{"pageNumber":"599","pageRowStart":"14950","pageSize":"25","recordCount":46883,"records":[{"id":70147945,"text":"70147945 - 2013 - Sampling efficiency of the Moore egg collector","interactions":[],"lastModifiedDate":"2015-05-11T10:35:37","indexId":"70147945","displayToPublicDate":"2013-01-09T11:45:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Sampling efficiency of the Moore egg collector","docAbstract":"<p>Quantitative studies focusing on the collection of semibuoyant fish eggs, which are associated with a pelagic broadcast-spawning reproductive strategy, are often conducted to evaluate reproductive success. Many of the fishes in this reproductive guild have suffered significant reductions in range and abundance. However, the efficiency of the sampling gear used to evaluate reproduction is often unknown and renders interpretation of the data from these studies difficult. Our objective was to assess the efficiency of a modified Moore egg collector (MEC) using field and laboratory trials. Gear efficiency was assessed by releasing a known quantity of gellan beads with a specific gravity similar to that of eggs from representatives of this reproductive guild (e.g., the Arkansas River Shiner Notropis girardi) into an outdoor flume and recording recaptures. We also used field trials to determine how discharge and release location influenced gear efficiency given current methodological approaches. The flume trials indicated that gear efficiency ranged between 0.0% and 9.5% (n = 57) in a simple 1.83-m-wide channel and was positively related to discharge. Efficiency in the field trials was lower, ranging between 0.0% and 3.6%, and was negatively related to bead release distance from the MEC and discharge. The flume trials indicated that the gellan beads were not distributed uniformly across the channel, although aggregation was reduced at higher discharges. This clustering of passively drifting particles should be considered when selecting placement sites for an MEC; further, the use of multiple devices may be warranted in channels with multiple areas of concentrated flow.</p>","language":"English","publisher":"American Fisheries Society","publisherLocation":"Lawrence, KS","doi":"10.1080/02755947.2012.741557","usgsCitation":"Worthington, T.A., Brewer, S.K., Grabowski, T.B., and Mueller, J., 2013, Sampling efficiency of the Moore egg collector: North American Journal of Fisheries Management, v. 33, no. 1, p. 79-88, https://doi.org/10.1080/02755947.2012.741557.","productDescription":"10 p.","startPage":"79","endPage":"88","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-039684","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":300274,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"1","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2013-01-09","publicationStatus":"PW","scienceBaseUri":"5551d2b8e4b0a92fa7e93c0b","contributors":{"authors":[{"text":"Worthington, Thomas A.","contributorId":140662,"corporation":false,"usgs":false,"family":"Worthington","given":"Thomas","email":"","middleInitial":"A.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":546577,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":546474,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grabowski, Timothy B. 0000-0001-9763-8948 tgrabowski@usgs.gov","orcid":"https://orcid.org/0000-0001-9763-8948","contributorId":4178,"corporation":false,"usgs":true,"family":"Grabowski","given":"Timothy","email":"tgrabowski@usgs.gov","middleInitial":"B.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":546578,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mueller, Julia","contributorId":140663,"corporation":false,"usgs":false,"family":"Mueller","given":"Julia","affiliations":[],"preferred":false,"id":546579,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70042497,"text":"sir20125265 - 2013 - Summary and interpretation of discrete and continuous water-quality monitoring data, Mattawoman Creek, Charles County, Maryland, 2000-11","interactions":[],"lastModifiedDate":"2023-03-10T12:37:02.469065","indexId":"sir20125265","displayToPublicDate":"2013-01-09T00:00:00","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":"2012-5265","title":"Summary and interpretation of discrete and continuous water-quality monitoring data, Mattawoman Creek, Charles County, Maryland, 2000-11","docAbstract":"Discrete samples and continuous (15-minute interval) water-quality data were collected at Mattawoman Creek (U.S. Geological Survey station number 01658000) from October 2000 through January 2011, in cooperation with the Charles County (Maryland) Department of Planning and Growth Management, the Maryland Department of the Environment, and the Maryland Geological Survey. Mattawoman Creek is a fourth-order Maryland tributary to the tidal freshwater Potomac River; the creek’s watershed is experiencing development pressure due to its proximity to Washington, D.C. Data were analyzed for the purpose of describing ambient water quality, identifying potential contaminant sources, and quantifying nutrient and sediment loads to the tidal freshwater Mattawoman estuary. Continuous data, collected at 15-minute intervals, included discharge, derived from stage measurements made using a pressure transducer, as well as water temperature, pH, specific conductance, dissolved oxygen, and turbidity, all measured using a water-quality sonde. In addition to the continuous data, a total of 360 discrete water-quality samples, representative of monthly low-flow and targeted storm conditions, were analyzed for suspended sediment and nutrients. Continuous observations gathered by a second water-quality sonde, which was temporarily deployed in 2011 for quality-control purposes, indicated substantial lateral water-quality gradients due to inflow from a nearby tributary, representing about 10 percent of the total gaged area upstream of the sampling location. These lateral gradients introduced a time-varying bias into both the continuous and discrete data, resulting in observations that were at some times representative of water-quality conditions in the main channel and at other times biased towards conditions in the tributary. Despite this limitation, both the continuous and discrete data provided insight into the watershed-scale factors that influence water quality in Mattawoman Creek. Annual precipitation over the study period was representative of the long-term record for southern Maryland. The median value of continuously measured discharge was 25 cubic feet per second (ft<sup>3</sup>/s), and the maximum observed value was 3,210 ft<sup>3</sup>/s; there were 498 days, or about 15 percent of the study period, when flow was zero or too low to measure. Continuously measured water temperature followed a seasonal trend characteristic of the geographic setting; the trend in dissolved oxygen was inverted relative to temperature, and reflected nearly saturated conditions year round. Relations between discharge and both pH and specific conductance indicate that stream water can be conceptualized as a mixture of acidic, dilute precipitation with pH-neutral groundwater of higher conductance. Specific conductance data showed a pronounced winter peak in both median and extreme measurements, indicating the influence of road salt. However, this influence is minor relative to that observed in the Northeast Branch Anacostia River (U.S. Geological Survey station number 01649500), a nearby, more heavily urbanized comparison basin. The median suspended-sediment concentration in discrete samples was 24 milligrams per liter (mg/L), with minimum and maximum concentrations of 1 mg/L and 2,890 mg/L, respectively. Total nitrogen ranged from 0.21 mg/L to 4.09 mg/L, with a median of 0.69 mg/L; total phosphorus ranged from less than 0.01 mg/L to 0.98 mg/L, with a median of 0.07 mg/L. Total nitrogen was dominated by the dissolved organic fraction (49 percent based on median species concentrations); total phosphorus was predominantly particulate (70 percent). Seasonal trends in suspended-sediment concentration indicate a supply subsidy in late winter and spring; this could be linked to flood-plain interaction, mobilization of sediment from the channel or banks, or anthropogenic input. Seasonal trends for both total phosphorus and total nitrogen generally corresponded to seasonal trends for suspended sediment, indicating a common underlying physical control, likely acting in synchrony with seasonal biological controls on total nutrient concentrations. Speciation of phosphorus, including proportional concentration of the biologically available dissolved inorganic fraction, did not vary seasonally. The speciation of nitrogen reflected demand for inorganic nitrogen and associated transformation into organic nitrogen during the growing season. Stepwise regression models were developed, using continuous data corresponding to collection times for discrete samples as candidate surrogates for suspended sediment, total phosphorus, and total nitrogen. Turbidity and discharge were both included in the model for suspended sediment (R<sup>2</sup> = 0.76, n = 185); only turbidity was selected as a robust predictor of total phosphorus and nitrogen (R<sup>2</sup> = 0.68 and 0.61, respectively, n = 186 for both). Loads of sediment and nutrients to the downstream Mattawoman estuary were computed using the U.S. Geological Survey computer program LOADEST. Load estimation included comparison of a routinely applied seven-parameter regression model based on time, season, and discharge, with an eight-parameter model that also includes turbidity. Adding turbidity decreased total load estimates, based on hourly data for a fixed 2-month period, by 21, 8, and 3 percent for suspended sediment, total phosphorus, and total nitrogen, respectively, in addition to decreasing the standard error of prediction for all three constituents. The seasonal pattern in specific conductance, reflecting road salt application, is the strongest evidence of the effect of upstream development on water quality at Mattawoman Creek. Accordingly, ongoing continuous monitoring for trends in specific conductance would be the most reliable means of detecting further degradation associated with increased development.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125265","collaboration":"Prepared in cooperation with the Charles County Department of Planning and Growth Management; Maryland Department of the Environment; Maryland Geological Survey","usgsCitation":"Chanat, J.G., Miller, C.V., Bell, J.M., Majedi, B.F., and Brower, D.P., 2013, Summary and interpretation of discrete and continuous water-quality monitoring data, Mattawoman Creek, Charles County, Maryland, 2000-11: U.S. Geological Survey Scientific Investigations Report 2012-5265, vii, 42 p., https://doi.org/10.3133/sir20125265.","productDescription":"vii, 42 p.","startPage":"i","endPage":"42","numberOfPages":"54","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2000-10-01","temporalEnd":"2011-01-31","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"links":[{"id":265497,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5265.gif"},{"id":265498,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5265/"},{"id":265499,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5265/pdf/sir2012-5265.pdf"}],"state":"Maryl","city":"Charles County","otherGeospatial":"Mattawoman Creek","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -77.3155,38.1713 ], [ -77.3155,38.7047 ], [ -76.6719,38.7047 ], [ -76.6719,38.1713 ], [ -77.3155,38.1713 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50ee9177e4b0160a2d0ee34b","contributors":{"authors":[{"text":"Chanat, Jeffrey G. 0000-0002-3629-7307 jchanat@usgs.gov","orcid":"https://orcid.org/0000-0002-3629-7307","contributorId":5062,"corporation":false,"usgs":true,"family":"Chanat","given":"Jeffrey","email":"jchanat@usgs.gov","middleInitial":"G.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":471653,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Cherie V. 0000-0001-7765-5919 cvmiller@usgs.gov","orcid":"https://orcid.org/0000-0001-7765-5919","contributorId":863,"corporation":false,"usgs":true,"family":"Miller","given":"Cherie","email":"cvmiller@usgs.gov","middleInitial":"V.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":471651,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bell, Joseph M. 0000-0002-2536-2070 jmbell@usgs.gov","orcid":"https://orcid.org/0000-0002-2536-2070","contributorId":5063,"corporation":false,"usgs":true,"family":"Bell","given":"Joseph","email":"jmbell@usgs.gov","middleInitial":"M.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":471654,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Majedi, Brenda Feit","contributorId":81361,"corporation":false,"usgs":true,"family":"Majedi","given":"Brenda","email":"","middleInitial":"Feit","affiliations":[],"preferred":false,"id":471655,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brower, David P. dpbrower@usgs.gov","contributorId":5061,"corporation":false,"usgs":true,"family":"Brower","given":"David","email":"dpbrower@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":471652,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70042440,"text":"70042440 - 2013 - Accuracy assessment of NLCD 2006 land cover and impervious surface","interactions":[],"lastModifiedDate":"2013-01-09T10:23:55","indexId":"70042440","displayToPublicDate":"2013-01-09T00:00:00","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":"Accuracy assessment of NLCD 2006 land cover and impervious surface","docAbstract":"Release of NLCD 2006 provides the first wall-to-wall land-cover change database for the conterminous United States from Landsat Thematic Mapper (TM) data. Accuracy assessment of NLCD 2006 focused on four primary products: 2001 land cover, 2006 land cover, land-cover change between 2001 and 2006, and impervious surface change between 2001 and 2006. The accuracy assessment was conducted by selecting a stratified random sample of pixels with the reference classification interpreted from multi-temporal high resolution digital imagery. The NLCD Level II (16 classes) overall accuracies for the 2001 and 2006 land cover were 79% and 78%, respectively, with Level II user's accuracies exceeding 80% for water, high density urban, all upland forest classes, shrubland, and cropland for both dates. Level I (8 classes) accuracies were 85% for NLCD 2001 and 84% for NLCD 2006. The high overall and user's accuracies for the individual dates translated into high user's accuracies for the 2001–2006 change reporting themes water gain and loss, forest loss, urban gain, and the no-change reporting themes for water, urban, forest, and agriculture. The main factor limiting higher accuracies for the change reporting themes appeared to be difficulty in distinguishing the context of grass. We discuss the need for more research on land-cover change accuracy assessment.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Remote Sensing of Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.rse.2012.12.001","usgsCitation":"Wickham, J.D., Stehman, S.V., Gass, L., Dewitz, J., Fry, J.A., and Wade, T., 2013, Accuracy assessment of NLCD 2006 land cover and impervious surface: Remote Sensing of Environment, v. 130, p. 294-304, https://doi.org/10.1016/j.rse.2012.12.001.","productDescription":"11 p.","startPage":"294","endPage":"304","ipdsId":"IP-040031","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":265420,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":265419,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2012.12.001"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.8,24.5 ], [ -124.8,49.383333 ], [ -66.95,49.383333 ], [ -66.95,24.5 ], [ -124.8,24.5 ] ] ] } } ] }","volume":"130","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50ee916de4b0160a2d0ee327","chorus":{"doi":"10.1016/j.rse.2012.12.001","url":"http://dx.doi.org/10.1016/j.rse.2012.12.001","publisher":"Elsevier BV","authors":"Wickham James D., Stehman Stephen V., Gass Leila, Dewitz Jon, Fry Joyce A., Wade Timothy G.","journalName":"Remote Sensing of Environment","publicationDate":"3/2013"},"contributors":{"authors":[{"text":"Wickham, James D.","contributorId":72278,"corporation":false,"usgs":false,"family":"Wickham","given":"James","email":"","middleInitial":"D.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":471534,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stehman, Stephen V.","contributorId":77283,"corporation":false,"usgs":true,"family":"Stehman","given":"Stephen","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":471535,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gass, Leila 0000-0002-3436-262X lgass@usgs.gov","orcid":"https://orcid.org/0000-0002-3436-262X","contributorId":3770,"corporation":false,"usgs":true,"family":"Gass","given":"Leila","email":"lgass@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":471531,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dewitz, Jon 0000-0002-0458-212X dewitz@usgs.gov","orcid":"https://orcid.org/0000-0002-0458-212X","contributorId":2401,"corporation":false,"usgs":true,"family":"Dewitz","given":"Jon","email":"dewitz@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":471530,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fry, Joyce A. 0000-0002-8466-9582","orcid":"https://orcid.org/0000-0002-8466-9582","contributorId":69293,"corporation":false,"usgs":true,"family":"Fry","given":"Joyce","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":471533,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wade, Timothy G.","contributorId":48845,"corporation":false,"usgs":true,"family":"Wade","given":"Timothy G.","affiliations":[],"preferred":false,"id":471532,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70042412,"text":"ofr20061210 - 2013 - Final report and archive of the swath bathymetry and ancillary data collected in the Puerto Rico Trench region in 2002 and 2003","interactions":[],"lastModifiedDate":"2017-11-18T12:01:51","indexId":"ofr20061210","displayToPublicDate":"2013-01-07T00:00:00","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":"2006-1210","title":"Final report and archive of the swath bathymetry and ancillary data collected in the Puerto Rico Trench region in 2002 and 2003","docAbstract":"In 2002 and 2003, the U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA), conducted three exploration cruises that mapped for the first time the morphology of the entire tectonic plate boundary stretching from the Dominican Republic in the west to the Lesser Antilles in the east, a distance of approximately 700 kilometers (430 miles). Observations from these three exploration cruises, coupled with computer modeling and published Global Positioning System (GPS) results and earthquake focal mechanisms, have provided new information that is changing the evaluation of the seismic and tsunami hazard from this plate boundary. The observations collected during these cruises also contributed to the basic understanding of the mechanisms that govern plate tectonics, in this case, the creation of the island of Puerto Rico and the deep trench north of it. Results of the sea floor mapping have been an important component of the study of tsunami and earthquake hazards to the northeastern Caribbean and the U.S. Atlantic coast off the United States.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20061210","usgsCitation":"ten Brink, U., Danforth, W.W., and Polloni, C.F., 2013, Final report and archive of the swath bathymetry and ancillary data collected in the Puerto Rico Trench region in 2002 and 2003: U.S. Geological Survey Open-File Report 2006-1210, HTML Document, https://doi.org/10.3133/ofr20061210.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2002-01-01","temporalEnd":"2003-12-31","costCenters":[{"id":680,"text":"Woods Hole Science Center","active":false,"usgs":true}],"links":[{"id":265368,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2006_1210.jpg"},{"id":265366,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2006/1210/"},{"id":265367,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2006/1210/title_page.html"}],"country":"United States","otherGeospatial":"Puerto Rico","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -70.25,17.88 ], [ -70.25,22.03 ], [ -59.4,22.03 ], [ -59.4,17.88 ], [ -70.25,17.88 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50ebee63e4b07f1501afcfac","contributors":{"authors":[{"text":"ten Brink, Uri S. 0000-0001-6858-3001 utenbrink@usgs.gov","orcid":"https://orcid.org/0000-0001-6858-3001","contributorId":127560,"corporation":false,"usgs":true,"family":"ten Brink","given":"Uri S.","email":"utenbrink@usgs.gov","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":471490,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Danforth, William W. 0000-0002-6382-9487 bdanforth@usgs.gov","orcid":"https://orcid.org/0000-0002-6382-9487","contributorId":3292,"corporation":false,"usgs":true,"family":"Danforth","given":"William","email":"bdanforth@usgs.gov","middleInitial":"W.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":471489,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Polloni, Christopher F.","contributorId":93087,"corporation":false,"usgs":true,"family":"Polloni","given":"Christopher","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":471491,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70192405,"text":"70192405 - 2013 - Predicting thermal reference conditions for USA streams and rivers","interactions":[],"lastModifiedDate":"2017-10-26T13:31:18","indexId":"70192405","displayToPublicDate":"2013-01-07T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Predicting thermal reference conditions for USA streams and rivers","docAbstract":"<p>Temperature is a primary driver of the structure and function of stream ecosystems. However, the lack of stream temperature (ST) data for the vast majority of streams and rivers severely compromises our ability to describe patterns of thermal variation among streams, test hypotheses regarding the effects of temperature on macroecological patterns, and assess the effects of altered STs on ecological resources. Our goal was to develop empirical models that could: 1) quantify the effects of stream and watershed alteration (SWA) on STs, and 2) accurately and precisely predict natural (i.e., reference condition) STs in conterminous USA streams and rivers. We modeled 3 ecologically important elements of the thermal regime: mean summer, mean winter, and mean annual ST. To build reference-condition models (RCMs), we used daily mean ST data obtained from several thousand US Geological Survey temperature sites distributed across the conterminous USA and iteratively modeled ST with Random Forests to identify sites in reference condition. We first created a set of dirty models (DMs) that related STs to both natural factors (e.g., climate, watershed area, topography) and measures of SWA, i.e., reservoirs, urbanization, and agriculture. The 3 models performed well (r<sup>2</sup> = 0.84–0.94, residual mean square error [RMSE] = 1.2–2.0<span>°</span>C). For each DM, we used partial dependence plots to identify SWA thresholds below which response in ST was minimal. We then used data from only the sites with upstream SWA below these thresholds to build RCMs with only natural factors as predictors (r<sup>2</sup> = 0.87–0.95, RMSE = 1.1–1.9<span>°</span>C). Use of only reference-quality sites caused RCMs to suffer modest loss of predictor space and spatial coverage, but this loss was associated with parts of ST response curves that were flat and, therefore, not responsive to further variation in predictor space. We then compared predictions made with the RCMs to predictions made with the DMs with SWA set to 0. For most DMs, setting SWAs to 0 resulted in biased estimates of thermal reference condition.</p>","language":"English","publisher":"University of Chicago Press","doi":"10.1899/12-009.1","usgsCitation":"Hill, R.A., Hawkins, C.P., and Carlisle, D.M., 2013, Predicting thermal reference conditions for USA streams and rivers: Freshwater Science, v. 32, no. 1, p. 39-55, https://doi.org/10.1899/12-009.1.","productDescription":"17 p.","startPage":"39","endPage":"55","ipdsId":"IP-039780","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":473978,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.bioone.org/doi/10.1899/12-009.1","text":"External Repository"},{"id":347475,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a07ef3de4b09af898c8cd84","contributors":{"authors":[{"text":"Hill, Ryan A.","contributorId":198332,"corporation":false,"usgs":false,"family":"Hill","given":"Ryan","email":"","middleInitial":"A.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":715712,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hawkins, Charles P.","contributorId":198331,"corporation":false,"usgs":false,"family":"Hawkins","given":"Charles","email":"","middleInitial":"P.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":715711,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carlisle, Daren M. 0000-0002-7367-348X dcarlisle@usgs.gov","orcid":"https://orcid.org/0000-0002-7367-348X","contributorId":513,"corporation":false,"usgs":true,"family":"Carlisle","given":"Daren","email":"dcarlisle@usgs.gov","middleInitial":"M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":715710,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70042380,"text":"tm7C9 - 2013 - Approaches in highly parameterized inversion: bgaPEST, a Bayesian geostatistical approach implementation with PEST: documentation and instructions","interactions":[],"lastModifiedDate":"2013-01-06T13:04:47","indexId":"tm7C9","displayToPublicDate":"2013-01-06T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"7-C9","title":"Approaches in highly parameterized inversion: bgaPEST, a Bayesian geostatistical approach implementation with PEST: documentation and instructions","docAbstract":"The application bgaPEST is a highly parameterized inversion software package implementing the Bayesian Geostatistical Approach in a framework compatible with the parameter estimation suite PEST. Highly parameterized inversion refers to cases in which parameters are distributed in space or time and are correlated with one another. The Bayesian aspect of bgaPEST is related to Bayesian probability theory in which prior information about parameters is formally revised on the basis of the calibration dataset used for the inversion. Conceptually, this approach formalizes the conditionality of estimated parameters on the specific data and model available. The geostatistical component of the method refers to the way in which prior information about the parameters is used. A geostatistical autocorrelation function is used to enforce structure on the parameters to avoid overfitting and unrealistic results. Bayesian Geostatistical Approach is designed to provide the smoothest solution that is consistent with the data. Optionally, users can specify a level of fit or estimate a balance between fit and model complexity informed by the data. Groundwater and surface-water applications are used as examples in this text, but the possible uses of bgaPEST extend to any distributed parameter applications.","largerWorkTitle":"Automated Data Processing and Computations (Book 7)","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm7C9","collaboration":"Groundwater Resources Program and Global Change Research and Development. This report is Chapter 9 of Section C, Computer programs, in Book 7, Automated Data Processing and Computations.","usgsCitation":"Fienen, M., D'Oria, M., Doherty, J.E., and Hunt, R.J., 2013, Approaches in highly parameterized inversion: bgaPEST, a Bayesian geostatistical approach implementation with PEST: documentation and instructions: U.S. Geological Survey Techniques and Methods 7-C9, Report: vi, 86 p.; Software; Development GIT Repository, https://doi.org/10.3133/tm7C9.","productDescription":"Report: vi, 86 p.; Software; Development GIT Repository","numberOfPages":"96","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":265307,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm_7_C9.gif"},{"id":265304,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/07/c09/"},{"id":265305,"type":{"id":4,"text":"Application Site"},"url":"https://pubs.usgs.gov/tm/07/c09/Downloads"},{"id":265306,"type":{"id":7,"text":"Companion Files"},"url":"https://github.com/mnfienen-usgs/bgaPEST"},{"id":265308,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/07/c09/pdf/TM7-C9.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50ea9ce2e4b02dd6076fad83","contributors":{"authors":[{"text":"Fienen, Michael N. 0000-0002-7756-4651 mnfienen@usgs.gov","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":893,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","email":"mnfienen@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":471424,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"D'Oria, Marco","contributorId":24253,"corporation":false,"usgs":true,"family":"D'Oria","given":"Marco","affiliations":[],"preferred":false,"id":471427,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Doherty, John E.","contributorId":8817,"corporation":false,"usgs":false,"family":"Doherty","given":"John","email":"","middleInitial":"E.","affiliations":[{"id":7046,"text":"Watermark Numerical Computing","active":true,"usgs":false}],"preferred":false,"id":471426,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hunt, Randall J. 0000-0001-6465-9304 rjhunt@usgs.gov","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":1129,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall","email":"rjhunt@usgs.gov","middleInitial":"J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":471425,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70042378,"text":"sir20125217 - 2013 - Effects of best-management practices in Bower Creek in the East River priority watershed, Wisconsin, 1991-2009","interactions":[],"lastModifiedDate":"2013-01-06T12:06:52","indexId":"sir20125217","displayToPublicDate":"2013-01-05T00:00:00","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":"2012-5217","title":"Effects of best-management practices in Bower Creek in the East River priority watershed, Wisconsin, 1991-2009","docAbstract":"Hydrologic and water-quality data were collected at Bower Creek during the periods before best-management practices (BMPs), and after BMPs were installed for evaluation of water-quality improvements. The monitoring was done between 1990 and 2009 with the pre-BMP period ending in July 1994 and the post-BMP period beginning in October 2006. BMPs installed in this basin included streambank protection and fencing, stream crossings, grade stabilization, buffer strips, various barnyard-runoff controls, nutrient management, and a low degree of upland BMPs. Water-quality evaluations included base-flow concentrations and storm loads for total suspended solids, total phosphorus, and ammonia nitrogen. The only reductions detected between the base-flow samples of the pre- and post-BMP periods were in median concentrations of total phosphorus from base-flow samples, but not for total suspended solids or dissolved ammonia nitrogen. Differences in storm loads for the three water-quality constituents monitored were not observed during the study period.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125217","collaboration":"Prepared in cooperation with the Wisconsin Department of Natural Resources","usgsCitation":"Corsi, S., Horwatich, J.A., Rutter, T.D., and Bannerman, R.T., 2013, Effects of best-management practices in Bower Creek in the East River priority watershed, Wisconsin, 1991-2009: U.S. Geological Survey Scientific Investigations Report 2012-5217, viii, 21 p., https://doi.org/10.3133/sir20125217.","productDescription":"viii, 21 p.","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1990-01-01","temporalEnd":"2009-12-31","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":265296,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5217.gif"},{"id":265294,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5217/"},{"id":265295,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5217/pdf/sir2012-5217_508.pdf"}],"scale":"24000","country":"United States","state":"Wisconsin","county":"Brown","city":"Bellevue;De Pere;Green Leaf;Morrison","otherGeospatial":"Bower Creek","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.016667,44.341667 ], [ -88.016667,44.433333 ], [ -87.925,44.433333 ], [ -87.925,44.341667 ], [ -88.016667,44.341667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50eaab77e4b02dd6076fada3","contributors":{"authors":[{"text":"Corsi, Steven R. srcorsi@usgs.gov","contributorId":511,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven R.","email":"srcorsi@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":471416,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Horwatich, Judy A. 0000-0003-0582-0836 jahorwat@usgs.gov","orcid":"https://orcid.org/0000-0003-0582-0836","contributorId":1388,"corporation":false,"usgs":true,"family":"Horwatich","given":"Judy","email":"jahorwat@usgs.gov","middleInitial":"A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":471417,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rutter, Troy D. 0000-0001-5130-204X tdrutter@usgs.gov","orcid":"https://orcid.org/0000-0001-5130-204X","contributorId":2081,"corporation":false,"usgs":true,"family":"Rutter","given":"Troy","email":"tdrutter@usgs.gov","middleInitial":"D.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":471418,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bannerman, Roger T. 0000-0001-9221-2905 rbannerman@usgs.gov","orcid":"https://orcid.org/0000-0001-9221-2905","contributorId":5560,"corporation":false,"usgs":true,"family":"Bannerman","given":"Roger","email":"rbannerman@usgs.gov","middleInitial":"T.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":471419,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70042371,"text":"ofr20121271 - 2013 - An automated digital imaging system for environmental monitoring applications","interactions":[],"lastModifiedDate":"2013-01-04T14:48:12","indexId":"ofr20121271","displayToPublicDate":"2013-01-04T00:00:00","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":"2012-1271","title":"An automated digital imaging system for environmental monitoring applications","docAbstract":"Recent improvements in the affordability and availability of high-resolution digital cameras, data loggers, embedded computers, and radio/cellular modems have advanced the development of sophisticated automated systems for remote imaging. Researchers have successfully placed and operated automated digital cameras in remote locations and in extremes of temperature and humidity, ranging from the islands of the South Pacific to the Mojave Desert and the Grand Canyon. With the integration of environmental sensors, these automated systems are able to respond to local conditions and modify their imaging regimes as needed. In this report we describe in detail the design of one type of automated imaging system developed by our group. It is easily replicated, low-cost, highly robust, and is a stand-alone automated camera designed to be placed in remote locations, without wireless connectivity.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121271","usgsCitation":"Bogle, R., Velasco, M., and Vogel, J., 2013, An automated digital imaging system for environmental monitoring applications: U.S. Geological Survey Open-File Report 2012-1271, vi, 18 p., https://doi.org/10.3133/ofr20121271.","productDescription":"vi, 18 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":265280,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1271.gif"},{"id":265278,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1271/"},{"id":265279,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1271/of2012-1271.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e7f9e2e4b033ce2d2433e5","contributors":{"authors":[{"text":"Bogle, Rian rbogle@usgs.gov","contributorId":81378,"corporation":false,"usgs":true,"family":"Bogle","given":"Rian","email":"rbogle@usgs.gov","affiliations":[],"preferred":false,"id":471399,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Velasco, Miguel","contributorId":50214,"corporation":false,"usgs":true,"family":"Velasco","given":"Miguel","affiliations":[],"preferred":false,"id":471398,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vogel, John","contributorId":99825,"corporation":false,"usgs":true,"family":"Vogel","given":"John","affiliations":[],"preferred":false,"id":471400,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70042297,"text":"70042297 - 2013 - Distribution and environmental persistence of the causative agent of white-nose syndrome, <i>Geomyces destructans</i>, in bat hibernacula of the eastern United States","interactions":[],"lastModifiedDate":"2018-01-24T13:39:00","indexId":"70042297","displayToPublicDate":"2013-01-03T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":850,"text":"Applied and Environmental Microbiology","active":true,"publicationSubtype":{"id":10}},"title":"Distribution and environmental persistence of the causative agent of white-nose syndrome, <i>Geomyces destructans</i>, in bat hibernacula of the eastern United States","docAbstract":"<p>White-nose syndrome (WNS) is an emerging disease of hibernating bats caused by the recently described fungus <i>Geomyces destructans</i>. First isolated in 2008, the origins of this fungus in North America and its ability to persist in the environment remain undefined. To investigate the correlation between manifestation of WNS and distribution of <i>G. destructans</i> in the U.S., we analyzed sediment samples collected from 55 bat hibernacula (caves and mines) both within and outside the known range of WNS using a newly developed real-time PCR assay. <i>Geomyces destructans</i> was detected in 17 of 21 sites within the known range of WNS at the time the samples were collected; the fungus was not found in 28 sites beyond the known range of the disease at the time that environmental samples were collected. These data indicate that distribution of <i>G. destructans</i> is correlated with disease in hibernating bats and support the hypothesis that the fungus is likely an exotic species in North America. Additionally, we examined whether <i>G. destructans</i> persists in infested bat hibernacula when bats are absent. Sediment samples were collected from 14 WNS-positive hibernacula, and the samples were screened for viable fungus using a culture technique. Viable <i>G. destructans</i> was cultivated from 7 of the 14 sites sampled during late summer when bats were no longer in hibernation, suggesting the fungus can persist in the environment in the absence of bat hosts for long periods of time.</p>","language":"English","publisher":"American Society for Microbiology","publisherLocation":"Washington, D.C.","doi":"10.1128/AEM.02939-12","usgsCitation":"Lorch, J.M., Muller, L.K., Russell, R.E., O’Connor, M., Lindner, D.L., and Blehert, D., 2013, Distribution and environmental persistence of the causative agent of white-nose syndrome, <i>Geomyces destructans</i>, in bat hibernacula of the eastern United States: Applied and Environmental Microbiology, v. 79, no. 4, p. 1293-1301, https://doi.org/10.1128/AEM.02939-12.","productDescription":"36 p.","startPage":"1293","endPage":"1301","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-041188","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":473982,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1128/aem.02939-12","text":"External Repository"},{"id":265034,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":265033,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1128/AEM.02939-12"}],"country":"United 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,{"id":70049004,"text":"sir20135203 - 2013 - Comparison of water consumption in two riparian vegetation communities along the central Platte River, Nebraska, 2008–09 and 2011","interactions":[],"lastModifiedDate":"2014-01-02T11:46:06","indexId":"sir20135203","displayToPublicDate":"2013-01-02T11:21:11","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":"2013-5203","title":"Comparison of water consumption in two riparian vegetation communities along the central Platte River, Nebraska, 2008–09 and 2011","docAbstract":"The Platte River is a vital natural resource for the people, plants, and animals of Nebraska. A recent study quantified water use by riparian woodlands along central reaches of the Platte River, Nebraska, finding that water use was mainly regulated below maximum predicted levels. A comparative study was launched through a cooperative partnership between the U.S. Geological Survey, the Central Platte Natural Resources District, the Nebraska Department of Natural Resources, and the Nebraska Environmental Trust to compare water use of a riparian woodland with that of a grazed riparian grassland along the central Platte River. This report describes the results of the 3-year study by the U.S. Geological Survey to measure the evapotranspiration (ET) rates in the two riparian vegetation communities.  Evapotranspiration was measured during 2008–09 and 2011 using the eddy-covariance method at a riparian woodland near Odessa, hereinafter referred to as the “woodland site,” and a riparian grassland pasture near Elm Creek, hereinafter referred to as the “grassland site.” Overall, annual ET totals at the grassland site were 90 percent of the annual ET measured at the woodland site, with averages of 653 millimeters (mm) and 726 mm, respectively. Evapotranspiration rates were similar at the grassland site and the woodland site during the spring and fall seasons, but at the woodland site ET rates were higher than those of the grassland site during the peak-growth summer months of June through August. These seasonal differences and the slightly lower ET rates at the grassland site were likely the result of differing plant communities, disturbance effects related to grazing and flooding, and climatic differences between the sites.  The annual water balance was calculated for each site and indicated that the predominant factors in the water balance at both sites were ET and precipitation. Annual precipitation for the study period ranged from near to above the normal precipitation of 640 mm. Substantial precipitation fell in May and October 2008 that caused flooding along the Platte River in May of this especially wet year. There was a deficit in precipitation compared to ET at both sites in 2009 and 2011, leading to a net groundwater use of greater than 140 mm per year at the woodland site and greater than 55 mm per year at the grassland site. This indicates that the net annual groundwater use or recharge depends predominately upon the relation between ET and precipitation in these riparian areas with shallow soil layers above the groundwater table.  Prior research at the woodland site provided four additional annual water balances dating back to 2002 for comparison with the study period at the woodland site. Perhaps most striking in this comparison was the 25-percent increase in annual ET for 2008–09 and 2011 despite precipitation totals and potential ET rates that were within the range of those measured in 2002–05. As a result, the water balance indicates that groundwater was discharged 2 of the 3 years of the study. This likely was caused by higher groundwater levels and a healthier plant community in 2008–09 and 2011 relative to the drought-affected years of 2002–05. As a result of these changes, the crop coefficients developed for riparian woodlands during the prior research underestimated 2008–09 and 2011 annual ET rates by an average of 35 percent. Though new crop coefficients were developed by this study, the importance of soil-moisture stress and plant community successional dynamics need to be considered when applying these coefficients at other riparian sites or into the future. Nonetheless, their development and the data on which they are based may provide improved understanding of water consumption by riparian grasslands and riparian woodlands along the central Platte River.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135203","collaboration":"Prepared in cooperation with the Central Platte Natural Resources District, the Nebraska Department of Natural Resources, and the Nebraska Environmental Trust","usgsCitation":"Hall, B.M., and Rus, D.L., 2013, Comparison of water consumption in two riparian vegetation communities along the central Platte River, Nebraska, 2008–09 and 2011: U.S. Geological Survey Scientific Investigations Report 2013-5203, Report: vi, 26 p.; Downloads Directory, https://doi.org/10.3133/sir20135203.","productDescription":"Report: vi, 26 p.; Downloads Directory","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-045289","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":280577,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":280572,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5203/"},{"id":280575,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5203/pdf/sir2013-5203.pdf"},{"id":280576,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2013/5203/downloads/"}],"country":"United States","state":"Nebraska","otherGeospatial":"Central Platte River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -100.5,40 ], [ -100.5,41.5 ], [ 98,41.5 ], [ 98,40 ], [ -100.5,40 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd521ee4b0b290850f4577","contributors":{"authors":[{"text":"Hall, Brent M. 0000-0003-3815-5158 bhall@usgs.gov","orcid":"https://orcid.org/0000-0003-3815-5158","contributorId":4547,"corporation":false,"usgs":true,"family":"Hall","given":"Brent","email":"bhall@usgs.gov","middleInitial":"M.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485985,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rus, David L. 0000-0003-3538-7826 dlrus@usgs.gov","orcid":"https://orcid.org/0000-0003-3538-7826","contributorId":881,"corporation":false,"usgs":true,"family":"Rus","given":"David","email":"dlrus@usgs.gov","middleInitial":"L.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485984,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70044662,"text":"70044662 - 2013 - Mississippi River streamflow measurement techniques at St. Louis, Missouri","interactions":[],"lastModifiedDate":"2013-10-28T15:45:07","indexId":"70044662","displayToPublicDate":"2013-01-01T21:59:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2338,"text":"Journal of Hydraulic Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Mississippi River streamflow measurement techniques at St. Louis, Missouri","docAbstract":"Streamflow measurement techniques of the Mississippi River at St. Louis have changed through time (1866–present). In addition to different methods used for discrete streamflow measurements, the density and range of discrete measurements used to define the rating curve (stage versus streamflow) have also changed. Several authors have utilized published water surface elevation (stage) and streamflow data to assess changes in the rating curve, which may be attributed to be caused by flood control and/or navigation structures. The purpose of this paper is to provide a thorough review of the available flow measurement data and techniques and to assess how a strict awareness of the limitations of the data may affect previous analyses. It is concluded that the pre-1930s discrete streamflow measurement data are not of sufficient accuracy to be compared with modern streamflow values in establishing long-term trends of river behavior.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Hydraulic Engineering","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Society of Civil Engineers","doi":"10.1061/(ASCE)HY.1943-7900.0000752","usgsCitation":"Wastson, C.C., Holmes, R.R., and Biedenham, D.S., 2013, Mississippi River streamflow measurement techniques at St. Louis, Missouri: Journal of Hydraulic Engineering, v. 139, no. 10, p. 1062-1070, https://doi.org/10.1061/(ASCE)HY.1943-7900.0000752.","productDescription":"9 p.","startPage":"1062","endPage":"1070","numberOfPages":"9","ipdsId":"IP-044176","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":278492,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278491,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1061/(ASCE)HY.1943-7900.0000752"}],"country":"United States","state":"Missouri","city":"St. Louis","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -90.320515,38.532322 ], [ -90.320515,38.774346 ], [ -90.166721,38.774346 ], [ -90.166721,38.532322 ], [ -90.320515,38.532322 ] ] ] } } ] }","volume":"139","issue":"10","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"526f8779e4b0493c992ecdaa","contributors":{"authors":[{"text":"Wastson, Chester C.","contributorId":102376,"corporation":false,"usgs":true,"family":"Wastson","given":"Chester","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":476188,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holmes, Robert R. Jr. 0000-0002-5060-3999 bholmes@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-3999","contributorId":1624,"corporation":false,"usgs":true,"family":"Holmes","given":"Robert","suffix":"Jr.","email":"bholmes@usgs.gov","middleInitial":"R.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":false,"id":476186,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Biedenham, David S.","contributorId":27782,"corporation":false,"usgs":true,"family":"Biedenham","given":"David","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":476187,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70126204,"text":"70126204 - 2013 - Methylmercury is the predominant form of mercury in bird eggs: a synthesis","interactions":[],"lastModifiedDate":"2017-07-19T15:48:25","indexId":"70126204","displayToPublicDate":"2013-01-01T18:05:24","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Methylmercury is the predominant form of mercury in bird eggs: a synthesis","docAbstract":"Bird eggs are commonly used in mercury monitoring programs to assess methylmercury contamination and toxicity to birds. However, only 6% of >200 studies investigating mercury in bird eggs have actually measured methylmercury concentrations in eggs. Instead, studies typically measure total mercury in eggs (both organic and inorganic forms of mercury), with the explicit assumption that total mercury concentrations in eggs are a reliable proxy for methylmercury concentrations in eggs. This assumption is rarely tested, but has important implications for assessing risk of mercury to birds. We conducted a detailed assessment of this assumption by (1) collecting original data to examine the relationship between total and methylmercury in eggs of two species, and (2) reviewing the published literature on mercury concentrations in bird eggs to examine whether the percentage of total mercury in the methylmercury form differed among species. Within American avocets (<i>Recurvirostra americana</i>) and Forster’s terns (<i>Sterna forsteri</i>), methylmercury concentrations were highly correlated (R<sup>2</sup> = 0.99) with total mercury concentrations in individual eggs (range: 0.03–7.33 μg/g fww), and the regression slope (log scale) was not different from one (m = 0.992). The mean percentage of total mercury in the methylmercury form in eggs was 97% for American avocets (n = 30 eggs), 96% for Forster’s terns (n = 30 eggs), and 96% among all 22 species of birds (n = 30 estimates of species means). The percentage of total mercury in the methylmercury form ranged from 63% to 116% among individual eggs and 82% to 111% among species means, but this variation was not related to total mercury concentrations in eggs, foraging guild, nor to a species life history strategy as characterized along the precocial to altricial spectrum. Our results support the use of total mercury concentrations to estimate methylmercury concentrations in bird eggs.","language":"English","publisher":"American Chemical Society","doi":"10.1021/es304385y","usgsCitation":"Ackerman, J., Herzog, M., and Schwarzbach, S.E., 2013, Methylmercury is the predominant form of mercury in bird eggs: a synthesis: Environmental Science & Technology, v. 47, no. 4, p. 2052-2060, https://doi.org/10.1021/es304385y.","productDescription":"9 p.","startPage":"2052","endPage":"2060","numberOfPages":"9","ipdsId":"IP-043304","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":294255,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294225,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/es304385y"}],"volume":"47","issue":"4","noUsgsAuthors":false,"publicationDate":"2013-01-31","publicationStatus":"PW","scienceBaseUri":"541d459fe4b0f68901ec30ca","contributors":{"authors":[{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":501921,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Herzog, Mark P. mherzog@usgs.gov","contributorId":3965,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark P.","email":"mherzog@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":501920,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schwarzbach, Steven E. steven_schwarzbach@usgs.gov","contributorId":1025,"corporation":false,"usgs":true,"family":"Schwarzbach","given":"Steven","email":"steven_schwarzbach@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":501919,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70047211,"text":"70047211 - 2013 - A support system for assessing local vulnerability to weather and climate","interactions":[],"lastModifiedDate":"2019-06-04T08:55:18","indexId":"70047211","displayToPublicDate":"2013-01-01T16:45:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2822,"text":"Natural Hazards","active":true,"publicationSubtype":{"id":10}},"title":"A support system for assessing local vulnerability to weather and climate","docAbstract":"<p>The changing number and nature of weather- and climate-related natural hazards is causing more communities to need to assess their vulnerabilities. Vulnerability assessments, however, often require considerable expertise and resources that are not available or too expensive for many communities. To meet the need for an easy-to-use, cost-effective vulnerability assessment tool for communities, a prototype online vulnerability assessment support system was built and tested. This prototype tool guides users through a stakeholder-based vulnerability assessment that breaks the process into four easy-to-implement steps. Data sources are integrated in the online environment so that perceived risks—defined and prioritized qualitatively by users—can be compared and discussed against the impacts that past events have had on the community. The support system is limited in scope, and the locations of the case studies do not provide a sufficiently broad range of sample cases. The addition of more publicly available hazard databases combined with future improvements in the support system architecture and software will expand opportunities for testing and fully implementing the support system.</p>","language":"English","publisher":"Springer","doi":"10.1007/s11069-012-0366-3","usgsCitation":"Coletti, A., Howe, P.D., Yarnal, B., and Wood, N.J., 2013, A support system for assessing local vulnerability to weather and climate: Natural Hazards, v. 65, no. 1, p. 999-1008, https://doi.org/10.1007/s11069-012-0366-3.","productDescription":"10 p.","startPage":"999","endPage":"1008","ipdsId":"IP-040114","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":275419,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"65","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-10-05","publicationStatus":"PW","scienceBaseUri":"51f2541ee4b0279fe2e1bfe0","contributors":{"authors":[{"text":"Coletti, Alex","contributorId":69866,"corporation":false,"usgs":true,"family":"Coletti","given":"Alex","email":"","affiliations":[],"preferred":false,"id":481407,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Howe, Peter D.","contributorId":60931,"corporation":false,"usgs":true,"family":"Howe","given":"Peter","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":481406,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yarnal, Brent","contributorId":31839,"corporation":false,"usgs":true,"family":"Yarnal","given":"Brent","email":"","affiliations":[],"preferred":false,"id":481405,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wood, Nathan J. 0000-0002-6060-9729 nwood@usgs.gov","orcid":"https://orcid.org/0000-0002-6060-9729","contributorId":3347,"corporation":false,"usgs":true,"family":"Wood","given":"Nathan","email":"nwood@usgs.gov","middleInitial":"J.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":481404,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70198396,"text":"70198396 - 2013 - Testing the use of microfossils to reconstruct great earthquakes at Cascadia","interactions":[],"lastModifiedDate":"2018-08-21T16:20:06","indexId":"70198396","displayToPublicDate":"2013-01-01T16:21:30","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Testing the use of microfossils to reconstruct great earthquakes at Cascadia","docAbstract":"<p><span>Coastal stratigraphy from the Pacific Northwest of the United States contains evidence of sudden subsidence during ruptures of the Cascadia subduction zone. Transfer functions (empirical relationships between assemblages and elevation) can convert microfossil data into coastal subsidence estimates. Coseismic deformation models use the subsidence values to constrain earthquake magnitudes. To test the response of foraminifera, the accuracy of the transfer function method, and the presence of a pre-seismic signal, we simulated a great earthquake near Coos Bay, Oregon, by transplanting a bed of modern high salt-marsh sediment into the tidal flat, an elevation change that mimics a coseismic subsidence of 0.64 m. The transplanted bed was quickly buried by mud; after 12 mo and 5 yr, we sampled it for foraminifera. Reconstruction of the simulated coseismic subsidence using our transfer function was 0.61 m, nearly identical to the actual elevation change. Our transplant experiment, and additional analyses spanning the A.D. 1700 earthquake contact at the nearby Coquille River 15 km to the south, show that sediment mixing may explain assemblage changes previously interpreted as evidence of pre-seismic land-level change in Cascadia and elsewhere.</span></p>","language":"English","publisher":"Geological Survey of America","doi":"10.1130/G34544.1","usgsCitation":"Engelhart, S.E., Horton, B.P., Nelson, A.R., Hawkes, A.D., Witter, R., Wang, K., Wang, P., and Vane, C.H., 2013, Testing the use of microfossils to reconstruct great earthquakes at Cascadia: Geology, v. 41, no. 10, p. 1067-1070, https://doi.org/10.1130/G34544.1.","productDescription":"4 p.","startPage":"1067","endPage":"1070","ipdsId":"IP-046321","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":473983,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://durham-repository.worktribe.com/output/1285333","text":"External Repository"},{"id":356121,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fd37fe4b0f5d57878edba","contributors":{"authors":[{"text":"Engelhart, S. E.","contributorId":206643,"corporation":false,"usgs":false,"family":"Engelhart","given":"S.","email":"","middleInitial":"E.","affiliations":[{"id":37366,"text":"Sea Level Reserach Dept of Geosciences U of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":741345,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Horton, B. P","contributorId":193401,"corporation":false,"usgs":false,"family":"Horton","given":"B.","email":"","middleInitial":"P","affiliations":[],"preferred":false,"id":741455,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nelson, Alan R. 0000-0001-7117-7098 anelson@usgs.gov","orcid":"https://orcid.org/0000-0001-7117-7098","contributorId":812,"corporation":false,"usgs":true,"family":"Nelson","given":"Alan","email":"anelson@usgs.gov","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":741339,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hawkes, A. D.","contributorId":206639,"corporation":false,"usgs":false,"family":"Hawkes","given":"A.","email":"","middleInitial":"D.","affiliations":[{"id":37362,"text":"Geography and Geology,U of North Carolina","active":true,"usgs":false}],"preferred":false,"id":741341,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Witter, Robert C. 0000-0002-1721-254X rwitter@usgs.gov","orcid":"https://orcid.org/0000-0002-1721-254X","contributorId":4528,"corporation":false,"usgs":true,"family":"Witter","given":"Robert C.","email":"rwitter@usgs.gov","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":741456,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wang, K.","contributorId":206641,"corporation":false,"usgs":false,"family":"Wang","given":"K.","email":"","affiliations":[{"id":37364,"text":"Pacific Geoscience Center Geological Survery of Canada","active":true,"usgs":false}],"preferred":false,"id":741343,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wang, P.-L.","contributorId":206642,"corporation":false,"usgs":false,"family":"Wang","given":"P.-L.","email":"","affiliations":[{"id":37365,"text":"Dept of Geosciences, National Taiwan University.","active":true,"usgs":false}],"preferred":false,"id":741344,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Vane, C. H.","contributorId":206640,"corporation":false,"usgs":false,"family":"Vane","given":"C.","email":"","middleInitial":"H.","affiliations":[{"id":37363,"text":"British Geological Survey, Nottingham UK","active":true,"usgs":false}],"preferred":false,"id":741342,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70074095,"text":"70074095 - 2013 - Quantifying landscape change in an arctic coastal lowland using repeat airborne LiDAR","interactions":[],"lastModifiedDate":"2018-03-29T11:16:02","indexId":"70074095","displayToPublicDate":"2013-01-01T16:20:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying landscape change in an arctic coastal lowland using repeat airborne LiDAR","docAbstract":"<p><span>Increases in air, permafrost, and sea surface temperature, loss of sea ice, the potential for increased wave energy, and higher river discharge may all be interacting to escalate erosion of arctic coastal lowland landscapes. Here we use airborne light detection and ranging (LiDAR) data acquired in 2006 and 2010 to detect landscape change in a 100&nbsp;km</span><sup>2</sup><span><span>&nbsp;</span>study area on the Beaufort Sea coastal plain of northern Alaska. We detected statistically significant change (99% confidence interval), defined as contiguous areas (&gt;10&nbsp;m</span><sup>2</sup><span>) that had changed in height by at least 0.55&nbsp;m, in 0.3% of the study region. Erosional features indicative of ice-rich permafrost degradation were associated with ice-bonded coastal, river, and lake bluffs, frost mounds, ice wedges, and thermo-erosional gullies. These features accounted for about half of the area where vertical change was detected. Inferred thermo-denudation and thermo-abrasion of coastal and river bluffs likely accounted for the dominant permafrost-related degradational processes with respect to area (42%) and volume (51%). More than 300 thermokarst pits significantly subsided during the study period, likely as a result of storm surge flooding of low-lying tundra (&lt;1.4&nbsp;m asl) as well as the lasting impact of warm summers in the late-1980s and mid-1990s. Our results indicate that repeat airborne LiDAR can be used to detect landscape change in arctic coastal lowland regions at large spatial scales over sub-decadal time periods.</span></p>","language":"English","publisher":"IOP Publishing","doi":"10.1088/1748-9326/8/4/045025","usgsCitation":"Jones, B.M., Stoker, J.M., Gibbs, A.E., Grosse, G., Romanovsky, V.E., Douglas, T.A., Kinsman, N.E., and Richmond, B.M., 2013, Quantifying landscape change in an arctic coastal lowland using repeat airborne LiDAR: Environmental Research Letters, v. 8, no. 4, Article 045025; 10 p., https://doi.org/10.1088/1748-9326/8/4/045025.","productDescription":"Article 045025; 10 p.","onlineOnly":"Y","ipdsId":"IP-051098","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":473984,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/8/4/045025","text":"Publisher Index Page"},{"id":281597,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Beaufort Sea","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -148.5,70.0 ], [ -148.5,70.5 ], [ -146.5,70.5 ], [ -146.5,70.0 ], [ -148.5,70.0 ] ] ] } } ] }","volume":"8","issue":"4","noUsgsAuthors":false,"publicationDate":"2013-11-21","publicationStatus":"PW","scienceBaseUri":"53cd6ec7e4b0b29085105fdb","contributors":{"authors":[{"text":"Jones, Benjamin M. 0000-0002-1517-4711 bjones@usgs.gov","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":2286,"corporation":false,"usgs":true,"family":"Jones","given":"Benjamin","email":"bjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":489384,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stoker, Jason M. 0000-0003-2455-0931 jstoker@usgs.gov","orcid":"https://orcid.org/0000-0003-2455-0931","contributorId":3021,"corporation":false,"usgs":true,"family":"Stoker","given":"Jason","email":"jstoker@usgs.gov","middleInitial":"M.","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":489389,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gibbs, Ann E. 0000-0002-0883-3774 agibbs@usgs.gov","orcid":"https://orcid.org/0000-0002-0883-3774","contributorId":2644,"corporation":false,"usgs":true,"family":"Gibbs","given":"Ann","email":"agibbs@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":489386,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grosse, Guido","contributorId":101475,"corporation":false,"usgs":true,"family":"Grosse","given":"Guido","affiliations":[{"id":34291,"text":"University of Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":489391,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Romanovsky, Vladimir E.","contributorId":40113,"corporation":false,"usgs":true,"family":"Romanovsky","given":"Vladimir","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":489387,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Douglas, Thomas A. 0000-0003-1314-1905","orcid":"https://orcid.org/0000-0003-1314-1905","contributorId":64553,"corporation":false,"usgs":false,"family":"Douglas","given":"Thomas","email":"","middleInitial":"A.","affiliations":[{"id":33087,"text":"Cold Regions Research and Engineering Laboratory","active":true,"usgs":false}],"preferred":true,"id":489388,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kinsman, Nichole E.M.","contributorId":100285,"corporation":false,"usgs":true,"family":"Kinsman","given":"Nichole","email":"","middleInitial":"E.M.","affiliations":[],"preferred":false,"id":489390,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Richmond, Bruce M. 0000-0002-0056-5832 brichmond@usgs.gov","orcid":"https://orcid.org/0000-0002-0056-5832","contributorId":2459,"corporation":false,"usgs":true,"family":"Richmond","given":"Bruce","email":"brichmond@usgs.gov","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":489385,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70048255,"text":"70048255 - 2013 - Status of a reconnaissance field study of the Susitna basin, 2011","interactions":[],"lastModifiedDate":"2023-06-05T16:08:38.338897","indexId":"70048255","displayToPublicDate":"2013-01-01T16:15:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"title":"Status of a reconnaissance field study of the Susitna basin, 2011","docAbstract":"<p>The Alaska Division of Geological & Geophysical Surveys (DGGS) and Alaska Division of Oil and Gas\n(DOG), in collaboration with the U.S. Geological Survey (USGS) performed reconnaissance field studies for ten\ndays in late June 2011, in the Susitna basin, directly north of Cook Inlet, south-central Alaska (fig. 1). The purpose\nof our investigation was to reconnoiter outcrops in the basin and along its periphery to gather new information\ntowards understanding the basin formation history and stratigraphy. This reconnaissance data represents the first\nstep toward better understanding the basin’s hydrocarbon potential, a key component of DGGS’s multi-year In-\nState Gas Program. This program is focused on collecting baseline geologic information from potential frontier\ngas basins to encourage new exploration to help, in part, reduce the high cost of energy in rural Alaska. Our work\nrepresents the first season of this three-year project. Preliminary results from year two, a companion project within\nthe Nenana and Tanana basins in interior Alaska, are described by Wartes and others (2013). DGGS plans to return\nto the Susitna basin for follow-up fieldwork during the third and final year of the program.</p>\n<br>\n<p>The motivation for developing a better understanding of the Susitna basin stems from the recognition that\nthe Susitna basin shares similar age coal-bearing strata with the adjacent, petroliferous Cook Inlet forearc basin\n(Barnes, 1966; Reed and Nelson, 1980) and with exhumed strata in the Matanuska Valley forearc basin (Trop and\nothers, 2003) (figs. 1 and 2). Cook Inlet basin has eight producing oil fields, more than 25 producing gas fields,\nand likely contains many additional undiscovered oil and gas accumulations (LePain and others, in press). Most\nof the Cook Inlet gas is of microbial origin and apparently was sourced from abundant coalbeds of primarily\nMiocene age in the Tyonek, Beluga, and Sterling Formations (Claypool and others, 1980; Magoon, 1994). If the\nbiogenic gas model for Cook Inlet is applicable to the Susitna basin, then the latter may be a viable source for\nAlaska Railbelt and rural energy needs.</p>\n<br>\n<p>This brief overview report summarizes the reconnaissance field data collected in the Susitna basin during the\nfirst summer of the program. As the data are developed, this report will be followed by interpretive technical reports\naddressing the stratigraphy, reservoir quality, coal quality and gas potential, hydrocarbon seal integrity, subsurface\nstructure, and uplift history of the basin and sub-basin margins.</p>","language":"English","publisher":"Alaska Division of Geological and Geophysical Surveys","publisherLocation":"Fairbanks, AK","doi":"10.14509/25015","usgsCitation":"Gillis, R., Stanley, R.G., LePain, D., Mauel, D.J., Herriott, T., Helmold, K.P., Peterson, C.S., Wartes, M.A., and Shellenbaum, D.P., 2013, Status of a reconnaissance field study of the Susitna basin, 2011, 8 p., https://doi.org/10.14509/25015.","productDescription":"8 p.","numberOfPages":"12","ipdsId":"IP-042889","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":473985,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.14509/25015","text":"Publisher Index Page"},{"id":287641,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Susitna Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -152.0762,61.2797 ], [ -152.0762,62.9966 ], [ -147.3878,62.9966 ], [ -147.3878,61.2797 ], [ -152.0762,61.2797 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5385b401e4b09e18fc023aaa","contributors":{"authors":[{"text":"Gillis, Robert J.","contributorId":69438,"corporation":false,"usgs":true,"family":"Gillis","given":"Robert J.","affiliations":[],"preferred":false,"id":484184,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stanley, Richard G. 0000-0001-6192-8783 rstanley@usgs.gov","orcid":"https://orcid.org/0000-0001-6192-8783","contributorId":1832,"corporation":false,"usgs":true,"family":"Stanley","given":"Richard","email":"rstanley@usgs.gov","middleInitial":"G.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":484179,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"LePain, David L.","contributorId":105209,"corporation":false,"usgs":true,"family":"LePain","given":"David L.","affiliations":[],"preferred":false,"id":484187,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mauel, David J.","contributorId":99049,"corporation":false,"usgs":true,"family":"Mauel","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":484186,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Herriott, Trystan M.","contributorId":68845,"corporation":false,"usgs":true,"family":"Herriott","given":"Trystan M.","affiliations":[],"preferred":false,"id":484183,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Helmold, Kenneth P.","contributorId":69456,"corporation":false,"usgs":true,"family":"Helmold","given":"Kenneth","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":484185,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Peterson, C. Shaun","contributorId":54100,"corporation":false,"usgs":true,"family":"Peterson","given":"C.","email":"","middleInitial":"Shaun","affiliations":[],"preferred":false,"id":484182,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wartes, Marwan A.","contributorId":47476,"corporation":false,"usgs":true,"family":"Wartes","given":"Marwan","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":484181,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Shellenbaum, Diane P.","contributorId":45225,"corporation":false,"usgs":true,"family":"Shellenbaum","given":"Diane","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":484180,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70095609,"text":"70095609 - 2013 - Mount Rainier National Park and Olympic National Park elk monitoring program annual report 2011","interactions":[],"lastModifiedDate":"2014-05-27T15:47:32","indexId":"70095609","displayToPublicDate":"2013-01-01T15:28:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":52,"text":"Natural Resource Data Series","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"NPS/NCCN/NRDS-2013/437","title":"Mount Rainier National Park and Olympic National Park elk monitoring program annual report 2011","docAbstract":"<p>Fiscal year 2011 was the first year of implementing an approved elk monitoring protocol in \nMount Rainier (MORA) and Olympic (OLYM) National Parks in the North Coast and Cascades \nNetwork (NCCN) (Griffin et al. 2012). However, it was the fourth and second year of gathering \ndata according to protocol in MORA and OLYM respectively; data gathered during the protocol \ndevelopment phase followed procedures that are laid out in the protocol. Elk monitoring in these \nlarge wilderness parks relies on aerial surveys from a helicopter. Summer surveys are intended to \nprovide quantitative estimates of abundance, sex and age composition, and distribution of \nmigratory elk in high elevation trend count areas.</p>\n<br>\n<p>An unknown number of elk is not detected during surveys; however the protocol estimates the \nnumber of missed elk by applying a model that accounts for detection bias. Detection bias in elk \nsurveys in MORA is estimated using a double-observer sightability model that was developed \nusing survey data from 2008-2010 (Griffin et al. 2012). That model was developed using elk that \nwere previously equipped with radio collars by cooperating tribes. At the onset of protocol \ndevelopment in OLYM there were no existing radio-collars on elk. Consequently the majority of \nthe effort in OLYM in the past 4 years has been focused on capturing and radio-collaring elk and \nconducting sightability trials needed to develop a double-observer sightability model in OLYM. \nIn this annual report we provide estimates of abundance and composition for MORA elk, raw \ncounts of elk made in OLYM, and describe sightability trials conducted in OLYM.</p>\n<br>\n<p>At MORA the North trend count area was surveyed twice and the South once (North Rainier \nherd, and South Rainier herd). We counted 373 and 267 elk during two replicate surveys of the \nNorth Rainier herd, and 535 elk in the South Rainier herd. Using the model, we estimated that \n413 and 320 elk were in the North and 652 elk were in the South trend count areas during the \ntime of the respective surveys. </p>\n<br>\n<p>At OLYM, the Core and Northwest trend count areas were completely surveyed, as were \nportions of the Quinault. In addition, we surveyed 10 survey units specifically to get resight data. \nTwo-hundred and forty eight elk were counted in the Core, 19 in the Northwest, and 169 in the \nQuinault. We conducted double-observer sightability trials associated with 14 collared elk \ngroups for use in developing the double-observer sightability model for OLYM.</p>","language":"English","publisher":"National Park Service","publisherLocation":"Fort Collins, CO","usgsCitation":"Happe, P.J., Reid, M., Griffin, P., Jenkins, K.J., Vales, D.J., Moeller, B.J., Tirhi, M., and McCorquodale, S., 2013, Mount Rainier National Park and Olympic National Park elk monitoring program annual report 2011: Natural Resource Data Series NPS/NCCN/NRDS-2013/437, ix, 21 p.","productDescription":"ix, 21 p.","numberOfPages":"34","ipdsId":"IP-043404","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":287636,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287635,"type":{"id":15,"text":"Index Page"},"url":"https://data.doi.gov/dataset/mount-rainier-national-park-and-olympic-national-park-elk-monitoring-program-annual-report-5c94a"}],"country":"United States","state":"Washington","otherGeospatial":"Mount Rainier National Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -121.921037,46.707817 ], [ -121.921037,47.001077 ], [ -121.442875,47.001077 ], [ -121.442875,46.707817 ], [ -121.921037,46.707817 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5385b3f9e4b09e18fc023a6a","contributors":{"authors":[{"text":"Happe, Patricia J.","contributorId":50983,"corporation":false,"usgs":false,"family":"Happe","given":"Patricia","email":"","middleInitial":"J.","affiliations":[{"id":16133,"text":"National Park Service, Olympic National Park","active":true,"usgs":false}],"preferred":false,"id":491317,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reid, Mason","contributorId":51639,"corporation":false,"usgs":true,"family":"Reid","given":"Mason","affiliations":[],"preferred":false,"id":491318,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Griffin, Paul C.","contributorId":7802,"corporation":false,"usgs":true,"family":"Griffin","given":"Paul C.","affiliations":[],"preferred":false,"id":491314,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jenkins, Kurt J. 0000-0003-1415-6607 kurt_jenkins@usgs.gov","orcid":"https://orcid.org/0000-0003-1415-6607","contributorId":3415,"corporation":false,"usgs":true,"family":"Jenkins","given":"Kurt","email":"kurt_jenkins@usgs.gov","middleInitial":"J.","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":491313,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vales, David J.","contributorId":74662,"corporation":false,"usgs":true,"family":"Vales","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":491319,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Moeller, Barbara J.","contributorId":87446,"corporation":false,"usgs":true,"family":"Moeller","given":"Barbara","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":491320,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tirhi, Michelle","contributorId":28168,"corporation":false,"usgs":false,"family":"Tirhi","given":"Michelle","affiliations":[{"id":13269,"text":"Washington Department of Fish & Wildlife","active":true,"usgs":false}],"preferred":false,"id":491315,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McCorquodale, Scott","contributorId":28515,"corporation":false,"usgs":true,"family":"McCorquodale","given":"Scott","affiliations":[],"preferred":false,"id":491316,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70046960,"text":"70046960 - 2013 - Identification of metrics to monitor salt marsh integrity on National Wildlife Refuges in relation to conservation and management objectives","interactions":[],"lastModifiedDate":"2016-08-10T15:52:10","indexId":"70046960","displayToPublicDate":"2013-01-01T15:25:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"title":"Identification of metrics to monitor salt marsh integrity on National Wildlife Refuges in relation to conservation and management objectives","docAbstract":"<h1>Executive Summary</h1>\n<p>Most salt marshes in the US have been degraded by human activities, and threats from physical alterations, surrounding land-use, species invasions, and global climate change persist. Salt marshes are unique and highly productive ecosystems with high intrinsic value to wildlife, and many National Wildlife Refuges (NWRs) have been established in coastal areas to protect large tracts of salt marsh and wetland-dependent species. Various management practices are employed routinely on coastal NWRs to restore and enhance marsh integrity and ensure ecosystem sustainability. Prioritizing NWR salt marshes for application of management actions and choosing among multiple management options requires scientifically-based methods for assessing marsh condition.</p>\n<p>Monitoring is integral to structured decision-making (SDM), a formal process for decomposing a decision into its essential elements. Within a natural resource context, SDM involves identifying management objectives, alternative management actions, and expected management outcomes. The core of SDM is a set of criteria for measuring system performance and evaluating management responses. Therefore, use of SDM to frame natural resource decisions leads to logical selection of monitoring attributes that are linked explicitly to management needs.</p>\n<p>We used SDM to guide selection of variables for monitoring the ecological integrity of salt marshes within the National Wildlife Refuge System (NWRS). Our objectives were to identify indicators of salt marsh integrity that are effective across large geographic regions, responsive to a wide range of threats, and feasible to implement within funding and staffing constraints of the NWRS. In April, 2008, we engaged interdisciplinary experts in a week-long rapid prototyping SDM workshop to define the essential elements of salt marsh management decisions on refuges throughout the northeastern, southwestern, and northwestern US, corresponding to respective Regions 5, 2, and 1 of the US Fish and Wildlife Service (FWS). Through this process we identified measurable attributes for monitoring salt marsh ecosystems that are integrated into conservation practice and target management objectives.</p>\n<p>The following salt marsh attributes were identified through the SDM process either for describing state condition to determine management needs or for evaluating the achievement of management objectives: historical condition and geomorphic setting; ditch density; surrounding land use; ratio of open water area to vegetation area; rate of pesticide application; environmental contaminant concentration; change in marsh surface elevation relative to sea level rise; tidal range and groundwater level; surface topography; salinity; and species composition and abundance of vegetation, invasive species, invertebrates, nekton, and breeding and wintering birds.</p>\n<p>The identified attributes were too broadly defined to serve as operational monitoring variables. Therefore, we tested specific metrics for quantifying most of these attributes in summers of 2008 and 2009. The first four attributes in the above list can be characterized by office-based analysis of existing GIS data layers. The remaining attributes require field-based methods for assessment. We were forced to exclude a small number of attributes from field tests due to inconsistent data (pesticide application rate, environmental contaminant concentrations) or requirements that exceeded the scope of this project (change in marsh surface elevation; surface topography; benthic invertebrates; wintering birds). We evaluated potential metrics for evaluating all remaining field attributes.</p>\n<p>In partnership with NWRS biologists, we tested rapid versus intensive metrics for monitoring field attributes (tidal range and groundwater level; marsh surface elevation; salinity; and species composition and abundance of vegetation, invasive species, nekton, and breeding birds) at coastal refuges throughout FWS Region 5. Seven refuges participated in metric testing in 2008: Rachel Carson (ME), Parker River (MA), Wertheim (NY), E. B. Forsythe (NJ), Bombay Hook (DE), Prime Hook (DE), and Eastern Shore of Virginia Complex (VA). These seven and two additional refuges participated in metric testing in 2009: Rhode Island Complex (RI) and Stewart B. McKinney (CT). We based all field metrics on existing protocols for salt marsh assessment. Sampling locations were determined randomly within delineated marsh study units (MSUs) at each refuge. Detailed field methods are provided in appendices to this report.</p>\n<p>Measurements for individual metrics were averaged across samples within MSUs during each year of sampling. Each year, correlation or regression analysis was conducted on average measurements across MSUs within each attribute set to identify redundant metrics. Statistical redundancy between a pair of metrics within an attribute set (i.e., correlation or regression slopes with p-values &lt; 0.05) was considered justification for eliminating one of the pair from the regional set of monitoring metrics. Decisions regarding metric elimination versus retention were based on feasibility of monitoring, considering such factors as sampling time, resources required, and potential for regional standardization in implementation.</p>\n<p>The result of these tests is a reduced suite of monitoring metrics that targets NWRS management decisions and is practicable for implementing on a regional scale. Based on these tests, we recommend the following list of metrics for monitoring integrity of NWRS salt marshes (marsh attribute category is in parentheses): (historical condition and geomorphic setting) position of marsh in the landscape, marsh shape, degree of fill and/or fragmentation, degree of tidal flushing, amount of aquatic edge; (ditch density) ranking of ditch density from none to severe; (surrounding land use) relative proportion of agricultural land in a 150-m buffer around the marsh, relative proportion of natural land in a 150-m buffer around the marsh, relative proportion of natural land in a 1-km buffer around the marsh; (ratio of open water area to vegetation area) ratio of open water to emergent herbaceous wetlands within the marsh; (marsh surface elevation) elevation referenced to NAVD88 in a representative area of the marsh; (tidal range and groundwater level) percent of time the marsh surface is flooded during deployment of a continuous water-level monitor at a representative marsh location, mean depth of surface flooding as measured by a continuous water-level monitor at a representative location; (salinity) salinity measured in surface water; (vegetation community) vegetation species richness using the point-intercept method in 100-m diameter survey plots, percent cover of various marsh community types within 100-m diameter survey plots; (invasive species abundance) percent cover of invasive plant species measured using the point-intercept method in 100-m diameter survey plots; (nekton community) nekton density, nekton species richness, length of <i>Fundulus heteroclitus</i>; (breeding bird community) abundance of Willets counted per point during standard call-broadcast surveys, summed abundance of tidal marsh obligate species (Clapper Rail, Willet, Saltmarsh Sparrow, Seaside Sparrow) counted per point during standard call-broadcast surveys. Metrics describing the historical condition, geomorphic setting, and broad landscape features can be assessed using existing GIS databases. Our results support use of rapid methods to assess the majority of field metrics; only those used to describe the nekton community must be measured using intensive methods (throw traps or ditch nets, dependant on habitat configuration).</p>\n<p>Implementation of these metrics for quantitative assessment of NWRS salt marsh integrity in FWS Region 5 requires developing sampling designs for each refuge. Additionally, it is important to determine how the monitoring information will be used within a management context. SDM should be used to complete the analysis of salt marsh management decisions. The next steps would involve 1) prioritizing and weighting the management objectives; 2) predicting responses to individual management actions in terms of objectives and metrics; 3) using multiattribute utility theory to convert all measurable attributes to a common utility scale; 4) determining the total management benefit of each action by summing utilities across objectives; and 5) maximizing the total management benefits within cost constraints for each refuge. This process would allow the optimum management decisions for NWRS salt marshes to be selected and implemented based directly on monitoring data and current understanding of marsh responses to management actions. Monitoring the outcome of management actions would then allow new monitoring data to be incorporated into subsequent decisions.&nbsp;</p>","language":"English","publisher":"U.S. Geological Survey","collaboration":"Report submitted to U.S. Fish and Wildlife Service, Northeast Region, Hadley, MA","usgsCitation":"Neckles, H.A., Guntenspergen, G.R., Shriver, W.G., Danz, N.P., Wiest, W.A., Nagel, J.L., and Olker, J., 2013, Identification of metrics to monitor salt marsh integrity on National Wildlife Refuges in relation to conservation and management objectives, x, 226 p.","productDescription":"x, 226 p.","numberOfPages":"240","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-043211","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":286296,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":326161,"type":{"id":11,"text":"Document"},"url":"https://www.pwrc.usgs.gov/prodabs/pubpdfs/7828_Neckles.pdf","text":"Report","size":"21.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Connecticut, Delaware, Maine, Massachusetts, New Jersey, New York, Rhode Island, Virginia","otherGeospatial":"Bombay Hook National Wildlife Refuge, Eastern Shore of Virginia National Wildlife Refuge Complex, E. 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,{"id":70058718,"text":"70058718 - 2013 - GEM Building Taxonomy (Version 2.0)","interactions":[],"lastModifiedDate":"2014-04-14T16:05:45","indexId":"70058718","displayToPublicDate":"2013-01-01T15:13:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":253,"text":"GEM Technical Report","active":false,"publicationSubtype":{"id":4}},"seriesNumber":"2013-02","title":"GEM Building Taxonomy (Version 2.0)","docAbstract":"<p>This report documents the development and applications of the Building Taxonomy for the Global Earthquake Model (GEM). The purpose of the GEM Building Taxonomy is to describe and classify buildings in a uniform manner as a key step towards assessing their seismic risk, Criteria for development of the GEM Building Taxonomy were that the Taxonomy be relevant to seismic performance of different construction types; be comprehensive yet simple; be collapsible; adhere to principles that are familiar to the range of users; and ultimately be extensible to non-buildings and other hazards. The taxonomy was developed in conjunction with other GEM researchers and builds on the knowledge base from other taxonomies, including the EERI and IAEE World Housing Encyclopedia, PAGER-STR, and HAZUS.</p>\n<br>\n<p>The taxonomy is organized as a series of expandable tables, which contain information pertaining to various building attributes. Each attribute describes a specific characteristic of an individual building or a class of buildings that could potentially affect their seismic performance. The following 13 attributes have been included in the GEM Building Taxonomy Version 2.0 (v2.0): 1.) direction, 2.)material of the lateral load-resisting system, 3.) lateral load-resisting system, 4.) height, 5.) date of construction of retrofit, 6.) occupancy, 7.) building position within a block, 8.) shape of the building plan, 9.) structural irregularity, 10.) exterior walls, 11.) roof, 12.) floor, 13.) foundation system.</p>\n<br>\n<p>The report illustrates the pratical use of the GEM Building Taxonomy by discussing example case studies, in which the building-specific characteristics are mapped directly using GEM taxonomic attributes and the corresponding taxonomic string is constructed for that building, with \"/\" slash marks separating attributes. For example, for the building shown to the right, the GEM Taxonomy string is:</p>\n<br>\n<p>DX<sup>1</sup>/MUR+CLBRS+MOCL<sup>2</sup>/LWAL<sup>3</sup>/</p>\n<p>DY/MUR+CLBRS+MOCL/LWAL/YPRE:1939<sup>4</sup>/HEX:2<sup>5</sup>/RES<sup>6</sup></p>\n<p>/<sup>7</sup>/<sup>8</sup>/IRRE<sup>9</sup>/10/RSH3+RWO2<sup>11</sup>/FW<sup>12</sup>/<sup>13</sup>/</p>\n<br>\n<p>which can be read as (1) Direction = [DX or DY] (the building has the same lateral load-resisting system in both directions); (2) Material = [Unreinforced Masonry + solid fired clay bricks + cement: lime mortar]; (3) Lateral Load-Resisting System = [Wall]; (4) Date of construction = [pre-1939]; (5) Heaight = [exactly 2 storeys]; (6) Occupancy = [residential, unknown type]; (7) Building Position = [unknown = no entry]; (8) Shape of building plan = [unknown = no entry]; (9) Structural irregularity = [regular]; (10) Exterior walls = [unknown = no entry]; (11) Roof = [Shape: pitched and hipped, Roof covering: clay tiles, Roof system material: wood, Roof system type: wood trusses]; (12) Floor = [Floor system: Wood, unknown]; (13) Foundation = [unknown = no entry].</p>\n<br>\n<p>Mapping of GEM Building Taxonomy to selected taxonomies is included in the report -- for example, the above building would be referenced by previous structural taxonomies as: PAGER-STR as UFB or UFB4, by the World Housing Encyclopedia as 7 or 8 and by the European Macroseismic Scale (98) as M5. The Building Taxonomy data model is highly flexible and has been incorporated within a relational database architecture. Due to its ability to represent building typologies using a shorthand form, it is also possible to use the taxonomy for non-database applications, and we discuss possible application of adaptation for Building Information Modelling (BIM) systems, and for the insurance industry.</p>\n<br>\n<p>The GEM Building Taxonomy was independently evaluated and tested by the Earthquake Engineering Research Institute (EERI), which received 217 TaxT reports from 49 countries, representing a wide range of building typologies, including single and multi-storey buildings, reinforced and unreinforced masonry, confined masonry, concrete, steel, wood, and earthern buildings used for residential, commercial, industrial, and educational occupancy.  Based on these submissions and other feedback, the EERI team validated that the GEM Building Taxonomy is highly functional, robust and able to describe different buildings around the world.</p>\n<br>\n<p>The GEM Building Taxonomy is accompanied by supplementary resources. All terms have been explained in a companion online Glossary, which provides both text and graphic descriptions. The Taxonomy is accompanied by TaxT, a computer application that enables a user record information about a building or a building typology using the attributes of the GEM Building Taxonomy v2.0. TaxT can generate a taxonomy string and enable a user to generate a report in PDF format which summarizes the attribute values (s)he has chosen as representative of the building typology under consideration.</p>\n<br>\n<p>The report concludes with recommendations for future development of the GEM Building Taxonomy. Appendices provide the detailed GEM Building Taxonomy tables and additional resource, as well as mappings to other taxonomies.</p>","language":"English","publisher":"GEM Foundation","usgsCitation":"Brzev, S., Scawthorn, C., Charleson, A., Allen, L., Greene, M., Jaiswal, K., and Silva, V., 2013, GEM Building Taxonomy (Version 2.0) (Version 1.0): GEM Technical Report 2013-02, xiii, 163 p.","productDescription":"xiii, 163 p.","numberOfPages":"180","ipdsId":"IP-051658","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":286345,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286344,"type":{"id":15,"text":"Index Page"},"url":"https://www.globalquakemodel.org/resources/publications/technical-reports/gem-building-taxonomy-report/"}],"edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5355943ae4b0120853e8bf91","contributors":{"authors":[{"text":"Brzev, S.","contributorId":47291,"corporation":false,"usgs":true,"family":"Brzev","given":"S.","email":"","affiliations":[],"preferred":false,"id":487301,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scawthorn, C.","contributorId":65763,"corporation":false,"usgs":true,"family":"Scawthorn","given":"C.","email":"","affiliations":[],"preferred":false,"id":487302,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Charleson, A.W.","contributorId":23845,"corporation":false,"usgs":true,"family":"Charleson","given":"A.W.","email":"","affiliations":[],"preferred":false,"id":487300,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Allen, L.","contributorId":76225,"corporation":false,"usgs":true,"family":"Allen","given":"L.","email":"","affiliations":[],"preferred":false,"id":487303,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Greene, M.","contributorId":85069,"corporation":false,"usgs":true,"family":"Greene","given":"M.","email":"","affiliations":[],"preferred":false,"id":487304,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jaiswal, Kishor kjaiswal@usgs.gov","contributorId":861,"corporation":false,"usgs":true,"family":"Jaiswal","given":"Kishor","email":"kjaiswal@usgs.gov","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":false,"id":487298,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Silva, V.","contributorId":13136,"corporation":false,"usgs":true,"family":"Silva","given":"V.","affiliations":[],"preferred":false,"id":487299,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70058720,"text":"70058720 - 2013 - Metadata for selecting or submitting generic seismic vulnerability functions via GEM's vulnerability database","interactions":[],"lastModifiedDate":"2014-04-14T15:10:07","indexId":"70058720","displayToPublicDate":"2013-01-01T15:06:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Metadata for selecting or submitting generic seismic vulnerability functions via GEM's vulnerability database","docAbstract":"This memo lays out a procedure for the GEM software to offer an available vulnerability function for any acceptable set of attributes that the user specifies for a particular building category. The memo also provides general guidelines on how to submit the vulnerability or fragility functions to the GEM vulnerability repository, stipulating which attributes modelers must provide so that their vulnerability or fragility functions can be queried appropriately by the vulnerability database. An important objective is to provide users guidance on limitations and applicability by providing the associated modeling assumptions and applicability of each vulnerability or fragility function.","language":"English","publisher":"GEM","usgsCitation":"Jaiswal, K., 2013, Metadata for selecting or submitting generic seismic vulnerability functions via GEM's vulnerability database (Version 2.0), iv, 12 p.","productDescription":"iv, 12 p.","numberOfPages":"18","ipdsId":"IP-045656","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":286343,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286342,"type":{"id":15,"text":"Index Page"},"url":"https://www.nexus.globalquakemodel.org/gem-vulnerability/posts/metadata-for-selecting-or-submitting-vulnerability-fragility-functions-into-gem-vulnerability-database"}],"edition":"Version 2.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"535594b5e4b0120853e8c07d","contributors":{"authors":[{"text":"Jaiswal, Kishor kjaiswal@usgs.gov","contributorId":861,"corporation":false,"usgs":true,"family":"Jaiswal","given":"Kishor","email":"kjaiswal@usgs.gov","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":false,"id":487305,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70073514,"text":"70073514 - 2013 - Movement and longevity of imperiled Okaloosa Darters (Etheostoma okaloosae)","interactions":[],"lastModifiedDate":"2014-01-21T14:48:23","indexId":"70073514","displayToPublicDate":"2013-01-01T14:43:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1337,"text":"Copeia","active":true,"publicationSubtype":{"id":10}},"title":"Movement and longevity of imperiled Okaloosa Darters (Etheostoma okaloosae)","docAbstract":"Movement and longevity studies inform management and conservation plans for imperiled organisms. We used a mark–recapture study to reveal information about these key biological characteristics for imperiled Okaloosa Darters (Etheostoma okaloosae). Okaloosa Darters were captured from 20 m reaches at six separate streams, marked with VIE on the left or right dorsum according to the side of the stream from which they were captured, and released on the same side where they were captured. Okaloosa Darters were recounted (but not recaptured) at 24 h and one month, and then recaptured once per year for the following eight years. During the final recapture year, we measured standard length of all Okaloosa Darters and constructed length frequency distributions to identify distinct cohorts. We found that significant numbers of Okaloosa Darters remained within their 20 m reaches after 24 h (31%), one month (45%), and one year (22%) and rarely crossed open, sandy stream channels from one side to the other. Our recapture data and length frequency distributions indicate that Okaloosa Darters live longer than the 2–3 years suggested by previous authors. One of our recaptured fish was at least eight years old, making Okaloosa Darters the most long-lived etheostomine.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Copeia","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Society of Ichthyologists and Herpetologists","doi":"10.1643/CE-12-175","usgsCitation":"Holt, D.E., Jelks, H.L., and Jordan, F., 2013, Movement and longevity of imperiled Okaloosa Darters (Etheostoma okaloosae): Copeia, v. 2013, no. 4, p. 653-659, https://doi.org/10.1643/CE-12-175.","productDescription":"7 p.","startPage":"653","endPage":"659","numberOfPages":"7","ipdsId":"IP-042687","costCenters":[],"links":[{"id":281341,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281338,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1643/CE-12-175"}],"volume":"2013","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd684fe4b0b29085101f15","contributors":{"authors":[{"text":"Holt, Daniel E.","contributorId":102381,"corporation":false,"usgs":true,"family":"Holt","given":"Daniel","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":488878,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jelks, Howard L. 0000-0002-0672-6297 hjelks@usgs.gov","orcid":"https://orcid.org/0000-0002-0672-6297","contributorId":2962,"corporation":false,"usgs":true,"family":"Jelks","given":"Howard","email":"hjelks@usgs.gov","middleInitial":"L.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":488877,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jordan, Frank","contributorId":103405,"corporation":false,"usgs":true,"family":"Jordan","given":"Frank","affiliations":[],"preferred":false,"id":488879,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70098030,"text":"70098030 - 2013 - Application of ground-truth for classification and quantification of bird movements on migratory bird habitat initiative sites in southwest Louisiana: final report","interactions":[],"lastModifiedDate":"2014-04-09T14:47:23","indexId":"70098030","displayToPublicDate":"2013-01-01T14:31:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"title":"Application of ground-truth for classification and quantification of bird movements on migratory bird habitat initiative sites in southwest Louisiana: final report","docAbstract":"<p>This project was initiated to assess migrating and wintering bird use of lands \nenrolled in the Natural Resources Conservation Service’s (NRCS) Migratory Bird Habitat \nInitiative (MBHI). The MBHI program was developed in response to the Deepwater \nHorizon oil spill in 2010, with the goal of improving/creating habitat for waterbirds \naffected by the spill. In collaboration with the University of Delaware (UDEL), we used \nweather surveillance radar data (Sieges 2014), portable marine radar data, thermal \ninfrared images, and visual observations to assess bird use of MBHI easements. \nMigrating and wintering birds routinely make synchronous flights near dusk (e.g., \ndeparture during migration, feeding flights during winter). Weather radars readily detect \nbirds at the onset of these flights and have proven to be useful remote sensing tools for \nassessing bird-habitat relations during migration and determining the response of \nwintering waterfowl to wetland restoration (e.g., Wetlands Reserve Program lands). \nHowever, ground-truthing is required to identify radar echoes to species or species group. \nWe designed a field study to ground-truth a larger-scale, weather radar assessment of bird \nuse of MBHI sites in southwest Louisiana. We examined seasonal bird use of MBHI \nfields in fall, winter, and spring of 2011-2012. To assess diurnal use, we conducted total \narea surveys of MBHI sites in the afternoon, collecting data on bird species composition, \nabundance, behavior, and habitat use. In the evenings, we quantified bird activity at the \nMBHI easements and described flight behavior (i.e., birds landing in, departing from, \ncircling, or flying over the MBHI tract). Our field sampling captured the onset of evening \nflights and spanned the period of collection of the weather radar data analyzed. Pre- and \npost-dusk surveys were conducted using a portable radar system and a thermal infrared \ncamera. </p>\n<br>\n<p>Landbirds, shorebirds, and wading birds were commonly found on MBHI fields \nduring diurnal surveys in the fall. Ducks (breeding and early migrating species) were also \ndetected on diurnal surveys, but were less abundant than the previously mentioned taxa. \nWading birds were the most abundant taxa observed during evening surveys up to 5 min \nbefore dusk when their numbers declined and duck densities increased. Ducks accounted \nfor 64.0% of all birds detected from 0-5 min before dusk. Most ducks observed at that time were flyovers (71.4%), but circling (9.2%), departing (12.1%), and landing birds \n(7.4%) were also detected.</p>\n<br>\n<p>In fall, the portable radar system detected two peaks in bird movement: one \nshortly before sunset and a second shortly after dusk. The later movement began just \nbefore dusk, peaked approximately 9 min after dusk, and concluded within 20 min after \ndusk. The flight headings of birds changed in relation to time from dusk. In general, the \nmajority of targets flew towards the southwest before dusk and towards the northeast \nafter dusk. The change in flight direction pre- and post-dusk may be related to \nmovements dominated by migratory versus local flight.</p> \n<br>\n<p>In winter, ducks, shorebirds, wading birds, and landbirds were the most abundant \ntaxa in diurnal surveys. Geese were abundant at times, but their frequency of occurrence \nand densities were highly variable. The majority of ducks, shorebirds, and wading birds \nwere observed feeding in MBHI fields. Landbirds and geese were more commonly seen \nresting. Overwintering ducks and geese dominated the movements near dusk (95.9% of \nall birds ≤ 5 min pre-dusk). Ducks were more frequently observed landing in (40.8%) and \nflying over (33.5%) MBHI fields while geese were mainly observed circling (54.7%) and \nflying over (38.9%) sites. Most of the shorebirds detected < 5 min before dusk (74.6% of \nall shorebirds) were departing the MBHI fields. Portable radar and thermal infrared \ncamera data indicate that large northeastward movements of waterfowl (99.9% of birds \nidentified to taxa) occurred after dusk (~10 min post-dusk). Most birds observed on radar \nduring this peak were flyovers and did not use the MBHI fields (78.9%); however, birds \nwere detected landing in (10.9%) and departing from (2.9%) MBHI fields. The post-dusk \nmovements may have been waterfowl feeding flights that routinely occur in southwest \nLouisiana between roost sites in coastal marsh and foraging sites in agricultural fields to \nthe north. After the conclusion of these movements ca. 30 min post-dusk, portable radar \ndata showed little activity through the night until approximately 0.5 to 1.5 hr pre-dawn. \nRadar data within 30 min pre-dawn indicate that most birds departed MBHI fields on \nflight headings toward the southwest. The pre-dawn movements were likely waterfowl \ndeparting from their foraging sites and returning to roosting areas in coastal marshes to \nthe south.</p>\n<br>\n<p>Shorebirds, ducks, and wading birds were the most abundant taxa during diurnal \nsurveys of MBHI fields in spring, and the majority of individuals were observed actively \nforaging rather than resting. Breeding, overwintering, and transient migrant species were \nall detected on MBHI fields. Near dusk, the majority of birds in flight were ducks (67.7% of all birds) that were flying over (38.2%), departing from (34.2%), or landing in (22.9%) MBHI fields. These results contrast with our winter observations when 40.8% of ducks landed in MBHI fields and 9.1% departed from fields. Portable radar and thermal camera data documented a peak in bird movements shortly after dusk, however, the peak was of lower magnitude than observed in the winter. Thermal camera data identified the birds as mostly shorebirds (57.3%) and waterfowl (40.4%). Flight headings were more variable than winter and lacked an undirectional flow. After the post-dusk movement had concluded, bird activity remained low throughout the night until approximately 30 min before dawn when a small peck in activity was observed. Flight headings during the pre-dawn were variable and multidirectional.</p>\n<br>\n<p>We compared bird abundance data collected by each of our three sampling \ntechniques (portable radar, thermal infrared camera, and direct visual observation) for the \n45-min observation period immediately preceding dusk; the period when all three survey \nmethods were used simultaneously. Abundance data from the three methods were \nsignificantly correlated at P &le; 0.05.</p>\n<br>\n<p>We documented diurnal and nocturnal bird use of MBHI fields. Most \nobservations near dusk in winter, when weather radar data were sampled, were of ducks \nand geese, and in spring, shorebirds and ducks. Our winter observations show large \nsynchronous movements of waterfowl occurring near dusk. These birds were moving to \nthe NE and feeding in agricultural fields at night. Portable radar data suggest that birds \nstay in these fields through the night and make return flights near dawn.</p>","language":"English","publisher":"U.S. Department of Agriculture","usgsCitation":"Barrow, W., Baldwin, M., Randall, L.A., Pitre, J., and Dudley, K.J., 2013, Application of ground-truth for classification and quantification of bird movements on migratory bird habitat initiative sites in southwest Louisiana: final report, ix, 102 p.","productDescription":"ix, 102 p.","numberOfPages":"111","ipdsId":"IP-051038","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":286056,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":284055,"type":{"id":15,"text":"Index Page"},"url":"https://www.nrcs.usda.gov/wps/portal/nrcs/detail/national/technical/nra/ceap/?cid=stelprdb1186080"}],"country":"United States","state":"Louisiana","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -93.4281,29.7777 ], [ -93.4281,30.6302 ], [ -92.5736,30.6302 ], [ -92.5736,29.7777 ], [ -93.4281,29.7777 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53558fc8e4b0120853e8be3f","contributors":{"authors":[{"text":"Barrow, Wylie C. 0000-0003-4671-2823 barroww@usgs.gov","orcid":"https://orcid.org/0000-0003-4671-2823","contributorId":1988,"corporation":false,"usgs":true,"family":"Barrow","given":"Wylie C.","email":"barroww@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":491547,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baldwin, Michael J. 0000-0003-1939-5439 baldwinm@usgs.gov","orcid":"https://orcid.org/0000-0003-1939-5439","contributorId":3294,"corporation":false,"usgs":true,"family":"Baldwin","given":"Michael J.","email":"baldwinm@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":491549,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Randall, Lori A. 0000-0003-0100-994X randalll@usgs.gov","orcid":"https://orcid.org/0000-0003-0100-994X","contributorId":2678,"corporation":false,"usgs":true,"family":"Randall","given":"Lori","email":"randalll@usgs.gov","middleInitial":"A.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":491548,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pitre, John","contributorId":83024,"corporation":false,"usgs":true,"family":"Pitre","given":"John","email":"","affiliations":[],"preferred":false,"id":491550,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dudley, Kyle J.","contributorId":93821,"corporation":false,"usgs":true,"family":"Dudley","given":"Kyle","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":491551,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70058653,"text":"70058653 - 2013 - User's guide and metadata for WestuRe: U.S. Pacific Coast estuary/watershed data and R tools","interactions":[],"lastModifiedDate":"2016-05-04T15:26:52","indexId":"70058653","displayToPublicDate":"2013-01-01T14:22:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"title":"User's guide and metadata for WestuRe: U.S. Pacific Coast estuary/watershed data and R tools","docAbstract":"<h1>Overview</h1>\n<p>There are about 350 estuaries along the U.S. Pacific Coast (U.S. Fish andWildlife 2011). Basic descriptive data for these estuaries, such as their size and watershed area, are important for coastal-scale research and conservation planning. However, this information is spread among many sources, making it difficult to find and standardize. The goal of the WestuRe Project is to provide a framework to: (1) make general descriptive data for estuaries and their watersheds more accessible, and (2) provide tools to make analyzing and visualizing these data easier.</p>\n<p>The WestuRe download includes data describing U.S. Pacific Coast estuaries and their corresponding watersheds from northern Washington (including the region located along the Strait of Juan de Fuca that goes from Port Townsend to Cape Flattery, 48.383&deg;N) to southern California (Tijuana Estuary, 32.557&deg;N), excluding Puget Sound proper and coastal islands (Fig. 1). The WestuRe data currently include shapefiles of estuary and watershed polygons as well as CSV files summarizing geomorphological and climate data (Fig. 2, Section 2). The WestuRe tools help users extract and view relevant data using the statistical program R and Google Earth (Fig. 3, Section 3).</p>\n<p>Potential applications of the data include:</p>\n<ul>\n<li>Describing and comparing estuaries and watersheds at the landscape scale</li>\n<li>Identifying relationships between estuary/watershed variables</li>\n<li>Incorporating estuary/watershed attributes in models to predict species and habitat distributions</li>\n<li>Classifying estuaries according to morphology, climate, and habitat (Lee and Brown 2009)</li>\n</ul>","language":"English","publisher":"Environmental Protection Agency","usgsCitation":"Frazier, M., Reusser, D., Lee, H., McCoy, L., Brown, C., and Nelson, W., 2013, User's guide and metadata for WestuRe: U.S. Pacific Coast estuary/watershed data and R tools, 41 p.","productDescription":"41 p.","numberOfPages":"42","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-045236","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":320981,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://nepis.epa.gov/Exe/ZyNET.exe/P100JQKG.TXT?ZyActionD=ZyDocument&Client=EPA&Index=2011+Thru+2015&Docs=&Query=&Time=&EndTime=&SearchMethod=1&TocRestrict=n&Toc=&TocEntry=&QField=&QFieldYear=&QFieldMonth=&QFieldDay=&IntQFieldOp=0&ExtQFieldOp=0&XmlQuery=&File=D%3A%5Czyfiles%5CIndex%20Data%5C11thru15%5CTxt%5C00000010%5CP100JQKG.txt&User=ANONYMOUS&Password=anonymous&SortMethod=h%7C-&MaximumDocuments=1&FuzzyDegree=0&ImageQuality=r75g8/r75g8/x150y150g16/i425&Display=p%7Cf&DefSeekPage=x&SearchBack=ZyActionL&Back=ZyActionS&BackDesc=Results%20page&MaximumPages=1&ZyEntry=1&SeekPage=x&ZyPURL"},{"id":286335,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon, Washington","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.79,32.47 ], [ -124.79,49.0 ], [ -114.59,49.0 ], [ -114.59,32.47 ], [ -124.79,32.47 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"535595d7e4b0120853e8c2df","contributors":{"authors":[{"text":"Frazier, M.R.","contributorId":37647,"corporation":false,"usgs":true,"family":"Frazier","given":"M.R.","email":"","affiliations":[],"preferred":false,"id":487218,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reusser, D.A.","contributorId":61251,"corporation":false,"usgs":true,"family":"Reusser","given":"D.A.","email":"","affiliations":[],"preferred":false,"id":487221,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lee, H. II","contributorId":9077,"corporation":false,"usgs":true,"family":"Lee","given":"H.","suffix":"II","affiliations":[],"preferred":false,"id":487216,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCoy, L.M.","contributorId":52885,"corporation":false,"usgs":true,"family":"McCoy","given":"L.M.","email":"","affiliations":[],"preferred":false,"id":487220,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brown, C.","contributorId":21484,"corporation":false,"usgs":true,"family":"Brown","given":"C.","affiliations":[],"preferred":false,"id":487217,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nelson, W.","contributorId":45365,"corporation":false,"usgs":true,"family":"Nelson","given":"W.","affiliations":[],"preferred":false,"id":487219,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70099268,"text":"70099268 - 2013 - Modeling trends from North American Breeding Bird Survey data: a spatially explicit approach","interactions":[],"lastModifiedDate":"2014-03-24T13:49:18","indexId":"70099268","displayToPublicDate":"2013-01-01T13:41:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Modeling trends from North American Breeding Bird Survey data: a spatially explicit approach","docAbstract":"Population trends, defined as interval-specific proportional changes in population size, are often used to help identify species of conservation interest. Efficient modeling of such trends depends on the consideration of the correlation of population changes with key spatial and environmental covariates. This can provide insights into causal mechanisms and allow spatially explicit summaries at scales that are of interest to management agencies. We expand the hierarchical modeling framework used in the North American Breeding Bird Survey (BBS) by developing a spatially explicit model of temporal trend using a conditional autoregressive (CAR) model. By adopting a formal spatial model for abundance, we produce spatially explicit abundance and trend estimates. Analyses based on large-scale geographic strata such as Bird Conservation Regions (BCR) can suffer from basic imbalances in spatial sampling. Our approach addresses this issue by providing an explicit weighting based on the fundamental sample allocation unit of the BBS. We applied the spatial model to three species from the BBS. Species have been chosen based upon their well-known population change patterns, which allows us to evaluate the quality of our model and the biological meaning of our estimates. We also compare our results with the ones obtained for BCRs using a nonspatial hierarchical model (Sauer and Link 2011). Globally, estimates for mean trends are consistent between the two approaches but spatial estimates provide much more precise trend estimates in regions on the edges of species ranges that were poorly estimated in non-spatial analyses. Incorporating a spatial component in the analysis not only allows us to obtain relevant and biologically meaningful estimates for population trends, but also enables us to provide a flexible framework in order to obtain trend estimates for any area.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS ONE","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0081867","usgsCitation":"Bled, F., Sauer, J., Pardieck, K.L., Doherty, P., and Royle, J.A., 2013, Modeling trends from North American Breeding Bird Survey data: a spatially explicit approach: PLoS ONE, v. 8, no. 12, 14 p., https://doi.org/10.1371/journal.pone.0081867.","productDescription":"14 p.","ipdsId":"IP-052066","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":473991,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0081867","text":"Publisher Index Page"},{"id":284404,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":284402,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0081867"},{"id":284403,"type":{"id":15,"text":"Index Page"},"url":"https://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0081867;jsessionid=FCB75EDDD2621890E310AC85F997B517"}],"volume":"8","issue":"12","noUsgsAuthors":false,"publicationDate":"2013-12-13","publicationStatus":"PW","scienceBaseUri":"535594b6e4b0120853e8c08b","contributors":{"authors":[{"text":"Bled, Florent","contributorId":93613,"corporation":false,"usgs":true,"family":"Bled","given":"Florent","affiliations":[],"preferred":false,"id":491909,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sauer, John R. jrsauer@usgs.gov","contributorId":3737,"corporation":false,"usgs":true,"family":"Sauer","given":"John R.","email":"jrsauer@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":491905,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pardieck, Keith L. 0000-0003-2779-4392 kpardieck@usgs.gov","orcid":"https://orcid.org/0000-0003-2779-4392","contributorId":4104,"corporation":false,"usgs":true,"family":"Pardieck","given":"Keith","email":"kpardieck@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":491906,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Doherty, Paul","contributorId":64155,"corporation":false,"usgs":true,"family":"Doherty","given":"Paul","affiliations":[],"preferred":false,"id":491908,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Royle, J. Andy","contributorId":55741,"corporation":false,"usgs":true,"family":"Royle","given":"J.","email":"","middleInitial":"Andy","affiliations":[],"preferred":false,"id":491907,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70119411,"text":"70119411 - 2013 - Moving forward with imperfect information","interactions":[],"lastModifiedDate":"2022-12-29T17:13:49.42493","indexId":"70119411","displayToPublicDate":"2013-01-01T13:39:00","publicationYear":"2013","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"19","title":"Moving forward with imperfect information","docAbstract":"<p>This chapter summarized the scope of what is known and not known about climate in the Southwestern United States. There is now more evidence and more agreement among climate scientists about the physical climate and related impacts in the Southwest compared with that represented in the 2009 National Climate Assessment (Karl, Melillo, and Peterson 2009). However, there remain uncertainties about the climate system, the complexities within climate models, the related impacts to the biophysical environment, and the use of climate information on decision making.</p>\n<br>\n<p>Uncertainty is introduced in each step of the climate planning-an-response process--in the scenarios used to drive the climate models, the information used to construct  the models, and the interpretation and use of the model' data for planning and decision making (Figure 19.1).</p>\n<br>\n<p>There are server key challenge, drawn from recommendations of the authors of this report, that contribute to these uncertainties in the Southwest:</p>\n<br>\n<p>- There is a dearth of climate observations at high elevations and on the lands of Native nations.</p>\n<p>- There is limited understanding of the influence of climate change on natural variability (e.g. El Niño-Southern Oscillations, Pacific Decadal Oscillation), extreme events (droughts, floods), and the marine layer align coastal California.</p>\n<p>- Climate models, downscaling, and resulting projection of the physical climate are imperfect. Representing the influence of the diverse topography of the Southwest on regional climate is a particular challenge.</p>\n<p>- The impacts of climate change on key components of the natural ecosystems (including species and terrestrial ecosystems) are ill-defined.</p>\n<p>- The adaptive capacity of decision-making entities and legal systems to handle climate impacts is unclear. This creates a challenge for identifying vulnerabilities to climate in the Southwest.</p>\n<p>- Regulation, legislation, and political and social responses too climate all play important roles in our ability to adapt to climate impacts and mitigate greenhouse gas (GHG) emissions.</p>\n<p>- Climate change is one of multiple stresses affecting the physical, biological, social, and economic systems of the Southwest, with population growth (and its related resource consumption, pollution, and land-sue changes) being particularly important.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Assessment of climate change in the southwest United States: A report prepared for the National Climate Assessment","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Island Press","publisherLocation":"Washington D.C.","usgsCitation":"Averyt, K., Brekke, L.D., Busch, D.E., Kaatz, L., Welling, L., Hartge, E.H., and Iseman, T., 2013, Moving forward with imperfect information, chap. 19 <i>of</i> Assessment of climate change in the southwest United States: A report prepared for the National Climate Assessment, p. 436-461.","productDescription":"26 p.","startPage":"436","endPage":"461","numberOfPages":"26","ipdsId":"IP-040677","costCenters":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"links":[{"id":294860,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294859,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.swcarr.arizona.edu/chapter/19"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"542e6972e4b092f17df5a974","contributors":{"authors":[{"text":"Averyt, Kristen","contributorId":63331,"corporation":false,"usgs":true,"family":"Averyt","given":"Kristen","email":"","affiliations":[],"preferred":false,"id":497666,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brekke, Levi D.","contributorId":6776,"corporation":false,"usgs":true,"family":"Brekke","given":"Levi","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":497663,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Busch, David E. dave_busch@usgs.gov","contributorId":3392,"corporation":false,"usgs":true,"family":"Busch","given":"David","email":"dave_busch@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":860495,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kaatz, Laurna","contributorId":34065,"corporation":false,"usgs":true,"family":"Kaatz","given":"Laurna","email":"","affiliations":[],"preferred":false,"id":497664,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Welling, Leigh","contributorId":77864,"corporation":false,"usgs":true,"family":"Welling","given":"Leigh","email":"","affiliations":[],"preferred":false,"id":497667,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hartge, Eric H.","contributorId":36070,"corporation":false,"usgs":true,"family":"Hartge","given":"Eric","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":497665,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Iseman, Tom","contributorId":82236,"corporation":false,"usgs":true,"family":"Iseman","given":"Tom","email":"","affiliations":[],"preferred":false,"id":497668,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
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