Contours maps (such as topographic maps) compress the information of a function over a two-dimensional area into a discrete set of closed lines that connect points of equal value (isolines), striking a fine balance between expressiveness and cognitive simplicity. They allow humans to perform many common sense reasoning tasks about the underlying function (e.g. elevation).
\nThis paper analyses and formalizes contour semantics in a first-order logic ontology that forms the basis for enabling computational common sense reasoning about contour information. The elicited contour semantics comprises four key concepts – contour regions, contour lines, contour values, and contour sets – and their subclasses and associated relations, which are grounded in an existing qualitative spatial ontology. All concepts and relations are illustrated and motivated by physical-geographic features identifiable on topographic contour maps. The encoding of the semantics of contour concepts in first-order logic and a derived conceptual model as basis for an OWL ontology lay the foundation for fully automated, semantically-aware qualitative and quantitative reasoning about contours.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Spatial information theory: 12th International Conference, COSIT 2015 Santa Fe, NM, USA, October 12–16, 2015, proceedings","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-319-23374-1_18","usgsCitation":"Usery, E.L., and Hahmann, T., 2015, What is in a contour map? A region-based logical formalization of contour semantics, chap. of Spatial information theory: 12th International Conference, COSIT 2015 Santa Fe, NM, USA, October 12–16, 2015, proceedings, v. 9368, p. 375-399, https://doi.org/10.1007/978-3-319-23374-1_18.","productDescription":"25 p.","startPage":"375","endPage":"399","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065389","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":311569,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9368","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-15","publicationStatus":"PW","scienceBaseUri":"564ef2bbe4b064dd1d095566","contributors":{"authors":[{"text":"Usery, E. Lynn 0000-0002-2766-2173 usery@usgs.gov","orcid":"https://orcid.org/0000-0002-2766-2173","contributorId":231,"corporation":false,"usgs":true,"family":"Usery","given":"E.","email":"usery@usgs.gov","middleInitial":"Lynn","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":580288,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hahmann, Torsten","contributorId":149994,"corporation":false,"usgs":false,"family":"Hahmann","given":"Torsten","email":"","affiliations":[{"id":17881,"text":"Assistant Professor, University of Maine","active":true,"usgs":false}],"preferred":false,"id":580289,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70159728,"text":"70159728 - 2015 - Biofilm formation of Francisella noatunensis subsp. orientalis","interactions":[],"lastModifiedDate":"2016-12-19T11:59:44","indexId":"70159728","displayToPublicDate":"2015-11-19T12:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3685,"text":"Veterinary Microbiology","active":true,"publicationSubtype":{"id":10}},"title":"Biofilm formation of Francisella noatunensis subsp. orientalis","docAbstract":"Francisella noatunensis subsp. orientalis (Fno) is an emergent fish pathogen in both marine and fresh water environments. The bacterium is suspected to persist in the environment even without the presence of a suitable fish host. In the present study, the influence of different abiotic factors such as salinity and temperature were used to study the biofilm formation of different isolates of Fno including intracellular growth loci C (iglC)and pathogenicity determinant protein A (pdpA) knockout strains. Finally, we compared the susceptibility of planktonic and biofilm to three disinfectants used in the aquaculture and ornamental fish industry, namely Virkon®, bleach and hydrogen peroxide. The data indicates that Fno is capable of producing biofilms within 24 h where both salinity as well as temperature plays a role in the growth and biofilm formation of Fno. Mutations in theiglC or pdpA, both known virulence factors, do not appear to affect the capacity of Fno to produce biofilms, and the minimum inhibitory concentration, and minimum biocidal concentration for the three disinfectants were lower than the minimum biofilm eradication concentration values. This information needs to be taken into account if trying to eradicate the pathogen from aquaculture facilities or aquariums.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.vetmic.2015.10.007","usgsCitation":"Soto, E., Halliday-Wimmonds, I., Francis, S., Kearney, M.T., and Hansen, J.D., 2015, Biofilm formation of Francisella noatunensis subsp. orientalis: Veterinary Microbiology, v. 181, no. 3-4, p. 313-317, https://doi.org/10.1016/j.vetmic.2015.10.007.","productDescription":"5 p.","startPage":"313","endPage":"317","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061353","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":311568,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"181","issue":"3-4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"564ef2b5e4b064dd1d095552","contributors":{"authors":[{"text":"Soto, Esteban","contributorId":64142,"corporation":false,"usgs":true,"family":"Soto","given":"Esteban","email":"","affiliations":[],"preferred":false,"id":580224,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Halliday-Wimmonds, Iona","contributorId":149970,"corporation":false,"usgs":false,"family":"Halliday-Wimmonds","given":"Iona","email":"","affiliations":[{"id":17866,"text":"Department of Biomedical Sciences, Ross University School of Veterinary Medicine, PO Box 334, Basseterre, St. Kitts, West Indies","active":true,"usgs":false}],"preferred":false,"id":580225,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Francis, Stewart","contributorId":177541,"corporation":false,"usgs":false,"family":"Francis","given":"Stewart","email":"","affiliations":[],"preferred":false,"id":656130,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kearney, Michael T.","contributorId":149971,"corporation":false,"usgs":false,"family":"Kearney","given":"Michael","email":"","middleInitial":"T.","affiliations":[{"id":17867,"text":"Department of Pathobiological Sciences, School of Veterinary Medicine, Louisiana State University, Baton Rouge, Louisiana, USA 70803","active":true,"usgs":false}],"preferred":false,"id":580226,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hansen, John D. 0000-0002-3006-2734 jhansen@usgs.gov","orcid":"https://orcid.org/0000-0002-3006-2734","contributorId":3440,"corporation":false,"usgs":true,"family":"Hansen","given":"John","email":"jhansen@usgs.gov","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":580223,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70154881,"text":"70154881 - 2015 - Assessment and Mmanagement of North American horseshoe crab populations, with emphasis on a multispecies framework for Delaware Bay, U.S.A. populations: Chapter 24","interactions":[],"lastModifiedDate":"2016-08-17T11:33:56","indexId":"70154881","displayToPublicDate":"2015-11-19T12:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Assessment and Mmanagement of North American horseshoe crab populations, with emphasis on a multispecies framework for Delaware Bay, U.S.A. populations: Chapter 24","docAbstract":"The horseshoe crab fishery on the US Atlantic coast represents a compelling fishery management story for many reasons, including ecological complexity, health and human safety ramifications, and socio-economic conflicts. Knowledge of stock status and assessment and monitoring capabilities for the species have increased greatly in the last 15 years and permitted managers to make more informed harvest recommendations. Incorporating the bioenergetics needs of migratory shorebirds, which feed on horseshoe crab eggs, into the management framework for horseshoe crabs was identified as a goal, particularly in the Delaware Bay region where the birds and horseshoe crabs exhibit an important ecological interaction. In response, significant effort was invested in studying the population dynamics, migration ecology, and the ecologic relationship of a key migratory shorebird, the Red Knot, to horseshoe crabs. A suite of models was developed that linked Red Knot populations to horseshoe crab populations through a mass gain function where female spawning crab abundance determined what proportion of the migrating Red Knot population reached a critical body mass threshold. These models were incorporated in an adaptive management framework wherein optimal harvest decisions for horseshoe crab are recommended based on several resource-based and value-based variables and thresholds. The current adaptive framework represents a true multispecies management effort where additional data over time are employed to improve the predictive models and reduce parametric uncertainty. The possibility of increasing phenologic asynchrony between the two taxa in response to climate change presents a potential challenge to their ecologic interaction in Delaware Bay.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Changing Global Perspectives on Horseshoe Crab Biology, Conservation and Management","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","publisherLocation":"Cham","doi":"10.1007/978-3-319-19542-1_24","usgsCitation":"Millard, M.J., Sweka, J.A., McGowan, C., and Smith, D., 2015, Assessment and Mmanagement of North American horseshoe crab populations, with emphasis on a multispecies framework for Delaware Bay, U.S.A. populations: Chapter 24, chap. of Changing Global Perspectives on Horseshoe Crab Biology, Conservation and Management, p. 407-431, https://doi.org/10.1007/978-3-319-19542-1_24.","startPage":"407","endPage":"431","numberOfPages":"25","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059817","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":326655,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57b58abee4b03bcb0104bb5e","contributors":{"authors":[{"text":"Millard, Michael J.","contributorId":23411,"corporation":false,"usgs":false,"family":"Millard","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":645754,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sweka, John A.","contributorId":80945,"corporation":false,"usgs":true,"family":"Sweka","given":"John","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":645755,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGowan, Conor P. cmcgowan@usgs.gov","contributorId":145496,"corporation":false,"usgs":true,"family":"McGowan","given":"Conor P.","email":"cmcgowan@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":564308,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, David R.","contributorId":173756,"corporation":false,"usgs":false,"family":"Smith","given":"David R.","affiliations":[],"preferred":false,"id":645756,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159331,"text":"sir20155154 - 2015 - Streambed scour evaluations and conditions at selected bridge sites in Alaska, 2012","interactions":[],"lastModifiedDate":"2022-03-15T17:20:23.416494","indexId":"sir20155154","displayToPublicDate":"2015-11-19T12:00:00","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":"2015-5154","title":"Streambed scour evaluations and conditions at selected bridge sites in Alaska, 2012","docAbstract":"Streambed scour potential was evaluated at 18 river- and stream-spanning bridges in Alaska that have unknown foundation details or a lack of existing scour analysis. All sites were evaluated for stream stability and long-term scour potential. Contraction scour and abutment scour were calculated for 17 bridges, and pier scour was calculated for 7 bridges that had piers. Vertical contraction (pressure flow) scour was calculated for sites with overtopping floods (where the modeled water surface was higher than the superstructure of the bridge). In most cases, hydraulic models of the 1- and 0.2-percent annual exceedance probability floods (also known as the 100- and 500-year floods, respectively) were used to derive hydraulic variables for the scour calculations. Alternate flood values were used in scour calculations for sites where smaller floods overtopped a bridge or where standard flood-frequency estimation techniques did not apply. Scour was also calculated for large recorded floods at several sites. Equations for scour in cohesive soils were used for sites where streambed sediment was silt-sized or smaller.
\nChannel instability at four sites was related to human activities (in-channel mining, dredging, and channel relocation). Three of the dredged sites are located on active unstable alluvial fans and were graded to inhibit aggradation. The trend toward aggradation during major floods at these sites greatly reduces confidence in scour estimates.
\nVertical contraction and pressure flow occurred during 1 percent or smaller annual exceedance probability floods at five sites, including three aggradation sites. Contraction scour exceeded 5 feet at two sites, and total scour at piers (pier scour plus contraction scour) exceeded 5 feet at two sites. Debris accumulation increased calculated pier scour at six sites by an average of 1.2 feet. Total scour at abutments including contraction scour exceeded 5 feet at seven sites. Scour estimates seemed excessive at aggradation sites where upstream sediment supply controls scour and deposition processes, at cohesive soil sites where conservative assumptions were made for soil strength and flood duration, and for abutment scour at sites where failure of the embankment and attendant channel widening would reduce scour.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155154","collaboration":"Prepared in cooperation with the Alaska Department of Transporation and Public Facilities","usgsCitation":"Beebee, R.A., and Schauer, P.V., 2015, Streambed scour evaluations and conditions at selected bridge sites in Alaska, 2012: U.S. Geological Survey Scientific Investigations Report 2015–5154, 45 p., https://dx.doi.org/10.3133/sir20155154.","productDescription":"Report: vi, 45 p.; Appendix","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2012-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-064803","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":311582,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5154/sir20155154_appendixa.xlsx","text":"Appendix A","size":"105 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5154 Appendix A"},{"id":311546,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5154/sir20155154.pdf","text":"Report","size":"3.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5154 PDF"},{"id":311545,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5154/coverthb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -131.748046875,\n 54.265224078605655\n ],\n [\n -129.7265625,\n 55.37911044801047\n ],\n [\n -131.044921875,\n 56.70450561416937\n ],\n [\n -135.439453125,\n 59.80063426102869\n ],\n [\n -137.63671875,\n 59.265880628258095\n ],\n [\n -139.658203125,\n 60.326947742998414\n ],\n [\n -140.888671875,\n 60.413852350464914\n ],\n [\n -141.064453125,\n 67.57571741708057\n ],\n [\n -145.546875,\n 67.60922060496382\n ],\n [\n -149.677734375,\n 66.65297740055279\n ],\n [\n -154.16015625,\n 64.20637724320852\n ],\n [\n -154.16015625,\n 61.98026726504402\n ],\n [\n -152.666015625,\n 59.80063426102869\n ],\n [\n -151.962890625,\n 59.085738569819505\n ],\n [\n -148.359375,\n 59.80063426102869\n ],\n [\n -146.162109375,\n 60.45721779774397\n ],\n [\n -142.91015625,\n 59.84481485969105\n ],\n [\n -140.44921875,\n 59.712097173322924\n ],\n [\n -136.845703125,\n 58.03137242177637\n ],\n [\n -133.41796874999997,\n 54.316523240258284\n ],\n [\n -131.748046875,\n 54.265224078605655\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -154.86328125,\n 57.37393841871411\n ],\n [\n -152.578125,\n 58.53959476664049\n ],\n [\n -151.78710937499997,\n 58.07787626787517\n ],\n [\n -152.490234375,\n 57.18390185831188\n ],\n [\n -154.423828125,\n 56.559482483762245\n ],\n [\n -154.86328125,\n 57.37393841871411\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Alaska Science Center
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4210 University Drive
Anchorage, Alaska 99508-4560
http://alaska.usgs.gov
Piscine reovirus (PRV) is a double stranded non-enveloped RNA virus detected in farmed and wild salmonids. This study examined the phylogenetic relationships among different PRV sequence types present in samples from salmonids in Western Canada and the US, including Alaska (US), British Columbia (Canada) and Washington State (US). Tissues testing positive for PRV were partially sequenced for segment S1, producing 71 sequences that grouped into 10 unique sequence types. Sequence analysis revealed no identifiable geographical or temporal variation among the sequence types. Identical sequence types were found in fish sampled in 2001, 2005 and 2014. In addition, PRV positive samples from fish derived from Alaska, British Columbia and Washington State share identical sequence types. Comparative analysis of the phylogenetic tree indicated that Canada/US Pacific Northwest sequences formed a subgroup with some Norwegian sequence types (group II), distinct from other Norwegian and Chilean sequences (groups I, III and IV). Representative PRV positive samples from farmed and wild fish in British Columbia and Washington State were subjected to genome sequencing using next generation sequencing methods. Individual analysis of each of the 10 partial segments indicated that the Canadian and US PRV sequence types clustered separately from available whole genome sequences of some Norwegian and Chilean sequences for all segments except the segment S4. In summary, PRV was genetically homogenous over a large geographic distance (Alaska to Washington State), and the sequence types were relatively stable over a 13 year period.
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2015 - Estimating occupancy dynamics for large-scale monitoring networks: amphibian breeding occupancy across protected areas in the northeast United States","interactions":[],"lastModifiedDate":"2015-11-19T09:30:04","indexId":"70159743","displayToPublicDate":"2015-11-19T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Estimating occupancy dynamics for large-scale monitoring networks: amphibian breeding occupancy across protected areas in the northeast United States","docAbstract":"Regional monitoring strategies frequently employ a nested sampling design where a finite set of study areas from throughout a region are selected within which intensive sub-sampling occurs. This sampling protocol naturally lends itself to a hierarchical analysis to account for dependence among sub-samples. Implementing such an analysis within a classic likelihood framework is computationally prohibitive with species occurrence data when accounting for detection probabilities. Bayesian methods offer an alternative framework to make this analysis feasible. We demonstrate a general approach for estimating occupancy when data come from a nested sampling design. Using data from a regional monitoring program of wood frogs (Lithobates sylvaticus) and spotted salamanders (Ambystoma maculatum) in vernal pools, we analyzed data using static and dynamic occupancy frameworks. We analyzed observations from 2004-2013collected within 14 protected areas located throughout the northeast United States . We use the data set to estimate trends in occupancy at both the regional and individual protected area level. We show that occupancy at the regional level was relatively stable for both species. Much more variation occurred within individual study areas, with some populations declining and some increasing for both species. We found some evidence for a latitudinal gradient in trends among protected areas. However, support for this pattern is overestimated when the hierarchical nature of the data collection is not controlled for in the analysis. For both species, occupancy appeared to be declining in the most southern areas, while occupancy was stable or increasing in more northern areas. These results shed light on the range-level population status of these pond-breeding amphibians and our approach provides a framework that can be used to examine drivers of change including among-year and among-site variation in occurrence dynamics, while properly accounting for nested structure of data collection.
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Species in naturally intermittent streams display adaptations that enhance persistence during extreme events; however, the fate of populations in perennial streams during unprecedented low-flow periods is not well-understood. Biota requiring swift-flowing habitats may be especially vulnerable to flow reductions. We estimated the abundance and local survival of a native fluvial-dependent fish species (Etheostoma inscriptum) across 5 years encompassing historic low flows in a sixth-order southeastern USA perennial river. Based on capturemark-recapture data, the study shoal may have acted as a refuge during severe drought, with increased young-of-the-year (YOY) recruitment and occasionally high adult immigration. Contrary to expectations, summer and autumn survival rates (30 days) were not strongly depressed during low-flow periods, despite 25%-80% reductions in monthly discharge. Instead, YOY survival increased with lower minimum discharge and in response to small rain events that increased low-flow variability. Age-1+ fish showed the opposite pattern, with survival decreasing in response to increasing low-flow variability. Results from this population dynamics study of a small fish in a perennial river suggest that fluvial-dependent species can be resistant to extreme flow reductions through enhanced YOY recruitment and high survival
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2015 - Geotechnical effects of the 2015 magnitude 7.8 Gorkha, Nepal, earthquake and aftershocks","interactions":[],"lastModifiedDate":"2018-10-24T16:49:14","indexId":"70156260","displayToPublicDate":"2015-11-18T16:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Geotechnical effects of the 2015 magnitude 7.8 Gorkha, Nepal, earthquake and aftershocks","docAbstract":"This article summarizes the geotechnical effects of the 25 April 2015 M 7.8 Gorkha, Nepal, earthquake and aftershocks, as documented by a reconnaissance team that undertook a broad engineering and scientific assessment of the damage and collected perishable data for future analysis. Brief descriptions are provided of ground shaking, surface fault rupture, landsliding, soil failure, and infrastructure performance. The goal of this reconnaissance effort, led by Geotechnical Extreme Events Reconnaissance, is to learn from earthquakes and mitigate hazards in future earthquakes.
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This network includes 19 stations in the bay; currently, 8 stations are in operation (fig. 1). All eight stations are equipped with specific conductance (which can be related to salinity) and water-temperature sensors that record measurements at 15-minute intervals. Water quality in the bay constantly changes with the ocean tides and with seasonal and interannual differences in river inflows. Our network was designed to observe and characterize some of these changes in the bay across space and over time. Our data demonstrated a high degree of variability both in specific conductance and temperature at time scales from tidal to annual and also revealed longer term changes that are likely to influence overall environmental health in the bay (San Francisco Estuary Institute, 2014). Figure 1. Locations of fixed water-quality monitoring stations in San Francisco Bay, California, for the 2014 water year (October 1, 2013 to September 30, 2014).
\nIn water year (WY) 2014 (October 1, 2013, through September 30, 2014), our network measured record-high values of specific conductance and water temperature at several stations during a period of very little freshwater inflow from the Sacramento–San Joaquin Delta and other tributaries because of severe drought conditions in California. This report summarizes our observations for WY2014 and compares them to previous years that had different levels of freshwater inflow.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151213","usgsCitation":"Downing-Kunz, M.A., Work, P.A., and Shellenbarger, G.G., 2015, Record-high specific\nconductance and temperature in San Francisco Bay during water year 2014 (ver. 1.1,\nDecember 28, 2015): U.S. Geological Survey Open-File Report 2015–1213, 4 p.","productDescription":"4 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066727","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true}],"links":[{"id":311511,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1213/coverthb.jpg"},{"id":313213,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2015/1213/ofr20151213.txt","size":"2 KB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2015-1213 Version History"},{"id":311512,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1213/ofr20151213.pdf","text":"Report","size":"1.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1213"}],"country":"United States","state":"California","otherGeospatial":"Sacramento–San Joaquin Delta, San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.70379638671874,\n 37.933366792504366\n ],\n [\n -121.66534423828125,\n 38.04592811939912\n ],\n [\n -121.75048828124999,\n 38.11943249695316\n ],\n [\n -121.90979003906249,\n 38.151837403006766\n ],\n [\n -122.07183837890625,\n 38.18638677411551\n ],\n [\n -122.178955078125,\n 38.20797181420939\n ],\n [\n -122.26684570312499,\n 38.26621945628273\n ],\n [\n -122.39593505859376,\n 38.26621945628273\n ],\n [\n -122.55249023437501,\n 38.16047628099622\n ],\n [\n -122.61291503906249,\n 37.996162679728116\n ],\n [\n -122.5689697265625,\n 37.861844098370945\n ],\n [\n -122.53326416015624,\n 37.77505678240509\n ],\n [\n -122.45635986328124,\n 37.63815995799935\n ],\n [\n -122.39593505859376,\n 37.51626173528878\n ],\n [\n -122.24761962890625,\n 37.413800350662875\n ],\n [\n -122.06359863281249,\n 37.35487607348372\n ],\n [\n -121.85211181640625,\n 37.38107035775657\n ],\n [\n -121.86035156249999,\n 37.5249753680482\n ],\n [\n -122.03613281249999,\n 37.655557695625056\n ],\n [\n -122.15698242187499,\n 37.81846319511331\n ],\n [\n -122.25585937500001,\n 37.92903406232562\n ],\n [\n -122.25036621093749,\n 37.983174833513395\n ],\n [\n -122.18170166015625,\n 38.00049145082287\n ],\n [\n -121.981201171875,\n 37.996162679728116\n ],\n [\n -121.86584472656251,\n 37.96801944035648\n ],\n [\n -121.75048828124999,\n 37.93553306183642\n ],\n [\n -121.70379638671874,\n 37.933366792504366\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
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","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151196","issn":"2331-1258","usgsCitation":"Williamson, T.N., and Lant, J.G., 2015, User manuals for the Delaware River Basin Water Availability Tool for Environmental Resources (DRB–WATER) and associated WATER application utilities: U.S. Geological Survey Open-File Report 2015–1196, 32 p., https://dx.doi.org/10.3133/ofr20151196.","productDescription":"Report: vi, 32 p.; Database","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-066506","costCenters":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":311459,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/publication/sir20155143","text":"Scientific Investigations Report 2015-5143","description":"OFR 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U.S. Geological Survey
1770 Corporate Drive, Ste. 500
Norcross, GA 30093
678-524-1544
http://water.usgs.gov/watercensus/
The Water Availability Tool for Environmental Resources (WATER) is a decision support system for the nontidal part of the Delaware River Basin that provides a consistent and objective method of simulating streamflow under historical, forecasted, and managed conditions. In order to quantify the uncertainty associated with these simulations, however, streamflow and the associated hydroclimatic variables of potential evapotranspiration, actual evapotranspiration, and snow accumulation and snowmelt must be simulated and compared to long-term, daily observations from sites. This report details model development and optimization, statistical evaluation of simulations for 57 basins ranging from 2 to 930 km2 and 11.0 to 99.5 percent forested cover, and how this statistical evaluation of daily streamflow relates to simulating environmental changes and management decisions that are best examined at monthly time steps normalized over multiple decades. The decision support system provides a database of historical spatial and climatic data for simulating streamflow for 2001–11, in addition to land-cover and general circulation model forecasts that focus on 2030 and 2060. WATER integrates geospatial sampling of landscape characteristics, including topographic and soil properties, with a regionally calibrated hillslope-hydrology model, an impervious-surface model, and hydroclimatic models that were parameterized by using three hydrologic response units: forested, agricultural, and developed land cover. This integration enables the regional hydrologic modeling approach used in WATER without requiring site-specific optimization or those stationary conditions inferred when using a statistical model.
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1770 Corporate Drive, Ste. 500
Norcross, GA 30093
678-524-1544
http://water.usgs.gov/watercensus/
Mineral extraction and associated industries play an important role in the Afghan economy, particularly in the “transitional era” of declining foreign aid and withdrawal of foreign troops post 2014. In addition to providing a substantial source of government revenue, other potential benefits of natural resource development include boosted exports, employment opportunities, and strengthened industrialization (Joya, 2012). Continued exploration and investment in these industries has resulted in large economic improvements since 2007, when this series of studies was initiated. At that time, the “Preliminary Non-Fuel Mineral Resource Assessment of Afghanistan” was completed by members of the U.S. Geological Survey and Afghanistan Geological Survey (Peters and others, 2007). The assessment published a series of country-wide datasets, including a digital elevation model (DEM), elevation contours, hydrography, transportation routes, geophysics, and cultural datasets (Peters and others, 2007). It also delineated 20 mineralized areas for further study using a geologic-based methodology. A second data product, “Summaries of Important Areas for Mineral Investment and Production Opportunities of Nonfuel Minerals in Afghanistan,” was released by Peters and others in 2011. This work highlighted geologic, geohydrologic, and hyperspectral studies that were carried out in specific Areas of Interest (AOIs) to assess the location and characteristics of mineral resources. Also included in the 2011 publication is a collection of appendixes and inventories of Geographic Information System (GIS) datasets for each of the 24 identified AOIs. A third data product was released in 2013 (Casey and Chirico, 2013), publishing datasets for five different AOIs, two subareas, and one AOI extension. Each dataset contains vector shapefiles of the AOI boundary, streams, roads, and contours at 25-, 50-, and 100-meter (m) intervals, as well as raster files of the AOI’s DEM and hillshade.
\nThis work represents the fourth installment of the series, and publishes a dataset of eight new AOIs and one subarea within Afghanistan. These areas include Dasht-e-Nawar, Farah, North Ghazni, South Ghazni, Chakhansur, Godzareh East, Godzareh West, and Namaksar-e-Herat AOIs and the Central Bamyan subarea of the South Bamyan AOI (datasets for South Bamyan were published previously in Casey and Chirico, 2013). For each AOI and subarea, this dataset collection consists of the areal extent boundaries, elevation contours at 25-, 50-, and 100-m intervals, and an enhanced DEM. Hydrographic datasets covering the extent of four AOIs and one subarea are also included in the collection. The resulting raster and vector layers are intended for use by government agencies, developmental organizations, and private companies in Afghanistan to support mineral assessments, monitoring, management, and investment.
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Or
Jessica D. DeWitt
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Birds can cause extensive crop damage in the United States. In some regions, depredating species comprise a substantial portion of the total avian population, emphasizing their importance both economically and ecologically. We used the National Audubon Society Christmas Bird Count data from the south-central United States and mixed-effects models to identify habitat factors associated with population trend and abundance for 5 species: red-winged blackbird (Agelaius phoeniceus), common grackle (Quiscalus quiscula), rusty blackbird (Euphagus carolinus), Brewer’s blackbird (Euphagus cyanocephalus), and European starling (Sturnus vulgaris). Overall, we found positive associations between bird abundance and agricultural land-cover for all species. Relationships between abundance and other land-cover types were species-specific, often with contrasting relationships among species. Likewise, we found no consistent patterns among abundance and climate. Of the 5 species, only red-winged blackbirds had a significant population trend in our study area, increasing annually by 2.4%. There was marginal evidence to suggest population increases for rusty blackbirds, whereas all other species showed no trend in population size within our study area. Our study provides managers who are interested in limiting crop damage in the south-central United States with novel information on habitat associations in the region that could be used to improve management and control actions.
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Berryman Institute","publisherLocation":"Logan, UT","doi":"10.26077/mej7-v607","usgsCitation":"Strassburg, M., Crimmins, S.M., McKann, P.C., and Thogmartin, W.E., 2015, Winter habitat associations of blackbirds and starlings wintering in the south-central United States: Human-Wildlife Interactions, v. 9, no. 2, p. 171-179, https://doi.org/10.26077/mej7-v607.","productDescription":"9 p.","startPage":"171","endPage":"179","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053796","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":311495,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Arkansas, Kansas, Louisiana, Mississippi, Missouri, Oklahoma, Tennessee, Texas","otherGeospatial":"Mississippi Flyway","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -102.0849609375,\n 40.04443758460859\n ],\n [\n -95.2294921875,\n 40.111688665595956\n ],\n [\n -95.80078125,\n 40.613952441166596\n ],\n [\n -91.23046875,\n 40.613952441166596\n ],\n [\n -90.5712890625,\n 39.33429742980725\n ],\n [\n -89.4287109375,\n 37.50972584293751\n ],\n [\n -88.9013671875,\n 36.5978891330702\n ],\n [\n -81.5185546875,\n 36.77409249464195\n ],\n [\n -82.353515625,\n 35.24561909420681\n ],\n [\n -83.4521484375,\n 34.813803317113155\n ],\n [\n -85.60546875,\n 34.88593094075317\n ],\n [\n -85.0341796875,\n 32.509761735919426\n ],\n [\n -84.9462890625,\n 30.86451022625836\n ],\n [\n -87.62695312499999,\n 30.90222470517144\n ],\n [\n -87.3193359375,\n 30.29701788337205\n ],\n [\n -88.1982421875,\n 30.031055426540206\n ],\n [\n -89.07714843749999,\n 29.99300228455108\n ],\n [\n -88.72558593749999,\n 29.726222319395504\n ],\n [\n -88.59374999999999,\n 29.267232865200878\n ],\n [\n -89.82421875,\n 29.036960648558267\n ],\n [\n -91.4501953125,\n 29.036960648558267\n ],\n [\n -92.4169921875,\n 29.38217507514529\n ],\n [\n -93.8232421875,\n 29.34387539941801\n ],\n [\n -95.1416015625,\n 29.036960648558267\n ],\n [\n -96.328125,\n 28.22697003891834\n ],\n [\n -96.8994140625,\n 27.72243591897343\n ],\n [\n -97.0751953125,\n 26.980828590472107\n ],\n [\n -97.119140625,\n 26.352497858154\n ],\n [\n -97.998046875,\n 26.70635985763354\n ],\n [\n -99.49218749999999,\n 28.34306490482549\n ],\n [\n -101.0302734375,\n 31.80289258670676\n ],\n [\n -101.953125,\n 35.42486791930556\n ],\n [\n -102.9638671875,\n 36.949891786813296\n ],\n [\n -102.12890625,\n 37.125286284966776\n ],\n [\n -102.0849609375,\n 40.04443758460859\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"2","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"564da137e4b0112df6c62dd7","contributors":{"authors":[{"text":"Strassburg, Matthew","contributorId":139647,"corporation":false,"usgs":false,"family":"Strassburg","given":"Matthew","email":"","affiliations":[{"id":12813,"text":"Department of Biological Sciences, North Dakota State University","active":true,"usgs":false}],"preferred":false,"id":542195,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crimmins, Shawn M. 0000-0001-6229-5543 scrimmins@usgs.gov","orcid":"https://orcid.org/0000-0001-6229-5543","contributorId":5498,"corporation":false,"usgs":true,"family":"Crimmins","given":"Shawn","email":"scrimmins@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":542193,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McKann, Patrick C.","contributorId":149776,"corporation":false,"usgs":false,"family":"McKann","given":"Patrick","email":"","middleInitial":"C.","affiliations":[{"id":6733,"text":"former UMESC employee, USGS","active":true,"usgs":false}],"preferred":false,"id":542196,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":542197,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159815,"text":"70159815 - 2015 - Mapping physiological suitability limits for malaria in Africa under climate change","interactions":[],"lastModifiedDate":"2015-12-21T13:42:22","indexId":"70159815","displayToPublicDate":"2015-11-18T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3675,"text":"Vector-Borne and Zoonotic Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Mapping physiological suitability limits for malaria in Africa under climate change","docAbstract":"We mapped current and future temperature suitability for malaria transmission in Africa using a published model that incorporates nonlinear physiological responses to temperature of the mosquito vector Anopheles gambiae and the malaria parasite Plasmodium falciparum. We found that a larger area of Africa currently experiences the ideal temperature for transmission than previously supposed. Under future climate projections, we predicted a modest increase in the overall area suitable for malaria transmission, but a net decrease in the most suitable area. Combined with human population density projections, our maps suggest that areas with temperatures suitable for year-round, highest-risk transmission will shift from coastal West Africa to the Albertine Rift between the Democratic Republic of Congo and Uganda, whereas areas with seasonal transmission suitability will shift toward sub-Saharan coastal areas. Mapping temperature suitability places important bounds on malaria transmissibility and, along with local level demographic, socioeconomic, and ecological factors, can indicate where resources may be best spent on malaria control.
","language":"English","publisher":"Mary Ann Liebert, Inc.","publisherLocation":"New Rochelle, NY","doi":"10.1089/vbz.2015.1822","usgsCitation":"Ryan, S.J., McNally, A., Johnson, L., Mordecai, E., Ben-Horin, T., Paaijmans, K.P., and Lafferty, K.D., 2015, Mapping physiological suitability limits for malaria in Africa under climate change: Vector-Borne and Zoonotic Diseases, v. 15, no. 12, p. 718-725, https://doi.org/10.1089/vbz.2015.1822.","productDescription":"8 p.","startPage":"718","endPage":"725","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068714","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":471637,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1089/vbz.2015.1822","text":"Publisher Index Page"},{"id":311744,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Africa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -14.150390625,\n 33.211116472416855\n ],\n [\n -8.876953125,\n 35.460669951495305\n ],\n [\n -3.779296875,\n 36.4566360115962\n ],\n [\n 5.625,\n 37.85750715625203\n ],\n [\n 11.25,\n 37.78808138412046\n ],\n [\n 13.271484375,\n 35.96022296929667\n ],\n [\n 15.8203125,\n 34.30714385628804\n ],\n [\n 23.203125,\n 34.08906131584996\n ],\n [\n 32.6953125,\n 32.24997445586331\n ],\n [\n 33.92578125,\n 30.14512718337613\n ],\n [\n 44.12109374999999,\n 11.092165893502013\n ],\n [\n 46.845703125,\n 12.12526421833159\n ],\n [\n 51.240234375,\n 13.325484885597936\n ],\n [\n 52.64648437499999,\n 9.882275493429953\n ],\n [\n 51.15234375,\n 1.0546279422758869\n ],\n [\n 51.943359375,\n -7.18810087117902\n ],\n [\n 51.50390625,\n -21.207458730482642\n ],\n [\n 42.890625,\n -28.92163128242129\n ],\n [\n 36.474609375,\n -26.980828590472093\n ],\n [\n 30.585937499999996,\n -33.578014746143985\n ],\n [\n 16.875,\n -35.17380831799957\n ],\n [\n 7.998046875,\n -15.707662769583505\n ],\n [\n 9.404296875,\n -9.622414142924793\n ],\n [\n 5.537109374999999,\n -0.08789059053082422\n ],\n [\n 2.109375,\n 2.811371193331128\n ],\n [\n -4.21875,\n 1.7575368113083254\n ],\n [\n -11.953125,\n 2.28455066023697\n ],\n [\n -17.2265625,\n 7.013667927566642\n ],\n [\n -20.214843749999996,\n 14.093957177836236\n ],\n [\n -20.56640625,\n 21.37124437061832\n ],\n [\n -19.951171875,\n 26.745610382199022\n ],\n [\n -16.787109375,\n 31.728167146023935\n ],\n [\n -14.150390625,\n 33.211116472416855\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","issue":"12","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"565d813fe4b071e7ea54347c","contributors":{"authors":[{"text":"Ryan, Sadie J.","contributorId":102738,"corporation":false,"usgs":true,"family":"Ryan","given":"Sadie","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":580570,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McNally, Amy","contributorId":53225,"corporation":false,"usgs":true,"family":"McNally","given":"Amy","affiliations":[],"preferred":false,"id":580571,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Leah R.","contributorId":83382,"corporation":false,"usgs":true,"family":"Johnson","given":"Leah R.","affiliations":[],"preferred":false,"id":580572,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mordecai, Erin A.","contributorId":9113,"corporation":false,"usgs":true,"family":"Mordecai","given":"Erin A.","affiliations":[],"preferred":false,"id":580573,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ben-Horin, Tal","contributorId":58137,"corporation":false,"usgs":false,"family":"Ben-Horin","given":"Tal","email":"","affiliations":[],"preferred":false,"id":580574,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Paaijmans, Krijn P.","contributorId":62459,"corporation":false,"usgs":true,"family":"Paaijmans","given":"Krijn","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":580575,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":580569,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70142276,"text":"sir20105090V - 2015 - Porphyry copper assessment of the Tethys region of western and southern Asia: Chapter V in Global mineral resource assessment","interactions":[{"subject":{"id":70142276,"text":"sir20105090V - 2015 - Porphyry copper assessment of the Tethys region of western and southern Asia: Chapter V in Global mineral resource assessment","indexId":"sir20105090V","publicationYear":"2015","noYear":false,"chapter":"V","title":"Porphyry copper assessment of the Tethys region of western and southern Asia: Chapter V in Global mineral resource assessment"},"predicate":"IS_PART_OF","object":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"id":1}],"isPartOf":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"lastModifiedDate":"2020-08-18T22:18:50.767782","indexId":"sir20105090V","displayToPublicDate":"2015-11-18T08:00:00","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":"2010-5090","chapter":"V","title":"Porphyry copper assessment of the Tethys region of western and southern Asia: Chapter V in Global mineral resource assessment","docAbstract":"A probabilistic mineral resource assessment of undiscovered resources in porphyry copper deposits in the Tethys region of western and southern Asia was carried out as part of a global mineral resource assessment led by the U.S. Geological Survey (USGS). The purpose of the study was to delineate geographic areas as permissive tracts for the occurrence of porphyry copper deposits at a scale of 1:1,000,000 and to provide probabilistic estimates of amounts of copper likely to be contained in undiscovered porphyry copper deposits in those tracts. The team did the assessment using the USGS three-part form of mineral resource assessment, which is based on (1) mineral deposit and grade-tonnage models constructed from known deposits as analogs for undiscovered deposits, (2) delineation of permissive tracts based on geoscientific information, and (3) estimation of numbers of undiscovered deposits.
\nThe assessment area includes the Asian part of Turkey and Georgia, Armenia, Azerbaijan, Iran, western Pakistan, and southwestern Afghanistan. Selected tracts also extend marginally into southwesternmost Russia and northeasternmost Iraq. This region is located in the central part of the larger Tethyan Eurasian Metallogenic Belt, which extends from western Europe to eastern Asia. Mining in this part of the Tethyan Eurasian Metallogenic Belt has occurred for thousands of years; in 2011 the region produced 420,000 metric tons (t) of copper (2.6 percent of global production), 8,300 t of molybdenum (3 percent), and 29,600 kilograms of gold (1 percent).
\nThe assessment team defined 26 tracts permissive for Late Triassic to Holocene porphyry copper-molybdenum and porphyry copper-gold deposits. Permissive tracts range in extent from 2,960 to 194,000 square kilometers (km2) and cover a total area of 924,000 km2. Younger tracts overlap older tracts in several areas. Three permissive tracts include sub-tracts in order to separate tract segments on the basis of geography, data quality, or likelihood of occurrence of undiscovered deposits. About 65 percent of all known porphyry sites occur in only five tracts, which also host most of the identified copper resources. In terms of tectonic setting, 58 percent of the permissive tracts are related to continental arcs; 19 percent to island arcs or back arcs; and 24 percent to postcollisional settings. Of the known porphyry copper deposits, subequal fractions are spread among these three settings.
\nThe spatial distribution of known porphyry deposits and prospects is also related to the level of erosion. Magmatic belts with numerous known porphyry sites exhibit subequal areas of coeval plutonic and volcanic units and lesser amounts of cover rocks. Belts with fewer known porphyry sites display either high or low volcanic-to-plutonic ratios and (or) greater cover, indicating crustal levels that are too shallow or too deep for exposure of porphyry deposits.
\nProbabilistic estimates of numbers of undiscovered porphyry copper deposits were made for 18 of the 26 tracts. The undiscovered porphyry copper endowment for 8 tracts is discussed qualitatively.
\nThe assessment estimates that the Tethys region contains 47 undiscovered deposits within 1 kilometer of the surface. Probabilistic estimates of numbers of undiscovered deposits were combined with grade and tonnage models in a Monte Carlo simulation to estimate probable amounts of contained metal. The 47 undiscovered deposits are estimated to contain a mean of 180 million metric tons (Mt) of copper distributed among the 18 tracts for which probabilistic estimates were made, in addition to the 62 Mt of copper already identified in the 42 known porphyry deposits in the study area. Results of Monte Carlo simulations show that 80 percent of the estimated undiscovered porphyry copper resources in the Tethys region are located in four tracts or sub-tracts.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Global mineral resource assessment (Scientific Investigations Report 2010-5090)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20105090V","issn":"2328-0328","collaboration":"Prepared in cooperation with the Natural History Museum, London","usgsCitation":"Zürcher, L., Bookstrom A.A., Hammarstrom, J.M., Mars, J.C., Ludington, S., Zientek, M.L., Dunlap, P., and Wallis, J.C., with contributions from Drew, L.J., Sutphin, D.M., Berger, B.R., Herrington, R.J., Billa, M., Kuşcu, I., Moon, C.J. ,and Richards, J.P., 2015, Porphyry copper assessment of the Tethys region of western and southern Asia: U.S. Geological Survey Scientific Investigations Report 2010–5090–V, 232 p., and spatial data, https://dx.doi.org/10.3133/sir20105090V.","productDescription":"Report: xvii, 232 p.; 7 Figures: 17.0 x 11.0 inches; Appendices A-C; Spatial Data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-053054","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":311125,"rank":7,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2010/5090/v/sir20105090v_fig07.pdf","text":"Tabloid Figure 7","size":"1.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2010-5090V Figure 7","linkHelpText":"Eocene to Miocene permissive tracts for porphyry copper deposits in the Tethys region of western and southern Asia."},{"id":311126,"rank":8,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2010/5090/v/sir20105090v_fig08.pdf","text":"Tabloid Figure 8","size":"1.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2010-5090V Figure 8","linkHelpText":"Pliocene to Holocene permissive tract for porphyry copper deposits in the Tethys region of western and southern Asia."},{"id":311127,"rank":9,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2010/5090/v/sir20105090v_fig57.pdf","text":"Tabloid Figure 57","size":"1.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2010-5090V Figure 57","linkHelpText":"Map showing the distribution of permissive intrusive and extrusive rocks used to define tract 142pCu9017, Plio-Quaternary— Afghanistan, Armenia, Azerbaijan, Georgia, Iran, Pakistan, Russian Federation, and Turkey. Sub-tracts: 142pCu9017a, Plio-Quaternary—Konya, Turkey; 142pCu9017b, Plio-Quaternary—Postcollisional, Armenia, Azerbaijan, Georgia, Iran, Russian Federation, and Turkey; and 142pCu9017c, Plio-Quaternary—Bazman, Afghanistan, Iran, Pakistan."},{"id":311122,"rank":4,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2010/5090/v/sir20105090v_fig03.pdf","text":"Tabloid Figure 3","size":"3.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2010-5090V Figure 3","linkHelpText":"Map showing tectono-stratigraphic terranes, accretionary prisms, and metamorphic belts of the Tethys region of western and southern Asia. After Abdullah and Chmyriov (1977b) and Peters and others (2011) for Afghanistan, Kazmi and Rana (1982) for Pakistan, Stöcklin (1968) for Iran, Pollastro and others (1998) for Iraq, Kaymakci and others (2010) and Yigit (2009) for Turkey, and Kekelia and others (2001) for the Caucasus."},{"id":311121,"rank":3,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2010/5090/v/sir20105090v_fig02.pdf","text":"Tabloid Figure 2","size":"1.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2010-5090V Figure 2","linkHelpText":"Map showing major sutures, faults, and geologic and geographic features in the Tethys region of western and southern Asia (assessment area) and vicinity on a digital elevation base."},{"id":311129,"rank":11,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2010/5090/v/sir20105090v_gis.zip","text":"GIS Data","size":"88.1 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2010-5090V GIS Data"},{"id":311128,"rank":10,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2010/5090/v/sir20105090v_appendixes_a_c.xlsx","text":"Appendices A–C","size":"516 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2010-5090V Appendixes A–C"},{"id":311124,"rank":6,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2010/5090/v/sir20105090v_fig06.pdf","text":"Tabloid Figure 6","size":"1.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2010-5090V Figure 6","linkHelpText":"Late Cretaceous to late Eocene permissive tracts for porphyry copper deposits in the Tethys region of western and southern Asia."},{"id":311123,"rank":5,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2010/5090/v/sir20105090v_fig05.pdf","text":"Tabloid Figure 5","size":"1.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2010-5090V Figure 5","linkHelpText":"Late Triassic to Early Cretaceous permissive tracts for porphyry copper deposits in the Tethys region of western and southern Asia."},{"id":311120,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2010/5090/v/sir20105090v.pdf","text":"Report","size":"28.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2010-5090V"},{"id":311118,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2010/5090/v/coverthb.jpg"}],"country":"Afghanistan, Armenia, Azerbaijan, Georgia, Iran, Iraq, Pakistan, Russia, Turkey","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 24.609375,\n 39.90973623453719\n ],\n [\n 25.13671875,\n 41.83682786072714\n ],\n [\n 26.630859375,\n 42.87596410238254\n ],\n [\n 27.94921875,\n 43.32517767999296\n ],\n [\n 34.27734375,\n 42.87596410238254\n ],\n [\n 38.759765625,\n 42.22851735620852\n ],\n [\n 40.341796875,\n 42.94033923363181\n ],\n [\n 40.517578125,\n 43.96119063892024\n ],\n [\n 44.12109374999999,\n 43.644025847699496\n ],\n [\n 46.93359375,\n 43.32517767999296\n ],\n [\n 49.39453125,\n 42.68243539838623\n ],\n [\n 50.2734375,\n 41.244772343082076\n ],\n [\n 50.009765625,\n 39.232253141714885\n ],\n [\n 50.88867187499999,\n 38.47939467327645\n ],\n [\n 52.82226562499999,\n 38.272688535980976\n ],\n [\n 55.107421875,\n 38.685509760012\n ],\n [\n 58.447265625,\n 38.89103282648849\n ],\n [\n 61.17187499999999,\n 37.50972584293751\n ],\n [\n 64.6875,\n 36.1733569352216\n ],\n [\n 68.5546875,\n 35.88905007936091\n ],\n [\n 74.00390625,\n 32.91648534731439\n ],\n [\n 74.70703125,\n 32.10118973232094\n ],\n [\n 73.916015625,\n 30.751277776257812\n ],\n [\n 72.24609375,\n 29.22889003019423\n ],\n [\n 69.9609375,\n 27.839076094777816\n ],\n [\n 68.5546875,\n 27.21555620902969\n ],\n [\n 66.181640625,\n 26.43122806450644\n ],\n [\n 62.9296875,\n 25.48295117535531\n ],\n [\n 59.765625,\n 25.3241665257384\n ],\n [\n 56.42578125,\n 25.799891182088334\n ],\n [\n 53.26171875,\n 26.745610382199022\n ],\n [\n 50.009765625,\n 28.76765910569123\n ],\n [\n 47.548828125,\n 29.53522956294847\n ],\n [\n 43.2421875,\n 31.728167146023935\n ],\n [\n 38.408203125,\n 34.30714385628804\n ],\n [\n 33.83789062499999,\n 35.60371874069731\n ],\n [\n 27.773437499999996,\n 35.31736632923788\n ],\n [\n 25.224609375,\n 36.24427318493909\n ],\n [\n 24.169921875,\n 38.685509760012\n ],\n [\n 24.609375,\n 39.90973623453719\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Mineral Resources Program
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12201 Sunrise Valley Drive
913 National Center
Reston, VA 20192
http://minerals.usgs.gov/
Approximately two thirds of migratory songbirds in eastern North America negotiate the Gulf of Mexico (GOM), where inclement weather coupled with no refueling or resting opportunities can be lethal. However, decisions made when navigating such features and their consequences remain largely unknown due to technological limitations of tracking small animals over large areas. We used automated radio telemetry to track three songbird species (Red-eyed Vireo, Swainson’s Thrush, Wood Thrush) from coastal Alabama to the northern Yucatan Peninsula (YP) during fall migration. Detecting songbirds after crossing ∼1,000 km of open water allowed us to examine intrinsic (age, wing length, fat) and extrinsic (weather, date) variables shaping departure decisions, arrival at the YP, and crossing times. Large fat reserves and low humidity, indicative of beneficial synoptic weather patterns, favored southward departure across the Gulf. Individuals detected in the YP departed with large fat reserves and later in the fall with profitable winds, and flight durations (mean = 22.4 h) were positively related to wind profit. Age was not related to departure behavior, arrival, or travel time. However, vireos negotiated the GOM differently than thrushes, including different departure decisions, lower probability of detection in the YP, and longer crossing times. Defense of winter territories by thrushes but not vireos and species-specific foraging habits may explain the divergent migratory behaviors. Fat reserves appear extremely important to departure decisions and arrival in the YP. As habitat along the GOM is degraded, birds may be limited in their ability to acquire fat to cross the Gulf.
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in the face of uncertainty","docAbstract":"Population viability analyses provide a quantitative approach that seeks to predict the possible future status of a species of interest under different scenarios and, therefore, can be important components of large-scale species’ conservation programs. We created a model and simulated range-wide population and breeding habitat dynamics for an endangered woodland warbler, the golden-cheeked warbler (Setophaga chrysoparia). Habitat-transition probabilities were estimated across the warbler's breeding range by combining National Land Cover Database imagery with multistate modeling. Using these estimates, along with recently published demographic estimates, we examined if the species can remain viable into the future given the current conditions. Lastly, we evaluated if protecting a greater amount of habitat would increase the number of warblers that can be supported in the future by systematically increasing the amount of protected habitat and comparing the estimated terminal carrying capacity at the end of 50 years of simulated habitat change. The estimated habitat-transition probabilities supported the hypothesis that habitat transitions are unidirectional, whereby habitat is more likely to diminish than regenerate. The model results indicated population viability could be achieved under current conditions, depending on dispersal. However, there is considerable uncertainty associated with the population projections due to parametric uncertainty. Model results suggested that increasing the amount of protected lands would have a substantial impact on terminal carrying capacities at the end of a 50-year simulation. Notably, this study identifies the need for collecting the data required to estimate demographic parameters in relation to changes in habitat metrics and population density in multiple regions, and highlights the importance of establishing a common definition of what constitutes protected habitat, what management goals are suitable within those protected areas, and a standard operating procedure to identify areas of priority for habitat conservation efforts. Therefore, we suggest future efforts focus on these aspects of golden-cheeked warbler conservation and ecology.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.ecolmodel.2015.09.018","usgsCitation":"Adam Duarte, Hatfield, J., Swannack, T.M., Forstner, M.R., Green, M.C., and Floyd W. Weckerly, 2015, Simulating range-wide population and breeding habitat dynamics for an endangered woodland warbler in the face of uncertainty: Ecological Modelling, v. 320, no. 7691, p. 52-61, https://doi.org/10.1016/j.ecolmodel.2015.09.018.","productDescription":"10 p.","startPage":"52","endPage":"61","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068943","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":471640,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2015.09.018","text":"Publisher Index Page"},{"id":311531,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"320","issue":"7691","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"564daf53e4b0112df6c62e2e","chorus":{"doi":"10.1016/j.ecolmodel.2015.09.018","url":"http://dx.doi.org/10.1016/j.ecolmodel.2015.09.018","publisher":"Elsevier BV","authors":"Duarte Adam, Hatfield Jeff S., Swannack Todd M., Forstner Michael R.J., Green M. 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Infectious hematopoietic necrosis virus (IHNV) is endemic to the Pacific Northwest and infectious to Pacific salmon and trout (Oncorhynchus spp.). Emergence of the M genogroup of IHNV in steelhead trout O. mykiss in the coastal streams of Washington State, between 2007 and 2011, was geographically heterogeneous. Differences in host resistance due to genetic change were hypothesized to be a factor influencing the IHNV emergence patterns. For example, juvenile steelhead trout losses at the Quinault National Fish Hatchery (QNFH) were much lower than those at a nearby facility that cultures a stock originally derived from the same source population. Using a classical quantitative genetic approach, we determined the potential for the QNFH steelhead trout population to respond to selection caused by the pathogen, by estimating the heritability for 2 traits indicative of IHNV resistance, mortality (h2 = 0.377 (0.226 - 0.550)) and days to death (h2 = 0.093 (0.018 - 0.203)). These results confirm that there is a genetic basis for resistance and that this population has the potential to adapt to IHNV. Additionally, genetic correlation between days to death and fish length suggests a correlated response in these traits to selection. Reduction of genetic variation, as well as the presence or absence of resistant alleles, could affect the ability of populations to adapt to the pathogen. Identification of the genetic basis for IHNV resistance could allow the assessment of the susceptibility of other steelhead populations.
","language":"English","publisher":"Inter-Research","doi":"10.3354/dao02933","usgsCitation":"Brieuc, M.S., Purcell, M., Palmer, A.D., and Naish, K., 2015, Genetic variation underlying resistance to infectious hematopoietic necrosis virus in a steelhead trout (Oncorhynchus mykiss) population: Diseases of Aquatic Organisms, v. 117, p. 77-83, https://doi.org/10.3354/dao02933.","productDescription":"7 p.","startPage":"77","endPage":"83","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066503","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":471639,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/dao02933","text":"Publisher Index Page"},{"id":311441,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"117","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"564c4fbae4b0ebfbef0d3457","contributors":{"authors":[{"text":"Brieuc, Marine S. O.","contributorId":149933,"corporation":false,"usgs":false,"family":"Brieuc","given":"Marine","email":"","middleInitial":"S. O.","affiliations":[{"id":17855,"text":"School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":580065,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Purcell, Maureen K. mpurcell@usgs.gov","contributorId":3061,"corporation":false,"usgs":true,"family":"Purcell","given":"Maureen K.","email":"mpurcell@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":580064,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Palmer, Alexander D. apalmer@usgs.gov","contributorId":5304,"corporation":false,"usgs":true,"family":"Palmer","given":"Alexander","email":"apalmer@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":580066,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Naish, Kerry A.","contributorId":20243,"corporation":false,"usgs":true,"family":"Naish","given":"Kerry A.","affiliations":[],"preferred":false,"id":580067,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159660,"text":"70159660 - 2015 - Web based visualization of large climate data sets","interactions":[],"lastModifiedDate":"2015-11-17T14:07:35","indexId":"70159660","displayToPublicDate":"2015-11-17T15:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Web based visualization of large climate data sets","docAbstract":"We have implemented the USGS National Climate Change Viewer (NCCV), which is an easy-to-use web application that displays future projections from global climate models over the United States at the state, county and watershed scales. We incorporate the NASA NEX-DCP30 statistically downscaled temperature and precipitation for 30 global climate models being used in the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC), and hydrologic variables we simulated using a simple water-balance model. Our application summarizes very large, complex data sets at scales relevant to resource managers and citizens and makes climate-change projection information accessible to users of varying skill levels. Tens of terabytes of high-resolution climate and water-balance data are distilled to compact binary format summary files that are used in the application. To alleviate slow response times under high loads, we developed a map caching technique that reduces the time it takes to generate maps by several orders of magnitude. The reduced access time scales to >500 concurrent users. We provide code examples that demonstrate key aspects of data processing, data exporting/importing and the caching technique used in the NCCV.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2015.02.016","usgsCitation":"Alder, J.R., and Hostetler, S.W., 2015, Web based visualization of large climate data sets: Environmental Modelling and Software, v. 68, p. 175-180, https://doi.org/10.1016/j.envsoft.2015.02.016.","productDescription":"6 p.","startPage":"175","endPage":"180","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057365","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":311437,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"68","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"564c4fbee4b0ebfbef0d345f","contributors":{"authors":[{"text":"Alder, Jay R. 0000-0003-2378-2853 jalder@usgs.gov","orcid":"https://orcid.org/0000-0003-2378-2853","contributorId":5118,"corporation":false,"usgs":true,"family":"Alder","given":"Jay","email":"jalder@usgs.gov","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":579955,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hostetler, Steven W. 0000-0003-2272-8302 swhostet@usgs.gov","orcid":"https://orcid.org/0000-0003-2272-8302","contributorId":3249,"corporation":false,"usgs":true,"family":"Hostetler","given":"Steven","email":"swhostet@usgs.gov","middleInitial":"W.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":579956,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70159613,"text":"70159613 - 2015 - Ecotoxicoparasitology: Understanding mercury concentrations in gut contents, intestinal helminths and host tissues of Alaskan gray wolves (Canis lupus)","interactions":[],"lastModifiedDate":"2015-11-17T13:49:24","indexId":"70159613","displayToPublicDate":"2015-11-17T14:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Ecotoxicoparasitology: Understanding mercury concentrations in gut contents, intestinal helminths and host tissues of Alaskan gray wolves (Canis lupus)","docAbstract":"Some gastrointestinal helminths acquire nutrients from the lumen contents in which they live; thus, they may be exposed to non-essential elements, such as mercury (Hg), during feeding. The objectives of this study were: 1) determine the total mercury concentrations ([THg]) in Gray wolves (Canis lupus) and their parasites, and 2) use stable isotopes to evaluate the trophic relationships within the host. [THg] and stable isotopes (C and N) were determined for helminths, host tissues, and lumen contents from 88 wolves. Sixty-three wolves contained grossly visible helminths (71.5%). The prevalence of taeniids and ascarids was 63.6% (56/88) and 20.5% (18/88), respectively. Nine of these 63 wolves contained both taeniids and ascarids (14.3%). All ascarids were determined to beToxascaris leonina. Taenia species present included T. krabbei and T. hydatigena. Within the GI tract, [THg] in the lumen contents of the proximal small intestine were significantly lower than in the distal small intestine. There was a significant positive association between hepatic and taeniid [THg]. Bioaccumulation factors (BAF) ranged from < 1 to 22.9 in taeniids, and 1.1 to 12.3 in T. leonina. Taeniid and ascarid BAF were significantly higher than 1, suggesting that both groups are capable of THg accumulation in their wolf host. δ13C in taeniids was significantly lower than in host liver and skeletal muscle. [THg] in helminths and host tissues, in conjunction with stable isotope (C and N) values, provides insight into food-web dynamics of the host GI tract, and aids in elucidating ecotoxicoparasitologic relationships. Variation of [THg] throughout the GI tract, and between parasitic groups, underscores the need to further evaluate the effect(s) of feeding niche, and the nutritional needs of parasites, as they relate to toxicant exposure and distribution within the host.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2015.07.106","usgsCitation":"McGrew, A.K., O'Hara, T., Stricker, C.A., Castellini, M., Beckmen, K.B., Salman, M.D., and Ballweber, L.R., 2015, Ecotoxicoparasitology: Understanding mercury concentrations in gut contents, intestinal helminths and host tissues of Alaskan gray wolves (Canis lupus): Science of the Total Environment, v. 536, p. 866-871, https://doi.org/10.1016/j.scitotenv.2015.07.106.","productDescription":"6 p.","startPage":"866","endPage":"871","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065164","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":471641,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://doi.org/10.1016/j.scitotenv.2015.07.106","text":"External Repository"},{"id":311435,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"536","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"564c4fb9e4b0ebfbef0d3453","contributors":{"authors":[{"text":"McGrew, Ashley K.","contributorId":64149,"corporation":false,"usgs":true,"family":"McGrew","given":"Ashley","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":579714,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O'Hara, Todd M.","contributorId":34768,"corporation":false,"usgs":false,"family":"O'Hara","given":"Todd M.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":579715,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stricker, Craig A. 0000-0002-5031-9437 cstricker@usgs.gov","orcid":"https://orcid.org/0000-0002-5031-9437","contributorId":1097,"corporation":false,"usgs":true,"family":"Stricker","given":"Craig","email":"cstricker@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":579713,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Castellini, Margaret","contributorId":149833,"corporation":false,"usgs":false,"family":"Castellini","given":"Margaret","email":"","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":579716,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beckmen, Kimberlee B.","contributorId":12770,"corporation":false,"usgs":true,"family":"Beckmen","given":"Kimberlee","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":579717,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Salman, Mo D.","contributorId":39283,"corporation":false,"usgs":true,"family":"Salman","given":"Mo","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":579718,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ballweber, Lora R.","contributorId":30537,"corporation":false,"usgs":true,"family":"Ballweber","given":"Lora","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":579719,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70159663,"text":"70159663 - 2015 - Anaerobic chemolithotrophic growth of the haloalkaliphilic bacterium strain MLMS‑1 by disproportionation of monothioarsenate","interactions":[],"lastModifiedDate":"2015-11-17T13:33:27","indexId":"70159663","displayToPublicDate":"2015-11-17T14:30:00","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":"Anaerobic chemolithotrophic growth of the haloalkaliphilic bacterium strain MLMS‑1 by disproportionation of monothioarsenate","docAbstract":"A novel chemolithotrophic metabolism based on a mixed arsenic−sulfur species has been discovered for the anaerobic deltaproteobacterium, strain MLMS-1, a haloalkaliphile isolated from Mono Lake, California, U.S. Strain MLMS‑1 is the first reported obligate arsenate-respiring chemoautotroph which grows by coupling arsenate reduction to arsenite with the oxidation of sulfide to sulfate. In that pathway the formation of a mixed arsenic−sulfur species was reported. That species was assumed to be monothioarsenite ([H2AsIIIS−IIO2] −), formed as an intermediate by abiotic reaction of arsenite with sulfide. We now report that this species is monothioarsenate ([HAsVS−IIO3] 2−) as revealed by X-ray absorption spectroscopy. Monothioarsenate forms by abiotic reaction of arsenite with zerovalent sulfur. Monothioarsenate is kinetically stable under a wide range of pH and redox conditions. However, it was metabolized rapidly by strain MLMS-1 when incubated with arsenate. Incubations using monothioarsenate confirmed that strain MLMS-1 was able to grow (μ = 0.017 h−1 ) on this substrate via a disproportionation reaction by oxidizing the thio-group-sulfur (S−II) to zerovalent sulfur or sulfate while concurrently reducing the central arsenic atom (AsV) to arsenite. Monothioarsenate disproportionation could be widespread in nature beyond the already studied arsenic and sulfide rich hot springs and soda lakes where it was discovered.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.5b01165","usgsCitation":"Planer-Friedrich, B., Hartig, C., Lohmayer, R., Suess, E., McCann, S., and Oremland, R.S., 2015, Anaerobic chemolithotrophic growth of the haloalkaliphilic bacterium strain MLMS‑1 by disproportionation of monothioarsenate: Environmental Science & Technology, v. 49, no. 11, p. 6554-6563, https://doi.org/10.1021/acs.est.5b01165.","productDescription":"10 p.","startPage":"6554","endPage":"6563","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060782","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":311433,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"49","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-05-21","publicationStatus":"PW","scienceBaseUri":"564c4fb3e4b0ebfbef0d344c","contributors":{"authors":[{"text":"Planer-Friedrich, B.","contributorId":87749,"corporation":false,"usgs":true,"family":"Planer-Friedrich","given":"B.","email":"","affiliations":[],"preferred":false,"id":579971,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hartig, C.","contributorId":149903,"corporation":false,"usgs":false,"family":"Hartig","given":"C.","email":"","affiliations":[{"id":17852,"text":"University of Bayreuth, Germany","active":true,"usgs":false}],"preferred":false,"id":579969,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lohmayer, R.","contributorId":149904,"corporation":false,"usgs":false,"family":"Lohmayer","given":"R.","email":"","affiliations":[{"id":17852,"text":"University of Bayreuth, Germany","active":true,"usgs":false}],"preferred":false,"id":579972,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Suess, E.","contributorId":77667,"corporation":false,"usgs":true,"family":"Suess","given":"E.","email":"","affiliations":[],"preferred":false,"id":579970,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCann, Shelley 0000-0002-9753-7968 smccann@usgs.gov","orcid":"https://orcid.org/0000-0002-9753-7968","contributorId":149902,"corporation":false,"usgs":true,"family":"McCann","given":"Shelley","email":"smccann@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":579968,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Oremland, Ronald S. 0000-0001-7382-0147 roremlan@usgs.gov","orcid":"https://orcid.org/0000-0001-7382-0147","contributorId":931,"corporation":false,"usgs":true,"family":"Oremland","given":"Ronald","email":"roremlan@usgs.gov","middleInitial":"S.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":579967,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70159608,"text":"70159608 - 2015 - Dynamic response of desert wetlands to abrupt climate change","interactions":[],"lastModifiedDate":"2015-11-30T11:25:02","indexId":"70159608","displayToPublicDate":"2015-11-17T14:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2982,"text":"PNAS","active":true,"publicationSubtype":{"id":10}},"title":"Dynamic response of desert wetlands to abrupt climate change","docAbstract":"Desert wetlands are keystone ecosystems in arid environments and are preserved in the geologic record as groundwater discharge (GWD) deposits. GWD deposits are inherently discontinuous and stratigraphically complex, which has limited our understanding of how desert wetlands responded to past episodes of rapid climate change. Previous studies have shown that wetlands responded to climate change on glacial to interglacial timescales, but their sensitivity to short-lived climate perturbations is largely unknown. Here, we show that GWD deposits in the Las Vegas Valley (southern Nevada, United States) provide a detailed and nearly complete record of dynamic hydrologic changes during the past 35 ka (thousands of calibrated 14C years before present), including cycles of wetland expansion and contraction that correlate tightly with climatic oscillations recorded in the Greenland ice cores. Cessation of discharge associated with rapid warming events resulted in the collapse of entire wetland systems in the Las Vegas Valley at multiple times during the late Quaternary. On average, drought-like conditions, as recorded by widespread erosion and the formation of desert soils, lasted for a few centuries. This record illustrates the vulnerability of desert wetland flora and fauna to abrupt climate change. It also shows that GWD deposits can be used to reconstruct paleohydrologic conditions at millennial to submillennial timescales and informs conservation efforts aimed at protecting these fragile ecosystems in the face of anthropogenic warming.
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L.","contributorId":149932,"corporation":false,"usgs":false,"family":"Anderson","given":"Michael","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":579974,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70159678,"text":"70159678 - 2015 - Karst mapping in the United States: Past, present and future","interactions":[],"lastModifiedDate":"2017-04-14T10:20:04","indexId":"70159678","displayToPublicDate":"2015-11-17T14:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1727,"text":"GSA Special Papers","active":true,"publicationSubtype":{"id":10}},"title":"Karst mapping in the United States: Past, present and future","docAbstract":"The earliest known comprehensive karst map of the entire USA was published by Stringfield and LeGrand (1969), based on compilations of William E. Davies of the U.S. Geological Survey (USGS). Various versions of essentially the same map have been published since. The USGS recently published new digital maps and databases depicting the extent of known karst, potential karst, and pseudokarst areas of the United States of America including Puerto Rico and the U.S. Virgin Islands (Weary and Doctor, 2014). These maps are based primarily on the extent of potentially karstic soluble rock types, and rocks with physical properties conducive to the formation of pseudokarst features. These data were compiled and refined from multiple sources at various spatial resolutions, mostly as digital data supplied by state geological surveys. The database includes polygons delineating areas with potential for karst and that are tagged with attributes intended to facilitate classification of karst regions. Approximately 18% of the surface of the fifty United States is underlain by significantly soluble bedrock. In the eastern United States the extent of outcrop of soluble rocks provides a good first-approximation of the distribution of karst and potential karst areas. In the arid western states, the extent of soluble rock outcrop tends to overestimate the extent of regions that might be considered as karst under current climatic conditions, but the new dataset encompasses those regions nonetheless. This database will be revised as needed, and the present map will be updated as new information is incorporated.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/2015.2516(04)","usgsCitation":"Weary, D.J., and Doctor, D.H., 2015, Karst mapping in the United States: Past, present and future: GSA Special Papers, v. 516, p. 177-211, https://doi.org/10.1130/2015.2516(04).","productDescription":"15 p.","startPage":"177","endPage":"211","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062964","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":311430,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"516","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"564c4fbbe4b0ebfbef0d3459","contributors":{"authors":[{"text":"Weary, David J. 0000-0002-6115-6397 dweary@usgs.gov","orcid":"https://orcid.org/0000-0002-6115-6397","contributorId":545,"corporation":false,"usgs":true,"family":"Weary","given":"David","email":"dweary@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":580049,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doctor, Daniel H. 0000-0002-8338-9722 dhdoctor@usgs.gov","orcid":"https://orcid.org/0000-0002-8338-9722","contributorId":2037,"corporation":false,"usgs":true,"family":"Doctor","given":"Daniel","email":"dhdoctor@usgs.gov","middleInitial":"H.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":580050,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}