{"pageNumber":"602","pageRowStart":"15025","pageSize":"25","recordCount":40828,"records":[{"id":70106982,"text":"70106982 - 2014 - Beach science in the Great Lakes","interactions":[],"lastModifiedDate":"2014-05-19T15:00:53","indexId":"70106982","displayToPublicDate":"2014-05-19T14:57:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Beach science in the Great Lakes","docAbstract":"Monitoring beach waters for human health has led to an increase and evolution of science in the Great Lakes, which includes microbiology, limnology, hydrology, meteorology, epidemiology, and metagenomics, among others. In recent years, concerns over the accuracy of water quality standards at protecting human health have led to a significant interest in understanding the risk associated with water contact in both freshwater and marine environments. Historically, surface waters have been monitored for fecal indicator bacteria (fecal coliforms, <i>Escherichia coli</i>, enterococci), but shortcomings of the analytical test (lengthy assay) have resulted in a re-focusing of scientific efforts to improve public health protection. Research has led to the discovery of widespread populations of fecal indicator bacteria present in natural habitats such as soils, beach sand, and stranded algae. Microbial source tracking has been used to identify the source of these bacteria and subsequently assess their impact on human health. As a result of many findings, attempts have been made to improve monitoring efficiency and efficacy with the use of empirical predictive models and molecular rapid tests. All along, beach managers have actively incorporated new findings into their monitoring programs. With the abundance of research conducted and information gained over the last 25 years, “Beach Science” has emerged, and the Great Lakes have been a focal point for much of the ground-breaking work. Here, we review the accumulated research on microbiological water quality of Great Lakes beaches and provide a historic context to the collaborative efforts that have advanced this emerging science.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Great Lakes Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2013.12.011","usgsCitation":"Nevers, M.B., Byappanahalli, M.N., Edge, T.A., and Whitman, R.L., 2014, Beach science in the Great Lakes: Journal of Great Lakes Research, v. 40, no. 1, p. 1-14, https://doi.org/10.1016/j.jglr.2013.12.011.","productDescription":"14 p.","startPage":"1","endPage":"14","numberOfPages":"14","ipdsId":"IP-052073","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":287292,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287282,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jglr.2013.12.011"}],"country":"Canada;United States","otherGeospatial":"Great Lakes","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92.44,41.18 ], [ -92.44,49.28 ], [ -75.71,49.28 ], [ -75.71,41.18 ], [ -92.44,41.18 ] ] ] } } ] }","volume":"40","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"537b19d0e4b0929ba496ab26","contributors":{"authors":[{"text":"Nevers, Meredith B.","contributorId":91803,"corporation":false,"usgs":true,"family":"Nevers","given":"Meredith","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":493826,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Byappanahalli, Murulee N.","contributorId":79027,"corporation":false,"usgs":true,"family":"Byappanahalli","given":"Murulee","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":493825,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Edge, Thomas A.","contributorId":21074,"corporation":false,"usgs":true,"family":"Edge","given":"Thomas","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":493824,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Whitman, Richard L. rwhitman@usgs.gov","contributorId":542,"corporation":false,"usgs":true,"family":"Whitman","given":"Richard","email":"rwhitman@usgs.gov","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":493823,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70127601,"text":"70127601 - 2014 - Factors affecting public-supply well vulnerability in two karst aquifers","interactions":[],"lastModifiedDate":"2014-09-30T13:57:53","indexId":"70127601","displayToPublicDate":"2014-05-19T13:55:46","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1861,"text":"Ground Water","active":true,"publicationSubtype":{"id":10}},"title":"Factors affecting public-supply well vulnerability in two karst aquifers","docAbstract":"Karst aquifers occur in a range of climatic and geologic settings. Nonetheless, they are commonly characterized by their vulnerability to water-quality impairment. Two karst aquifers, the Edwards aquifer in south-central Texas and the Upper Floridan aquifer in western Florida, were investigated to assess factors that control the movement of contaminants to public-supply wells (PSWs). The geochemistry of samples from a selected PSW or wellfield in each aquifer was compared with that from nearby monitoring wells and regional PSWs. Geochemistry results were integrated with age tracers, flow modeling, and depth-dependent data to refine aquifer conceptual models and to identify factors that affect contaminant movement to PSWs. The oxic Edwards aquifer is vertically well mixed at the selected PSW/wellfield, although regionally the aquifer is geochemically variable downdip. The mostly anoxic Upper Floridan aquifer is affected by denitrification and also is geochemically variable with depth. In spite of considerable differences in geology and hydrogeology, the two aquifers are similarly vulnerable to anthropogenic contamination. Vulnerability in studied PSWs in both aquifers is strongly influenced by rapid karst flowpaths and the dominance of young (<10 years) groundwater. Vulnerability was demonstrated by the frequent detection of similar constituents of concern in both aquifers (nitrate, atrazine, deethylatrazine, tetrachloroethene, and chloroform). Specific consideration of water-quality protection efforts, well construction and placement, and aquifer response times to land-use changes and contaminant loading are discussed, with implications for karst groundwater management.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ground Water","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"National Ground Water Association","publisherLocation":"Westerville, OH","doi":"10.1111/gwat.12201","usgsCitation":"Musgrove, M., Katz, B.G., Fahlquist, L.S., Crandall, C.A., and Lindgren, R.J., 2014, Factors affecting public-supply well vulnerability in two karst aquifers: Ground Water, v. 52, no. 1, p. 63-75, https://doi.org/10.1111/gwat.12201.","productDescription":"13 p.","startPage":"63","endPage":"75","numberOfPages":"13","ipdsId":"IP-052620","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":472988,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gwat.12201","text":"Publisher Index Page"},{"id":294662,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294659,"type":{"id":15,"text":"Index Page"},"url":"https://onlinelibrary.wiley.com/doi/10.1111/gwat.12201/pdf"},{"id":294661,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/gwat.12201"}],"volume":"52","issue":"1","noUsgsAuthors":false,"publicationDate":"2014-05-19","publicationStatus":"PW","scienceBaseUri":"542bc636e4b0abfb4c8097f5","chorus":{"doi":"10.1111/gwat.12201","url":"http://dx.doi.org/10.1111/gwat.12201","publisher":"Wiley-Blackwell","authors":"Musgrove MaryLynn, Katz Brian G., Fahlquist Lynne S., Crandall Christy A., Lindgren Richard J.","journalName":"Groundwater","publicationDate":"5/19/2014","auditedOn":"3/17/2016"},"contributors":{"authors":[{"text":"Musgrove, MaryLynn","contributorId":34878,"corporation":false,"usgs":true,"family":"Musgrove","given":"MaryLynn","affiliations":[],"preferred":false,"id":502506,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Katz, Brian G. bkatz@usgs.gov","contributorId":1093,"corporation":false,"usgs":true,"family":"Katz","given":"Brian","email":"bkatz@usgs.gov","middleInitial":"G.","affiliations":[],"preferred":true,"id":502504,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fahlquist, Lynne S. 0000-0002-4993-4037 lfahlqst@usgs.gov","orcid":"https://orcid.org/0000-0002-4993-4037","contributorId":1051,"corporation":false,"usgs":true,"family":"Fahlquist","given":"Lynne","email":"lfahlqst@usgs.gov","middleInitial":"S.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":502502,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crandall, Christy A. crandall@usgs.gov","contributorId":1091,"corporation":false,"usgs":true,"family":"Crandall","given":"Christy","email":"crandall@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":502503,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lindgren, Richard J. lindgren@usgs.gov","contributorId":1667,"corporation":false,"usgs":true,"family":"Lindgren","given":"Richard","email":"lindgren@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":502505,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70093891,"text":"ofr20141025A - 2014 - Earthquake catalog for estimation of maximum earthquake magnitude, Central and Eastern United States: Part A, Prehistoric earthquakes","interactions":[],"lastModifiedDate":"2014-05-16T15:15:49","indexId":"ofr20141025A","displayToPublicDate":"2014-05-16T15:10:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1025","chapter":"A","title":"Earthquake catalog for estimation of maximum earthquake magnitude, Central and Eastern United States: Part A, Prehistoric earthquakes","docAbstract":"Computation of probabilistic earthquake hazard requires an estimate of Mmax, the maximum earthquake magnitude thought to be possible within a specified geographic region. This report is Part A of an Open-File Report that describes the construction of a global catalog of moderate to large earthquakes, from which one can estimate Mmax for most of the Central and Eastern United States and adjacent Canada. The catalog and Mmax estimates derived from it were used in the 2014 edition of the U.S. Geological Survey national seismic-hazard maps. This Part A discusses prehistoric earthquakes that occurred in eastern North America, northwestern Europe, and Australia, whereas a separate Part B deals with historical events.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141025A","issn":"2331-1258","usgsCitation":"Wheeler, R.L., 2014, Earthquake catalog for estimation of maximum earthquake magnitude, Central and Eastern United States: Part A, Prehistoric earthquakes: U.S. Geological Survey Open-File Report 2014-1025, iv, 26 p., https://doi.org/10.3133/ofr20141025A.","productDescription":"iv, 26 p.","numberOfPages":"30","onlineOnly":"Y","ipdsId":"IP-050768","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":287265,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141025A.jpg"},{"id":287264,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1025/a/pdf/ofr2014-1025.pdf"},{"id":287263,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1025/a/"}],"otherGeospatial":"Australia;Europe;North America","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53771744e4b02eab8669ebc7","contributors":{"authors":[{"text":"Wheeler, Russell L. wheeler@usgs.gov","contributorId":858,"corporation":false,"usgs":true,"family":"Wheeler","given":"Russell","email":"wheeler@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":false,"id":490259,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70102282,"text":"70102282 - 2014 - Distribution and landscape controls of organic layer thickness and carbon within the Alaskan Yukon River Basin","interactions":[],"lastModifiedDate":"2014-05-16T14:38:14","indexId":"70102282","displayToPublicDate":"2014-05-16T14:26:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1760,"text":"Geoderma","active":true,"publicationSubtype":{"id":10}},"title":"Distribution and landscape controls of organic layer thickness and carbon within the Alaskan Yukon River Basin","docAbstract":"Understanding of the organic layer thickness (OLT) and organic layer carbon (OLC) stocks in subarctic ecosystems is critical due to their importance in the global carbon cycle. Moreover, post-fire OLT provides an indicator of long-term successional trajectories and permafrost susceptibility to thaw. To these ends, we 1) mapped OLT and associated uncertainty at 30 m resolution in the Yukon River Basin (YRB), Alaska, employing decision tree models linking remotely sensed imagery with field and ancillary data, 2) converted OLT to OLC using a non-linear regression, 3) evaluate landscape controls on OLT and OLC, and 4) quantified the post-fire recovery of OLT and OLC. Areas of shallow (< 10 cm), moderate (≥ 10 cm and < 20 cm), moderately thick (≥ 20 cm and < 30 cm), and thick (≥ 30 cm) OLT, composed 34, 20, 14, and 18% of the YRB, respectively; the average OLT was 19.4 cm. Total OLC was estimated to be 3.38 Pg. A regional chronosequence analysis over 30 years revealed that OLT and OLC increased with stand age (OLT: R<sup>2</sup> = 0.68; OLC: R<sup>2</sup> = 0.66), where an average of 16 cm OLT and 5.3 kg/m<sup>2</sup> OLC were consumed by fires. Strong predictors of OLT included climate, topography, near-surface permafrost distributions, soil wetness, and spectral information. Our modeling approach enabled us to produce regional maps of OLT and OLC, which will be useful in understanding risks and feedbacks associated with fires and climate feedbacks.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geoderma","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.geoderma.2014.04.008","usgsCitation":"Pastick, N.J., Rigge, M.B., Wylie, B.K., Jorgenson, M., Rose, J.R., Johnson, K.D., and Ji, L., 2014, Distribution and landscape controls of organic layer thickness and carbon within the Alaskan Yukon River Basin: Geoderma, v. 230-231, p. 79-94, https://doi.org/10.1016/j.geoderma.2014.04.008.","productDescription":"16 p.","startPage":"79","endPage":"94","numberOfPages":"16","ipdsId":"IP-055907","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":287261,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287260,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.geoderma.2014.04.008"}],"country":"United States","state":"Alaska","otherGeospatial":"Yukon River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -166.45,60.22 ], [ -166.45,69.68 ], [ -141.02,69.68 ], [ -141.02,60.22 ], [ -166.45,60.22 ] ] ] } } ] }","volume":"230-231","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53771742e4b02eab8669ebb1","contributors":{"authors":[{"text":"Pastick, Neal J. 0000-0002-8169-3018 njpastick@usgs.gov","orcid":"https://orcid.org/0000-0002-8169-3018","contributorId":4785,"corporation":false,"usgs":true,"family":"Pastick","given":"Neal","email":"njpastick@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":492877,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rigge, Matthew B. 0000-0003-4471-8009 mrigge@usgs.gov","orcid":"https://orcid.org/0000-0003-4471-8009","contributorId":751,"corporation":false,"usgs":true,"family":"Rigge","given":"Matthew","email":"mrigge@usgs.gov","middleInitial":"B.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":492875,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":492874,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jorgenson, M. Torre","contributorId":40486,"corporation":false,"usgs":true,"family":"Jorgenson","given":"M. Torre","affiliations":[],"preferred":false,"id":492878,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rose, Joshua R.","contributorId":90147,"corporation":false,"usgs":true,"family":"Rose","given":"Joshua","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":492880,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Kristofer D.","contributorId":81027,"corporation":false,"usgs":true,"family":"Johnson","given":"Kristofer","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":492879,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ji, Lei 0000-0002-6133-1036 lji@usgs.gov","orcid":"https://orcid.org/0000-0002-6133-1036","contributorId":2832,"corporation":false,"usgs":true,"family":"Ji","given":"Lei","email":"lji@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":492876,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70104621,"text":"70104621 - 2014 - Corticosterone metabolite concentrations in greater sage-grouse are positively associated with the presence of cattle grazing","interactions":[],"lastModifiedDate":"2018-09-18T16:27:03","indexId":"70104621","displayToPublicDate":"2014-05-15T16:23:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"Corticosterone metabolite concentrations in greater sage-grouse are positively associated with the presence of cattle grazing","docAbstract":"<p><span>The sagebrush biome in the western United States is home to the imperiled greater sage-grouse (</span><i>Centrocercus urophasianus</i><span>) and encompasses rangelands used for cattle production. Cattle grazing activities have been implicated in the range-wide decline of the sage-grouse, but no studies have investigated the relationship between the physiological condition of sage-grouse and the presence of grazing cattle. We sampled 329 sage-grouse across four sites (two grazed and two ungrazed) encompassing 13 600 km</span><sup>2</sup><span><span>&nbsp;</span>during the spring and late summer–early autumn of 2005 to evaluate whether demographic factors, breeding status, plasma protein levels, and residence in a cattle-grazed habitat were associated with the stress hormone corticosterone. Corticosterone was measured in feces as immunoreactive corticosterone metabolites (ICM). Males captured during the lekking season exhibited higher ICM levels than all others. Prenesting female sage-grouse captured in a grazed site had higher ICM levels than those in ungrazed sites and prenesting female plasma protein levels were negatively correlated with ICM concentrations. With the use of a small-scale spatial model, we identified a positive correlation between cattle pat count and sage-grouse ICM levels. Our model indicated that ICM levels increased by 2.60 ng · g</span><sup>-1</sup><span><span>&nbsp;</span>dry feces for every increase in the number of cow pats found in the vicinity. Management practices will benefit from future research regarding the consistency and mechanism(s) responsible for this association and, importantly, how ICM levels and demographic rates are related in this species of conservation concern.</span></p>","language":"English","publisher":"Society for Range Management","doi":"10.2111/REM-D-13-00137.1","usgsCitation":"Jankowski, M., Russell, R.E., Franson, J., Dusek, R., Hines, M., Gregg, M., and Hofmeister, E.K., 2014, Corticosterone metabolite concentrations in greater sage-grouse are positively associated with the presence of cattle grazing: Rangeland Ecology and Management, v. 67, no. 3, p. 237-246, https://doi.org/10.2111/REM-D-13-00137.1.","productDescription":"10 p.","startPage":"237","endPage":"246","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-038634","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology 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Christian","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":493764,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dusek, Robert J. 0000-0001-6177-7479","orcid":"https://orcid.org/0000-0001-6177-7479","contributorId":30203,"corporation":false,"usgs":true,"family":"Dusek","given":"Robert J.","affiliations":[],"preferred":false,"id":493762,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hines, M.K.","contributorId":17920,"corporation":false,"usgs":true,"family":"Hines","given":"M.K.","email":"","affiliations":[],"preferred":false,"id":493760,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gregg, M.","contributorId":27366,"corporation":false,"usgs":true,"family":"Gregg","given":"M.","email":"","affiliations":[],"preferred":false,"id":493761,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hofmeister, Erik K. 0000-0002-6360-3912 ehofmeister@usgs.gov","orcid":"https://orcid.org/0000-0002-6360-3912","contributorId":3230,"corporation":false,"usgs":true,"family":"Hofmeister","given":"Erik","email":"ehofmeister@usgs.gov","middleInitial":"K.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":493758,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70095808,"text":"70095808 - 2014 - Physiological and ecological effects of increasing temperature on fish production in lakes of Arctic Alaska","interactions":[],"lastModifiedDate":"2014-05-29T15:28:09","indexId":"70095808","displayToPublicDate":"2014-05-15T15:16:28","publicationYear":"2014","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":"Physiological and ecological effects of increasing temperature on fish production in lakes of Arctic Alaska","docAbstract":"Lake ecosystems in the Arctic are changing rapidly due to climate warming. Lakes are sensitive integrators of climate-induced changes and prominent features across the Arctic landscape, especially in lowland permafrost regions such as the Arctic Coastal Plain of Alaska. Despite many studies on the implications of climate warming, how fish populations will respond to lake changes is uncertain for Arctic ecosystems. Least Cisco (Coregonus sardinella) is a bellwether for Arctic lakes as an important consumer and prey resource. To explore the consequences of climate warming, we used a bioenergetics model to simulate changes in Least Cisco production under future climate scenarios for lakes on the Arctic Coastal Plain. First, we used current temperatures to fit Least Cisco consumption to observed annual growth. We then estimated growth, holding food availability, and then feeding rate constant, for future projections of temperature. Projected warmer water temperatures resulted in reduced Least Cisco production, especially for larger size classes, when food availability was held constant. While holding feeding rate constant, production of Least Cisco increased under all future scenarios with progressively more growth in warmer temperatures. Higher variability occurred with longer projections of time mirroring the expanding uncertainty in climate predictions further into the future. In addition to direct temperature effects on Least Cisco growth, we also considered changes in lake ice phenology and prey resources for Least Cisco. A shorter period of ice cover resulted in increased production, similar to warming temperatures. Altering prey quality had a larger effect on fish production in summer than winter and increased relative growth of younger rather than older age classes of Least Cisco. Overall, we predicted increased production of Least Cisco due to climate warming in lakes of Arctic Alaska. Understanding the implications of increased production of Least Cisco to the entire food web will be necessary to predict ecosystem responses in lakes of the Arctic.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecology and Evolution","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley Online Library","doi":"10.1002/ece3.1080","usgsCitation":"Carey, M.P., and Zimmerman, C.E., 2014, Physiological and ecological effects of increasing temperature on fish production in lakes of Arctic Alaska: Ecology and Evolution, v. 4, no. 10, p. 1981-1993, https://doi.org/10.1002/ece3.1080.","productDescription":"13 p.","startPage":"1981","endPage":"1993","ipdsId":"IP-053143","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":472990,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.1080","text":"Publisher Index Page"},{"id":287839,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287838,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/ece3.1080"}],"country":"United States","state":"Alaska","otherGeospatial":"Arctic Coastal Plain","volume":"4","issue":"10","noUsgsAuthors":false,"publicationDate":"2014-04-22","publicationStatus":"PW","scienceBaseUri":"5388570ae4b0318b93124aed","contributors":{"authors":[{"text":"Carey, Michael P. 0000-0002-3327-8995 mcarey@usgs.gov","orcid":"https://orcid.org/0000-0002-3327-8995","contributorId":5397,"corporation":false,"usgs":true,"family":"Carey","given":"Michael","email":"mcarey@usgs.gov","middleInitial":"P.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":491459,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zimmerman, Christian E. 0000-0002-3646-0688 czimmerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3646-0688","contributorId":410,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Christian","email":"czimmerman@usgs.gov","middleInitial":"E.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":491458,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70100427,"text":"ofr20141070 - 2014 - The shallow stratigraphy and sand resources offshore from Cat Island, Mississippi","interactions":[],"lastModifiedDate":"2014-05-15T13:12:24","indexId":"ofr20141070","displayToPublicDate":"2014-05-15T13:08:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1070","title":"The shallow stratigraphy and sand resources offshore from Cat Island, Mississippi","docAbstract":"<p>In collaboration with the U.S. Army Corps of Engineers, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center collected over 487 line kilometers (> 300 miles) of high-resolution geophysical data around Cat Island, Mississippi, to improve understanding of the island's geologic evolution and identify potential sand resources for coastal restoration. In addition, 40 vibracores were collected on and around the island, generating more than 350 samples for grain-size analysis.</p>\n<br>\n<p>The results indicate that the geologic evolution of Cat Island has been influenced by deltaic, lagoonal/estuarine, tidal, and oceanographic processes, resulting in a stratigraphic record that is quite complex. The region north of the island is dominated by lagoonal/estuarine deposition, whereas the region south of the island is dominated by deltaic and tidal deposition. In general, the veneer of modern sediment surrounding the island is composed of newly deposited sediment and highly reworked relict sediments. The region east of the island shows the interplay of antecedent barrier-island change with delta development despite a significant ravinement of sediments. The data show from little to no modern sediment east of the island, exposing relict sediments at the seafloor.</p>\n<br>\n<p>Finally, the data reveal four subaqueous sand units around the island. Two of the units are northwest of the modern island and one is southwest. Given the dominant, westward, longshore transport along the Mississippi and Alabama barrier islands, the geographic location of these three units suggests that they do not contribute to the modern sediment budget of Cat Island. The last unit is directly east of the island and represents the antecedent island platform that has supplied sand over geologic time for creation of the spits that form the eastern shoreline. Because of its location east of the island, the antecedent island unit may still supply sediment to the island today.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141070","issn":"2331-1258","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Kindinger, J.L., Miselis, J.L., and Buster, N.A., 2014, The shallow stratigraphy and sand resources offshore from Cat Island, Mississippi: U.S. Geological Survey Open-File Report 2014-1070, viii, 74 p., https://doi.org/10.3133/ofr20141070.","productDescription":"viii, 74 p.","numberOfPages":"83","onlineOnly":"Y","ipdsId":"IP-052803","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":287234,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141070.jpg"},{"id":287232,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1070/"},{"id":287233,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1070/pdf/ofr2014-1070.pdf"}],"country":"United States","state":"Mississippi","otherGeospatial":"Cat Island","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -89.5,29.5 ], [ -89.5,30.5 ], [ -88.0,30.5 ], [ -88.0,29.5 ], [ -89.5,29.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5375d3d3e4b010920bbded07","contributors":{"authors":[{"text":"Kindinger, Jack L. jkindinger@usgs.gov","contributorId":815,"corporation":false,"usgs":true,"family":"Kindinger","given":"Jack","email":"jkindinger@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":492204,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miselis, Jennifer L. 0000-0002-4925-3979 jmiselis@usgs.gov","orcid":"https://orcid.org/0000-0002-4925-3979","contributorId":3914,"corporation":false,"usgs":true,"family":"Miselis","given":"Jennifer","email":"jmiselis@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":492206,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buster, Noreen A. 0000-0001-5069-9284 nbuster@usgs.gov","orcid":"https://orcid.org/0000-0001-5069-9284","contributorId":3750,"corporation":false,"usgs":true,"family":"Buster","given":"Noreen","email":"nbuster@usgs.gov","middleInitial":"A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":492205,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70058501,"text":"sir20105090L - 2014 - Porphyry copper assessment of eastern Australia","interactions":[{"subject":{"id":70058501,"text":"sir20105090L - 2014 - Porphyry copper assessment of eastern Australia","indexId":"sir20105090L","publicationYear":"2014","noYear":false,"chapter":"L","title":"Porphyry copper assessment of eastern Australia"},"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":"2022-12-09T20:56:23.37247","indexId":"sir20105090L","displayToPublicDate":"2014-05-15T12:44:00","publicationYear":"2014","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":"L","title":"Porphyry copper assessment of eastern Australia","docAbstract":"<p>The U.S. Geological Survey (USGS) conducts national and global assessments of resources (mineral, energy, water, and biologic) to provide science in support of decision making. Mineral resource assessments provide syntheses of available information about where mineral deposits are known and suspected to occur in the Earth&rsquo;s crust and which commodities may be present, together with estimates of amounts of resources that may be present in undiscovered deposits. The USGS collaborated with geologists of the Geological Survey of New South Wales and Geoscience Australia (formerly the Australian Geological Survey Organisation) on an assessment of Phanerozoic-age porphyry copper resources in Australia. Porphyry copper deposits contain about 11 percent of the identified copper resources in Australia. This study addresses resources of known porphyry copper deposits and expected resources of undiscovered porphyry copper deposits in eastern Australia.</p>\n<p>A three-part form of assessment was used for estimation of undiscovered resources. Using this method, four tracts were delineated that are permissive for porphyry copper deposits. A probabilistic estimate of the expected number of deposits in each tract was prepared on the basis of existing information about geology, geochemistry, geophysics, exploration history, and mineral occurrences. Monte Carlo simulation was used to combine the estimated number of deposits with an appropriate model of grade and tonnage for porphyry copper deposits to provide a probabilistic estimate of metal content and total tonnage for undiscovered deposits.</p>\n<p>The Delamerian permissive tract comprises igneous rocks of Cambrian age in the Delamerian Orogen, which borders the western margin of the Tasmanides. The Delamerian tract contains no known porphyry copper deposits, but the Adelaide sub-tract, one of three sub-tracts that compose the Delamerian tract, contains four porphyry copper prospects. The Adelaide sub-tract is estimated to contain 2.5&plusmn;2.2 undiscovered deposits in an area of about 50,700 square kilometers.</p>\n<p>The Macquarie permissive tract comprises volcanic, volcaniclastic, and minor exposed intrusive igneous rocks of the Macquarie Arc. The nine known deposits in this tract are now estimated to contain a total of about 13.5 million metric tons of copper and 1,700 metric tons of gold. This tract is estimated to contain 6.9&plusmn;3.5 undiscovered deposits for a total of about 16 deposits in an area of about 41,500 square kilometers.</p>\n<p>The Yeoval permissive tract includes subequal areas of permissive volcanic and intrusive rocks of Silurian to Devonian age exposed in and around the Cowra-Buchan Rift System, which overlaps the previously accreted Macquarie Arc. The Yeoval tract contains one porphyry copper deposit and several porphyry copper prospects. This tract is estimated to contain 1.3&plusmn;0.75 undiscovered porphyry copper deposits, for a total of about 2 expected deposits in an area of about 53,200 square kilometers.</p>\n<p>The East Tasmanide permissive tract includes a semi-continuous belt of plutonic and subordinate volcanic rocks along the eastern margins of Queensland and northeastern New South Wales. The East Tasmanide tract contains 14 known porphyry copper deposits and many porphyry copper prospects, which are all in the Central sub-tract. This sub-tract is expected to contain 4.8&plusmn;3.3 undiscovered porphyry copper deposits, for a total of about 19 deposits in an area of about 291,000 square kilometers.&nbsp;</p>\n<p>This assessment estimates that 15 undiscovered deposits contain an arithmetic mean of ~21 million metric tons or more of copper in four tracts, in addition to the 24 known porphyry copper deposits that contain identified resources of ~16 million metric tons of copper. In addition to copper, the mean expected amount of undiscovered byproduct gold predicted by the simulation is ~1,500 metric tons. The probability associated with these arithmetic means is on the order of 30 percent. Median expected amounts of metals predicted by the simulations may be ~50 percent lower than mean estimates.</p>","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/sir20105090L","collaboration":"Prepared in cooperation with Geological Survey of New South Wales and Geoscience Australia","usgsCitation":"Bookstrom, A.A., Len, R.A., Hammarstrom, J.M., Robinson, G.R., Zientek, M.L., Drenth, B.J., Jaireth, S., Cossette, P.M., and Wallis, J., 2014, Porphyry copper assessment of eastern Australia: U.S. Geological Survey Scientific Investigations Report 2010-5090, Report: x, 160 p.; Spatial Data, https://doi.org/10.3133/sir20105090L.","productDescription":"Report: x, 160 p.; Spatial Data","numberOfPages":"172","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-040368","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"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},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":287228,"rank":11,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5090/l/"},{"id":287230,"rank":1,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2010/5090/l/sir2010-5090-l_gis.zip","text":"GIS package","size":"1 MB","linkFileType":{"id":6,"text":"zip"},"description":"GIS package"},{"id":287229,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2010/5090/l/sir2010-5090-L.pdf","text":"Report","size":"36 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Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":487131,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Len, Richard A.","contributorId":36858,"corporation":false,"usgs":true,"family":"Len","given":"Richard","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":487135,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hammarstrom, Jane M. 0000-0003-2742-3460 jhammars@usgs.gov","orcid":"https://orcid.org/0000-0003-2742-3460","contributorId":1226,"corporation":false,"usgs":true,"family":"Hammarstrom","given":"Jane","email":"jhammars@usgs.gov","middleInitial":"M.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":487128,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Robinson, Gilpin R. Jr. grobinso@usgs.gov","contributorId":3083,"corporation":false,"usgs":true,"family":"Robinson","given":"Gilpin","suffix":"Jr.","email":"grobinso@usgs.gov","middleInitial":"R.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":487133,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zientek, Michael L. 0000-0002-8522-9626 mzientek@usgs.gov","orcid":"https://orcid.org/0000-0002-8522-9626","contributorId":2420,"corporation":false,"usgs":true,"family":"Zientek","given":"Michael","email":"mzientek@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":487132,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Drenth, Benjamin J. 0000-0002-3954-8124 bdrenth@usgs.gov","orcid":"https://orcid.org/0000-0002-3954-8124","contributorId":1315,"corporation":false,"usgs":true,"family":"Drenth","given":"Benjamin","email":"bdrenth@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":487129,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jaireth, Subhash","contributorId":7190,"corporation":false,"usgs":true,"family":"Jaireth","given":"Subhash","email":"","affiliations":[],"preferred":false,"id":487134,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cossette, Pamela M. 0000-0002-9608-6595 pcossette@usgs.gov","orcid":"https://orcid.org/0000-0002-9608-6595","contributorId":1458,"corporation":false,"usgs":true,"family":"Cossette","given":"Pamela","email":"pcossette@usgs.gov","middleInitial":"M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":487130,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wallis, John C.","contributorId":45755,"corporation":false,"usgs":true,"family":"Wallis","given":"John C.","affiliations":[],"preferred":false,"id":487136,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70099845,"text":"70099845 - 2014 - Unified facilities criteria 3-301-01: structural engineering","interactions":[],"lastModifiedDate":"2014-07-02T11:36:11","indexId":"70099845","displayToPublicDate":"2014-05-15T11:28:34","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Unified facilities criteria 3-301-01: structural engineering","docAbstract":"<p>This Unified Facility Criteria (UFC) provides requirements for structures designed and \nconstructed for the Department of Defense (DoD). These technical requirements are \nbased on the 2012 International Building Code (IBC 2012), as modified by UFC 1-200-\n01. This information shall be used by structural engineers to develop design \ncalculations, specifications, plans, and design-build Requests for Proposal (RFPs).</p>","language":"English","publisher":"National Institute of Building Sciences","publisherLocation":"Washington, D.C.","usgsCitation":"McGowan, S.M., Rezaeian, S., and Luco, N., 2014, Unified facilities criteria 3-301-01: structural engineering, vi, 162 p.","productDescription":"vi, 162 p.","numberOfPages":"172","ipdsId":"IP-055768","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":289371,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53b7b278e4b0388651d91973","contributors":{"authors":[{"text":"McGowan, Sean M. smcgowan@usgs.gov","contributorId":4370,"corporation":false,"usgs":true,"family":"McGowan","given":"Sean","email":"smcgowan@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":492038,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rezaeian, Sanaz 0000-0001-7589-7893 srezaeian@usgs.gov","orcid":"https://orcid.org/0000-0001-7589-7893","contributorId":4395,"corporation":false,"usgs":true,"family":"Rezaeian","given":"Sanaz","email":"srezaeian@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":492039,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Luco, Nicolas 0000-0002-5763-9847 nluco@usgs.gov","orcid":"https://orcid.org/0000-0002-5763-9847","contributorId":1188,"corporation":false,"usgs":true,"family":"Luco","given":"Nicolas","email":"nluco@usgs.gov","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":false,"id":492037,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70187699,"text":"70187699 - 2014 - Mapping large-area landscape suitability for honey bees to assess the influence of land-use change on sustainability of national pollination services","interactions":[],"lastModifiedDate":"2017-05-15T14:41:19","indexId":"70187699","displayToPublicDate":"2014-05-15T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Mapping large-area landscape suitability for honey bees to assess the influence of land-use change on sustainability of national pollination services","docAbstract":"<p><span>Pollination is a critical ecosystem service affected by various drivers of land-use change, such as policies and programs aimed at land resources, market values for crop commodities, local land-management decisions, and shifts in climate. The United States is the world's most active market for pollination services by honey bees, and the Northern Great Plains provide the majority of bee colonies used to meet the Nation's annual pollination needs. Legislation requiring increased production of biofuel crops, increasing commodity prices for crops of little nutritional value for bees in the Northern Great Plains, and reductions in government programs aimed at promoting land conservation are converging to alter the regional landscape in ways that challenge beekeepers to provide adequate numbers of hives for national pollination services. We developed a spatially explicit model that identifies sites with the potential to support large apiaries based on local-scale land-cover requirements for honey bees. We produced maps of potential apiary locations for North Dakota, a leading producer of honey, based on land-cover maps representing (1) an annual time series compiled from existing operational products and (2) a realistic scenario of land change. We found that existing land-cover products lack sufficient local accuracy to monitor actual changes in landscape suitability for honey bees, but our model proved informative for evaluating effects on suitability under scenarios of land change. The scenario we implemented was aligned with current drivers of land-use change in the Northern Great Plains and highlighted the importance of conservation lands in landscapes intensively and extensively managed for crops.</span></p>","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0099268","usgsCitation":"Gallant, A.L., Euliss, N.H., and Browning, Z., 2014, Mapping large-area landscape suitability for honey bees to assess the influence of land-use change on sustainability of national pollination services: PLoS ONE, v. 9, no. 6, p. 1-14, https://doi.org/10.1371/journal.pone.0099268.","productDescription":"e99268; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-044117","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472992,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0099268","text":"Publisher Index Page"},{"id":341316,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"6","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2014-06-11","publicationStatus":"PW","scienceBaseUri":"591abe38e4b0a7fdb43c8bfd","contributors":{"authors":[{"text":"Gallant, Alisa L. 0000-0002-3029-6637 gallant@usgs.gov","orcid":"https://orcid.org/0000-0002-3029-6637","contributorId":2940,"corporation":false,"usgs":true,"family":"Gallant","given":"Alisa","email":"gallant@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":695163,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Euliss, Ned H. Jr. ceuliss@usgs.gov","contributorId":2916,"corporation":false,"usgs":true,"family":"Euliss","given":"Ned","suffix":"Jr.","email":"ceuliss@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":false,"id":695162,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Browning, Zac","contributorId":192022,"corporation":false,"usgs":false,"family":"Browning","given":"Zac","email":"","affiliations":[],"preferred":false,"id":695164,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70156335,"text":"70156335 - 2014 - A new Liopropoma sea bass (Serranidae, Epinephelinae, Liopropomini) from deep reefs off Curaçao, southern Caribbean, with comments on depth distributions of western Atlantic liopropomins","interactions":[],"lastModifiedDate":"2022-11-09T16:53:20.190775","indexId":"70156335","displayToPublicDate":"2014-05-15T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3808,"text":"ZooKeys","active":true,"publicationSubtype":{"id":10}},"displayTitle":"A new <i>Liopropoma</i> sea bass (Serranidae, Epinephelinae, Liopropomini) from deep reefs off Curaçao, southern Caribbean, with comments on depth distributions of western Atlantic liopropomins","title":"A new Liopropoma sea bass (Serranidae, Epinephelinae, Liopropomini) from deep reefs off Curaçao, southern Caribbean, with comments on depth distributions of western Atlantic liopropomins","docAbstract":"<p><span>Collecting reef-fish specimens using a manned submersible diving to 300 m off Cura&ccedil;ao, southern Caribbean, is resulting in the discovery of numerous new fish species. The new&nbsp;</span><i>Liopropoma</i><span>&nbsp;sea bass described here differs from other western Atlantic members of the genus in having VIII, 13 dorsal-fin rays; a moderately indented dorsal-fin margin; a yellow-orange stripe along the entire upper lip; a series of approximately 13 white, chevron-shaped markings on the ventral portion of the trunk; and a reddish-black blotch on the tip of the lower caudal-fin lobe. The new species, with predominantly yellow body and fins, closely resembles the other two &ldquo;golden basses&rdquo; found together with it at Cura&ccedil;ao:&nbsp;</span><i>L. aberrans</i><span>and&nbsp;</span><i>L. olneyi</i><span>. It also shares morphological features with the other western Atlantic liopropomin genus,</span><i>Bathyanthias</i><span>. Preliminary phylogenetic data suggest that western Atlantic liopropomins, including</span><i>Bathyanthias</i><span>, are monophyletic with respect to Indo-Pacific&nbsp;</span><i>Liopropoma</i><span>, and that&nbsp;</span><i>Bathyanthias</i><span>&nbsp;is nested within&nbsp;</span><i>Liopropoma</i><span>, indicating a need for further study of the generic limits of&nbsp;</span><i>Liopropoma</i><span>. The phylogenetic data also suggest that western Atlantic liopropomins comprise three monophyletic clades that have overlapping depth distributions but different depth maxima (3&ndash;135 m, 30&ndash;150 m, 133&ndash;411 m). The new species has the deepest depth range (182&ndash;241 m) of any known western Atlantic&nbsp;</span><i>Liopropoma</i><span>species. Both allopatric and depth-mediated ecological speciation may have contributed to the evolution of western Atlantic Liopropomini.</span></p>","language":"English","publisher":"Pensoft","doi":"10.3897/zookeys.409.7249","usgsCitation":"Baldwin, C.C., and Robertson, D.R., 2014, A new Liopropoma sea bass (Serranidae, Epinephelinae, Liopropomini) from deep reefs off Curaçao, southern Caribbean, with comments on depth distributions of western Atlantic liopropomins: ZooKeys, v. 409, p. 71-92, https://doi.org/10.3897/zookeys.409.7249.","productDescription":"21 p.","startPage":"71","endPage":"92","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":472993,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3897/zookeys.409.7249","text":"Publisher Index Page"},{"id":306972,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Curaçao","otherGeospatial":"Caribbean Sea","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -69.15329234262654,\n              12.384060135399267\n            ],\n            [\n              -69.18094060579891,\n              12.411063779703056\n            ],\n            [\n              -69.25466969272212,\n              12.438064664798205\n            ],\n            [\n              -69.39175971371935,\n              12.358178939513664\n            ],\n            [\n              -69.40903996846703,\n              12.25350298488344\n            ],\n            [\n              -69.32494272869563,\n              12.100353754334805\n            ],\n            [\n              -69.17518052088319,\n              11.951624926797635\n            ],\n            [\n              -68.88026417319077,\n              11.831004389698933\n            ],\n            [\n              -68.65907691242161,\n              11.800559003146262\n            ],\n            [\n              -68.63258052180896,\n              11.99782980112245\n            ],\n            [\n              -68.73511003331132,\n              12.041773432250253\n            ],\n            [\n              -68.7754306277219,\n              12.048533353486093\n            ],\n            [\n              -68.80307903531833,\n              12.042900097607273\n            ],\n            [\n              -68.83303162130423,\n              12.065432452958348\n            ],\n            [\n              -68.83763968923722,\n              12.090215810791918\n            ],\n            [\n              -68.87680826666508,\n              12.093595181789254\n            ],\n            [\n              -68.90100062331175,\n              12.107112238600564\n            ],\n            [\n              -68.90100062331175,\n              12.13864937650338\n            ],\n            [\n              -68.9228889459919,\n              12.145406849234362\n            ],\n            [\n              -68.92980104789089,\n              12.134144299441047\n            ],\n            [\n              -68.95860147247,\n              12.13527057584787\n            ],\n            [\n              -68.97818576118418,\n              12.153290350641385\n            ],\n            [\n              -69.01505030464554,\n              12.194956402793878\n            ],\n            [\n              -69.06458703492211,\n              12.21972770967487\n            ],\n            [\n              -69.11873183313116,\n              12.286148389039383\n            ],\n            [\n              -69.14407620676106,\n              12.314287692758043\n            ],\n            [\n              -69.14868427469355,\n              12.340173188153827\n            ],\n            [\n              -69.15329234262654,\n              12.384060135399267\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"409","noUsgsAuthors":false,"publicationDate":"2014-05-15","publicationStatus":"PW","scienceBaseUri":"55d5a8abe4b0518e3546a4a4","contributors":{"authors":[{"text":"Baldwin, Carole C.","contributorId":146698,"corporation":false,"usgs":false,"family":"Baldwin","given":"Carole","email":"","middleInitial":"C.","affiliations":[{"id":13062,"text":"Department of Vertebrate Zoology, National Museum of Natural History, Smithsonian Institution","active":true,"usgs":false}],"preferred":false,"id":568747,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robertson, D. Ross","contributorId":146699,"corporation":false,"usgs":false,"family":"Robertson","given":"D.","email":"","middleInitial":"Ross","affiliations":[{"id":12671,"text":"Smithsonian Tropical Research Institute","active":true,"usgs":false}],"preferred":false,"id":568748,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70077617,"text":"sir20145023 - 2014 - Status and understanding of groundwater quality in the South Coast Interior groundwater basins, 2008: California GAMA Priority Basin Project","interactions":[],"lastModifiedDate":"2014-05-14T10:24:01","indexId":"sir20145023","displayToPublicDate":"2014-05-14T10:07:28","publicationYear":"2014","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":"2014-5023","title":"Status and understanding of groundwater quality in the South Coast Interior groundwater basins, 2008: California GAMA Priority Basin Project","docAbstract":"<p>Groundwater quality in the approximately 653-square-mile (1,691-square-kilometer) South Coast Interior Basins (SCI) study unit was investigated as part of the Priority Basin Project of the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The South Coast Interior Basins study unit contains eight priority groundwater basins grouped into three study areas, Livermore, Gilroy, and Cuyama, in the Southern Coast Ranges hydrogeologic province. The GAMA Priority Basin Project is being conducted by the California State Water Resources Control Board in collaboration with the U.S. Geological Survey (USGS) and the Lawrence Livermore National Laboratory.</p>\n\n<br>\n\n<p>The GAMA South Coast Interior Basins study was designed to provide a spatially unbiased assessment of untreated (raw) groundwater quality within the primary aquifer system, as well as a statistically consistent basis for comparing water quality between basins. The assessment was based on water-quality and ancillary data collected by the USGS from 50 wells in 2008 and on water-quality data from the California Department of Public Health (CDPH) database. The primary aquifer system was defined by the depth intervals of the wells listed in the CDPH database for the SCI study unit. The quality of groundwater in the primary aquifer system may be different from that in the shallower or deeper water-bearing zones; shallow groundwater may be more vulnerable to surficial contamination.</p>\n\n<br>\n\n<p>The first component of this study, the status of the current quality of the groundwater resource, was assessed by using data from samples analyzed for volatile organic compounds (VOCs), pesticides, and naturally occurring inorganic constituents, such as trace elements and minor ions. This status assessment is intended to characterize the quality of groundwater resources within the primary aquifer system of the SCI study unit, not the treated drinking water delivered to consumers by water purveyors.</p>\n\n<br>\n\n<p>Relative-concentrations (sample concentration divided by the health- or aesthetic-based benchmark concentration) were used for evaluating groundwater quality for those constituents that have Federal or California regulatory or non-regulatory benchmarks for drinking-water quality. A relative-concentration greater than 1.0 indicates a concentration greater than a benchmark, and a relative-concentration less than or equal to 1.0 indicates a concentration equal to or less than a benchmark. Relative-concentrations of organic constituents and special-interest constituents were classified as “high” (relative-concentration greater than 1.0), “moderate” (relative-concentration greater than 0.1 and less than or equal to 1.0), or “low” (relative-concentration less than or equal to 0.1). Relative-concentrations of inorganic constituents were classified as “high” (relative-concentration greater than 1.0), “moderate” (relative-concentration greater than 0.5 and less than or equal to 1.0), or “low” (relative-concentration less than or equal to 0.5).</p>\n\n<br>\n\n<p>Aquifer-scale proportion was used as the primary metric in the status assessment for evaluating regional-scale groundwater quality. High aquifer-scale proportion is defined as the percentage of the area of the primary aquifer system with a relative-concentration greater than 1.0 for a particular constituent or class of constituents; percentage is based on an areal rather than a volumetric basis. Moderate and low aquifer-scale proportions were defined as the areal percentage of the primary aquifer system with moderate and low relative-concentrations, respectively. Two statistical approaches—grid-based and spatially weighted—were used to evaluate aquifer-scale proportions for individual constituents and classes of constituents. Grid-based and spatially weighted estimates were comparable in the SCI study unit (within 90-percent confidence intervals).</p>\n\n<br>\n\n<p>Inorganic constituents (one or more) with health-based benchmarks were detected at high relative-concentrations in 29 percent of the primary aquifer system, at moderate relative-concentrations in 37 percent, and at low relative-concentrations in 34 percent. High aquifer-scale proportions of inorganic constituents primarily reflected high aquifer-scale proportions of nitrate (14 percent), boron (8.6 percent), molybdenum (8.6 percent), and arsenic (5.7 percent). In contrast, the relative-concentrations of organic constituents (one or more) were high in 1.6 percent, moderate in 2.0 percent, and low or not detected in 96 percent of the primary aquifer system. Of the 207 organic and special-interest constituents analyzed for, 15 constituents were detected. Perchlorate was found at moderate relative-concentrations in 34 percent of the aquifer. Two organic constituents were frequently detected (in greater than 10 percent of samples): the trihalomethane chloroform and the herbicide simazine.</p>\n\n<br>\n\n<p>The second component of this study, the understanding assessment, identified natural and human factors that may have affected groundwater quality by evaluating land use, physical characteristics of the wells, and geochemical conditions of the aquifer. This evaluation was done by using statistical tests of correlations between these potential explanatory factors and water-quality data. Concentrations of arsenic, molybdenum, and manganese were generally greater in anoxic and pre-modern groundwater than other groundwater. In contrast, concentrations of nitrate and perchlorate were significantly higher in oxic and modern groundwater. Concentrations of simazine were greater in modern than pre-modern groundwater. Chloroform detections were positively correlated with greater urban land use. Boron concentrations and chloroform detections were higher in the Livermore study area than in the other study areas of the SCI; total dissolved solids and sulfate concentrations were greater in the Cuyama study area.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145023","collaboration":"A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program; Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Parsons, M.C., Kulongoski, J., and Belitz, K., 2014, Status and understanding of groundwater quality in the South Coast Interior groundwater basins, 2008: California GAMA Priority Basin Project: U.S. Geological Survey Scientific Investigations Report 2014-5023, Report: x, 68 p.; Related Report, https://doi.org/10.3133/sir20145023.","productDescription":"Report: x, 68 p.; Related Report","numberOfPages":"82","additionalOnlineFiles":"Y","ipdsId":"IP-026177","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":287116,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145023.jpg"},{"id":287112,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5023/"},{"id":287115,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/fs/2013/3088/"},{"id":287114,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5023/pdf/sir2014-5023.pdf"}],"projection":"Albers Equal Area Conic Projection","country":"United States","state":"California","otherGeospatial":"South Coast Interior Basins","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -0.01611111111111111,8.333333333333334E-4 ], [ -0.01611111111111111,0.0011111111111111111 ], [ -0.01638888888888889,0.0011111111111111111 ], [ -0.01638888888888889,8.333333333333334E-4 ], [ -0.01611111111111111,8.333333333333334E-4 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53748252e4b0870f4d23cf94","contributors":{"authors":[{"text":"Parsons, Mary C. mparsons@usgs.gov","contributorId":1571,"corporation":false,"usgs":true,"family":"Parsons","given":"Mary","email":"mparsons@usgs.gov","middleInitial":"C.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":489938,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kulongoski, Justin T. 0000-0002-3498-4154","orcid":"https://orcid.org/0000-0002-3498-4154","contributorId":94750,"corporation":false,"usgs":true,"family":"Kulongoski","given":"Justin T.","affiliations":[],"preferred":false,"id":489939,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":489937,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70104282,"text":"70104282 - 2014 - Habitat coupling in a large lake system: delivery of an energy subsidy by an offshore planktivore to the nearshore zone of Lake Superior","interactions":[],"lastModifiedDate":"2014-05-13T13:22:22","indexId":"70104282","displayToPublicDate":"2014-05-13T13:14:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Habitat coupling in a large lake system: delivery of an energy subsidy by an offshore planktivore to the nearshore zone of Lake Superior","docAbstract":"<p>1.  We hypothesised that the autumn spawning migration of Lake Superior cisco (<i>Coregonus artedi</i>) provides a resource subsidy, in the form of energy-rich cisco eggs, from the offshore pelagic to the nearshore benthic community over winter, when alternate prey production is likely to be low.</p>\n<br/>\n<p>2.  We tested this hypothesis using fish and macroinvertebrate surveys, fish population demographics, diet and stable isotope analyses, and bioenergetics modelling.</p>\n<br/>\n<p>3.  The benthic, congeneric lake whitefish (<i>C. clupeaformis</i>) was a clear beneficiary of cisco spawning. Cisco eggs represented 16% of lake whitefish annual consumption in terms of biomass, but 34% of energy (because of their high energy density: >10 kJ g wet mass<sup>−1</sup>). Stable isotope analyses were consistent with these results and suggest that other nearshore fish species may also rely on cisco eggs.</p>\n<br/>\n<p>4.  The lipid content of lake whitefish liver almost doubled from 26 to 49% between November and March, while that of muscle increased from 14 to 26% over the same period, suggesting lake whitefish were building, rather than depleting, lipid reserves during winter.</p>\n<br/>\n<p>5.  In the other Laurentian Great Lakes, where cisco populations remain very low and rehabilitation efforts are underway, the offshore-to-nearshore ecological link apparent in Lake Superior has been replaced by non-native planktivorous species. These non-native species spawn in spring have smaller eggs and shorter incubation periods. The rehabilitation of cisco in these systems should reinstate the onshore subsidy as it has in Lake Superior.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Freshwater Biology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/fwb.12340","usgsCitation":"Stockwell, J.D., Yule, D., Hrabik, T.R., Sierszen, M.E., and Isaac, E.J., 2014, Habitat coupling in a large lake system: delivery of an energy subsidy by an offshore planktivore to the nearshore zone of Lake Superior: Freshwater Biology, v. 59, no. 6, p. 1197-1212, https://doi.org/10.1111/fwb.12340.","productDescription":"16 p.","startPage":"1197","endPage":"1212","numberOfPages":"16","ipdsId":"IP-050829","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":287094,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287093,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/fwb.12340"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Great Lakes;Lake Superior","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92.373,46.4974 ], [ -92.373,47.3983 ], [ -90.2362,47.3983 ], [ -90.2362,46.4974 ], [ -92.373,46.4974 ] ] ] } } ] }","volume":"59","issue":"6","noUsgsAuthors":false,"publicationDate":"2014-02-21","publicationStatus":"PW","scienceBaseUri":"537330d4e4b04970612788b8","contributors":{"authors":[{"text":"Stockwell, Jason D. 0000-0003-3393-6799","orcid":"https://orcid.org/0000-0003-3393-6799","contributorId":61004,"corporation":false,"usgs":false,"family":"Stockwell","given":"Jason","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":493657,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yule, Daniel L.","contributorId":92130,"corporation":false,"usgs":true,"family":"Yule","given":"Daniel L.","affiliations":[],"preferred":false,"id":493660,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hrabik, Thomas R.","contributorId":35614,"corporation":false,"usgs":false,"family":"Hrabik","given":"Thomas","email":"","middleInitial":"R.","affiliations":[{"id":6915,"text":"University of Minnesota - Duluth","active":true,"usgs":false}],"preferred":false,"id":493656,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sierszen, Michael E.","contributorId":63320,"corporation":false,"usgs":false,"family":"Sierszen","given":"Michael","email":"","middleInitial":"E.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":493658,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Isaac, Edmund J.","contributorId":64120,"corporation":false,"usgs":true,"family":"Isaac","given":"Edmund","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":493659,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70095522,"text":"tm6A50 - 2014 - Two graphical user interfaces for managing and analyzing MODFLOW groundwater-model scenarios","interactions":[],"lastModifiedDate":"2014-05-13T11:56:05","indexId":"tm6A50","displayToPublicDate":"2014-05-13T11:52:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"6-A50","title":"Two graphical user interfaces for managing and analyzing MODFLOW groundwater-model scenarios","docAbstract":"<p>Scenario Manager and Scenario Analyzer are graphical user interfaces that facilitate the use of calibrated, MODFLOW-based groundwater models for investigating possible responses to proposed stresses on a groundwater system. Scenario Manager allows a user, starting with a calibrated model, to design and run model scenarios by adding or modifying stresses simulated by the model. Scenario Analyzer facilitates the process of extracting data from model output and preparing such display elements as maps, charts, and tables. Both programs are designed for users who are familiar with the science on which groundwater modeling is based but who may not have a groundwater modeler’s expertise in building and calibrating a groundwater model from start to finish.</p>\n<br/>\n<p>With Scenario Manager, the user can manipulate model input to simulate withdrawal or injection wells, time-variant specified hydraulic heads, recharge, and such surface-water features as rivers and canals. Input for stresses to be simulated comes from user-provided geographic information system files and time-series data files. A Scenario Manager project can contain multiple scenarios and is self-documenting.</p>\n<br/>\n<p>Scenario Analyzer can be used to analyze output from any MODFLOW-based model; it is not limited to use with scenarios generated by Scenario Manager. Model-simulated values of hydraulic head, drawdown, solute concentration, and cell-by-cell flow rates can be presented in display elements. Map data can be represented as lines of equal value (contours) or as a gradated color fill. Charts and tables display time-series data obtained from output generated by a transient-state model run or from user-provided text files of time-series data. A display element can be based entirely on output of a single model run, or, to facilitate comparison of results of multiple scenarios, an element can be based on output from multiple model runs. Scenario Analyzer can export display elements and supporting metadata as a Portable Document Format file.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section A: Groundwater in Book 6 <i>Modeling Techniques</i>","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6A50","collaboration":"Prepared in cooperation with Miami-Dade County Water and Sewer Department. This report is Chapter 50 of Section A: Groundwater in Book 6 <i>Modeling Techniques</i>.","usgsCitation":"Banta, E., 2014, Two graphical user interfaces for managing and analyzing MODFLOW groundwater-model scenarios: U.S. Geological Survey Techniques and Methods 6-A50, Report: v, 38 p.; Software Download, https://doi.org/10.3133/tm6A50.","productDescription":"Report: v, 38 p.; Software Download","numberOfPages":"47","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-049500","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":287086,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm6A50.jpg"},{"id":287084,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/6a50/pdf/tm6a50.pdf"},{"id":287085,"type":{"id":7,"text":"Companion Files"},"url":"https://water.usgs.gov/software/ScenarioTools/"},{"id":287083,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/6a50/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"537330d5e4b04970612788c2","contributors":{"authors":[{"text":"Banta, Edward R.","contributorId":49820,"corporation":false,"usgs":true,"family":"Banta","given":"Edward R.","affiliations":[],"preferred":false,"id":491226,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70104213,"text":"70104213 - 2014 - Evaluation of sensor types and environmental controls on mapping biomass of coastal marsh emergent vegetation","interactions":[],"lastModifiedDate":"2014-05-13T10:37:49","indexId":"70104213","displayToPublicDate":"2014-05-13T10:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of sensor types and environmental controls on mapping biomass of coastal marsh emergent vegetation","docAbstract":"There is a need to quantify large-scale plant productivity in coastal marshes to understand marsh resilience to sea level rise, to help define eligibility for carbon offset credits, and to monitor impacts from land use, eutrophication and contamination. Remote monitoring of aboveground biomass of emergent wetland vegetation will help address this need. Differences in sensor spatial resolution, bandwidth, temporal frequency and cost constrain the accuracy of biomass maps produced for management applications. In addition the use of vegetation indices to map biomass may not be effective in wetlands due to confounding effects of water inundation on spectral reflectance. To address these challenges, we used partial least squares regression to select optimal spectral features in situ and with satellite reflectance data to develop predictive models of aboveground biomass for common emergent freshwater marsh species, <i>Typha</i> spp. and <i>Schoenoplectus acutus</i>, at two restored marshes in the Sacramento–San Joaquin River Delta, California, USA. We used field spectrometer data to test model errors associated with hyperspectral narrowbands and multispectral broadbands, the influence of water inundation on prediction accuracy, and the ability to develop species specific models. We used Hyperion data, Digital Globe World View-2 (WV-2) data, and Landsat 7 data to scale up the best statistical models of biomass. Field spectrometer-based models of the full dataset showed that narrowband reflectance data predicted biomass somewhat, though not significantly better than broadband reflectance data [R<sup>2</sup> = 0.46 and percent normalized RMSE (%RMSE) = 16% for narrowband models]. However hyperspectral first derivative reflectance spectra best predicted biomass for plots where water levels were less than 15 cm (R<sup>2</sup> = 0.69, %RMSE = 12.6%). In species-specific models, error rates differed by species (<i>Typha</i> spp.: %RMSE = 18.5%; <i>S. acutus</i>: %RMSE = 24.9%), likely due to the more vertical structure and deeper water habitat of S. acutus. The Landsat 7 dataset (7 images) predicted biomass slightly better than the WV-2 dataset (6 images) (R<sup>2</sup> = 0.56, %RMSE = 20.9%, compared to R<sup>2</sup> = 0.45, RMSE = 21.5%). The Hyperion dataset (one image) was least successful in predicting biomass (R<sup>2</sup> = 0.27, %RMSE = 33.5%). Shortwave infrared bands on 30 m-resolution Hyperion and Landsat 7 sensors aided biomass estimation; however managers need to weigh tradeoffs between cost, additional spectral information, and high spatial resolution that will identify variability in small, fragmented marshes common to the Sacramento–San Joaquin River Delta and elsewhere in the Western U.S.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Remote Sensing of Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2014.04.003","usgsCitation":"Byrd, K.B., O'Connell, J., Di Tommaso, S., and Kelly, M., 2014, Evaluation of sensor types and environmental controls on mapping biomass of coastal marsh emergent vegetation: Remote Sensing of Environment, v. 149, p. 166-180, https://doi.org/10.1016/j.rse.2014.04.003.","productDescription":"15 p.","startPage":"166","endPage":"180","numberOfPages":"15","ipdsId":"IP-052200","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":287071,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287072,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2014.04.003"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-san Joaquin River Delta","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.7545,37.3797 ], [ -122.7545,38.2715 ], [ -121.2455,38.2715 ], [ -121.2455,37.3797 ], [ -122.7545,37.3797 ] ] ] } } ] }","volume":"149","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"537330d2e4b04970612788ae","chorus":{"doi":"10.1016/j.rse.2014.04.003","url":"http://dx.doi.org/10.1016/j.rse.2014.04.003","publisher":"Elsevier BV","authors":"Byrd Kristin B., O'Connell Jessica L., Di Tommaso Stefania, Kelly Maggi","journalName":"Remote Sensing of Environment","publicationDate":"6/2014"},"contributors":{"authors":[{"text":"Byrd, Kristin B. 0000-0002-5725-7486 kbyrd@usgs.gov","orcid":"https://orcid.org/0000-0002-5725-7486","contributorId":3814,"corporation":false,"usgs":true,"family":"Byrd","given":"Kristin","email":"kbyrd@usgs.gov","middleInitial":"B.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":493639,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O'Connell, Jessica L.","contributorId":86265,"corporation":false,"usgs":true,"family":"O'Connell","given":"Jessica L.","affiliations":[],"preferred":false,"id":493642,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Di Tommaso, Stefania","contributorId":9965,"corporation":false,"usgs":true,"family":"Di Tommaso","given":"Stefania","email":"","affiliations":[],"preferred":false,"id":493640,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kelly, Maggi","contributorId":14275,"corporation":false,"usgs":true,"family":"Kelly","given":"Maggi","affiliations":[],"preferred":false,"id":493641,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70104635,"text":"70104635 - 2014 - Evaluation of monkeypox virus infection of prairie dogs (Cynomys ludovicianus) using in vivo bioluminescent imaging","interactions":[],"lastModifiedDate":"2016-01-26T15:16:29","indexId":"70104635","displayToPublicDate":"2014-05-13T09:54:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of monkeypox virus infection of prairie dogs (Cynomys ludovicianus) using in vivo bioluminescent imaging","docAbstract":"<p>Monkeypox (MPX) is a re-emerging zoonotic disease that is endemic in Central and West Africa, where it can cause a smallpox-like disease in humans. Despite many epidemiologic and field investigations of MPX, no definitive reservoir species has been identified. Using recombinant viruses expressing the firefly luciferase (luc) gene, we previously demonstrated the suitability of in vivo bioluminescent imaging (BLI) to study the pathogenesis of MPX in animal models. Here, we evaluated BLI as a novel approach for tracking MPX virus infection in black-tailed prairie dogs (Cynomys ludovicianus). Prairie dogs were affected during a multistate outbreak of MPX in the US in 2003 and have since been used as an animal model of this disease. Our BLI results were compared with PCR and virus isolation from tissues collected postmortem. Virus was easily detected and quantified in skin and superficial tissues by BLI before and during clinical phases, as well as in subclinical secondary cases, but was not reliably detected in deep tissues such as the lung. Although there are limitations to viral detection in larger wild rodent species, BLI can enhance the use of prairie dogs as an animal model of MPX and can be used for the study of infection, disease progression, and transmission in potential wild rodent reservoirs.</p>","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/2013-07-171","usgsCitation":"Falendysz, E., Londono-Navas, A.M., Meteyer, C.U., Pussini, N., Lopera, J.G., Osorio, J., and Rocke, T.E., 2014, Evaluation of monkeypox virus infection of prairie dogs (Cynomys ludovicianus) using in vivo bioluminescent imaging: Journal of Wildlife Diseases, v. 50, no. 3, p. 524-536, https://doi.org/10.7589/2013-07-171.","productDescription":"13 p.","startPage":"524","endPage":"536","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-045588","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":472994,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://doi.org/10.7589/2013-07-171","text":"External Repository"},{"id":287256,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287255,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.7589/2013-07-171"}],"country":"United States","state":"South Dakota","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -104.17236328125,\n              46.01222384063238\n            ],\n            [\n              -96.52587890625,\n              46.027481852486645\n            ],\n            [\n              -96.50390625,\n              45.73685954736049\n            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}\n  ]\n}","volume":"50","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53771748e4b02eab8669ebfb","contributors":{"authors":[{"text":"Falendysz, Elizabeth A.","contributorId":28532,"corporation":false,"usgs":true,"family":"Falendysz","given":"Elizabeth A.","affiliations":[],"preferred":false,"id":493782,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Londono-Navas, Angela M.","contributorId":27365,"corporation":false,"usgs":true,"family":"Londono-Navas","given":"Angela","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":493781,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Meteyer, Carol U. 0000-0002-4007-3410 cmeteyer@usgs.gov","orcid":"https://orcid.org/0000-0002-4007-3410","contributorId":111,"corporation":false,"usgs":true,"family":"Meteyer","given":"Carol","email":"cmeteyer@usgs.gov","middleInitial":"U.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":493778,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pussini, Nicola","contributorId":85889,"corporation":false,"usgs":true,"family":"Pussini","given":"Nicola","email":"","affiliations":[],"preferred":false,"id":493784,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lopera, Juan G.","contributorId":7574,"corporation":false,"usgs":false,"family":"Lopera","given":"Juan","email":"","middleInitial":"G.","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":493780,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Osorio, Jorge E.","contributorId":50392,"corporation":false,"usgs":false,"family":"Osorio","given":"Jorge E.","affiliations":[{"id":13052,"text":"Department of Pathobiological Sciences, School of Veterinary Medicine, University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":493783,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rocke, Tonie E. 0000-0003-3933-1563 trocke@usgs.gov","orcid":"https://orcid.org/0000-0003-3933-1563","contributorId":2665,"corporation":false,"usgs":true,"family":"Rocke","given":"Tonie","email":"trocke@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":493779,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70104177,"text":"70104177 - 2014 - Assessment of suitable habitat for <i>Phragmites australis</i> (common reed) in the Great Lakes coastal zone","interactions":[],"lastModifiedDate":"2014-05-12T14:45:57","indexId":"70104177","displayToPublicDate":"2014-05-12T14:38:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":868,"text":"Aquatic Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of suitable habitat for <i>Phragmites australis</i> (common reed) in the Great Lakes coastal zone","docAbstract":"In the Laurentian Great Lakes, the invasive form of <i>Phragmites australis</i> (common reed) poses a threat to highly productive coastal wetlands and shorelines by forming impenetrable stands that outcompete native plants. Large, dominant stands can derail efforts to restore wetland ecosystems degraded by other stressors. To be proactive, landscape-level management of <i>Phragmites</i> requires information on the current spatial distribution of the species and a characterization of areas suitable for future colonization. Using a recent basin-scale map of this invasive plant’s distribution in the U.S. coastal zone of the Great Lakes, environmental data (e.g., soils, nutrients, disturbance, climate, topography), and climate predictions, we performed analyses of current and predicted suitable coastal habitat using boosted regression trees, a type of species distribution modeling. We also investigated differential influences of environmental variables in the upper lakes (Lakes Superior, Michigan, and Huron) and lower lakes (Lakes St. Clair, Erie, and Ontario). Basin-wide results showed that the coastal areas most vulnerable to <i>Phragmites</i> expansion were in close proximity to developed lands and had minimal topographic relief, poorly drained soils, and dense road networks. Elevated nutrients and proximity to agriculture also influenced the distribution of <i>Phragmites</i>. Climate predictions indicated an increase in suitable habitat in coastal Lakes Huron and Michigan in particular. The results of this study, combined with a publicly available online decision support tool, will enable resource managers and restoration practitioners to target and prioritize <i>Phragmites</i> control efforts in the Great Lakes coastal zone.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Aquatic Invasions","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Regional Euro-Asian Biological Invasions Centre","publisherLocation":"Helsinki, Finland","doi":"10.3391/ai.2014.9.1.01","usgsCitation":"Carlson Mazur, M.L., Kowalski, K., and Galbraith, D., 2014, Assessment of suitable habitat for <i>Phragmites australis</i> (common reed) in the Great Lakes coastal zone: Aquatic Invasions, v. 9, no. 1, p. 1-19, https://doi.org/10.3391/ai.2014.9.1.01.","productDescription":"19 p.","startPage":"1","endPage":"19","numberOfPages":"19","ipdsId":"IP-051546","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":472996,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/ai.2014.9.1.01","text":"Publisher Index Page"},{"id":287062,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287061,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3391/ai.2014.9.1.01"}],"country":"United States","otherGeospatial":"Great Lakes","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92.9911,39.981 ], [ -92.9911,49.0076 ], [ -73.9943,49.0076 ], [ -73.9943,39.981 ], [ -92.9911,39.981 ] ] ] } } ] }","volume":"9","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5371df51e4b08449547883cf","contributors":{"authors":[{"text":"Carlson Mazur, Martha L.","contributorId":95377,"corporation":false,"usgs":true,"family":"Carlson Mazur","given":"Martha","email":"","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":493591,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kowalski, Kurt P. 0000-0002-8424-4701 kkowalski@usgs.gov","orcid":"https://orcid.org/0000-0002-8424-4701","contributorId":3768,"corporation":false,"usgs":true,"family":"Kowalski","given":"Kurt P.","email":"kkowalski@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":493589,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Galbraith, David","contributorId":19479,"corporation":false,"usgs":true,"family":"Galbraith","given":"David","affiliations":[],"preferred":false,"id":493590,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70104182,"text":"70104182 - 2014 - Phytoplankton primary production in the world's estuarine-coastal ecosystems","interactions":[],"lastModifiedDate":"2014-05-12T14:15:49","indexId":"70104182","displayToPublicDate":"2014-05-12T14:08:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1011,"text":"Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Phytoplankton primary production in the world's estuarine-coastal ecosystems","docAbstract":"<p>Estuaries are biogeochemical hot spots because they receive large inputs of nutrients and organic carbon from land and oceans to support high rates of metabolism and primary production. We synthesize published rates of annual phytoplankton primary production (APPP) in marine ecosystems influenced by connectivity to land – estuaries, bays, lagoons, fjords and inland seas. Review of the scientific literature produced a compilation of 1148 values of APPP derived from monthly incubation assays to measure carbon assimilation or oxygen production. The median value of median APPP measurements in 131 ecosystems is 185 and the mean is 252 g C m<sup>−2</sup> yr<sup>−1</sup>, but the range is large: from −105 (net pelagic production in the Scheldt Estuary) to 1890 g C m<sup>−2</sup> yr</sup>−1</sup> (net phytoplankton production in Tamagawa Estuary). APPP varies up to 10-fold within ecosystems and 5-fold from year to year (but we only found eight APPP series longer than a decade so our knowledge of decadal-scale variability is limited). We use studies of individual places to build a conceptual model that integrates the mechanisms generating this large variability: nutrient supply, light limitation by turbidity, grazing by consumers, and physical processes (river inflow, ocean exchange, and inputs of heat, light and wind energy). We consider method as another source of variability because the compilation includes values derived from widely differing protocols. A simulation model shows that different methods reported in the literature can yield up to 3-fold variability depending on incubation protocols and methods for integrating measured rates over time and depth. </p>\n<br/>\n<p>Although attempts have been made to upscale measures of estuarine-coastal APPP, the empirical record is inadequate for yielding reliable global estimates. The record is deficient in three ways. First, it is highly biased by the large number of measurements made in northern Europe (particularly the Baltic region) and North America. Of the 1148 reported values of APPP, 958 come from sites between 30 and 60° N; we found only 36 for sites south of 20° N. Second, of the 131 ecosystems where APPP has been reported, 37% are based on measurements at only one location during 1 year. The accuracy of these values is unknown but probably low, given the large interannual and spatial variability within ecosystems. Finally, global assessments are confounded by measurements that are not intercomparable because they were made with different methods. </p>\n<br/>\n<p>Phytoplankton primary production along the continental margins is tightly linked to variability of water quality, biogeochemical processes including ocean–atmosphere CO<sub>2</sub> exchange, and production at higher trophic levels including species we harvest as food. The empirical record has deficiencies that preclude reliable global assessment of this key Earth system process. We face two grand challenges to resolve these deficiencies: (1) organize and fund an international effort to use a common method and measure APPP regularly across a network of coastal sites that are globally representative and sustained over time, and (2) integrate data into a unifying model to explain the wide range of variability across ecosystems and to project responses of APPP to regional manifestations of global change as it continues to unfold.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Biogeosciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Copernicus Publications on behalf of the European Geosciences Union","doi":"10.5194/bg-11-2477-2014","usgsCitation":"Cloern, J.E., Foster, S., and Kleckner, A., 2014, Phytoplankton primary production in the world's estuarine-coastal ecosystems: Biogeosciences, v. 11, p. 2477-2501, https://doi.org/10.5194/bg-11-2477-2014.","productDescription":"25 p.","startPage":"2477","endPage":"2501","numberOfPages":"25","ipdsId":"IP-049711","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":472998,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/bg-11-2477-2014","text":"Publisher Index Page"},{"id":287056,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287055,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.5194/bg-11-2477-2014"}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -180.0,-90.0 ], [ -180.0,90.0 ], [ 180.0,90.0 ], [ 180.0,-90.0 ], [ -180.0,-90.0 ] ] ] } } ] }","volume":"11","noUsgsAuthors":false,"publicationDate":"2014-05-07","publicationStatus":"PW","scienceBaseUri":"5371df52e4b08449547883d9","contributors":{"authors":[{"text":"Cloern, James E. 0000-0002-5880-6862 jecloern@usgs.gov","orcid":"https://orcid.org/0000-0002-5880-6862","contributorId":1488,"corporation":false,"usgs":true,"family":"Cloern","given":"James","email":"jecloern@usgs.gov","middleInitial":"E.","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":493615,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Foster, S.Q.","contributorId":103184,"corporation":false,"usgs":true,"family":"Foster","given":"S.Q.","email":"","affiliations":[],"preferred":false,"id":493617,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kleckner, A.E.","contributorId":33627,"corporation":false,"usgs":true,"family":"Kleckner","given":"A.E.","email":"","affiliations":[],"preferred":false,"id":493616,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70104153,"text":"ofr20141095 - 2014 - State-and-transition prototype model of riparian vegetation downstream of Glen Canyon Dam, Arizona","interactions":[],"lastModifiedDate":"2014-05-12T07:59:24","indexId":"ofr20141095","displayToPublicDate":"2014-05-12T07:37:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1095","title":"State-and-transition prototype model of riparian vegetation downstream of Glen Canyon Dam, Arizona","docAbstract":"Facing an altered riparian plant community dominated by nonnative species, resource managers are increasingly interested in understanding how to manage and promote healthy riparian habitats in which native species dominate. For regulated rivers, managing flows is one tool resource managers consider to achieve these goals. Among many factors that can influence riparian community composition, hydrology is a primary forcing variable. Frame-based models, used successfully in grassland systems, provide an opportunity for stakeholders concerned with riparian systems to evaluate potential riparian vegetation responses to alternative flows. Frame-based, state-and-transition models of riparian vegetation for reattachment bars, separation bars, and the channel margin found on the Colorado River downstream of Glen Canyon Dam were constructed using information from the literature. Frame-based models can be simple spreadsheet models (created in Microsoft® Excel) or developed further with programming languages (for example, C-sharp). The models described here include seven community states and five dam operations that cause transitions between states. Each model divides operations into growing (April–September) and non-growing seasons (October–March) and incorporates upper and lower bar models, using stage elevation as a division. The inputs (operations) can be used by stakeholders to evaluate flows that may promote dynamic riparian vegetation states, or identify those flow options that may promote less desirable states (for example, Tamarisk [Tamarix sp.] temporarily flooded shrubland). This prototype model, although simple, can still elicit discussion about operational options and vegetation response.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141095","collaboration":"Prepared in cooperation with AMS Consultants","usgsCitation":"Ralston, B., Starfield, A.M., Black, R.S., and Van Lonkhuyzen, R.A., 2014, State-and-transition prototype model of riparian vegetation downstream of Glen Canyon Dam, Arizona: U.S. Geological Survey Open-File Report 2014-1095, Report: iv, 26 p.;  Reattachment bar XLS; Separation bar XLS, https://doi.org/10.3133/ofr20141095.","productDescription":"Report: iv, 26 p.;  Reattachment bar XLS; Separation bar XLS","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-053362","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":287039,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141095.png"},{"id":287034,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1095/"},{"id":287036,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1095/pdf/ofr2014-1095.pdf"},{"id":287037,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1095/downloads/ofr2014-1095_Reattachmentbar.xls"},{"id":287038,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1095/downloads/ofr2014-1095_Separationbar.xls"}],"country":"United States","state":"Arizona;Nevada","otherGeospatial":"Glen Canyon Dam","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114.5,35.0 ], [ -114.5,37.5 ], [ -111.0,37.5 ], [ -111.0,35.0 ], [ -114.5,35.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5371df53e4b08449547883de","contributors":{"authors":[{"text":"Ralston, Barbara E.","contributorId":89848,"corporation":false,"usgs":true,"family":"Ralston","given":"Barbara E.","affiliations":[],"preferred":false,"id":493580,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Starfield, Anthony M.","contributorId":17142,"corporation":false,"usgs":true,"family":"Starfield","given":"Anthony","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":493577,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Black, Ronald S.","contributorId":65767,"corporation":false,"usgs":true,"family":"Black","given":"Ronald","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":493579,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Van Lonkhuyzen, Robert A.","contributorId":49705,"corporation":false,"usgs":true,"family":"Van Lonkhuyzen","given":"Robert","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":493578,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70103833,"text":"70103833 - 2014 - Investigating the importance of sediment resuspension in <i>Alexandrium fundyense</i> cyst population dynamics in the Gulf of Maine","interactions":[],"lastModifiedDate":"2014-05-29T15:09:13","indexId":"70103833","displayToPublicDate":"2014-05-08T09:49:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1371,"text":"Deep-Sea Research Part II: Topical Studies in Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Investigating the importance of sediment resuspension in <i>Alexandrium fundyense</i> cyst population dynamics in the Gulf of Maine","docAbstract":"Cysts of <i>Alexandrium fundyense</i>, a dinoflagellate that causes toxic algal blooms in the Gulf of Maine, spend the winter as dormant cells in the upper layer of bottom sediment or the bottom nepheloid layer and germinate in spring to initiate new blooms. Erosion measurements were made on sediment cores collected at seven stations in the Gulf of Maine in the autumn of 2011 to explore if resuspension (by waves and currents) could change the distribution of over-wintering cysts from patterns observed in the previous autumn; or if resuspension could contribute cysts to the water column during spring when cysts are viable. The mass of sediment eroded from the core surface at 0.4 Pa ranged from 0.05 kg m<sup>−2</sup> near Grand Manan Island, to 0.35 kg m<sup>−2</sup> in northern Wilkinson Basin. The depth of sediment eroded ranged from about 0.05 mm at a station with sandy sediment at 70 m water depth on the western Maine shelf, to about 1.2 mm in clayey–silt sediment at 250 m water depth in northern Wilkinson Basin. The sediment erodibility measurements were used in a sediment-transport model forced with modeled waves and currents for the period October 1, 2010 to May 31, 2011 to predict resuspension and bed erosion. The simulated spatial distribution and variation of bottom shear stress was controlled by the strength of the semi-diurnal tidal currents, which decrease from east to west along the Maine coast, and oscillatory wave-induced currents, which are strongest in shallow water. Simulations showed occasional sediment resuspension along the central and western Maine coast associated with storms, steady resuspension on the eastern Maine shelf and in the Bay of Fundy associated with tidal currents, no resuspension in northern Wilkinson Basin, and very small resuspension in western Jordan Basin. The sediment response in the model depended primarily on the profile of sediment erodibility, strength and time history of bottom stress, consolidation time scale, and the current in the water column. Based on analysis of wave data from offshore buoys from 1996 to 2012, the number of wave events inducing a bottom shear stress large enough to resuspend sediment at 80 m ranged from 0 to 2 in spring (April and May) and 0 to 10 in winter (October through March). Wave-induced resuspension is unlikely in water greater than about 100 m deep. The observations and model results suggest that a millimeter or so of sediment and associated cysts may be mobilized in both winter and spring, and that the frequency of resuspension will vary interannually. Depending on cyst concentration in the sediment and the vertical distribution in the water column, these events could result in a concentration in the water column of at least 10<sup>4</sup> cysts m<sup>−3</sup>. In some years, resuspension events could episodically introduce cysts into the water column in spring, where germination is likely to be facilitated at the time of bloom formation. An assessment of the quantitative effects of cyst resuspension on bloom dynamics in any particular year requires more detailed investigation.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Deep-Sea Research Part II: Topical Studies in Oceanography","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.dsr2.2013.10.011","usgsCitation":"Butman, B., Aretxabaleta, A., Dickhudt, P., Dalyander, P., Sherwood, C.R., Anderson, D.M., Keafer, B.A., and Signell, R.P., 2014, Investigating the importance of sediment resuspension in <i>Alexandrium fundyense</i> cyst population dynamics in the Gulf of Maine: Deep-Sea Research Part II: Topical Studies in Oceanography, v. 103, p. 79-95, https://doi.org/10.1016/j.dsr2.2013.10.011.","productDescription":"17 p.","startPage":"79","endPage":"95","numberOfPages":"17","ipdsId":"IP-044852","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":472999,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.dsr2.2013.10.011","text":"Publisher Index Page"},{"id":286986,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.dsr2.2013.10.011"},{"id":286987,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada;United States","otherGeospatial":"Bay Of Fundy;Grand Manan Island;Gulf Of Maine;Jordan Basin;Wilkinson Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -71.488,41.5003 ], [ -71.488,45.1549 ], [ -64.4678,45.1549 ], [ -64.4678,41.5003 ], [ -71.488,41.5003 ] ] ] } } ] }","volume":"103","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"536c9950e4b060efff280d88","contributors":{"authors":[{"text":"Butman, Bradford 0000-0002-4174-2073 bbutman@usgs.gov","orcid":"https://orcid.org/0000-0002-4174-2073","contributorId":943,"corporation":false,"usgs":true,"family":"Butman","given":"Bradford","email":"bbutman@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":493444,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aretxabaleta, Alfredo L.","contributorId":41311,"corporation":false,"usgs":true,"family":"Aretxabaleta","given":"Alfredo L.","affiliations":[],"preferred":false,"id":493447,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dickhudt, Patrick J.","contributorId":48302,"corporation":false,"usgs":true,"family":"Dickhudt","given":"Patrick J.","affiliations":[],"preferred":false,"id":493448,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dalyander, P. Soupy 0000-0001-9583-0872","orcid":"https://orcid.org/0000-0001-9583-0872","contributorId":65177,"corporation":false,"usgs":true,"family":"Dalyander","given":"P. Soupy","affiliations":[],"preferred":false,"id":493449,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":493446,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Anderson, Donald M.","contributorId":79801,"corporation":false,"usgs":true,"family":"Anderson","given":"Donald","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":493450,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Keafer, Bruce A.","contributorId":102795,"corporation":false,"usgs":true,"family":"Keafer","given":"Bruce","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":493451,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Signell, Richard P. rsignell@usgs.gov","contributorId":1435,"corporation":false,"usgs":true,"family":"Signell","given":"Richard","email":"rsignell@usgs.gov","middleInitial":"P.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":493445,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70103830,"text":"70103830 - 2014 - Stratigraphic controls on fluid and solute fluxes across the sediment-water interface of an estuary","interactions":[],"lastModifiedDate":"2014-05-08T09:43:58","indexId":"70103830","displayToPublicDate":"2014-05-08T09:35:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Stratigraphic controls on fluid and solute fluxes across the sediment-water interface of an estuary","docAbstract":"Shallow stratigraphic features, such as infilled paleovalleys, modify fresh groundwater discharge to coastal waters and fluxes of saltwater and nutrients across the sediment–water interface. We quantify the spatial distribution of shallow surface water–groundwater exchange and nitrogen fluxes near a paleovalley in Indian River Bay, Delaware, using a hand resistivity probe, conventional seepage meters, and pore-water samples. In the interfluve (region outside the paleovalley) most nitrate-rich fresh groundwater discharges rapidly near the coast with little mixing of saline pore water, and nitrogen transport is largely conservative. In the peat-filled paleovalley, fresh groundwater discharge is negligible, and saltwater exchange is deep (∼1 m). Long pore-water residence times and abundant sulfate and organic matter promote sulfate reduction and ammonium production in shallow sediment. Reducing, iron-rich fresh groundwater beneath paleovalley peat discharges diffusely around paleovalley margins offshore. In this zone of diffuse fresh groundwater discharge, saltwater exchange and dispersion are enhanced, ammonium is produced in shallow sediments, and fluxes of ammonium to surface water are large. By modifying patterns of groundwater discharge and the nature of saltwater exchange in shallow sediments, paleovalleys and other stratigraphic features influence the geochemistry of discharging groundwater. Redox reactions near the sediment–water interface affect rates and patterns of geochemical fluxes to coastal surface waters. For example, at this site, more than 99% of the groundwater-borne nitrate flux to the Delaware Inland Bays occurs within the interfluve portion of the coastline, and more than 50% of the ammonium flux occurs at the paleovalley margin.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Limnology and Oceanography","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.4319/lo.2014.59.3.0997","usgsCitation":"Sawyer, A.H., Lazareva, O., Kroeger, K.D., Crespo, K., Chan, C.S., Stieglitz, T., and Michael, H., 2014, Stratigraphic controls on fluid and solute fluxes across the sediment-water interface of an estuary: Limnology and Oceanography, v. 59, no. 3, p. 997-1010, https://doi.org/10.4319/lo.2014.59.3.0997.","productDescription":"14 p.","startPage":"997","endPage":"1010","numberOfPages":"14","ipdsId":"IP-054669","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":473000,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.4319/lo.2014.59.3.0997","text":"Publisher Index Page"},{"id":286983,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.4319/lo.2014.59.3.0997"},{"id":286984,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware","otherGeospatial":"Delaware Inland Bays;Indian River Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -75.7491,38.3974 ], [ -75.7491,39.5993 ], [ -74.1989,39.5993 ], [ -74.1989,38.3974 ], [ -75.7491,38.3974 ] ] ] } } ] }","volume":"59","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"536c9951e4b060efff280d8d","contributors":{"authors":[{"text":"Sawyer, Audrey H.","contributorId":48873,"corporation":false,"usgs":true,"family":"Sawyer","given":"Audrey","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":493436,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lazareva, Olesya","contributorId":97818,"corporation":false,"usgs":true,"family":"Lazareva","given":"Olesya","email":"","affiliations":[],"preferred":false,"id":493440,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kroeger, Kevin D. 0000-0002-4272-2349 kkroeger@usgs.gov","orcid":"https://orcid.org/0000-0002-4272-2349","contributorId":1603,"corporation":false,"usgs":true,"family":"Kroeger","given":"Kevin","email":"kkroeger@usgs.gov","middleInitial":"D.","affiliations":[{"id":41100,"text":"Coastal and Marine Hazards and Resources Program","active":true,"usgs":true}],"preferred":true,"id":493434,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crespo, Kyle","contributorId":93385,"corporation":false,"usgs":true,"family":"Crespo","given":"Kyle","email":"","affiliations":[],"preferred":false,"id":493439,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chan, Clara S.","contributorId":80191,"corporation":false,"usgs":true,"family":"Chan","given":"Clara","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":493438,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stieglitz, Thomas","contributorId":65005,"corporation":false,"usgs":true,"family":"Stieglitz","given":"Thomas","email":"","affiliations":[],"preferred":false,"id":493437,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Michael, Holly A.","contributorId":45998,"corporation":false,"usgs":true,"family":"Michael","given":"Holly A.","affiliations":[],"preferred":false,"id":493435,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70148490,"text":"70148490 - 2014 - Mechanisms of aquatic species invasions across the SALCC - an update","interactions":[],"lastModifiedDate":"2016-12-19T16:44:36","indexId":"70148490","displayToPublicDate":"2014-05-08T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Mechanisms of aquatic species invasions across the SALCC - an update","docAbstract":"The USGS Nonindigenous Aquatic Species Database (NAS; nas.er.usgs.gov) is a comprehensive tool for demonstrating where and when nonindigenous species have been sighted across the U.S. Information in the database is used for state-level invasive species management plans, to focus monitoring efforts, for public education, predictive modeling, and for avoiding unintentional introductions during inter-basin water transfers.\nOur project represents the first attempt to utilize the NAS Database within the context of a Landscape Conservation Cooperative conservation blueprint. A significant amount of effort during the past year was dedicated to determining the most appropriate use of these data for the purposes of identifying the mechanisms and patterns of aquatic species invasions. Descriptive analyses were first undertaken to characterize the spatial and temporal characteristics of the SALCC subset of NAS data.","language":"English","publisher":"Southeast Atlantic Landscape Conservation Cooperative","collaboration":"Robert Doarzio; Fred Johnson; Mike Turtora; Vic Engel; Pam Fuller","usgsCitation":"Benson, A.J., 2014, Mechanisms of aquatic species invasions across the SALCC - an update, HTML.","productDescription":"HTML","ipdsId":"IP-056360","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":332298,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":301092,"type":{"id":15,"text":"Index Page"},"url":"https://www.southatlanticlcc.org/profiles/blogs/mechanisms-of-aquatic-species-invasions-across-the-salcc-an"}],"publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5859000ae4b03639a6025e35","contributors":{"authors":[{"text":"Benson, Amy J. 0000-0002-4517-1466 abenson@usgs.gov","orcid":"https://orcid.org/0000-0002-4517-1466","contributorId":3836,"corporation":false,"usgs":true,"family":"Benson","given":"Amy","email":"abenson@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":548407,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70101719,"text":"ds709FF - 2014 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Farah mineral district in Afghanistan","interactions":[{"subject":{"id":70101719,"text":"ds709FF - 2014 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Farah mineral district in Afghanistan","indexId":"ds709FF","publicationYear":"2014","noYear":false,"chapter":"FF","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Farah mineral district in Afghanistan"},"predicate":"IS_PART_OF","object":{"id":70040370,"text":"ds709 - 2012 - Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","indexId":"ds709","publicationYear":"2012","noYear":false,"title":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan"},"id":1}],"isPartOf":{"id":70040370,"text":"ds709 - 2012 - Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","indexId":"ds709","publicationYear":"2012","noYear":false,"title":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan"},"lastModifiedDate":"2022-12-09T20:57:06.961314","indexId":"ds709FF","displayToPublicDate":"2014-05-07T12:42:20","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"709","chapter":"FF","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Farah mineral district in Afghanistan","docAbstract":"<p>The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Farah mineral district, which has spectral reflectance anomalies indicative of copper, zinc, lead, silver, and gold deposits.</p>\n\n<br>\n\n<p>ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2007, 2008, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement.</p>\n\n<br>\n\n<p>The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands).</p>\n\n<br>\n\n<p>All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (41 for Farah) and the WGS84 datum. The final image mosaics were subdivided into four overlapping tiles or quadrants because of the large size of the target area. The four image tiles (or quadrants) for the Farah area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Farah study area, five subareas were designated for detailed field investigations (that is, the FarahA through FarahE subareas); these subareas were extracted from the area’s image mosaic and are provided as separate embedded geotiff images.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (Data Series 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709FF","collaboration":"Prepared in cooperation with the U.S. Department of Defense <a href=\" http://tfbso.defense.gov/\" target=\"_blank\"> Task Force for Business and Stability Operations</a> and the <a href=\"http://www.bgs.ac.uk/AfghanMinerals/\" target=\"_blank\">Afghanistan Geological Survey</a>","usgsCitation":"Davis, P.A., 2014, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Farah mineral district in Afghanistan: U.S. Geological Survey Data Series 709, HTML Document; Readme Text; Index Maps; Image Files; Metadata Files;  Shapefiles, https://doi.org/10.3133/ds709FF.","productDescription":"HTML Document; Readme Text; Index Maps; Image Files; Metadata Files;  Shapefiles","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-055960","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":286977,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds709ff.jpg"},{"id":286974,"rank":11,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/ff/image_files/image_files.html","text":"Image Files"},{"id":286972,"rank":2,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/ff/1_readme.doc"},{"id":286975,"rank":1,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/ff/metadata/metadata.html"},{"id":286971,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/ff/"},{"id":286973,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/ff/index_maps/index_maps.html","text":"Index Maps"},{"id":286976,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/ff/shapefiles/shapefiles.html"}],"country":"Afghanistan","otherGeospatial":"Farah Mineral District","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              62.73978191168703,\n              32.9985359214848\n            ],\n            [\n              60.74259795471943,\n              32.9985359214848\n            ],\n            [\n              60.74259795471943,\n              31.463985777157987\n            ],\n            [\n              62.73978191168703,\n              31.463985777157987\n            ],\n            [\n              62.73978191168703,\n              32.9985359214848\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"536b47d1e4b0a51a87c4b125","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":492735,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70101718,"text":"ds709EE - 2014 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni2 mineral district in Afghanistan","interactions":[{"subject":{"id":70101718,"text":"ds709EE - 2014 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni2 mineral district in Afghanistan","indexId":"ds709EE","publicationYear":"2014","noYear":false,"chapter":"EE","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni2 mineral district in Afghanistan"},"predicate":"IS_PART_OF","object":{"id":70040370,"text":"ds709 - 2012 - Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","indexId":"ds709","publicationYear":"2012","noYear":false,"title":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan"},"id":1}],"isPartOf":{"id":70040370,"text":"ds709 - 2012 - Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","indexId":"ds709","publicationYear":"2012","noYear":false,"title":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan"},"lastModifiedDate":"2022-12-09T20:57:48.473565","indexId":"ds709EE","displayToPublicDate":"2014-05-07T12:17:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"709","chapter":"EE","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni2 mineral district in Afghanistan","docAbstract":"<p>The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ghazni2 mineral district, which has spectral reflectance anomalies indicative of gold, mercury, and sulfur deposits.</p>\n\n<br>\n\n<p>ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2008, 2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement.</p>\n\n<br>\n\n<p>The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands).</p>\n\n<br>\n\n<p>All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (42 for Ghazni2) and the WGS84 datum. The images for the Ghazni2 area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (Data Series 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709EE","collaboration":"Prepared in cooperation with the U.S. Department of Defense <a href=\" http://tfbso.defense.gov/\" target=\"_blank\"> Task Force for Business and Stability Operations</a> and the <a href=\"http://www.bgs.ac.uk/AfghanMinerals/\" target=\"_blank\">Afghanistan Geological Survey</a>","usgsCitation":"Davis, P.A., 2014, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni2 mineral district in Afghanistan: U.S. Geological Survey Data Series 709, HTML Document; Readme Text; Index Maps; Image Files; Metadata Files; Shapefiles, https://doi.org/10.3133/ds709EE.","productDescription":"HTML Document; Readme Text; Index Maps; Image Files; Metadata Files; Shapefiles","onlineOnly":"Y","ipdsId":"IP-054394","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":286970,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds709ee.jpg"},{"id":286964,"rank":11,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/ee/","linkFileType":{"id":5,"text":"html"}},{"id":286967,"rank":4,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/ee/image_files/image_files.html","text":"Image Files","linkFileType":{"id":5,"text":"html"}},{"id":286965,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/ee/1_readme.doc"},{"id":286968,"rank":1,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/ee/metadata/metadata.html","linkFileType":{"id":5,"text":"html"}},{"id":286969,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/ee/shapefiles/shapefiles.html"},{"id":286966,"rank":1,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/ee/index_maps/index_maps.html","text":"Index Maps","linkFileType":{"id":5,"text":"html"}}],"country":"Afghanistan","otherGeospatial":"Ghazni2 Mineral District","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              68.87252342306118,\n              33.400794951645565\n            ],\n            [\n              68.5382513185329,\n              33.71681758841511\n            ],\n            [\n              68.30727405623549,\n              33.72224478024398\n            ],\n            [\n              68.08601269164748,\n              34.1414227946527\n            ],\n            [\n              67.2638552357352,\n              34.07256923954678\n            ],\n            [\n              67.23635530353977,\n              33.52157172943353\n            ],\n            [\n              66.91878464275106,\n              33.262493443111566\n            ],\n            [\n              67.42957551466375,\n              32.86586167317263\n            ],\n            [\n              67.7125922483599,\n              32.561357509486314\n            ],\n            [\n              68.87252342306118,\n              33.400794951645565\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"536b47d3e4b0a51a87c4b12f","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":492734,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70101717,"text":"ds709DD - 2014 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni1 mineral district in Afghanistan","interactions":[{"subject":{"id":70101717,"text":"ds709DD - 2014 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni1 mineral district in Afghanistan","indexId":"ds709DD","publicationYear":"2014","noYear":false,"chapter":"DD","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni1 mineral district in Afghanistan"},"predicate":"IS_PART_OF","object":{"id":70040370,"text":"ds709 - 2012 - Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","indexId":"ds709","publicationYear":"2012","noYear":false,"title":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan"},"id":1}],"isPartOf":{"id":70040370,"text":"ds709 - 2012 - Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","indexId":"ds709","publicationYear":"2012","noYear":false,"title":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan"},"lastModifiedDate":"2022-12-09T20:58:26.596731","indexId":"ds709DD","displayToPublicDate":"2014-05-07T12:01:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"709","chapter":"DD","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni1 mineral district in Afghanistan","docAbstract":"<p>The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ghazni1 mineral district, which has spectral reflectance anomalies indicative of clay, aluminum, gold, silver, mercury, and sulfur deposits.</p>\n<br>\n<p>ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2008, 2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement.</p>\n<br>\n<p>The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands).</p>\n<br>\n<p>All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (42 for Ghazni1) and the WGS84 datum. The images for the Ghazni1 area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. 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