jason","affiliations":[],"preferred":false,"id":577981,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70157435,"text":"ofr20151162 - 2015 - U.S. Geological Survey Chesapeake science strategy, 2015-2025—Informing ecosystem management of America’s largest estuary","interactions":[],"lastModifiedDate":"2021-07-02T13:51:41.782847","indexId":"ofr20151162","displayToPublicDate":"2015-10-22T11:15:00","publicationYear":"2015","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":"2015-1162","title":"U.S. Geological Survey Chesapeake science strategy, 2015-2025—Informing ecosystem management of America’s largest estuary","docAbstract":"The U.S. Geological Survey (USGS) has the critical role of providing scientific information to improve the understanding and management of the Chesapeake Bay ecosystem. The USGS works with Federal, State, and academic science partners to provide research and monitoring, and communicate results of these activities to enhance ecosystem management for both the Chesapeake and other National ecosystems. The USGS Chesapeake Science Strategy was prepared to guide science activities to address the Chesapeake Bay Watershed Agreement (2014–2025), to support the Department of the Interior (DOI) involvement in the Bay restoration efforts, and align with the USGS Mission Area (MA) Science strategies.
\nThe Chesapeake Bay is our Nation’s largest estuary, and provides critical goods and services to the people, fish, and wildlife that use the 64,000-square-mile watershed. The Chesapeake Bay watershed contains over 3,600 species of fish, wildlife, and plants and provides spawning grounds for many ecologically and economically important species including striped bass and blue crabs. The Bay watershed lies in the heart of the Atlantic Flyway and has 29 species of waterfowl, about 1 million of which winter in the region. The size of the Chesapeake seafood harvest is third in the Nation, only behind the Atlantic and Pacific Oceans. Along with agricultural production, tourism, and recreation, the estimated economic value of the services from the Chesapeake Bay watershed is about $100 billion annually. However, the health of the Bay ecosystem began to decline at the beginning of the 20th century due to overfishing and increasing human population and associated land change.
\nThe Chesapeake Bay Program (CBP) is the Federal-State cooperative effort that started in 1983 to restore the Bay and watershed. Given the ecological and economic importance of the Chesapeake ecosystem, President Obama issued an Executive Order (EO) in 2009 for increased Federal leadership in the CBP to enhance the pace of restoration, and the supporting strategy was released in 2010. The EO directed the Federal Government, including the U.S. Department of the Interior (DOI), represented by the National Park Service (NPS), the U.S. Fish & Wildlife Service (FWS), and the USGS, to expand its efforts and increase leadership to restore the Bay and its watershed. The USGS and other Federal agencies expanded their activities in 2011 to meet the President’s Chesapeake EO. Since the EO was released, there have been several important changes in the USGS, DOI, and the CBP including: (1) the Chesapeake Bay Watershed Agreement, (2) increased DOI leadership in the CBP, and (3) the release of the USGS MA science strategies. The EO strategy served as a foundation for the Chesapeake Bay Watershed Agreement that was signed in 2014 by the CBP Partners, and has goals and outcomes to be met by 2025.
\nThe USGS developed the Chesapeake Science Strategy to guide our activities to address the Chesapeake Bay Watershed Agreement, DOI leadership in the CBP, and USGS MA strategies. Improving the understanding of fish and wildlife population and health, and the factors affecting their condition is the emphasis of the Strategy. The science focuses on documenting the critical ecosystem connections in the Chesapeake, and providing implications to enhance decision making for restoration and conservation activities.
\nThe revised Strategy has four themes that address 7 of the 10 goals in the Chesapeake Bay Watershed Agreement:
\nThe structure and function of biological communities of the Bay and its watershed are extremely complex and are affected by a variety of stressors and conditions. To better define the issues being addressed, the USGS has developed cross-cutting questions that define some of the most important scientific challenges where multiple disciplines and collaborators are needed to address an issue. The initial questions include:
\nChesapeake Bay Coordinator
Northeast Region
U.S. Geological Survey
12201 Sunrise Valley Drive, Mail Stop 953
Reston, VA 20192
http://chesapeake.usgs.gov