{"pageNumber":"571","pageRowStart":"14250","pageSize":"25","recordCount":46681,"records":[{"id":70046762,"text":"ofr20121244 - 2013 - Monitoring of stage and velocity, for computation of discharge in the Summit Conduit near Summit, Illinois, 2010-2012","interactions":[],"lastModifiedDate":"2013-07-02T10:56:34","indexId":"ofr20121244","displayToPublicDate":"2013-07-02T00:00:00","publicationYear":"2013","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":"2012-1244","title":"Monitoring of stage and velocity, for computation of discharge in the Summit Conduit near Summit, Illinois, 2010-2012","docAbstract":"Lake Michigan diversion accounting is the process used by the U. S. Army Corps of Engineers to quantify the amount of water that is diverted from the Lake Michigan watershed into the Illinois and Mississippi River Basins. A network of streamgages within the Chicago area waterway system monitor tributary river flows and the major river flow on the Chicago Sanitary and Ship Canal near Lemont as one of the instrumental tools used for Lake Michigan diversion accounting. The mean annual discharges recorded by these streamgages are used as additions or deductions to the mean annual discharge recorded by the main stream gaging station currently used in the Lake Michigan diversion accounting process, which is the Chicago Sanitary and Ship Canal near Lemont, Illinois (station number 05536890). A new stream gaging station, Summit Conduit near Summit, Illinois (station number 414757087490401), was installed on September 23, 2010, for the purpose of monitoring stage, velocity, and discharge through the Summit Conduit for the U.S. Army Corps of Engineers in accordance with Lake Michigan diversion accounting. Summit Conduit conveys flow from a small part of the lower Des Plaines River watershed underneath the Des Plaines River directly into the Chicago Sanitary and Ship Canal. Because the Summit Conduit discharges into the Chicago Sanitary and Ship Canal upstream from the stream gaging station at Lemont, Illinois, but does not contain flow diverted from the Lake Michigan watershed, it is considered a flow deduction to the discharge measured by the Lemont stream gaging station in the Lake Michigan diversion accounting process. This report offers a technical summary of the techniques and methods used for the collection and computation of the stage, velocity, and discharge data at the Summit Conduit near Summit, Illinois stream gaging station for the 2011 and 2012 Water Years. The stream gaging station Summit Conduit near Summit, Illinois (station number 414757087490401) is an example of a nonstandard stream gage. Traditional methods of equating stage to discharge historically were not effective. Examples of the nonstandard conditions include the converging tributary flows directly upstream of the gage; the trash rack and walkway near the opening of the conduit introducing turbulence and occasionally entraining air bubbles into the flow; debris within the conduit creating conditions of variable backwater and the constant influx of smaller debris that escapes the trash rack and catches or settles in the conduit and on the equipment. An acoustic Doppler velocity meter was installed to measure stage and velocity to compute discharge. The stage is used to calculate area based the stage-area rating. The index-velocity from the acoustic Doppler velocity meter is applied to the velocity-velocity rating and the product of the two rated values is a rated discharge by the index-velocity method. Nonstandard site conditions prevalent at the Summit Conduit stream gaging station generally are overcome through the index-velocity method. Despite the difficulties in gaging and measurements, improvements continue to be made in data collection, transmission, and measurements. Efforts to improve the site and to improve the ratings continue to improve the quality and quantity of the data available for Lake Michigan diversion accounting.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121244","collaboration":"In cooperation with U.S. Army Corps of Engineers","usgsCitation":"Johnson, K.K., and Goodwin, G.E., 2013, Monitoring of stage and velocity, for computation of discharge in the Summit Conduit near Summit, Illinois, 2010-2012: U.S. Geological Survey Open-File Report 2012-1244, vi, 45 p., appendixes, https://doi.org/10.3133/ofr20121244.","productDescription":"vi, 45 p., appendixes","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":274421,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20121244.jpg"},{"id":274419,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1244/pdf/ofr2012-1244.pdf"},{"id":274420,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1244/"}],"scale":"100000","projection":"Albers Equal-Area Conic","country":"United States","state":"Illinois","city":"Summit","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.249569,41.499964 ], [ -88.249569,42.154369 ], [ -87.399673,42.154369 ], [ -87.399673,41.499964 ], [ -88.249569,41.499964 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51d3e859e4b09630fbdc525e","contributors":{"authors":[{"text":"Johnson, Kevin K. 0000-0003-2703-5994 johnsonk@usgs.gov","orcid":"https://orcid.org/0000-0003-2703-5994","contributorId":4220,"corporation":false,"usgs":true,"family":"Johnson","given":"Kevin","email":"johnsonk@usgs.gov","middleInitial":"K.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480181,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goodwin, Greg E.","contributorId":45987,"corporation":false,"usgs":true,"family":"Goodwin","given":"Greg","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":480182,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70046764,"text":"sir20135126 - 2013 - Actual evapotranspiration modeling using the operational Simplified Surface Energy Balance (SSEBop) approach","interactions":[],"lastModifiedDate":"2017-05-31T16:21:40","indexId":"sir20135126","displayToPublicDate":"2013-07-02T00:00:00","publicationYear":"2013","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":"2013-5126","title":"Actual evapotranspiration modeling using the operational Simplified Surface Energy Balance (SSEBop) approach","docAbstract":"Remote-sensing technology and surface-energy-balance methods can provide accurate and repeatable estimates of actual evapotranspiration (<i>ETa</i>) when used in combination with local weather datasets over irrigated lands. Estimates of <i>ETa</i> may be used to provide a consistent, accurate, and efficient approach for estimating regional water withdrawals for irrigation and associated consumptive use (CU), especially in arid cropland areas that require supplemental water due to insufficient natural supplies from rainfall, soil moisture, or groundwater. <i>ETa</i> in these areas is considered equivalent to CU, and represents the part of applied irrigation water that is evaporated and/or transpired, and is not available for immediate reuse. A recent U.S. Geological Survey study demonstrated the application of the remote-sensing-based Simplified Surface Energy Balance (SSEB) model to estimate 10-year average <i>ETa </i>at 1-kilometer resolution on national and regional scales, and compared those <i>ETa</i> values to the U.S. Geological Survey’s National Water-Use Information Program’s 1995 county estimates of CU. The operational version of the operational SSEB (SSEBop) method is now used to construct monthly, county-level <i>ETa</i> maps of the conterminous United States for the years 2000, 2005, and 2010. The performance of the SSEBop was evaluated using eddy covariance flux tower datasets compiled from 2005 datasets, and the results showed a strong linear relationship in different land cover types across diverse ecosystems in the conterminous United States (correlation coefficient [r] ranging from 0.75 to 0.95). For example, r for woody savannas (0.75), grassland (0.75), forest (0.82), cropland (0.84), shrub land (0.89), and urban (0.95). A comparison of the remote-sensing SSEBop method for estimating <i>ETa</i> and the Hamon temperature method for estimating potential ET (<i>ETp</i>) also was conducted, using regressions of all available county averages of <i>ETa</i> for 2005 and 2010, and yielded correlations of r = 0.60 and r = 0.71, respectively. Correlations generally are stronger in the Southeast where <i>ETa</i> is close to <i>ETp</i>. SSEBop <i>ETa</i> provides more spatial detail and accuracy in the Southwest where irrigation is practiced in a smaller proportion of the region.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135126","collaboration":"Groundwater Resources Program","usgsCitation":"Savoca, M.E., Senay, G., Maupin, M.A., Kenny, J., and Perry, C.A., 2013, Actual evapotranspiration modeling using the operational Simplified Surface Energy Balance (SSEBop) approach: U.S. Geological Survey Scientific Investigations Report 2013-5126, iv, 15 p., https://doi.org/10.3133/sir20135126.","productDescription":"iv, 15 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":274426,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135126.jpg"},{"id":274424,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5126/"},{"id":274423,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5126/pdf/sir20135126.pdf"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.800,24.50000 ], [ -124.800,49.383333 ], [ -66.9500,49.383333 ], [ -66.9500,24.50000 ], [ -124.800,24.50000 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51d3e84fe4b09630fbdc5246","contributors":{"authors":[{"text":"Savoca, Mark E. mesavoca@usgs.gov","contributorId":1961,"corporation":false,"usgs":true,"family":"Savoca","given":"Mark","email":"mesavoca@usgs.gov","middleInitial":"E.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480186,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senay, Gabriel B. 0000-0002-8810-8539","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":66808,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel B.","affiliations":[],"preferred":false,"id":480188,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maupin, Molly A. 0000-0002-2695-5505 mamaupin@usgs.gov","orcid":"https://orcid.org/0000-0002-2695-5505","contributorId":951,"corporation":false,"usgs":true,"family":"Maupin","given":"Molly","email":"mamaupin@usgs.gov","middleInitial":"A.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480185,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kenny, Joan F.","contributorId":69132,"corporation":false,"usgs":true,"family":"Kenny","given":"Joan F.","affiliations":[],"preferred":false,"id":480189,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Perry, Charles A. cperry@usgs.gov","contributorId":2093,"corporation":false,"usgs":true,"family":"Perry","given":"Charles","email":"cperry@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":480187,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70048502,"text":"70048502 - 2013 - Modeling the colonization of Hawaii by hoary bats (<i>Lasiurus cinereus</i>)","interactions":[],"lastModifiedDate":"2013-11-15T10:23:34","indexId":"70048502","displayToPublicDate":"2013-07-01T15:33:00","publicationYear":"2013","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Modeling the colonization of Hawaii by hoary bats (<i>Lasiurus cinereus</i>)","docAbstract":"The Hawaiian archipelago, the most isolated cluster of islands on Earth, has been colonized successfully twice by bats. The putative “lava tube bat” of Hawaii is extinct, whereas the Hawaiian Hoary Bat, Lasiurus cinereus semotus, survives as an endangered species. We conducted a three-stage analysis to identify conditions under which hoary bats originally colonized Hawaii. We used FLIGHT to determine if stores of fat would provide the energy necessary to fly from the Farallon Islands (California) to Hawaii, a distance of 3,665 km. The Farallons are a known stopover and the closest landfall to Hawaii for hoary bats during migrations within North America. Our modeling variables included physiological, morphological, and behavioral data characterizing North American Hoary Bat populations. The second step of our modeling process investigated the potential limiting factor of water during flight. The third step in our modeling examines the role that prevailing trade winds may have played in colonization flights. Of our 36 modeling scenarios, 17 (47 %) require tailwind assistance within the range of observed wind speeds, and 7 of these scenarios required <10 m s<sup>−1</sup> tailwinds as regularly expected due to easterly trade winds. Therefore the climatic conditions needed for bats to colonize Hawaii may not occur infrequently either in contemporary times or since the end of the Pleistocene. Hawaii’s hoary bats have undergone divergence from mainland populations resulting in smaller body size and unique pelage color.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Bat Evolution, Ecology, and Conservation","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Springer","publisherLocation":"New York","doi":"10.1007/978-1-4614-7397-8_10","isbn":"9781461473961","usgsCitation":"Bonaccorso, F., and McGuire, L.P., 2013, Modeling the colonization of Hawaii by hoary bats (<i>Lasiurus cinereus</i>), chap. <i>of</i> Bat Evolution, Ecology, and Conservation, p. 187-205, https://doi.org/10.1007/978-1-4614-7397-8_10.","productDescription":"19 p.","startPage":"187","endPage":"205","numberOfPages":"19","ipdsId":"IP-038836","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":278661,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278660,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/978-1-4614-7397-8_10"}],"country":"United States","state":"Hawai'i","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -178.31,18.91 ], [ -178.31,28.4 ], [ -154.81,28.4 ], [ -154.81,18.91 ], [ -178.31,18.91 ] ] ] } } ] }","noUsgsAuthors":false,"publicationDate":"2013-07-08","publicationStatus":"PW","scienceBaseUri":"5274cd7ee4b089748f072438","contributors":{"authors":[{"text":"Bonaccorso, Frank J.","contributorId":73089,"corporation":false,"usgs":true,"family":"Bonaccorso","given":"Frank J.","affiliations":[],"preferred":false,"id":484859,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGuire, Liam P.","contributorId":66161,"corporation":false,"usgs":true,"family":"McGuire","given":"Liam","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":484858,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70043567,"text":"70043567 - 2013 - Effects of sampling conditions on DNA-based estimates of American black bear abundance","interactions":[],"lastModifiedDate":"2016-04-19T11:24:29","indexId":"70043567","displayToPublicDate":"2013-07-01T15:24:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Effects of sampling conditions on DNA-based estimates of American black bear abundance","docAbstract":"<p>DNA-based capture-mark-recapture techniques are commonly used to estimate American black bear (<i>Ursus americanus</i>) population abundance (N). Although the technique is well established, many questions remain regarding study design. In particular, relationships among N, capture probability of heterogeneity mixtures A and B (p<sub>A</sub> and p<sub>B</sub>, respectively, or <i>p</i>, collectively), the proportion of each mixture (&pi;), number of capture occasions (k), and probability of obtaining reliable estimates of N are not fully understood. We investigated these relationships using 1) an empirical dataset of DNA samples for which true N was unknown and 2) simulated datasets with known properties that represented a broader array of sampling conditions. For the empirical data analysis, we used the full closed population with heterogeneity data type in Program MARK to estimate N for a black bear population in Great Smoky Mountains National Park, Tennessee. We systematically reduced the number of those samples used in the analysis to evaluate the effect that changes in capture probabilities may have on parameter estimates. Model-averaged N for females and males were 161 (95% CI&thinsp;=&thinsp;114&ndash;272) and 100 (95% CI&thinsp;=&thinsp;74&ndash;167), respectively (pooled N&thinsp;=&thinsp;261, 95% CI&thinsp;=&thinsp;192&ndash;419), and the average weekly <i>p</i> was 0.09 for females and 0.12 for males. When we reduced the number of samples of the empirical data, support for heterogeneity models decreased. For the simulation analysis, we generated capture data with individual heterogeneity covering a range of sampling conditions commonly encountered in DNA-based capture-mark-recapture studies and examined the relationships between those conditions and accuracy (i.e., probability of obtaining an estimated N that is within 20% of true N), coverage (i.e., probability that 95% confidence interval includes true N), and precision (i.e., probability of obtaining a coefficient of variation &le;20%) of estimates using logistic regression. The capture probability for the larger of 2 mixture proportions of the population (i.e., p<sub>A</sub> or p<sub>B</sub>, depending on the value of &pi;) was most important for predicting accuracy and precision, whereas capture probabilities of both mixture proportions (p<sub>A</sub> and p<sub>B</sub>) were important to explain variation in coverage. Based on sampling conditions similar to parameter estimates from the empirical dataset (p<sub>A</sub>&thinsp;=&thinsp;0.30, p<sub>B</sub>&thinsp;=&thinsp;0.05, N&thinsp;=&thinsp;250, &pi;&thinsp;=&thinsp;0.15, and k&thinsp;=&thinsp;10), predicted accuracy and precision were low (60% and 53%, respectively), whereas coverage was high (94%). Increasing p<sub>B</sub>, the capture probability for the predominate but most difficult to capture proportion of the population, was most effective to improve accuracy under those conditions. However, manipulation of other parameters may be more effective under different conditions. In general, the probabilities of obtaining accurate and precise estimates were best when <i>p</i>&ge;&thinsp;0.2. Our regression models can be used by managers to evaluate specific sampling scenarios and guide development of sampling frameworks or to assess reliability of DNA-based capture-mark-recapture studies.</p>","language":"English","publisher":"Wildlife Society","doi":"10.1002/jwmg.534","usgsCitation":"Laufenberg, J.S., van Manen, F., and Clark, J.D., 2013, Effects of sampling conditions on DNA-based estimates of American black bear abundance: Journal of Wildlife Management, v. 77, no. 5, p. 1010-1020, https://doi.org/10.1002/jwmg.534.","productDescription":"11 p.","startPage":"1010","endPage":"1020","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-037908","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":288188,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288185,"type":{"id":10,"text":"Digital Object 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T.","affiliations":[],"preferred":false,"id":473858,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clark, Joseph D. 0000-0002-8547-8112 jclark1@usgs.gov","orcid":"https://orcid.org/0000-0002-8547-8112","contributorId":2265,"corporation":false,"usgs":true,"family":"Clark","given":"Joseph","email":"jclark1@usgs.gov","middleInitial":"D.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":473856,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70103838,"text":"70103838 - 2013 - Field calibration and validation of remote-sensing surveys","interactions":[],"lastModifiedDate":"2017-11-10T18:26:14","indexId":"70103838","displayToPublicDate":"2013-07-01T13:46:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2068,"text":"International Journal of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Field calibration and validation of remote-sensing surveys","docAbstract":"The Optical Collection Suite (OCS) is a ground-truth sampling system designed to perform in situ measurements that help calibrate and validate optical remote-sensing and swath-sonar surveys for mapping and monitoring coastal ecosystems and ocean planning. The OCS system enables researchers to collect underwater imagery with real-time feedback, measure the spectral response, and quantify the water clarity with simple and relatively inexpensive instruments that can be hand-deployed from a small vessel. This article reviews the design and performance of the system, based on operational and logistical considerations, as well as the data requirements to support a number of coastal science and management projects. The OCS system has been operational since 2009 and has been used in several ground-truth missions that overlapped with airborne lidar bathymetry (ALB), hyperspectral imagery (HSI), and swath-sonar bathymetric surveys in the Gulf of Maine, southwest Alaska, and the US Virgin Islands (USVI). Research projects that have used the system include a comparison of backscatter intensity derived from acoustic (multibeam/interferometric sonars) versus active optical (ALB) sensors, ALB bottom detection, and seafloor characterization using HSI and ALB.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"International Journal of Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Taylor & Francis","doi":"10.1080/01431161.2013.800655","usgsCitation":"Pe’eri, S., McLeod, A., Lavoie, P., Ackerman, S.D., Gardner, J., and Parrish, C., 2013, Field calibration and validation of remote-sensing surveys: International Journal of Remote Sensing, v. 34, no. 18, p. 6423-6436, https://doi.org/10.1080/01431161.2013.800655.","productDescription":"14 p.","startPage":"6423","endPage":"6436","numberOfPages":"14","ipdsId":"IP-044361","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":286999,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286989,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/01431161.2013.800655"}],"country":"United States;U.S. Virgin Islands","state":"Alaska","otherGeospatial":"Gulf Of Maine","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -133.810887,17.774787 ], [ -133.810887,56.580001 ], [ -64.599525,56.580001 ], [ -64.599525,17.774787 ], [ -133.810887,17.774787 ] ] ] } } ] }","volume":"34","issue":"18","noUsgsAuthors":false,"publicationDate":"2013-06-10","publicationStatus":"PW","scienceBaseUri":"536ca767e4b060efff280dab","contributors":{"authors":[{"text":"Pe’eri, Shachak","contributorId":106015,"corporation":false,"usgs":true,"family":"Pe’eri","given":"Shachak","email":"","affiliations":[],"preferred":false,"id":493459,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McLeod, Andy","contributorId":96592,"corporation":false,"usgs":true,"family":"McLeod","given":"Andy","email":"","affiliations":[],"preferred":false,"id":493457,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lavoie, Paul","contributorId":51206,"corporation":false,"usgs":true,"family":"Lavoie","given":"Paul","email":"","affiliations":[],"preferred":false,"id":493455,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ackerman, Seth D. 0000-0003-0945-2794 sackerman@usgs.gov","orcid":"https://orcid.org/0000-0003-0945-2794","contributorId":178676,"corporation":false,"usgs":true,"family":"Ackerman","given":"Seth","email":"sackerman@usgs.gov","middleInitial":"D.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":493454,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gardner, James","contributorId":93387,"corporation":false,"usgs":true,"family":"Gardner","given":"James","affiliations":[],"preferred":false,"id":493456,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Parrish, Christopher","contributorId":98635,"corporation":false,"usgs":true,"family":"Parrish","given":"Christopher","affiliations":[],"preferred":false,"id":493458,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70048501,"text":"70048501 - 2013 - A five-year study of Hawaiian hoary bat (<i>Lasiurus cinereus semotus</i>) occupancy on the island of Hawai`i","interactions":[],"lastModifiedDate":"2014-06-20T14:10:14","indexId":"70048501","displayToPublicDate":"2013-07-01T13:42:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesNumber":"HCSU-041","title":"A five-year study of Hawaiian hoary bat (<i>Lasiurus cinereus semotus</i>) occupancy on the island of Hawai`i","docAbstract":"Using acoustic recordings of the vocalizations of the endangered Hawaiian hoary bat (<i>Lasiurus \ncinereus semotus</i>) collected over a five-year period (2007–2011) from 25 survey areas across \nthe island of Hawai`i, we modeled the relationship between habitat attributes and bat \noccurrence. Our data support the conclusion that hoary bats concentrate in the coastal lowlands \nof Hawai`i during the breeding season, May through October, and migrate to interior highlands \nduring the winter non-breeding season. Highest occupancy peaked on the Julian date 15 \nSeptember across the five-year average and during the season of fledging by the young of the \nyear. Although the Hawaiian hoary bat is a habitat generalist species and occurs from sea level \nto the highest volcanic peaks on Hawai`i, there was a significant association between\noccupancy and the prevalence of mature forest cover. Trends in occupancy were stable to\nslightly increasing during the breeding season over the five years of our surveys.","language":"English","publisher":"University of Hawai‘i at Hilo","publisherLocation":"Hilo, HI","usgsCitation":"Gorressen, M.P., Bonaccorso, F., Pinzari, C., Todd, C.M., Montoya-Aiona, K., and Brinck, K., 2013, A five-year study of Hawaiian hoary bat (<i>Lasiurus cinereus semotus</i>) occupancy on the island of Hawai`i, iv, 48 p.","productDescription":"iv, 48 p.","numberOfPages":"54","ipdsId":"IP-046159","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":279187,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278237,"type":{"id":15,"text":"Index Page"},"url":"https://hilo.hawaii.edu/hcsu/publications.php"}],"projection":"Universal Transverse Mercator 5 North projection","datum":"North American Datum of 1983","country":"United States","state":"Hawai'i","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -156.2729,18.8676 ], [ -156.2729,20.2894 ], [ -154.6488,20.2894 ], [ -154.6488,18.8676 ], [ -156.2729,18.8676 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"528c96a9e4b0c629af44dd8f","contributors":{"authors":[{"text":"Gorressen, Marcos P.","contributorId":40887,"corporation":false,"usgs":true,"family":"Gorressen","given":"Marcos","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":484854,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bonaccorso, Frank J.","contributorId":73089,"corporation":false,"usgs":true,"family":"Bonaccorso","given":"Frank J.","affiliations":[],"preferred":false,"id":484857,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pinzari, Corinna A.","contributorId":57359,"corporation":false,"usgs":true,"family":"Pinzari","given":"Corinna A.","affiliations":[],"preferred":false,"id":484855,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Todd, Christopher M.","contributorId":64548,"corporation":false,"usgs":true,"family":"Todd","given":"Christopher","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":484856,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Montoya-Aiona, Kristina 0000-0002-1776-5443 kmontoya-aiona@usgs.gov","orcid":"https://orcid.org/0000-0002-1776-5443","contributorId":5899,"corporation":false,"usgs":true,"family":"Montoya-Aiona","given":"Kristina","email":"kmontoya-aiona@usgs.gov","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":484853,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brinck, Kevin W. 0000-0001-7581-2482 kbrinck@usgs.gov","orcid":"https://orcid.org/0000-0001-7581-2482","contributorId":3847,"corporation":false,"usgs":true,"family":"Brinck","given":"Kevin W.","email":"kbrinck@usgs.gov","affiliations":[],"preferred":false,"id":484852,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70125966,"text":"70125966 - 2013 - Comparative phylogeography reveals deep lineages and regional evolutionary hotspots in the Mojave and Sonoran Deserts","interactions":[],"lastModifiedDate":"2014-09-18T12:55:06","indexId":"70125966","displayToPublicDate":"2013-07-01T12:48:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1399,"text":"Diversity and Distributions","active":true,"publicationSubtype":{"id":10}},"title":"Comparative phylogeography reveals deep lineages and regional evolutionary hotspots in the Mojave and Sonoran Deserts","docAbstract":"<p>Aim: We explored lineage diversification within desert-dwelling fauna. Our goals were (1) to determine whether phylogenetic lineages and population expansions were consistent with younger Pleistocene climate fluctuation hypotheses or much older events predicted by pre-Pleistocene vicariance hypotheses, (2) to assess concordance in spatial patterns of genetic divergence and diversity among species and (3) to identify regional evolutionary hotspots of divergence and diversity and assess their conservation status.</p>\n<br/>\n<p>Location: Mojave, Colorado, and Sonoran Deserts, USA.</p>\n<br/>\n<p>Methods: We analysed previously published gene sequence data for twelve species. We used Bayesian gene tree methods to estimate lineages and divergence times. Within each lineage, we tested for population expansion and age of expansion using coalescent approaches. We mapped interpopulation genetic divergence and intra-population genetic diversity in a GIS to identify hotspots of highest genetic divergence and diversity and to assess whether protected lands overlapped with evolutionary hotspots.</p>\n<br/>\n<p>Results: In seven of the 12 species, lineage divergence substantially predated the Pleistocene. Historical population expansion was found in eight species, but expansion events postdated the Last Glacial Maximum (LGM) in only four. For all species assessed, six hotspots of high genetic divergence and diversity were concentrated in the Colorado Desert, along the Colorado River and in the Mojave/Sonoran ecotone. At least some proportion of the land within each recovered hotspot was categorized as protected, yet four of the six also overlapped with major areas of human development.</p>\n<br/>\n<p>Main conclusions: Most of the species studied here diversified into distinct Mojave and Sonoran lineages prior to the LGM – supporting older diversification hypotheses. Several evolutionary hotspots were recovered but are not strategically paired with areas of protected land. Long-term preservation of species-level biodiversity would entail selecting areas for protection in Mojave and Sonoran Deserts to retain divergent genetic diversity and ensure connectedness across environmental gradients.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Diversity and Distributions","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Blackwell Science","publisherLocation":"Oxford, England","doi":"10.1111/ddi.12022","usgsCitation":"Wood, D.A., Vandergast, A.G., Barr, K.R., Inman, R.D., Esque, T., Nussear, K.E., and Fisher, R.N., 2013, Comparative phylogeography reveals deep lineages and regional evolutionary hotspots in the Mojave and Sonoran Deserts: Diversity and Distributions, v. 19, no. 7, p. 722-737, https://doi.org/10.1111/ddi.12022.","productDescription":"16 p.","startPage":"722","endPage":"737","numberOfPages":"16","ipdsId":"IP-041224","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":473706,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.12022","text":"Publisher Index Page"},{"id":294158,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294151,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/ddi.12022"}],"country":"United States","otherGeospatial":"Colorado Desert;Mojave Desert;Sonoran Desert","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119.47,31.33 ], [ -119.47,37.78 ], [ -109.89,37.78 ], [ -109.89,31.33 ], [ -119.47,31.33 ] ] ] } } ] }","volume":"19","issue":"7","noUsgsAuthors":false,"publicationDate":"2012-12-04","publicationStatus":"PW","scienceBaseUri":"541bf421e4b0e96537ddf668","contributors":{"authors":[{"text":"Wood, Dustin A. 0000-0002-7668-9911 dawood@usgs.gov","orcid":"https://orcid.org/0000-0002-7668-9911","contributorId":4179,"corporation":false,"usgs":true,"family":"Wood","given":"Dustin","email":"dawood@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":501811,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vandergast, Amy G. 0000-0002-7835-6571","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":97617,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","email":"","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":501813,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barr, Kelly R. kelly_barr@usgs.gov","contributorId":5628,"corporation":false,"usgs":true,"family":"Barr","given":"Kelly","email":"kelly_barr@usgs.gov","middleInitial":"R.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":501812,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Inman, Richard D. rdinman@usgs.gov","contributorId":3316,"corporation":false,"usgs":true,"family":"Inman","given":"Richard","email":"rdinman@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":501810,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Esque, Todd C. tesque@usgs.gov","contributorId":3221,"corporation":false,"usgs":true,"family":"Esque","given":"Todd C.","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":501809,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nussear, Kenneth E. knussear@usgs.gov","contributorId":2695,"corporation":false,"usgs":true,"family":"Nussear","given":"Kenneth","email":"knussear@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":501808,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":501807,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70048579,"text":"70048579 - 2013 - Delivering integrated HAZUS-MH flood loss analyses and flood inundation maps over the Web","interactions":[],"lastModifiedDate":"2013-10-24T11:17:54","indexId":"70048579","displayToPublicDate":"2013-07-01T11:13:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2246,"text":"Journal of Emergency Management","active":true,"publicationSubtype":{"id":10}},"title":"Delivering integrated HAZUS-MH flood loss analyses and flood inundation maps over the Web","docAbstract":"Catastrophic flooding is responsible for more loss of life and damages to property than any other natural hazard. Recently developed flood inundation mapping technologies make it possible to view the extent and depth of flooding on the land surface over the Internet; however, by themselves these technologies are unable to provide estimates of losses to property and infrastructure. The Federal Emergency Management Agency’s (FEMA's) HAZUS-MH software is extensively used to conduct flood loss analyses in the United States, providing a nationwide database of population and infrastructure at risk. Unfortunately, HAZUS-MH requires a dedicated Geographic Information System (GIS) workstation and a trained operator, and analyses are not adapted for convenient delivery over the Web. This article describes a cooperative effort by the US Geological Survey (USGS) and FEMA to make HAZUS-MH output GIS and Web compatible and to integrate these data with digital flood inundation maps in USGS’s newly developed Inundation Mapping Web Portal. By running the computationally intensive HAZUS-MH flood analyses offline and converting the output to a Web-GIS compatible format, detailed estimates of flood losses can now be delivered to anyone with Internet access, thus dramatically increasing the availability of these forecasts to local emergency planners and first responders.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Emergency Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Prime National Publication Corporation","doi":"10.5055/jem.2013.0145","usgsCitation":"Hearn, Longenecker, H.E., Aguinaldo, J.J., and Rahav, A.N., 2013, Delivering integrated HAZUS-MH flood loss analyses and flood inundation maps over the Web: Journal of Emergency Management, v. 11, no. 4, p. 293-302, https://doi.org/10.5055/jem.2013.0145.","productDescription":"10 p.","startPage":"293","endPage":"302","numberOfPages":"10","ipdsId":"IP-039135","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":278377,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278373,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.5055/jem.2013.0145"}],"volume":"11","issue":"4","noUsgsAuthors":false,"publicationDate":"2017-02-16","publicationStatus":"PW","scienceBaseUri":"526a416fe4b0c0d229f9f66b","contributors":{"authors":[{"text":"Hearn, Jr. phearn@usgs.gov","contributorId":1950,"corporation":false,"usgs":true,"family":"Hearn","suffix":"Jr.","email":"phearn@usgs.gov","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":485124,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Longenecker, Herbert E. III","contributorId":105217,"corporation":false,"usgs":true,"family":"Longenecker","given":"Herbert","suffix":"III","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":485127,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aguinaldo, John J.","contributorId":73287,"corporation":false,"usgs":true,"family":"Aguinaldo","given":"John","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":485126,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rahav, Ami N. arahav@usgs.gov","contributorId":69463,"corporation":false,"usgs":true,"family":"Rahav","given":"Ami","email":"arahav@usgs.gov","middleInitial":"N.","affiliations":[],"preferred":false,"id":485125,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70048520,"text":"70048520 - 2013 - Rebuilding after collapse: evidence for long-term cohort dynamics in the native Hawaiian rain forest","interactions":[],"lastModifiedDate":"2013-11-15T10:25:05","indexId":"70048520","displayToPublicDate":"2013-07-01T11:04:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2490,"text":"Journal of Vegetation Science","active":true,"publicationSubtype":{"id":10}},"title":"Rebuilding after collapse: evidence for long-term cohort dynamics in the native Hawaiian rain forest","docAbstract":"Questions: Do long-term observations in permanent plots confirm the conceptual model of Metrosideros polymorpha cohort dynamics as postulated in 1987? Do regeneration patterns occur independently of substrate age, i.e. of direct volcanic disturbance impact?\n\nLocation: The windward mountain slopes of the younger Mauna Loa and the older Mauna Kea volcanoes (island of Hawaii, USA).\n\nMethods: After widespread forest decline (dieback), permanent plots were established in 1976 in 13 dieback and 13 non-dieback patches to monitor the population structure of M. polymorpha at ca. 5-yr intervals. Within each plot of 20 × 20 m, all trees with DBH >2.5 cm were individually tagged, measured and tree vigour assessed; regeneration was quantified in 16 systematically placed subplots of 3 × 5 m. Data collected in the subplots included the total number of M. polymorpha seedlings and saplings (five stem height classes). Here we analyse monitoring data from six time steps from 1976 to 2003 using repeated measures ANOVA to test specific predictions derived from the 1987 conceptual model.\n\nResults: Regeneration was significantly different between dieback and non-dieback plots. In dieback plots, the collapse in the 1970s was followed by a ‘sapling wave’ that by 2003 led to new cohort stands of M. polymorpha. In non-dieback stands, seedling emergence did not result in sapling waves over the same period. Instead, a ‘sapling gap’ (i.e. very few or no M. polymorpha saplings) prevailed as typical for mature stands. Canopy dieback in 1976, degree of recovery by 2003 and the number of living trees in 2003 were unrelated to substrate age.\n\nConclusions: Population development of M. polymorpha supports the cohort dynamics model, which predicts rebuilding of the forest with the same canopy species after dieback. The lack of association with substrate age suggests that the long-term maintenance of cohort structure in M. polymorpha does not depend on volcanic disturbance but may be related to other environmental mechanisms, such as climate anomalies.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Vegetation Science","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/jvs.12000","usgsCitation":"Boehmer, H., Wagner, H.H., Jacobi, J.D., Gerrish, G.C., and Mueller-Dombois, D., 2013, Rebuilding after collapse: evidence for long-term cohort dynamics in the native Hawaiian rain forest: Journal of Vegetation Science, v. 24, no. 4, p. 639-650, https://doi.org/10.1111/jvs.12000.","productDescription":"12 p.","startPage":"639","endPage":"650","numberOfPages":"12","ipdsId":"IP-026370","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":473711,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/75550","text":"External Repository"},{"id":278376,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278375,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/jvs.12000"}],"country":"United States","state":"Hawai'i","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -155.707,19.1549 ], [ -155.707,20.1673 ], [ -154.8068,20.1673 ], [ -154.8068,19.1549 ], [ -155.707,19.1549 ] ] ] } } ] }","volume":"24","issue":"4","noUsgsAuthors":false,"publicationDate":"2012-11-27","publicationStatus":"PW","scienceBaseUri":"526a4174e4b0c0d229f9f6ae","contributors":{"authors":[{"text":"Boehmer, Hans Juergen","contributorId":45996,"corporation":false,"usgs":true,"family":"Boehmer","given":"Hans Juergen","affiliations":[],"preferred":false,"id":484938,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wagner, Helene H.","contributorId":12309,"corporation":false,"usgs":true,"family":"Wagner","given":"Helene","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":484937,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jacobi, James D. 0000-0003-2313-7862 jjacobi@usgs.gov","orcid":"https://orcid.org/0000-0003-2313-7862","contributorId":3705,"corporation":false,"usgs":true,"family":"Jacobi","given":"James","email":"jjacobi@usgs.gov","middleInitial":"D.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":484936,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gerrish, Grant C.","contributorId":69049,"corporation":false,"usgs":true,"family":"Gerrish","given":"Grant","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":484939,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mueller-Dombois, Dieter","contributorId":100730,"corporation":false,"usgs":true,"family":"Mueller-Dombois","given":"Dieter","affiliations":[],"preferred":false,"id":484940,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70046757,"text":"ofr20121234 - 2013 - Application of a hydrodynamic and sediment transport model for guidance of response efforts related to the Deepwater Horizon oil spill in the Northern Gulf of Mexico along the coast of Alabama and Florida","interactions":[],"lastModifiedDate":"2014-09-04T15:49:18","indexId":"ofr20121234","displayToPublicDate":"2013-07-01T00:00:00","publicationYear":"2013","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":"2012-1234","title":"Application of a hydrodynamic and sediment transport model for guidance of response efforts related to the Deepwater Horizon oil spill in the Northern Gulf of Mexico along the coast of Alabama and Florida","docAbstract":"<p>U.S. Geological Survey (USGS) scientists have provided a model-based assessment of transport and deposition of residual Deepwater Horizon oil along the shoreline within the northern Gulf of Mexico in the form of mixtures of sand and weathered oil, known as surface residual balls (SRBs). The results of this USGS research, in combination with results from other components of the overall study, will inform operational decisionmaking. The results will provide guidance for response activities and data collection needs during future oil spills.</p>\n<br/>\n<p>In May 2012 the U.S. Coast Guard, acting as the Deepwater Horizon Federal on-scene coordinator, chartered an operational science advisory team to provide a science-based review of data collected and to conduct additional directed studies and sampling. The goal was to characterize typical shoreline profiles and morphology in the northern Gulf of Mexico to identify likely sources of residual oil and to evaluate mechanisms whereby reoiling phenomena may be occurring (for example, burial and exhumation and alongshore transport). A steering committee cochaired by British Petroleum Corporation (BP) and the National Oceanic and Atmospheric Administration (NOAA) is overseeing the project and includes State on-scene coordinators from four States (Alabama, Florida, Louisiana, and Mississippi), trustees of the U.S. Department of the Interior (DOI), and representatives from the U.S. Coast Guard.</p>\n<br/>\n<p>This report presents the results of hydrodynamic and sediment transport models and developed techniques for analyzing potential SRB movement and burial and exhumation along the coastline of Alabama and Florida. Results from these modeling efforts are being used to explain the complexity of reoiling in the nearshore environment and to broaden consideration of the different scenarios and difficulties that are being faced in identifying and removing residual oil. For instance, modeling results suggest that larger SRBs are not, under the most commonly observed low-energy wave conditions, likely to move very far alongshore. This finding suggests that SRBs from one source location may not (outside of storm conditions) be redistributed to other up or down coast locations. This information can guide operational response decisions. In addition, because SRBs are less mobile compared with sand, they are likely to become buried and unburied under normal sand transport processes thereby lengthening the time SRBs may take to move onshore. The rate of onshore movement was not specifically addressed by this study, yet the results resolve the cross-shore domain and cross-shore variations in alongshore transport that are relevant to achieving the primary objectives. Furthermore, during infrequent events (for example, winter storms and severe meteorological events such as Hurricane Isaac of August 2012), energy is shown to be sufficient to move a greater range of SRB sizes and potentially expose and break up submerged oil mats. When SRBs do move alongshore, the models indicate that there are regions that are more conducive to accumulation of SRB material than others. Accumulation can occur where there are reversals and decelerations in alongshore currents and where forces created by shear stress drops below critical thresholds to maintain or initiate SRB movement. In addition, flow and SRB mobility patterns around inlets indicate patterns in hydrodynamic forces that influence redistribution of SRBs and the surface oil that mixed with sediment to form oil mats in the first place.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121234","collaboration":"Prepared in cooperation with the Operational Science Advisory Team (OSAT3) Steering Committee chartered by the Deepwater Horizon Federal On-Scene Coordinator (FOSC)","usgsCitation":"Plant, N.G., Long, J.W., Dalyander, P., Thompson, D.M., and Raabe, E.A., 2013, Application of a hydrodynamic and sediment transport model for guidance of response efforts related to the Deepwater Horizon oil spill in the Northern Gulf of Mexico along the coast of Alabama and Florida (First posted July 2, 2013; Revised and reposted September 4, 2014, version 1.1): U.S. Geological Survey Open-File Report 2012-1234, Report PDF: vii, 47 p.; Report HTML and Digital Data, https://doi.org/10.3133/ofr20121234.","productDescription":"Report PDF: vii, 47 p.; Report HTML and Digital Data","numberOfPages":"60","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":274406,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20121234.PNG"},{"id":274405,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1234/pdf/ofr2012-1234.pdf"},{"id":274403,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1234/"},{"id":274404,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1234/title.html"}],"country":"United States","state":"Alabama;Florida","otherGeospatial":"Gulf Of Mexico","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -89.2862,29.6323 ], [ -89.2862,30.9921 ], [ -85.3716,30.9921 ], [ -85.3716,29.6323 ], [ -89.2862,29.6323 ] ] ] } } ] }","edition":"First posted July 2, 2013; Revised and reposted September 4, 2014, version 1.1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51d296cfe4b0ca184833899b","contributors":{"authors":[{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":480173,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Long, Joseph W. 0000-0003-2912-1992 jwlong@usgs.gov","orcid":"https://orcid.org/0000-0003-2912-1992","contributorId":3303,"corporation":false,"usgs":true,"family":"Long","given":"Joseph","email":"jwlong@usgs.gov","middleInitial":"W.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":480171,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":480174,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, David M. 0000-0002-7103-5740 dthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-7103-5740","contributorId":3502,"corporation":false,"usgs":true,"family":"Thompson","given":"David","email":"dthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":480172,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Raabe, Ellen A. eraabe@usgs.gov","contributorId":2125,"corporation":false,"usgs":true,"family":"Raabe","given":"Ellen","email":"eraabe@usgs.gov","middleInitial":"A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":480170,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70046723,"text":"ofr20131130 - 2013 - National assessment of hurricane-induced coastal erosion hazards: Southeast Atlantic Coast","interactions":[],"lastModifiedDate":"2013-07-01T08:11:17","indexId":"ofr20131130","displayToPublicDate":"2013-07-01T00:00:00","publicationYear":"2013","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":"2013-1130","title":"National assessment of hurricane-induced coastal erosion hazards: Southeast Atlantic Coast","docAbstract":"Beaches serve as a natural barrier between the ocean and inland communities, ecosystems, and natural resources. However, these dynamic environments move and change in response to winds, waves, and currents. During extreme storms, changes to beaches can be large, and the results are sometimes catastrophic. Lives may be lost, communities destroyed, and millions of dollars spent on rebuilding.\n\nDuring storms, large waves may erode beaches, and high storm surge shifts the erosive force of the waves higher on the beach. In some cases, the combined effects of waves and surge may cause overwash or flooding. Building and infrastructure on or near a dune can be undermined during wave attack and subsequent erosion. During Hurricane Ivan in 2004, a five-story condominium in Orange Beach, Alabama, collapsed after the sand dune supporting the foundation eroded. The September 1999 landfall of Hurricane Dennis caused erosion and undermining that destroyed roads, foundations, and septic systems.\n\nWaves overtopping a dune can transport sand inland, covering roads and blocking evacuation routes or emergency relief. If storm surge inundates barrier island dunes, currents flowing across the island can create a breach, or new inlet, completely severing evacuation routes. Waves and surge during the 2003 landfall of Hurricane Isabel left a 200-meter (m) wide breach that cut the only road to and from the village of Hatteras, N.C.\n\nExtreme coastal changes caused by hurricanes may increase the vulnerability of communities both during a storm and to future storms. For example, when sand dunes on a barrier island are eroded substantially, inland structures are exposed to storm surge and waves. Absent or low dunes also allow water to flow inland across the island, potentially increasing storm surge in the back bay, on the soundside of the barrier, and on the mainland. During Hurricane Isabel the protective sand dunes near the breach were completely eroded, increasing vulnerability to future storms.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131130","usgsCitation":"Stockdon, H.F., Doran, K., Thompson, D.M., Sopkin, K.L., and Plant, N.G., 2013, National assessment of hurricane-induced coastal erosion hazards: Southeast Atlantic Coast: U.S. Geological Survey Open-File Report 2013-1130, vi, 28 p., https://doi.org/10.3133/ofr20131130.","productDescription":"vi, 28 p.","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":564,"text":"Southeast Atlantic Coastal Erosion Hazards Dataset","active":false,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":274306,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1130/"},{"id":274307,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1130/pdf/ofr2013-1130.pdf"},{"id":274308,"type":{"id":7,"text":"Companion Files"},"url":"https://olga.er.usgs.gov/data/NACCH/GOM_erosion_hazards.zip"},{"id":274309,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131130.gif"}],"country":"United States","state":"North Carolina;South Carolina;Georgia;Florida","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -81.9,24.52 ], [ -81.9,36.5882 ], [ -75.37,36.5882 ], [ -75.37,24.52 ], [ -81.9,24.52 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51d296d8e4b0ca18483389b7","contributors":{"authors":[{"text":"Stockdon, Hilary F. 0000-0003-0791-4676 hstockdon@usgs.gov","orcid":"https://orcid.org/0000-0003-0791-4676","contributorId":2153,"corporation":false,"usgs":true,"family":"Stockdon","given":"Hilary","email":"hstockdon@usgs.gov","middleInitial":"F.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":480098,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doran, Kara S. 0000-0001-8050-5727 kdoran@usgs.gov","orcid":"https://orcid.org/0000-0001-8050-5727","contributorId":2496,"corporation":false,"usgs":true,"family":"Doran","given":"Kara S.","email":"kdoran@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":480099,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, David M. 0000-0002-7103-5740 dthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-7103-5740","contributorId":3502,"corporation":false,"usgs":true,"family":"Thompson","given":"David","email":"dthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":480100,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sopkin, Kristin L. ksopkin@usgs.gov","contributorId":4437,"corporation":false,"usgs":true,"family":"Sopkin","given":"Kristin","email":"ksopkin@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":480102,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":480101,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70168465,"text":"70168465 - 2013 - Fall survival of American woodcock in the western Great Lakes Region","interactions":[],"lastModifiedDate":"2016-02-16T11:49:27","indexId":"70168465","displayToPublicDate":"2013-07-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Fall survival of American woodcock in the western Great Lakes Region","docAbstract":"<p><span>We estimated fall (10 Sep&ndash;8 Nov) survival rates, cause-specific mortality rates, and determined the magnitude and sources of mortality of 1,035 radio-marked American woodcock (</span><i>Scolopax minor</i><span>) in Michigan, Minnesota, and Wisconsin during 2001&ndash;2004. In all 3 states, we radio-marked woodcock on paired study areas; 1 of which was open to hunting and expected to receive moderate to high hunter use and the other of which was either closed to hunting (Michigan and Minnesota) or was relatively inaccessible to hunters (Wisconsin). We used Program MARK to estimate fall survival rates, to evaluate a set of candidate models to examine the effects of hunting and several covariates (sex, age, year, state) on survival, and to examine the relationship between survival rates and kill rates due to hunting. Hunting accounted for 70% of the 86 woodcock deaths in the hunted areas, followed by predation (20%) and various other sources of mortality (10%). Woodcock deaths that occurred in the non-hunted and lightly hunted areas (</span><i>n</i><span>&thinsp;=&thinsp;50) were caused by predators (46%), hunting (32%), and various other sources (22%). Based on small-sample corrected Akaike's Information Criterion values, variation in fall survival of woodcock was best explained by treatment (i.e., hunted vs. non-hunted), year, and period (pre-hunting season intervals vs. hunting season intervals). The average fall survival estimate from our best model for woodcock in the non-hunted areas (0.893, 95% CI&thinsp;=&thinsp;0.864&ndash;0.923) was greater than the average for the hunted areas (0.820, 95% CI&thinsp;=&thinsp;0.786&ndash;0.854 [this estimate includes data from the lightly hunted area in Wisconsin]), and the average treatment effect (i.e., greater survival rates in non-hunted areas) was 0.074 (95% CI&thinsp;=&thinsp;0.018&ndash;0.129). The kill rate due to hunting was 0.120 (95% CI&thinsp;=&thinsp;0.090&ndash;0.151) when data were pooled among states and years. We detected a negative relationship between hunting kill rates and survival in our hunted areas, which suggests that hunting mortality was at least partially additive during fall. Our results illustrate the influence of hunting relative to other sources of mortality in Michigan, Minnesota, and Wisconsin, and indicate that managers may be able to influence fall survival rates by manipulating hunting regulations or access on public land.</span></p>","language":"English","publisher":"Wildlife Society","doi":"10.1002/jwmg.547","usgsCitation":"Bruggink, J.G., Oppelt, E.J., Doherty, K., Andersen, D., Jed Meunier, and Lutz, R.S., 2013, Fall survival of American woodcock in the western Great Lakes Region: Journal of Wildlife Management, v. 77, no. 5, p. 1021-1030, https://doi.org/10.1002/jwmg.547.","productDescription":"10 p.","startPage":"1021","endPage":"1030","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-032833","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":318070,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, Minnesota, Wisconsin","county":"Dickinson County, Lincoln County, Mille Lacs County","otherGeospatial":"Copper Country State Forest, Four Brooks Wildlife Management Area, Lincoln County Forest, Mille Lacs Wildlife Management Area, Tomahawk Timberland Forest","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -93.75869750976562,\n              45.907211023476776\n            ],\n            [\n              -93.75869750976562,\n              46.08942422913245\n            ],\n            [\n              -93.42910766601562,\n              46.08942422913245\n            ],\n            [\n              -93.42910766601562,\n              45.907211023476776\n            ],\n            [\n              -93.75869750976562,\n              45.907211023476776\n            ]\n      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MI","active":true,"usgs":false}],"preferred":false,"id":620467,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oppelt, Eileen J.","contributorId":166938,"corporation":false,"usgs":false,"family":"Oppelt","given":"Eileen","email":"","middleInitial":"J.","affiliations":[{"id":24575,"text":"Northern Michigan University, Marquette, MI","active":true,"usgs":false}],"preferred":false,"id":620468,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Doherty, Kevin","contributorId":166941,"corporation":false,"usgs":false,"family":"Doherty","given":"Kevin","email":"","affiliations":[{"id":24577,"text":"University of Minnesota, St. Paul, MN","active":true,"usgs":false}],"preferred":false,"id":620469,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Andersen, David E. 0000-0001-9535-3404 dea@usgs.gov","orcid":"https://orcid.org/0000-0001-9535-3404","contributorId":2168,"corporation":false,"usgs":true,"family":"Andersen","given":"David E.","email":"dea@usgs.gov","affiliations":[{"id":34539,"text":"Minnesota Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":620470,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jed Meunier","contributorId":166939,"corporation":false,"usgs":false,"family":"Jed Meunier","affiliations":[{"id":24576,"text":"University of Wisconsin, Madison, WI","active":true,"usgs":false}],"preferred":false,"id":620471,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lutz, R. Scott","contributorId":166942,"corporation":false,"usgs":false,"family":"Lutz","given":"R.","email":"","middleInitial":"Scott","affiliations":[{"id":24576,"text":"University of Wisconsin, Madison, WI","active":true,"usgs":false}],"preferred":false,"id":620472,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70041208,"text":"70041208 - 2013 - Assessment of the NASA-USGS Global Land Survey (GLS) Datasets","interactions":[],"lastModifiedDate":"2017-04-06T16:00:45","indexId":"70041208","displayToPublicDate":"2013-07-01T00:00:00","publicationYear":"2013","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":"Assessment of the NASA-USGS Global Land Survey (GLS) Datasets","docAbstract":"<p><span>The Global Land Survey (GLS) datasets are a collection of orthorectified, cloud-minimized Landsat-type satellite images, providing near complete coverage of the global land area decadally since the early 1970s. The global mosaics are centered on 1975, 1990, 2000, 2005, and 2010, and consist of data acquired from four sensors: Enhanced Thematic Mapper Plus, Thematic Mapper, Multispectral Scanner, and Advanced Land Imager. The GLS datasets have been widely used in land-cover and land-use change studies at local, regional, and global scales. This study evaluates the GLS datasets with respect to their spatial coverage, temporal consistency, geodetic accuracy, radiometric calibration consistency, image completeness, extent of cloud contamination, and residual gaps. In general, the three latest GLS datasets are of a better quality than the GLS-1990 and GLS-1975 datasets, with most of the imagery (85%) having cloud cover of less than 10%, the acquisition years clustered much more tightly around their target years, better co-registration relative to GLS-2000, and better radiometric absolute calibration. Probably, the most significant impediment to scientific use of the datasets is the variability of image phenology (i.e., acquisition day of year). This paper provides end-users with an assessment of the quality of the GLS datasets for specific applications, and where possible, suggestions for mitigating their deficiencies.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2013.02.026","usgsCitation":"Gutman, G., Huang, C., Chander, G., Noojipady, P., and Masek, J.G., 2013, Assessment of the NASA-USGS Global Land Survey (GLS) Datasets: Remote Sensing of Environment, v. 134, p. 249-265, https://doi.org/10.1016/j.rse.2013.02.026.","productDescription":"17 p.","startPage":"249","endPage":"265","ipdsId":"IP-037259","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":339371,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"UNITED STATES","volume":"134","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58e753eee4b09da6799c0c53","contributors":{"authors":[{"text":"Gutman, Garik","contributorId":190654,"corporation":false,"usgs":false,"family":"Gutman","given":"Garik","email":"","affiliations":[],"preferred":false,"id":690210,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huang, Chengquan","contributorId":25378,"corporation":false,"usgs":true,"family":"Huang","given":"Chengquan","affiliations":[],"preferred":false,"id":690211,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chander, Gyanesh gchander@usgs.gov","contributorId":3013,"corporation":false,"usgs":true,"family":"Chander","given":"Gyanesh","email":"gchander@usgs.gov","affiliations":[],"preferred":true,"id":690212,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Noojipady, Praveen","contributorId":24260,"corporation":false,"usgs":true,"family":"Noojipady","given":"Praveen","email":"","affiliations":[],"preferred":false,"id":690213,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Masek, Jeffery G.","contributorId":87438,"corporation":false,"usgs":true,"family":"Masek","given":"Jeffery","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":690214,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70046341,"text":"cir1390 - 2013 - Meeting the Science Needs of the Nation in the Wake of Hurricane Sandy-- A U.S. Geological Survey Science Plan for Support of Restoration and Recovery","interactions":[],"lastModifiedDate":"2013-07-01T15:40:19","indexId":"cir1390","displayToPublicDate":"2013-07-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1390","title":"Meeting the Science Needs of the Nation in the Wake of Hurricane Sandy-- A U.S. Geological Survey Science Plan for Support of Restoration and Recovery","docAbstract":"n late October 2012, Hurricane Sandy came ashore during a spring high tide on the New Jersey coastline, delivering hurricane-force winds, storm tides exceeding 19 feet, driving rain, and plummeting temperatures. Hurricane Sandy resulted in 72 direct fatalities in the mid-Atlantic and northeastern United States, and widespread and substantial physical, environmental, ecological, social, and economic impacts estimated at near $50 billion. Before the landfall of Hurricane Sandy, the USGS provided forecasts of potential coastal change; collected oblique aerial photography of pre-storm coastal morphology; deployed storm-surge sensors, rapid-deployment streamgages, wave sensors, and barometric pressure sensors; conducted Light Detection And Ranging (lidar) aerial topographic surveys of coastal areas; and issued a landslide alert for landslide prone areas. During the storm, Tidal Telemetry Networks provided real-time water-level information along the coast. Long-term network and rapid-deployment real-time streamgages and water-quality monitors reported on river levels and changes in water quality. Immediately after the storm, the USGS serviced real-time instrumentation, retrieved data from over 140 storm-surge sensors, and collected other essential environmental data, including more than 830 high-water marks mapping the extent and elevation of the storm surge. Post-storm lidar surveys documented storm impacts to coastal barriers informing response and recovery and providing a new baseline to assess vulnerability of the reconfigured coast. The USGS Hazard Data Distribution System served storm related information from many agencies on the Internet on a daily basis. This science plan was developed immediately following Hurricane Sandy to coordinate continuing USGS activities with other agencies and to guide continued data collection and analysis to ensure support for recovery and restoration efforts. The data, information, and tools that are produced by implementing this plan will: (1) further characterize impacts and changes, (2) guide mitigation and restoration of impacted communities and ecosystems, (3) inform a redevelopment strategy aimed at developing resilient coastal communities and ecosystems, (4) improve preparedness and responsiveness to the next hurricane or similar coastal disaster, and (5) enable improved hazard assessment, response, and recovery for future storms along the hurricane prone shoreline of the United States. The activities outlined in this plan are organized in five themes based on impact types and information needs. These USGS science themes are: Theme 1: Coastal topography and bathymetry. Theme 2: Impacts to coastal beaches and barriers. Theme 3: Impacts of storm surge and estuarine and bay hydrology. Theme 4: Impacts on environmental quality and persisting contaminant exposures. Theme 5: Impacts to coastal ecosystems, habitats, and fish and wildlife. A major emphasis in the implementation of this plan will be on interacting with stakeholders to better understand their specific data and information needs, to define the best way to make information available, and to support applications of USGS science and expertise to decisionmaking.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1390","usgsCitation":"Buxton, H.T., Andersen, M.E., Focazio, M.J., Haines, J.W., Hainly, R.A., Hippe, D.J., and Sugarbaker, L.J., 2013, Meeting the Science Needs of the Nation in the Wake of Hurricane Sandy-- A U.S. Geological Survey Science Plan for Support of Restoration and Recovery: U.S. Geological Survey Circular 1390, vi, 26 p., https://doi.org/10.3133/cir1390.","productDescription":"vi, 26 p.","numberOfPages":"32","additionalOnlineFiles":"N","ipdsId":"IP-046133","costCenters":[{"id":507,"text":"Office of the AD Energy and Mineralsand Environmental Health","active":false,"usgs":true}],"links":[{"id":274399,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/cir1390.gif"},{"id":274393,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1390/circ1390.pdf"},{"id":274392,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/circ/1390/"}],"country":"United States","state":"Connecticut;Delaware;Maine;Maryl;Massachusetts;New Hampshire;New Jersey;New York;Pennsylvania;Rhode Island;Vermont","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -77.94,36.87 ], [ -77.94,43.86 ], [ -69.62,43.86 ], [ -69.62,36.87 ], [ -77.94,36.87 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51d296d7e4b0ca18483389a3","contributors":{"authors":[{"text":"Buxton, Herbert T. hbuxton@usgs.gov","contributorId":1911,"corporation":false,"usgs":true,"family":"Buxton","given":"Herbert","email":"hbuxton@usgs.gov","middleInitial":"T.","affiliations":[{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true}],"preferred":true,"id":479516,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andersen, Matthew E. 0000-0003-4115-5028 mandersen@usgs.gov","orcid":"https://orcid.org/0000-0003-4115-5028","contributorId":3190,"corporation":false,"usgs":true,"family":"Andersen","given":"Matthew","email":"mandersen@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":479519,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Focazio, Michael J. 0000-0003-0967-5576 mfocazio@usgs.gov","orcid":"https://orcid.org/0000-0003-0967-5576","contributorId":1276,"corporation":false,"usgs":true,"family":"Focazio","given":"Michael","email":"mfocazio@usgs.gov","middleInitial":"J.","affiliations":[{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true},{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true}],"preferred":true,"id":479514,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haines, John W. 0000-0002-6475-8924 jhaines@usgs.gov","orcid":"https://orcid.org/0000-0002-6475-8924","contributorId":509,"corporation":false,"usgs":true,"family":"Haines","given":"John","email":"jhaines@usgs.gov","middleInitial":"W.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":479513,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hainly, Robert A. rahainly@usgs.gov","contributorId":1679,"corporation":false,"usgs":true,"family":"Hainly","given":"Robert","email":"rahainly@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":479515,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hippe, Daniel J. djhippe@usgs.gov","contributorId":2281,"corporation":false,"usgs":true,"family":"Hippe","given":"Daniel","email":"djhippe@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":479517,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sugarbaker, Larry J. lsugarbaker@usgs.gov","contributorId":3079,"corporation":false,"usgs":true,"family":"Sugarbaker","given":"Larry","email":"lsugarbaker@usgs.gov","middleInitial":"J.","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":479518,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70041498,"text":"70041498 - 2013 - Modeled distribution and abundance of a pelagic seabird reveal trends in relation to fisheries","interactions":[],"lastModifiedDate":"2013-07-01T11:40:22","indexId":"70041498","displayToPublicDate":"2013-07-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2663,"text":"Marine Ecology Progress Series","active":true,"publicationSubtype":{"id":10}},"title":"Modeled distribution and abundance of a pelagic seabird reveal trends in relation to fisheries","docAbstract":"The northern fulmar Fulmarus glacialis is one of the most visible and widespread seabirds in the eastern Bering Sea and Aleutian Islands. However, relatively little is known about its abundance, trends, or the factors that shape its distribution. We used a long-term pelagic dataset to model changes in fulmar at-sea distribution and abundance since the mid-1970s. We used an ensemble model, based on a weighted average of generalized additive model (GAM), multivariate adaptive regression splines (MARS), and random forest models to estimate the pelagic distribution and density of fulmars in the waters of the Aleutian Archipelago and Bering Sea. The most important predictor variables were colony effect, sea surface temperature, distribution of fisheries, location, and primary productivity. We calculated a time series from the ratio of observed to predicted values and found that fulmar at-sea abundance declined from the 1970s to the 2000s at a rate of 0.83% (± 0.39% SE) per annum. Interpolating fulmar densities on a spatial grid through time, we found that the center of fulmar distribution in the Bering Sea has shifted north, coinciding with a northward shift in fish catches and a warming ocean. Our study shows that fisheries are an important, but not the only factor, shaping fulmar distribution and abundance trends in the eastern Bering Sea and Aleutian Islands.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Marine Ecology Progress Series","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Inter-Research","doi":"10.3354/meps10347","usgsCitation":"Renner, M., Parrish, J.K., Piatt, J.F., Kuletz, K.J., Edwards, A.E., and Hunt, G.L., 2013, Modeled distribution and abundance of a pelagic seabird reveal trends in relation to fisheries: Marine Ecology Progress Series, v. 484, p. 259-277, https://doi.org/10.3354/meps10347.","productDescription":"19 p.","startPage":"259","endPage":"277","ipdsId":"IP-040194","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":473720,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/meps10347","text":"Publisher Index Page"},{"id":274354,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":274353,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3354/meps10347"}],"otherGeospatial":"Bering Sea;Aleutian Islands","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 161.98,51.2 ], [ 161.98,66.05 ], [ -150.9,66.05 ], [ -150.9,51.2 ], [ 161.98,51.2 ] ] ] } } ] }","volume":"484","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51d296d7e4b0ca18483389ab","contributors":{"authors":[{"text":"Renner, Martin","contributorId":18648,"corporation":false,"usgs":true,"family":"Renner","given":"Martin","affiliations":[],"preferred":false,"id":469852,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parrish, Julia K.","contributorId":47270,"corporation":false,"usgs":true,"family":"Parrish","given":"Julia","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":469854,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Piatt, John F. 0000-0002-4417-5748 jpiatt@usgs.gov","orcid":"https://orcid.org/0000-0002-4417-5748","contributorId":3025,"corporation":false,"usgs":true,"family":"Piatt","given":"John","email":"jpiatt@usgs.gov","middleInitial":"F.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","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}],"preferred":true,"id":469851,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kuletz, Kathy J.","contributorId":24669,"corporation":false,"usgs":true,"family":"Kuletz","given":"Kathy","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":469853,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Edwards, Ann E.","contributorId":62110,"corporation":false,"usgs":true,"family":"Edwards","given":"Ann","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":469856,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hunt, George L. Jr.","contributorId":56953,"corporation":false,"usgs":true,"family":"Hunt","given":"George","suffix":"Jr.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":469855,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70193590,"text":"70193590 - 2013 - Merapi 2010 eruption—Chronology and extrusion rates monitored with satellite radar and used in eruption forecasting","interactions":[],"lastModifiedDate":"2017-11-02T12:05:26","indexId":"70193590","displayToPublicDate":"2013-07-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Merapi 2010 eruption—Chronology and extrusion rates monitored with satellite radar and used in eruption forecasting","docAbstract":"<p><span>Despite dense cloud cover, satellite-borne commercial Synthetic Aperture Radar (SAR) enabled frequent monitoring of Merapi volcano's 2010 eruption. Near-real-time interpretation of images derived from the amplitude of the SAR signals and timely delivery of these interpretations to those responsible for warnings, allowed satellite remote sensing for the first time to play an equal role with&nbsp;</span><i>in situ</i><span><span>&nbsp;</span>seismic, geodetic and gas monitoring in guiding life-saving decisions during a major volcanic crisis. Our remotely sensed data provide an observational chronology for the main phase of the 2010 eruption, which lasted 12</span><span>&nbsp;</span><span>days (26 October–7 November, 2010). Unlike the prolonged low-rate and relatively low explosivity dome-forming and collapse eruptions of recent decades at Merapi, the eruption began with an explosive eruption that produced a new summit crater on 26 October and was accompanied by an ash column and pyroclastic flows that extended 8</span><span>&nbsp;</span><span>km down the flanks. This initial explosive event was followed by smaller explosive eruptions on 29 October–1 November, then by a period of rapid dome growth on 1–4 November, which produced a summit lava dome with a volume of ~</span><span>&nbsp;</span><span>5</span><span>&nbsp;</span><span>×</span><span>&nbsp;</span><span>10</span><sup>6</sup><span>&nbsp;</span><span>m</span><sup>3</sup><span>. A paroxysmal VEI 4 magmatic eruption (with ash column to 17</span><span>&nbsp;</span><span>km altitude) destroyed this dome, greatly enlarged the new summit crater and produced extensive pyroclastic flows (to ~</span><span>&nbsp;</span><span>16</span><span>&nbsp;</span><span>km radial distance in the Gendol drainage) and surges during the night of 4–5 November. The paroxysmal eruption was followed by a period of jetting of gas and tephra and by a second short period (12</span><span>&nbsp;</span><span>h) of rapid dome growth on 6 November. The eruption ended with low-level ash and steam emissions that buried the 6 November dome with tephra and continued at low levels until seismicity decreased to background levels by about 23 November. Our near-real-time commercial SAR documented the explosive events on 26 October and 4–5 November and high rates of dome growth (&gt;</span><span>&nbsp;</span><span>25</span><span>&nbsp;</span><span>m</span><sup>3</sup><span>&nbsp;</span><span>s</span><sup>−&nbsp;1</sup><span>). An event tree analysis for the previous 2006 Merapi eruption indicated that for lava dome extrusion rates &gt;</span><span>&nbsp;</span><span>1.2</span><span>&nbsp;</span><span>m</span><sup>3</sup><span>&nbsp;</span><span>s</span><sup>−&nbsp;1</sup><span>, the probability of a large (1872-scale) eruption was ~</span><span>&nbsp;</span><span>10%. Consequently, the order-of-magnitude greater rates in 2010, along with the explosive start of the eruption on 26 October, the large volume of lava accumulating at the summit by 4 November, and the rapid and large increases in seismic energy release, deformation and gas emissions were the basis for warnings of an unusually large eruption by the Indonesian Geological Agency's Center for Volcanology and Geologic Hazard Mitigation (CVGHM) and their Volcano Research and Technology Development Center (BPPTK) in Yogyakarta — warnings that saved thousands of lives.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2012.07.012","usgsCitation":"Pallister, J.S., Schneider, D.J., Griswold, J.P., Keeler, R.H., Burton, W.C., Noyles, C., Newhall, C.G., and Ratdomopurbo, A., 2013, Merapi 2010 eruption—Chronology and extrusion rates monitored with satellite radar and used in eruption forecasting: Journal of Volcanology and Geothermal Research, v. 261, p. 144-152, https://doi.org/10.1016/j.jvolgeores.2012.07.012.","productDescription":"9 p.","startPage":"144","endPage":"152","ipdsId":"IP-039184","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":348081,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Indonesia","otherGeospatial":"Merapi Volcano","volume":"261","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59fc2eade4b0531197b27fc5","contributors":{"authors":[{"text":"Pallister, John S. 0000-0002-2041-2147 jpallist@usgs.gov","orcid":"https://orcid.org/0000-0002-2041-2147","contributorId":2024,"corporation":false,"usgs":true,"family":"Pallister","given":"John","email":"jpallist@usgs.gov","middleInitial":"S.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":719512,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schneider, David J. 0000-0001-9092-1054 djschneider@usgs.gov","orcid":"https://orcid.org/0000-0001-9092-1054","contributorId":198601,"corporation":false,"usgs":true,"family":"Schneider","given":"David","email":"djschneider@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":719510,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Griswold, Julia P. griswold@usgs.gov","contributorId":4148,"corporation":false,"usgs":true,"family":"Griswold","given":"Julia","email":"griswold@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":719511,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keeler, Ronald H.","contributorId":199596,"corporation":false,"usgs":false,"family":"Keeler","given":"Ronald","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":719541,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Burton, William C. 0000-0001-7519-5787 bburton@usgs.gov","orcid":"https://orcid.org/0000-0001-7519-5787","contributorId":1293,"corporation":false,"usgs":true,"family":"Burton","given":"William","email":"bburton@usgs.gov","middleInitial":"C.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":719542,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Noyles, Christopher","contributorId":199597,"corporation":false,"usgs":false,"family":"Noyles","given":"Christopher","email":"","affiliations":[],"preferred":false,"id":719543,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Newhall, Christopher G.","contributorId":25557,"corporation":false,"usgs":true,"family":"Newhall","given":"Christopher","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":719544,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ratdomopurbo, Antonius","contributorId":22523,"corporation":false,"usgs":true,"family":"Ratdomopurbo","given":"Antonius","email":"","affiliations":[],"preferred":false,"id":719545,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70193598,"text":"70193598 - 2013 - Integrating satellite observations and modern climate measurements with the recent sedimentary record: An example from Southeast Alaska","interactions":[],"lastModifiedDate":"2017-11-02T14:32:48","indexId":"70193598","displayToPublicDate":"2013-07-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2321,"text":"Journal of Geophysical Research: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Integrating satellite observations and modern climate measurements with the recent sedimentary record: An example from Southeast Alaska","docAbstract":"<p><span>Assessments of climate change over time scales that exceed the last 100 years require robust integration of high-quality instrument records with high-resolution paleoclimate proxy data. In this study, we show that the recent biogenic sediments accumulating in two temperate ice-free fjords in Southeast Alaska preserve evidence of North Pacific Ocean climate variability as recorded by both instrument networks and satellite observations. Multicore samples EW0408-32MC and EW0408-43MC were investigated with&nbsp;</span><sup>137</sup><span>Cs and excess<span>&nbsp;</span></span><sup>210</sup><span>Pb geochronometry, three-dimensional computed tomography, high-resolution scanning XRF geochemistry, and organic stable isotope analyses. EW0408-32MC (57.162°N, 135.357°W, 146 m depth) is a moderately bioturbated continuous record that spans AD ∼1930–2004. EW0408-43MC (56.965°N, 135.268°W, 91 m depth) is composed of laminated diatom oozes, a turbidite, and a hypopycnal plume (river flood) deposit. A discontinuous event-based varve chronology indicates 43MC spans AD ∼1940–1981. Decadal-scale fluctuations in sedimentary Br/Cl ratios accurately reflect changes in marine organic matter accumulation that display the same temporal pattern as that of the Pacific Decadal Oscillation. An estimated Sitka summer productivity parameter calibrated using SeaWiFS satellite observations support these relationships. The correlation of North Pacific climate regime states, primary productivity, and sediment geochemistry indicate the accumulation of biogenic sediment in Southeast Alaska temperate fjords can be used as a sensitive recorder of past productivity variability, and by inference, past climate conditions in the high-latitude Gulf of Alaska.</span></p>","language":"English","publisher":"AGU","doi":"10.1002/jgrc.20243","usgsCitation":"Addison, J.A., Finney, B., Jaeger, J.M., Stoner, J.S., Norris, R.D., and Hangsterfer, A., 2013, Integrating satellite observations and modern climate measurements with the recent sedimentary record: An example from Southeast Alaska: Journal of Geophysical Research: Oceans, v. 118, no. 7, p. 3444-3461, https://doi.org/10.1002/jgrc.20243.","productDescription":"18 p.","startPage":"3444","endPage":"3461","ipdsId":"IP-043226","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":473724,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jgrc.20243","text":"Publisher Index Page"},{"id":348106,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -155,\n              50\n            ],\n            [\n              -120,\n              50\n            ],\n            [\n              -120,\n              61\n            ],\n            [\n              -155,\n              61\n            ],\n            [\n              -155,\n              50\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"118","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2013-07-17","publicationStatus":"PW","scienceBaseUri":"59fc2eace4b0531197b27fc1","contributors":{"authors":[{"text":"Addison, Jason A. 0000-0003-2416-9743 jaddison@usgs.gov","orcid":"https://orcid.org/0000-0003-2416-9743","contributorId":4192,"corporation":false,"usgs":true,"family":"Addison","given":"Jason","email":"jaddison@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":719559,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Finney, Bruce P.","contributorId":88074,"corporation":false,"usgs":true,"family":"Finney","given":"Bruce P.","affiliations":[],"preferred":false,"id":719561,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Jaeger, John M.","contributorId":11423,"corporation":false,"usgs":true,"family":"Jaeger","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":719562,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Stoner, Joseph S.","contributorId":84171,"corporation":false,"usgs":true,"family":"Stoner","given":"Joseph","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":719563,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Norris, Richard D.","contributorId":51651,"corporation":false,"usgs":true,"family":"Norris","given":"Richard","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":719564,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Hangsterfer, Alexandra","contributorId":199603,"corporation":false,"usgs":false,"family":"Hangsterfer","given":"Alexandra","email":"","affiliations":[],"preferred":false,"id":719560,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}}
,{"id":70046718,"text":"ofr20131142 - 2013 - The Regional Salmon Outmigration Study--survival and migration routing of juvenile Chinook salmon in the Sacramento-San Joaquin River Delta during the winter of 2008-09","interactions":[],"lastModifiedDate":"2013-06-28T11:49:19","indexId":"ofr20131142","displayToPublicDate":"2013-06-28T00:00:00","publicationYear":"2013","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":"2013-1142","title":"The Regional Salmon Outmigration Study--survival and migration routing of juvenile Chinook salmon in the Sacramento-San Joaquin River Delta during the winter of 2008-09","docAbstract":"Juvenile Chinook salmon (Oncorhynchus tshawytscha) emigrating from natal tributaries of the Sacramento River may use a number of migration routes to navigate the Sacramento-San Joaquin River Delta (hereafter called “the Delta”), each of which may influence their probability of surviving. We applied a mark-recapture model to data from acoustically tagged juvenile late fall-run Chinook salmon that migrated through the Delta during the winter of 2008–09 to estimate route entrainment, survival, and migration times through the Delta.\n\nA tag-life study was conducted to determine the potential for premature tag failure. Tag failure began after 12 days and continued until the 45th day. Travel times of tagged fish exceeded minimum tag-failure times, indicating that survival estimates obtained from this study were negatively biased due to tag failure prior to fish exiting the Delta. Survival estimates were not adjusted and represent the joint probability of tag survival and fish survival. However, relative comparisons of survival among Chinook salmon choosing different routes appeared to be robust to tag failure, and migration-routing parameters were unaffected by tag failure.\n\nMigration-routing patterns were consistent among release groups. The Sacramento River was the primary migration route for all release groups except one. The percentage of fish entering the Sacramento River ranged from 33 to 55 percent. Sutter and Steamboat Sloughs were the secondary migration route for 9 of the 10 releases. The percentage of fish migrating through this route ranged from 10 to 35 percent. Entrainment into the interior Delta ranged from 15 to 33 percent. The Delta Cross Channel gates were open for 7 of the 10 releases. Entrainment into the interior Delta through the cross channel ranged from 1 to 27 percent.\n\nWe estimated route-specific survival for 10 release groups that were released between November 14, 2008, and January 19, 2009. Population-level survival through the Delta (S<sub>Delta</sub>) ranged from 0.019 (standard error of 0.012) to 0.277 (standard error of 0.041) among releases, which represent the probability of a fish surviving from Sacramento to Chipps Island with an operational transmitter. Sacramento River flows throughout the study period were approximately 8,000–15,000 cubic feet per second at Freeport, suggesting that variability in flow contributed little to differences in survival between releases. Fish migrating through the Sacramento River had the highest survival for most releases. Survival in Sutter and Steamboat Sloughs was slightly lower than survival in the Sacramento River for 7 of the 10 releases, but higher than survival in the Sacramento River for 3 releases. Survival in the interior Delta was lowest for all release groups except for one release in November. With the exception of this November release, survival patterns across release groups were similar to those of previous studies.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131142","collaboration":"Prepared in cooperation with the California Department of Water Resources and Bureau of Reclamation","usgsCitation":"Romine, J.G., Perry, R.W., Brewer, S.J., Adams, N.S., Liedtke, T.L., Blake, A.R., and Burau, J.R., 2013, The Regional Salmon Outmigration Study--survival and migration routing of juvenile Chinook salmon in the Sacramento-San Joaquin River Delta during the winter of 2008-09: U.S. Geological Survey Open-File Report 2013-1142, vi, 36 p., https://doi.org/10.3133/ofr20131142.","productDescription":"vi, 36 p.","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2008-11-14","temporalEnd":"2009-01-19","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":274296,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131142.jpg"},{"id":274293,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1142/"},{"id":274294,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2013/1142/pdf/ofr20131142_appendixD.zip"},{"id":274295,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1142/pdf/ofr20131142.pdf"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-san Joaquin River Delta","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.0,37.833333 ], [ -122.0,38.583333 ], [ -121.333333,38.583333 ], [ -121.333333,37.833333 ], [ -122.0,37.833333 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51cea255e4b044272b8e890a","contributors":{"authors":[{"text":"Romine, Jason G. 0000-0002-6938-1185 jromine@usgs.gov","orcid":"https://orcid.org/0000-0002-6938-1185","contributorId":2823,"corporation":false,"usgs":true,"family":"Romine","given":"Jason","email":"jromine@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":480081,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":480080,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brewer, Scott J. sbrewer@usgs.gov","contributorId":4407,"corporation":false,"usgs":true,"family":"Brewer","given":"Scott","email":"sbrewer@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":480084,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Adams, Noah S. 0000-0002-8354-0293 nadams@usgs.gov","orcid":"https://orcid.org/0000-0002-8354-0293","contributorId":3521,"corporation":false,"usgs":true,"family":"Adams","given":"Noah","email":"nadams@usgs.gov","middleInitial":"S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":480083,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Liedtke, Theresa L. 0000-0001-6063-9867 tliedtke@usgs.gov","orcid":"https://orcid.org/0000-0001-6063-9867","contributorId":2999,"corporation":false,"usgs":true,"family":"Liedtke","given":"Theresa","email":"tliedtke@usgs.gov","middleInitial":"L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":480082,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blake, Aaron R. 0000-0001-7348-2336 ablake@usgs.gov","orcid":"https://orcid.org/0000-0001-7348-2336","contributorId":5059,"corporation":false,"usgs":true,"family":"Blake","given":"Aaron","email":"ablake@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480085,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Burau, Jon R. 0000-0002-5196-5035 jrburau@usgs.gov","orcid":"https://orcid.org/0000-0002-5196-5035","contributorId":1500,"corporation":false,"usgs":true,"family":"Burau","given":"Jon","email":"jrburau@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480079,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70046717,"text":"sir20135050 - 2013 - Brookian sequence well log correlation sections and occurrence of gas hydrates, north-central North Slope, Alaska","interactions":[],"lastModifiedDate":"2013-06-27T16:20:22","indexId":"sir20135050","displayToPublicDate":"2013-06-27T00:00:00","publicationYear":"2013","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":"2013-5050","title":"Brookian sequence well log correlation sections and occurrence of gas hydrates, north-central North Slope, Alaska","docAbstract":"Gas hydrates are naturally occurring crystalline, ice-like substances that consist of natural gas molecules trapped in a solid-water lattice. Because of the compact nature of their structure, hydrates can effectively store large volumes of gas and, consequently, have been identified as a potential unconventional energy source. First recognized to exist geologically in the 1960s, significant accumulations of gas hydrate have been found throughout the world. Gas hydrate occurrence is limited to environments such as permafrost regions and subsea sediments because of the pressure and temperature conditions required for their formation and stability. Permafrost-associated gas hydrate accumulations have been discovered in many regions of the Arctic, including Russia, Canada, and the North Slope of Alaska. Gas hydrate research has a long history in northern Alaska. This research includes the drilling, coring, and well log evaluation of two gas hydrate stratigraphic test wells and two resource assessments of gas hydrates on the Alaska North Slope. Building upon these previous investigations, this report provides a summary of the pertinent well log, gas hydrate, and stratigraphic data for key wells related to gas hydrate occurrence in the north-central North Slope. The data are presented in nine well log correlation sections with 122 selected wells to provide a regional context for gas hydrate accumulations and the relation of the accumulations to key stratigraphic horizons and to the base of the ice-bearing permafrost. Also included is a well log database that lists the location, available well logs, depths, and other pertinent information for each of the wells on the correlation section.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135050","usgsCitation":"Lewis, K.A., and Collett, T.S., 2013, Brookian sequence well log correlation sections and occurrence of gas hydrates, north-central North Slope, Alaska: U.S. Geological Survey Scientific Investigations Report 2013-5050, Report: vi, 25 p., https://doi.org/10.3133/sir20135050.","productDescription":"Report: vi, 25 p.","numberOfPages":"33","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":274283,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135050.gif"},{"id":274280,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5050/"},{"id":274281,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5050/SIR13-5050_508.pdf"},{"id":274282,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2013/5050/downloads2/"}],"country":"United States","state":"Alaska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -0.015277777777777777,6.151944444444445 ], [ -0.015277777777777777,0.0019444444444444444 ], [ -0.015555555555555555,0.0019444444444444444 ], [ -0.015555555555555555,6.151944444444445 ], [ -0.015277777777777777,6.151944444444445 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51cd50d6e4b0e7a904971bab","contributors":{"authors":[{"text":"Lewis, Kristen A. 0000-0003-4991-3399 klewis@usgs.gov","orcid":"https://orcid.org/0000-0003-4991-3399","contributorId":4120,"corporation":false,"usgs":true,"family":"Lewis","given":"Kristen","email":"klewis@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":480078,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collett, Timothy S. 0000-0002-7598-4708 tcollett@usgs.gov","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":1698,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"tcollett@usgs.gov","middleInitial":"S.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":480077,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70046716,"text":"ofr20131115 - 2013 - Assessing the use of existing data to compare plains fish assemblages collected from random and fixed sites in Colorado","interactions":[],"lastModifiedDate":"2013-06-27T16:04:29","indexId":"ofr20131115","displayToPublicDate":"2013-06-27T00:00:00","publicationYear":"2013","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":"2013-1115","title":"Assessing the use of existing data to compare plains fish assemblages collected from random and fixed sites in Colorado","docAbstract":"The U.S. Geological Survey, in cooperation with Colorado Parks and Wildlife, assessed the potential use of combining recently (2007 to 2010) and formerly (1992 to 1996) collected data to compare plains fish assemblages sampled from random and fixed sites located in the South Platte and Arkansas River Basins in Colorado. The first step was to determine if fish assemblages collected between 1992 and 1996 were comparable to samples collected at the same sites between 2007 and 2010. If samples from the two time periods were comparable, then it was considered reasonable that the combined time-period data could be used to make comparisons between random and fixed sites. In contrast, if differences were found between the two time periods, then it was considered unreasonable to use these data to make comparisons between random and fixed sites. One-hundred samples collected during the 1990s and 2000s from 50 sites dispersed among 19 streams in both basins were compiled from a database maintained by Colorado Parks and Wildlife. Nonparametric multivariate two-way analysis of similarities was used to test for fish-assemblage differences between time periods while accounting for stream-to-stream differences. Results indicated relatively weak but significant time-period differences in fish assemblages. Weak time-period differences in this case possibly were related to changes in fish assemblages associated with environmental factors; however, it is difficult to separate other possible explanations such as limited replication of paired time-period samples in many of the streams or perhaps differences in sampling efficiency and effort between the time periods. Regardless, using the 1990s data to fill data gaps to compare random and fixed-site fish-assemblage data is ill advised based on the significant separation in fish assemblages between time periods and the inability to determine conclusive explanations for these results. These findings indicated that additional sampling will be necessary before unbiased comparisons can be made between fish assemblages collected from random and fixed sites in the South Platte and Arkansas River Basins.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131115","collaboration":"Prepared in cooperation with Colorado Parks and Wildlife","usgsCitation":"Zuellig, R.E., and Crockett, H.J., 2013, Assessing the use of existing data to compare plains fish assemblages collected from random and fixed sites in Colorado: U.S. Geological Survey Open-File Report 2013-1115, iv, 9 p., https://doi.org/10.3133/ofr20131115.","productDescription":"iv, 9 p.","numberOfPages":"13","onlineOnly":"Y","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":274279,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131115.gif"},{"id":274278,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1115/OF13-1115_508.pdf"},{"id":274277,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1115/"}],"country":"United States","state":"Colorado","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -0.016666666666666666,8.333333333333334E-4 ], [ -0.016666666666666666,0.0011111111111111111 ], [ -0.016666666666666666,0.0011111111111111111 ], [ -0.016666666666666666,8.333333333333334E-4 ], [ -0.016666666666666666,8.333333333333334E-4 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51cd50d1e4b0e7a904971ba7","contributors":{"authors":[{"text":"Zuellig, Robert E. 0000-0002-4784-2905 rzuellig@usgs.gov","orcid":"https://orcid.org/0000-0002-4784-2905","contributorId":1620,"corporation":false,"usgs":true,"family":"Zuellig","given":"Robert","email":"rzuellig@usgs.gov","middleInitial":"E.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480075,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crockett, Harry J.","contributorId":75417,"corporation":false,"usgs":true,"family":"Crockett","given":"Harry","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":480076,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70046703,"text":"sir20125209 - 2013 - Estimates of the volume of water in five coal aquifers, Northern Cheyenne Indian Reservation, southeastern Montana","interactions":[],"lastModifiedDate":"2013-06-26T09:37:49","indexId":"sir20125209","displayToPublicDate":"2013-06-26T00:00:00","publicationYear":"2013","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":"2012-5209","title":"Estimates of the volume of water in five coal aquifers, Northern Cheyenne Indian Reservation, southeastern Montana","docAbstract":"The Tongue River Member of the Tertiary Fort Union Formation is the primary source of groundwater in the Northern Cheyenne Indian Reservation in southeastern Montana. Coal beds within this formation generally contain the most laterally extensive aquifers in much of the reservation. The U.S. Geological Survey, in cooperation with the Northern Cheyenne Tribe, conducted a study to estimate the volume of water in five coal aquifers.\n\nThis report presents estimates of the volume of water in five coal aquifers in the eastern and southern parts of the Northern Cheyenne Indian Reservation: the Canyon, Wall, Pawnee, Knobloch, and Flowers-Goodale coal beds in the Tongue River Member of the Tertiary Fort Union Formation. Only conservative estimates of the volume of water in these coal aquifers are presented.\n\nThe volume of water in the Canyon coal was estimated to range from about 10,400 acre-feet (75 percent saturated) to 3,450 acre-feet (25 percent saturated). The volume of water in the Wall coal was estimated to range from about 14,200 acre-feet (100 percent saturated) to 3,560 acre-feet (25 percent saturated). The volume of water in the Pawnee coal was estimated to range from about 9,440 acre-feet (100 percent saturated) to 2,360 acre-feet (25 percent saturated). The volume of water in the Knobloch coal was estimated to range from about 38,700 acre-feet (100 percent saturated) to 9,680 acre-feet (25 percent saturated). The volume of water in the Flowers-Goodale coal was estimated to be about 35,800 acre-feet (100 percent saturated).\n\nSufficient data are needed to accurately characterize coal-bed horizontal and vertical variability, which is highly complex both locally and regionally. Where data points are widely spaced, the reliability of estimates of the volume of coal beds is decreased. Additionally, reliable estimates of the volume of water in coal aquifers depend heavily on data about water levels and data about coal-aquifer characteristics. Because the data needed to define the volume of water were sparse, only conservative estimates of the volume of water in the five coal aquifers are presented in this report. These estimates need to be used with caution and mindfulness of the uncertainty associated with them.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125209","collaboration":"Prepared in cooperation with the Northern Cheyenne Tribe","usgsCitation":"Tuck, L., Pearson, D., Cannon, M.R., and Dutton, D., 2013, Estimates of the volume of water in five coal aquifers, Northern Cheyenne Indian Reservation, southeastern Montana: U.S. Geological Survey Scientific Investigations Report 2012-5209, vi, 26 p., https://doi.org/10.3133/sir20125209.","productDescription":"vi, 26 p.","numberOfPages":"35","additionalOnlineFiles":"N","costCenters":[{"id":400,"text":"Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":274237,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20125209.gif"},{"id":274235,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5209/"},{"id":274236,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5209/sir2012-5209.pdf"}],"country":"United States","state":"Montana","otherGeospatial":"Northern Cheyenne Indian Reservation","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -107.083333,45.166667 ], [ -107.083333,45.75 ], [ -106.166667,45.75 ], [ -106.166667,45.166667 ], [ -107.083333,45.166667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51cbff4fe4b052f2a453985f","contributors":{"authors":[{"text":"Tuck, L.K.","contributorId":54247,"corporation":false,"usgs":true,"family":"Tuck","given":"L.K.","email":"","affiliations":[],"preferred":false,"id":480041,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pearson, Daniel K.","contributorId":52014,"corporation":false,"usgs":true,"family":"Pearson","given":"Daniel K.","affiliations":[],"preferred":false,"id":480040,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cannon, M. R.","contributorId":99140,"corporation":false,"usgs":true,"family":"Cannon","given":"M.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":480042,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dutton, DeAnn M. ddutton@usgs.gov","contributorId":20762,"corporation":false,"usgs":true,"family":"Dutton","given":"DeAnn M.","email":"ddutton@usgs.gov","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":false,"id":480039,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70046704,"text":"ds778 - 2013 - SSR_pipeline--computer software for the identification of microsatellite sequences from paired-end Illumina high-throughput DNA sequence data","interactions":[],"lastModifiedDate":"2013-06-26T09:52:58","indexId":"ds778","displayToPublicDate":"2013-06-26T00:00:00","publicationYear":"2013","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":"778","title":"SSR_pipeline--computer software for the identification of microsatellite sequences from paired-end Illumina high-throughput DNA sequence data","docAbstract":"SSR_pipeline is a flexible set of programs designed to efficiently identify simple sequence repeats (SSRs; for example, microsatellites) from paired-end high-throughput Illumina DNA sequencing data. The program suite contains three analysis modules along with a fourth control module that can be used to automate analyses of large volumes of data. The modules are used to (1) identify the subset of paired-end sequences that pass quality standards, (2) align paired-end reads into a single composite DNA sequence, and (3) identify sequences that possess microsatellites conforming to user specified parameters. Each of the three separate analysis modules also can be used independently to provide greater flexibility or to work with FASTQ or FASTA files generated from other sequencing platforms (Roche 454, Ion Torrent, etc).\n\nAll modules are implemented in the Python programming language and can therefore be used from nearly any computer operating system (Linux, Macintosh, Windows). The program suite relies on a compiled Python extension module to perform paired-end alignments. Instructions for compiling the extension from source code are provided in the documentation. Users who do not have Python installed on their computers or who do not have the ability to compile software also may choose to download packaged executable files. These files include all Python scripts, a copy of the compiled extension module, and a minimal installation of Python in a single binary executable. See program documentation for more information.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds778","usgsCitation":"Miller, M.P., Knaus, B.J., Mullins, T., and Haig, S.M., 2013, SSR_pipeline--computer software for the identification of microsatellite sequences from paired-end Illumina high-throughput DNA sequence data: U.S. Geological Survey Data Series 778, HTML Document; Program Documentation; Program Executable Files, https://doi.org/10.3133/ds778.","productDescription":"HTML Document; Program Documentation; Program Executable Files","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":274247,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds778.jpg"},{"id":274240,"type":{"id":19,"text":"Raw Data"},"url":"https://pubs.usgs.gov/ds/778/01_SSR_pipeline_0.95_src_and_docs.tgz"},{"id":274241,"type":{"id":19,"text":"Raw Data"},"url":"https://pubs.usgs.gov/ds/778/03_SSR_pipeline_sample_data.zip"},{"id":274238,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/778/"},{"id":274242,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/778/04_SSR_pipeline_documentation.pdf"},{"id":274239,"type":{"id":19,"text":"Raw Data"},"url":"https://pubs.usgs.gov/ds/778/02_SSR_pipeline_0.95_src_and_docs.zip"},{"id":274243,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/778/05_SSR_pipeline_0.95_win32_executeables.zip"},{"id":274244,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/778/08_SSR_pipeline_0.95_32bit_linux.tar.gz"},{"id":274245,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/778/06_SSR_pipeline_0.95_64bit_linux.tar.gz"},{"id":274246,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/778/07_SSR_pipeline_0.95_OSX64bit.tar.gz"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51cbff57e4b052f2a453988b","contributors":{"authors":[{"text":"Miller, Mark P. 0000-0003-1045-1772 mpmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-1045-1772","contributorId":1967,"corporation":false,"usgs":true,"family":"Miller","given":"Mark","email":"mpmiller@usgs.gov","middleInitial":"P.","affiliations":[{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"preferred":true,"id":480044,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knaus, Brian J.","contributorId":107167,"corporation":false,"usgs":true,"family":"Knaus","given":"Brian","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":480046,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mullins, Thomas D.","contributorId":12819,"corporation":false,"usgs":true,"family":"Mullins","given":"Thomas D.","affiliations":[],"preferred":false,"id":480045,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haig, Susan M. 0000-0002-6616-7589 susan_haig@usgs.gov","orcid":"https://orcid.org/0000-0002-6616-7589","contributorId":719,"corporation":false,"usgs":true,"family":"Haig","given":"Susan","email":"susan_haig@usgs.gov","middleInitial":"M.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":480043,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70046705,"text":"ds762 - 2013 - Geophysical logging and geologic mapping data in the vicinity of the GMH Electronics Superfund site near Roxboro, North Carolina","interactions":[],"lastModifiedDate":"2013-06-26T13:05:09","indexId":"ds762","displayToPublicDate":"2013-06-26T00:00:00","publicationYear":"2013","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":"762","title":"Geophysical logging and geologic mapping data in the vicinity of the GMH Electronics Superfund site near Roxboro, North Carolina","docAbstract":"Geologic mapping, the collection of borehole geophysical logs and images, and passive diffusion bag sampling were conducted by the U.S. Geological Survey North Carolina Water Science Center in the vicinity of the GMH Electronics Superfund site near Roxboro, North Carolina, during March through October 2011. The study purpose was to assist the U.S. Environmental Protection Agency in the development of a conceptual groundwater model for the assessment of current contaminant distribution and future migration of contaminants. Data compilation efforts included geologic mapping of more than 250 features, including rock type and secondary joints, delineation of more than 1,300 subsurface features (primarily fracture orientations) in 15 open borehole wells, and the collection of passive diffusion-bag samples from 42 fracture zones at various depths in the 15 wells.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds762","collaboration":"Prepared in cooperation with U.S. Environmental Protection Agency Region 4 Superfund Section","usgsCitation":"Chapman, M.J., Clark, T.W., and Williams, J., 2013, Geophysical logging and geologic mapping data in the vicinity of the GMH Electronics Superfund site near Roxboro, North Carolina: U.S. Geological Survey Data Series 762, Report: viii, 37 p.; Appendixes 1-8, https://doi.org/10.3133/ds762.","productDescription":"Report: viii, 37 p.; Appendixes 1-8","numberOfPages":"47","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true}],"links":[{"id":274259,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds762.gif"},{"id":274258,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/762/appendix"},{"id":274256,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/762/"},{"id":274257,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/762/pdf/ds762.pdf"}],"country":"United States","state":"North Carolina","city":"Roxboro","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -84.32,33.84 ], [ -84.32,36.58 ], [ -75.46,36.58 ], [ -75.46,33.84 ], [ -84.32,33.84 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51cbff54e4b052f2a4539863","contributors":{"authors":[{"text":"Chapman, Melinda J. 0000-0003-4021-0320 mjchap@usgs.gov","orcid":"https://orcid.org/0000-0003-4021-0320","contributorId":1597,"corporation":false,"usgs":true,"family":"Chapman","given":"Melinda","email":"mjchap@usgs.gov","middleInitial":"J.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480048,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clark, Timothy W.","contributorId":104377,"corporation":false,"usgs":true,"family":"Clark","given":"Timothy","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":480049,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Williams, John H. 0000-0002-6054-6908 jhwillia@usgs.gov","orcid":"https://orcid.org/0000-0002-6054-6908","contributorId":1553,"corporation":false,"usgs":true,"family":"Williams","given":"John","email":"jhwillia@usgs.gov","middleInitial":"H.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480047,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70046040,"text":"70046040 - 2013 - Measuring the relative resilience of subarctic lakes to global change: redundancies of functions within and across temporal scales","interactions":[],"lastModifiedDate":"2017-02-13T14:31:47","indexId":"70046040","displayToPublicDate":"2013-06-26T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Measuring the relative resilience of subarctic lakes to global change: redundancies of functions within and across temporal scales","docAbstract":"1. Ecosystems at high altitudes and latitudes are expected to be particularly vulnerable to the effects of global change. We assessed the responses of littoral invertebrate communities to changing abiotic conditions in subarctic Swedish lakes with long-term data (1988–2010) and compared the responses of subarctic lakes with those of more southern, hemiboreal lakes. 2. We used a complex systems approach, based on multivariate time-series modelling, and identified dominant and distinct temporal frequencies in the data; that is, we tracked community change at distinct temporal scales. We determined the distribution of functional feeding groups of invertebrates within and across temporal scales. Within and cross-scale distributions of functions have been considered to confer resilience to ecosystems, despite changing environmental conditions. 3. Two patterns of temporal change within the invertebrate communities were identified that were consistent across the lakes. The first pattern was one of monotonic change associated with changing abiotic lake conditions. The second was one of showing fluctuation patterns largely unrelated to gradual environmental change. Thus, two dominant and distinct temporal frequencies (temporal scales) were present in all lakes analysed. 4. Although the contribution of individual feeding groups varied between subarctic and hemiboreal lakes, they shared overall similar functional attributes (richness, evenness, diversity) and redundancies of functions within and between the observed temporal scales. This highlights similar resilience characteristics in subarctic and hemiboreal lakes. 5. Synthesis and applications. The effects of global change can be particularly strong at a single scale in ecosystems. Over time, this can cause monotonic change in communities and eventually lead to a loss of important ecosystem services upon reaching a critical threshold. Dynamics at other spatial or temporal scales can be unrelated to environmental change. The relative ‘intactness’ of these scales that are unaffected by global change and the persistence of functions at those scales may safeguard the whole system from the potential loss of functions at the scale at which global change impacts can be substantial. Thus, an understanding of scale-specific processes provides managers with a realistic assessment of vulnerabilities and the relative resilience of ecosystems to environmental change. Explicit consideration of ‘intact’ and ‘affected’ scales in analyses of global change impacts provides opportunities to tailor more specific management plans.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Applied Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/1365-2664.12092","usgsCitation":"Angeler, D., Allen, C.R., and Johnson, R.K., 2013, Measuring the relative resilience of subarctic lakes to global change: redundancies of functions within and across temporal scales: Journal of Applied Ecology, v. 50, no. 3, p. 572-584, https://doi.org/10.1111/1365-2664.12092.","productDescription":"13 p.","startPage":"572","endPage":"584","ipdsId":"IP-043647","costCenters":[{"id":463,"text":"Nebraska Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":473729,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.12092","text":"Publisher Index Page"},{"id":274251,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":274250,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/1365-2664.12092"}],"volume":"50","issue":"3","noUsgsAuthors":false,"publicationDate":"2013-04-29","publicationStatus":"PW","scienceBaseUri":"51cbff56e4b052f2a4539877","contributors":{"authors":[{"text":"Angeler, David G.","contributorId":25027,"corporation":false,"usgs":true,"family":"Angeler","given":"David G.","affiliations":[],"preferred":false,"id":478742,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":478740,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Richard K.","contributorId":21810,"corporation":false,"usgs":true,"family":"Johnson","given":"Richard","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":478741,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70045753,"text":"70045753 - 2013 - The relative contribution of methanotrophs to microbial communities and carbon cycling in soil overlying a coal-bed methane seep","interactions":[],"lastModifiedDate":"2013-06-26T11:45:13","indexId":"70045753","displayToPublicDate":"2013-06-26T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1619,"text":"FEMS Microbiology Ecology","onlineIssn":"1574-6941","printIssn":"0168-6496","active":true,"publicationSubtype":{"id":10}},"title":"The relative contribution of methanotrophs to microbial communities and carbon cycling in soil overlying a coal-bed methane seep","docAbstract":"Seepage of coal-bed methane (CBM) through soils is a potential source of atmospheric CH<sub>4</sub> and also a likely source of ancient (i.e. <sup>14</sup>C-dead) carbon to soil microbial communities. Natural abundance <sup>13</sup>C and <sup>14</sup>C compositions of bacterial membrane phospholipid fatty acids (PLFAs) and soil gas CO<sub>2</sub> and CH<sub>4</sub> were used to assess the incorporation of CBM-derived carbon into methanotrophs and other members of the soil microbial community. Concentrations of type I and type II methanotroph PLFA biomarkers (16:1ω8c and 18:1ω8c, respectively) were elevated in CBM-impacted soils compared with a control site. Comparison of PLFA and 16s rDNA data suggested type I and II methanotroph populations were well estimated and overestimated by their PLFA biomarkers, respectively. The δ<sup>13</sup>C values of PLFAs common in type I and II methanotrophs were as negative as −67‰ and consistent with the assimilation of CBM. PLFAs more indicative of nonmethanotrophic bacteria had δ<sup>13</sup>C values that were intermediate indicating assimilation of both plant- and CBM-derived carbon. Δ<sup>14</sup>C values of select PLFAs (−351 to −936‰) indicated similar patterns of CBM assimilation by methanotrophs and nonmethanotrophs and were used to estimate that 35–91% of carbon assimilated by nonmethanotrophs was derived from CBM depending on time of sampling and soil depth.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"FEMS Microbiology Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/1574-6941.12079","usgsCitation":"Mills, C., Slater, G.F., Dias, R.F., Carr, S.A., Reddy, C., Schmidt, R., and Mandernack, K.W., 2013, The relative contribution of methanotrophs to microbial communities and carbon cycling in soil overlying a coal-bed methane seep: FEMS Microbiology Ecology, v. 84, no. 3, p. 474-494, https://doi.org/10.1111/1574-6941.12079.","productDescription":"21 p.","startPage":"474","endPage":"494","ipdsId":"IP-042235","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":274255,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":274254,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/1574-6941.12079"}],"volume":"84","issue":"3","noUsgsAuthors":false,"publicationDate":"2013-02-19","publicationStatus":"PW","scienceBaseUri":"51cbff58e4b052f2a453988f","contributors":{"authors":[{"text":"Mills, Christopher T. 0000-0001-8414-1414","orcid":"https://orcid.org/0000-0001-8414-1414","contributorId":93308,"corporation":false,"usgs":true,"family":"Mills","given":"Christopher T.","affiliations":[],"preferred":false,"id":478286,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Slater, Gregory F.","contributorId":108010,"corporation":false,"usgs":true,"family":"Slater","given":"Gregory","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":478288,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dias, Robert F. rfdias@usgs.gov","contributorId":3746,"corporation":false,"usgs":true,"family":"Dias","given":"Robert","email":"rfdias@usgs.gov","middleInitial":"F.","affiliations":[],"preferred":true,"id":478282,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carr, Stephanie A.","contributorId":8752,"corporation":false,"usgs":true,"family":"Carr","given":"Stephanie","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":478283,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reddy, Christopher M.","contributorId":103164,"corporation":false,"usgs":true,"family":"Reddy","given":"Christopher M.","affiliations":[],"preferred":false,"id":478287,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schmidt, Raleigh","contributorId":85306,"corporation":false,"usgs":true,"family":"Schmidt","given":"Raleigh","email":"","affiliations":[],"preferred":false,"id":478285,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mandernack, Kevin W.","contributorId":43258,"corporation":false,"usgs":true,"family":"Mandernack","given":"Kevin","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":478284,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
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