Biologic control of the introduced and invasive, woody plant tamarisk (Tamarix spp, saltcedar) in south-western states is controversial because it affects habitat of the federally endangered South-western Willow Flycatcher (Empidonax traillii extimus). These songbirds sometimes nest in tamarisk where floodplain-level invasion replaces native habitats. Biologic control, with the saltcedar leaf beetle (Diorhabda elongate), began along the Virgin River, Utah, in 2006, enhancing the need for comprehensive understanding of the tamarisk-flycatcher relationship. We used maximum entropy (Maxent) modeling to separately quantify the current extent of dense tamarisk habitat (>50% cover) and the potential extent of habitat available for E. traillii extimus within the studied watersheds. We used transformations of 2008 Landsat Thematic Mapper images and a digital elevation model as environmental input variables. Maxent models performed well for the flycatcher and tamarisk with Area Under the ROC Curve (AUC) values of 0.960 and 0.982, respectively. Classification of thresholds and comparison of the two Maxent outputs indicated moderate spatial overlap between predicted suitable habitat for E. traillii extimus and predicted locations with dense tamarisk stands, where flycatcher habitat will potentially change flycatcher habitats. Dense tamarisk habitat comprised 500 km2 within the study area, of which 11.4% was also modeled as potential habitat for E. traillii extimus. Potential habitat modeled for the flycatcher constituted 190 km2, of which 30.7% also contained dense tamarisk habitat. Results showed that both native vegetation and dense tamarisk habitats exist in the study area and that most tamarisk infestations do not contain characteristics that satisfy the habitat requirements of E. traillii extimus. Based on this study, effective biologic control of Tamarix spp. may, in the short term, reduce suitable habitat available to E. traillii extimus, but also has the potential in the long term to increase suitable habitat if appropriate mixes of native woody vegetation replace tamarisk in biocontrol areas.
","language":"English","publisher":"Springer","doi":"10.1007/s11707-011-0154-5","usgsCitation":"York, P., Evangelista, P., Kumar, S., Graham, J., Flather, C., and Stohlgren, T., 2011, A habitat overlap analysis derived from maxent for tamarisk and the south-western willow flycatcher: Frontiers of Earth Science, v. 5, no. 2, p. 120-129, https://doi.org/10.1007/s11707-011-0154-5.","productDescription":"10 p.","startPage":"120","endPage":"129","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":203829,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"2","noUsgsAuthors":false,"publicationDate":"2011-03-24","publicationStatus":"PW","scienceBaseUri":"4f4e4b24e4b07f02db6ae4e4","contributors":{"authors":[{"text":"York, Patricia","contributorId":79767,"corporation":false,"usgs":true,"family":"York","given":"Patricia","email":"","affiliations":[],"preferred":false,"id":348402,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evangelista, Paul","contributorId":46371,"corporation":false,"usgs":true,"family":"Evangelista","given":"Paul","affiliations":[],"preferred":false,"id":348401,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kumar, Sunil","contributorId":84992,"corporation":false,"usgs":true,"family":"Kumar","given":"Sunil","affiliations":[],"preferred":false,"id":348404,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Graham, James","contributorId":83398,"corporation":false,"usgs":true,"family":"Graham","given":"James","affiliations":[],"preferred":false,"id":348403,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Flather, Curtis","contributorId":104779,"corporation":false,"usgs":true,"family":"Flather","given":"Curtis","affiliations":[],"preferred":false,"id":348405,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stohlgren, Thomas","contributorId":22206,"corporation":false,"usgs":true,"family":"Stohlgren","given":"Thomas","affiliations":[],"preferred":false,"id":348400,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70148649,"text":"70148649 - 2011 - Secretive marsh aird species co-eccurrences and habitat associations across the midwest, USA","interactions":[],"lastModifiedDate":"2015-07-13T11:55:26","indexId":"70148649","displayToPublicDate":"2011-06-01T13:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Secretive marsh aird species co-eccurrences and habitat associations across the midwest, USA","docAbstract":"Because secretive marsh birds are difficult to detect, population status and habitat use for these birds are not well known. We conducted repeated surveys for secretive marsh birds across 264 sites in the Upper Mississippi River and Great Lakes Joint Venture region to estimate abundance, occupancy, and detection probabilities during the 2008 and 2009 breeding seasons. We identified species groups based on observed species co-occurrences. Two species, least bittern Ixobrychus exilis and American bittern Botaurus lentiginosus, co-occurred with other species less often than expected by chance, and two species groups, rails (Virginia rail Rallus limicola and sora Porzana carolina) and open-water birds (pied-billed grebe Podilymbus podiceps, common moorhen Gallinula chloropus, and American coot Fulica americana; coots were only surveyed in 2009), co-occurred more often than expected by chance. These groupings were consistent between years. We then estimated the relation of these species and groups to landscape and local site characteristics by using zero-inflated abundance models that accounted for incomplete detection. At the landscape level (5-km radius), the amount of emergent herbaceous wetland was positively associated with least bittern occupancy, whereas the amount of woody wetland was negatively associated with least bittern, rail, and open-water bird occupancy. At the local level, habitat variables that were associated with abundance were not consistent among groups or between years, with the exception that both least bitterns and open-water birds had a strong positive association between abundance and water-vegetation interspersion. Land managers interested in marsh bird management or conservation may want to consider focusing efforts on landscapes with high amounts of emergent herbaceous wetland and low amounts of woody wetland, and managing for high amounts of water-vegetation interspersion within the wetland.
","language":"English","publisher":"U.S. Fish and Wildlife Service","publisherLocation":"Washington, D.C.","doi":"10.3996/012011-JFWM-001","collaboration":"U.S. Fish and Wildlife Service, Division of Migratory Birds","usgsCitation":"Bolenbaugh, J.R., Krementz, D.G., and Lehnen, S.E., 2011, Secretive marsh aird species co-eccurrences and habitat associations across the midwest, USA: Journal of Fish and Wildlife Management, v. 2, no. 1, p. 49-60, https://doi.org/10.3996/012011-JFWM-001.","productDescription":"12 p.","startPage":"49","endPage":"60","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-026478","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":474994,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/012011-jfwm-001","text":"Publisher Index Page"},{"id":305684,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","issue":"1","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55a4e143e4b0183d66e453a2","contributors":{"authors":[{"text":"Bolenbaugh, Jason R.","contributorId":145589,"corporation":false,"usgs":false,"family":"Bolenbaugh","given":"Jason","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":564717,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krementz, David G. 0000-0002-5661-4541 dkrementz@usgs.gov","orcid":"https://orcid.org/0000-0002-5661-4541","contributorId":2827,"corporation":false,"usgs":true,"family":"Krementz","given":"David","email":"dkrementz@usgs.gov","middleInitial":"G.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":548948,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lehnen, Sarah E.","contributorId":145588,"corporation":false,"usgs":false,"family":"Lehnen","given":"Sarah","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":564718,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70223357,"text":"70223357 - 2011 - A model for assessing, quantifying, and correcting for index element mobility in weathering studies","interactions":[],"lastModifiedDate":"2021-08-24T16:46:52.587604","indexId":"70223357","displayToPublicDate":"2011-06-01T11:36:20","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"A model for assessing, quantifying, and correcting for index element mobility in weathering studies","docAbstract":"Evidence shows that high field strength (HFS) elements commonly used to index chemical weathering are variably mobile. This mobility may be linked to redistribution of suspended solids. A mass-balance model is presented that can quantify such redistribution without assuming immobility for any single element. Two tropical weathering profiles on quartz diorite and basalt are examined and redistribution of the HFS elements Zr and Ti is documented, along with potential corrections for the resulting changes in measured concentrations.
","language":"English","publisher":"Elsevier Ltd.","doi":"10.1016/j.apgeochem.2011.03.016","usgsCitation":"Bern, C.R., and White, A.F., 2011, A model for assessing, quantifying, and correcting for index element mobility in weathering studies: Applied Geochemistry, v. 26, p. S9-S11, https://doi.org/10.1016/j.apgeochem.2011.03.016.","productDescription":"3 p.","startPage":"S9","endPage":"S11","costCenters":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"links":[{"id":388427,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bern, Carleton R. 0000-0002-8980-1781 cbern@usgs.gov","orcid":"https://orcid.org/0000-0002-8980-1781","contributorId":201152,"corporation":false,"usgs":true,"family":"Bern","given":"Carleton","email":"cbern@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":821851,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White, Arthur F. afwhite@usgs.gov","contributorId":3718,"corporation":false,"usgs":true,"family":"White","given":"Arthur","email":"afwhite@usgs.gov","middleInitial":"F.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":821852,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70004525,"text":"ofr20111088 - 2011 - Demographics and run timing of adult Lost River (Deltistes luxatus) and short nose (Chasmistes brevirostris) suckers in Upper Klamath Lake, Oregon, 2009","interactions":[],"lastModifiedDate":"2017-05-30T13:33:07","indexId":"ofr20111088","displayToPublicDate":"2011-06-01T03:01:00","publicationYear":"2011","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":"2011-1088","title":"Demographics and run timing of adult Lost River (Deltistes luxatus) and short nose (Chasmistes brevirostris) suckers in Upper Klamath Lake, Oregon, 2009","docAbstract":"Data from a long-term capture-recapture program were used to assess the status and dynamics of populations of two long-lived, federally endangered catostomids in Upper Klamath Lake, Oregon. Lost River suckers (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris) have been captured and tagged with passive integrated transponder (PIT) tags during their spawning migrations in each year since 1995. In addition, beginning in 2005, individuals that had been previously PIT-tagged were reencountered on remote underwater antennas deployed throughout the spawning areas. Captures and remote encounters during spring 2009 were used to describe the spawning migrations in that year and also were incorporated into capture-recapture analyses of population dynamics over the last decade. Cormack-Jolly-Seber (CJS) open population capture-recapture models were used to estimate annual survival probabilities, and a reverse-time analog of the CJS model was used to estimate recruitment of new individuals into the spawning populations. In addition, data on the size composition of captured fish was examined for any additional evidence of recruitment. Survival and recruitment estimates were combined to estimate changes in population size over time and to determine the status of the populations through 2007. Separate analyses were conducted for each species and also for each subpopulation of Lost River suckers (LRS). One subpopulation of LRS migrates into tributaries to spawn, similar to shortnose suckers (SNS), whereas the other subpopulation spawns at upwelling areas along the eastern shoreline of the lake.
In 2009, we captured and tagged 781 LRS at four shoreline areas and recaptured an additional 638 individuals that had been tagged in previous years. Across all four areas, the remote antennas detected 6,056 individual LRS during the spawning season. Spawning activity peaked in April and most individuals were encountered at Sucker Springs and Cinder Flats. In the Williamson River, we captured and tagged 3,008 LRS and 287 SNS, and recaptured 271 LRS and 81 SNS that had been tagged in previous years. Remote antennas that spanned the river downstream of the tributary spawning areas detected a total of 12,509 LRS and 5,023 SNS. Most LRS passed upstream in mid-April when water temperatures were rising and near or greater than 10°C. In contrast, peaks in upstream passage of SNS occurred in late April and early May when water temperatures were rising and near or greater than 12°C. Finally, an additional 1,569 LRS and 1,794 SNS were captured in trammel net sampling at prespawn staging areas in the northeastern portion of the lake. Of these, 209 of the LRS and 452 of the SNS had been PIT-tagged in previous years. For LRS, encounter histories showed that nearly all of the fish captured at the staging areas were members of the subpopulation that spawns in the tributaries.
Capture-recapture analyses for the LRS subpopulation that spawns at the shoreline areas included encounter histories for more than 9,000 individuals, and analyses for the subpopulation that spawns in the tributaries included more than 14,000 encounter histories. With a few exceptions, the survival of males and females in both subpopulations was high (>0.9) between 1999 and 2007. Notably lower survival occurred for both sexes from the tributaries in 2000, for males from the shoreline areas in 2002, and for males from the tributaries in 2006. Recruitment of new individuals into either spawning population was trivial in all years between 2002 and 2007. Over that period, the abundance of males in the lakeshore spawning subpopulation declined by 44–53 percent and the abundance of females declined by 25–38 percent. Similarly, the abundance of males in the tributary spawning subpopulation declined by as much as 39 percent and the abundance of females declined by as much as 33 percent.
Capture-recapture analyses for SNS included encounter histories for more than 12,000 individuals. The majority of annual survival estimates between 2001 and 2007 were high (>0.8), but SNS experienced more years of low survival than either LRS subpopulation. The survival of both sexes was particularly low in both 2001 and 2004, and male survival also was somewhat low in 2002 and 2006. Similar to LRS, recruitment of new individuals into the spawning population was trivial in all years between 2001 and 2007. Over that period, the abundance of male SNS declined by 58–80 percent and the abundance of females declined by 52–73 percent.
Despite relatively high survival in most years, both species have experienced substantial declines in the abundance of spawning fish because losses from mortality have not been balanced by recruitment of new individuals. Indeed, all populations appear to be largely comprised of fish that were present in the late 1990s and early 2000s. As a result, the status of the endangered sucker populations in Upper Klamath Lake remains worrisome, and the situation is most dire for shortnose suckers. Survival analyses show that the two species do not necessarily experience poor survival in the same years and that poor survival on an annual scale is not predictable from fish die-offs observed in the summer and fall. Future analyses will explore the connections between annual sucker survival and environmental factors of interest, such as water quality and disease. Our monitoring program provides a robust platform for estimating vital population parameters, evaluating the status of the populations, and assessing the effectiveness of conservation and recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111088","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Hewitt, D.A., Hayes, B., Janney, E.C., Harris, A., Koller, J.P., and Johnson, M.A., 2011, Demographics and run timing of adult Lost River (Deltistes luxatus) and short nose (Chasmistes brevirostris) suckers in Upper Klamath Lake, Oregon, 2009: U.S. Geological Survey Open-File Report 2011-1088, iv, 20 p., https://doi.org/10.3133/ofr20111088.","productDescription":"iv, 20 p.","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":116648,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1088.bmp"},{"id":341861,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2011/1088/pdf/ofr20111088.pdf","text":"Report","size":"1.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":21827,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1088/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.1,42.233333333333334 ], [ -122.1,42.63333333333333 ], [ -121.71666666666667,42.63333333333333 ], [ -121.71666666666667,42.233333333333334 ], [ -122.1,42.233333333333334 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ab2e4b07f02db66ed0a","contributors":{"authors":[{"text":"Hewitt, David A. 0000-0002-5387-0275 dhewitt@usgs.gov","orcid":"https://orcid.org/0000-0002-5387-0275","contributorId":3767,"corporation":false,"usgs":false,"family":"Hewitt","given":"David","email":"dhewitt@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":350567,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hayes, Brian S. 0000-0001-8229-4070","orcid":"https://orcid.org/0000-0001-8229-4070","contributorId":37022,"corporation":false,"usgs":true,"family":"Hayes","given":"Brian S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":350568,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Janney, Eric C. 0000-0002-0228-2174","orcid":"https://orcid.org/0000-0002-0228-2174","contributorId":83629,"corporation":false,"usgs":true,"family":"Janney","given":"Eric","email":"","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":350570,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harris, Alta C. 0000-0002-2123-3028 aharris@usgs.gov","orcid":"https://orcid.org/0000-0002-2123-3028","contributorId":3490,"corporation":false,"usgs":true,"family":"Harris","given":"Alta C.","email":"aharris@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":350566,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Koller, Justin P.","contributorId":73720,"corporation":false,"usgs":true,"family":"Koller","given":"Justin","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":350569,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Mark A. majohnson@usgs.gov","contributorId":3373,"corporation":false,"usgs":true,"family":"Johnson","given":"Mark","email":"majohnson@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":350565,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70005065,"text":"70005065 - 2011 - Process-based model predictions of hurricane induced morphodynamic change on low-lying barrier islands","interactions":[],"lastModifiedDate":"2016-04-25T16:05:33","indexId":"70005065","displayToPublicDate":"2011-06-01T02:30:00","publicationYear":"2011","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"title":"Process-based model predictions of hurricane induced morphodynamic change on low-lying barrier islands","docAbstract":"Using Delft3D, a Chandeleur Island model was constructed to examine the sediment-transport patterns and morphodynamic change caused by Hurricane Katrina and similar storm events. The model setup included a coarse Gulf of Mexico domain and a nested finer-resolution Chandeleur Island domain. The finer-resolution domain resolved morphodynamic processes driven by storms and tides. A sensitivity analysis of the simulated morphodynamic response was performed to investigate the effects of variations in surge levels. The Chandeleur morphodynamic model reproduced several important features that matched observed morphodynamic changes. A simulation of bathymetric change driven by storm surge alone (no waves) along the central portion of the Chandeleur Islands showed (1) a general landward retreat and lowering of the island chain and (2) multiple breaches that increased the degree of island dissection. The locations of many of the breaches correspond with the low-lying or narrow sections of the initial bathymetry. The major part of the morphological change occurred prior to the peak of the surge when overtopping of the islands produced a strong water-level gradient and induced significant flow velocities.
Successful management of walleye and sauger populations often requires a detailed knowledge of prey resources. As with many fishes, diets of juvenile Sander spp. are often different than those of adult fish and can have important implications for growth and survival. Similarly, spatial and temporal variation in diet composition can contribute to variation in growth and production of Sander populations. Thus, management efforts (e.g., stocking) aimed at enhancing walleye and sauger populations benefit from the knowledge and tools to effectively quantify feeding patterns.
Today, fisheries managers face a myriad of challenges posed by nonnative species, eutrophication, climate change, and water availability, to name just a few. As a result, knowledge about prey use, energetics, and effects of Sander populations on food web structure has increased dramatically in the last 30 years. Experimental work with larval and juvenile walleyes has provided new insights into factors affecting growth and survival during early life stages (see Chapter 7) that has benefitted management and propagation efforts. Similarly, contemporary analytical approaches, such as bioenergetics modeling and stable isotope analysis, have improved our understanding of walleye foraging behavior and provided new tools for exploring trophic interactions. In this chapter, we review the general feeding ecology of walleye and sauger and highlight contemporary approaches for quantifying energy acquisition and trophic interactions.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Biology, management, and culture of walleye and sauger","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Fisheries Society","doi":"10.47886/9781934874226.ch8","usgsCitation":"Chipps, S.R., and Graeb, B.D., 2011, Feeding ecology and energetics, chap. 8 of Biology, management, and culture of walleye and sauger, https://doi.org/10.47886/9781934874226.ch8.","ipdsId":"IP-028686","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":332211,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58550b83e4b02bdf681568bb","contributors":{"editors":[{"text":"Barton, Bruce A.","contributorId":177521,"corporation":false,"usgs":false,"family":"Barton","given":"Bruce","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":656054,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Chipps, Steven R. 0000-0001-6511-7582 steve_chipps@usgs.gov","orcid":"https://orcid.org/0000-0001-6511-7582","contributorId":2243,"corporation":false,"usgs":true,"family":"Chipps","given":"Steven","email":"steve_chipps@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":640965,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graeb, Brian D. S.","contributorId":171851,"corporation":false,"usgs":false,"family":"Graeb","given":"Brian","email":"","middleInitial":"D. S.","affiliations":[{"id":26956,"text":"Departement of Natural Resource Management, Brookings, SD","active":true,"usgs":false}],"preferred":false,"id":656053,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70145800,"text":"70145800 - 2011 - Misidentification of freshwater mussel species (Bivalvia:Unionidae): Contributing factors, management implications, and potential solutions","interactions":[],"lastModifiedDate":"2021-05-11T13:48:54.281993","indexId":"70145800","displayToPublicDate":"2011-06-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2564,"text":"Journal of the North American Benthological Society","onlineIssn":"1937-237X","printIssn":"0887-3593","active":true,"publicationSubtype":{"id":10}},"title":"Misidentification of freshwater mussel species (Bivalvia:Unionidae): Contributing factors, management implications, and potential solutions","docAbstract":"Surveys of freshwater mussel populations are used frequently to inform conservation decisions by providing information about the status and distribution of species. It is generally accepted that not all mussels or species are collected during surveys, and incomplete detection of individuals and species can bias data and can affect inferences. However, considerably less attention has been given to the potential effects of species misidentification. To evaluate the prevalence of and potential reasons for species misidentification, we conducted a laboratory-based identification exercise and quantified the relationships between mussel species characteristics, observer experience, and misidentification rate. We estimated that misidentification was fairly common, with rates averaging 27% across all species and ranging from 0 to 56%, and was related to mussel shell characteristics and observer experience. Most notably, species with shell texturing were 6.09× less likely than smooth-shelled species to be misidentified. Misidentification rates declined with observer experience, but for many species the risk of misidentification averaged >10% even for observers with moderate levels of experience (5–6 y). In addition, misidentification rates among observers showed substantial variability after controlling for experience. Our results suggest that species misidentification may be common in field surveys of freshwater mussels and could potentially bias estimates of population status and trends. Misidentification rates possibly could be reduced through use of regional workshops, testing and certification programs, and the availability of archived specimens and tissue samples in museum collections.
","language":"English","publisher":"The Society for Freshwater Science","doi":"10.1899/10-073.1","usgsCitation":"Shea, C.P., Peterson, J., Wisniewski, J.M., and Johnson, N.A., 2011, Misidentification of freshwater mussel species (Bivalvia:Unionidae): Contributing factors, management implications, and potential solutions: Journal of the North American Benthological Society, v. 30, no. 2, p. 446-458, https://doi.org/10.1899/10-073.1.","productDescription":"13 p.","startPage":"446","endPage":"458","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-022576","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":299519,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"30","issue":"2","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55265129e4b026915857c64a","contributors":{"authors":[{"text":"Shea, Colin P.","contributorId":140147,"corporation":false,"usgs":false,"family":"Shea","given":"Colin","email":"","middleInitial":"P.","affiliations":[{"id":13267,"text":"Warnell School of Forestry and Natural Resources, University of Georgia","active":true,"usgs":false}],"preferred":false,"id":544445,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peterson, James T. 0000-0002-7709-8590 james_peterson@usgs.gov","orcid":"https://orcid.org/0000-0002-7709-8590","contributorId":2111,"corporation":false,"usgs":true,"family":"Peterson","given":"James","email":"james_peterson@usgs.gov","middleInitial":"T.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":544386,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wisniewski, Jason M.","contributorId":140148,"corporation":false,"usgs":false,"family":"Wisniewski","given":"Jason","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":544446,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Nathan A. 0000-0001-5167-1988 najohnson@usgs.gov","orcid":"https://orcid.org/0000-0001-5167-1988","contributorId":4175,"corporation":false,"usgs":true,"family":"Johnson","given":"Nathan","email":"najohnson@usgs.gov","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":544447,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70155352,"text":"70155352 - 2011 - The distribution and abundance ofa nuisance native alga, Didymosphenia geminata,in streams of Glacier National Park: Climate drivers and management implications","interactions":[],"lastModifiedDate":"2016-09-08T14:32:25","indexId":"70155352","displayToPublicDate":"2011-06-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3014,"text":"Park Science","active":true,"publicationSubtype":{"id":10}},"title":"The distribution and abundance ofa nuisance native alga, Didymosphenia geminata,in streams of Glacier National Park: Climate drivers and management implications","docAbstract":"Didymosphenia geminata (didymo) is a freshwater alga native to North America, including Glacier National Park, Montana. It has long been considered a cold-water species, but has recently spread to lower latitudes and warmer waters, and increasingly forms large blooms that cover streambeds. We used a comprehensive monitoring data set from the National Park Service (NPS) and USGS models of stream temperatures to explore the drivers of didymo abundance in Glacier National Park. We estimate that approximately 64% of the stream length in the park contains didymo, with around 5% in a bloom state. Results suggest that didymo abundance likely increased over the study period (2007–2009), with blooms becoming more common. Our models suggest that didymo abundance is positively related to summer stream temperatures and negatively related to total nitrogen and the distance downstream from lakes. Regional climate model simulations indicate that stream temperatures in the park will likely continue to increase over the coming decades, which may increase the extent and severity of didymo blooms. As a result, didymo may be a useful indicator of thermal and hydrological modification associated with climate warming, especially in a relatively pristine system like Glacier where proximate human-related disturbances are absent or reduced. Glacier National Park plays an important role as a sentinel for climate change and associated education across the Rocky Mountain region.
","language":"English","publisher":"Park Science","usgsCitation":"Muhlfeld, C.C., Jones, L.A., E. William Schweiger, Ashton, I.W., and Bahls, L.L., 2011, The distribution and abundance ofa nuisance native alga, Didymosphenia geminata,in streams of Glacier National Park: Climate drivers and management implications: Park Science, v. 28, no. 2, p. 88-91.","productDescription":"4 p. ","startPage":"88","endPage":"91","ipdsId":"IP-028364","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":328407,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Glacier National Park ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.147705078125,\n 48.98382212608503\n ],\n [\n -113.54919433593749,\n 48.99103162515997\n ],\n [\n -113.0987548828125,\n 48.352598707539286\n ],\n [\n -113.741455078125,\n 48.19904897935913\n ],\n [\n -115.147705078125,\n 48.929717630629554\n ],\n [\n -115.147705078125,\n 48.98382212608503\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57d28bafe4b0571647d0f94c","contributors":{"authors":[{"text":"Muhlfeld, Clint C. 0000-0002-4599-4059 cmuhlfeld@usgs.gov","orcid":"https://orcid.org/0000-0002-4599-4059","contributorId":924,"corporation":false,"usgs":true,"family":"Muhlfeld","given":"Clint","email":"cmuhlfeld@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":565541,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Leslie A. 0000-0002-4953-7189 lajones@usgs.gov","orcid":"https://orcid.org/0000-0002-4953-7189","contributorId":4599,"corporation":false,"usgs":true,"family":"Jones","given":"Leslie","email":"lajones@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":565542,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"E. 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Simulated daily streamflow and energy output from the watershed models were used to compute a range of statistics. With a side-by-side comparison of the statistical analyses for the 14 basins, regional climatic and hydrologic trends over the twenty-first century could be qualitatively identified. Low-flow statistics (95% exceedance, 7-day mean annual minimum, and summer mean monthly streamflow) decreased for almost all basins. Annual maximum daily streamflow also decreased in all the basins, except for all four basins in California and the Pacific Northwest. An analysis of the supply of available energy and water for the basins indicated that ratios of evaporation to precipitation and potential evapotranspiration to precipitation for most of the basins will increase. Probability density functions (PDFs) were developed to assess the uncertainty and multimodality in the impact of climate change on mean annual streamflow variability. Kolmogorov?Smirnov tests showed significant differences between the beginning and ending twenty-first-century PDFs for most of the basins, with the exception of four basins that are located in the western United States. Almost none of the basin PDFs were normally distributed, and two basins in the upper Midwest had PDFs that were extremely dispersed and skewed.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Earth Interactions","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Meteorological Society","doi":"10.1175/2010EI364.1","usgsCitation":"Risley, J., Moradkhani, H., Hay, L.E., and Markstrom, S., 2011, Statistical Comparisons of watershed scale response to climate change in selected basins across the United States: Earth Interactions, v. 15, no. 14, p. 1-26, https://doi.org/10.1175/2010EI364.1.","productDescription":"26 p.","startPage":"1","endPage":"26","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":474997,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/2010ei364.1","text":"Publisher Index Page"},{"id":204268,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":110886,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1175/2010EI364.1"}],"country":"United States","volume":"15","issue":"14","noUsgsAuthors":false,"publicationDate":"2011-05-01","publicationStatus":"PW","scienceBaseUri":"4f4e49dee4b07f02db5e2a24","contributors":{"authors":[{"text":"Risley, John","contributorId":38128,"corporation":false,"usgs":true,"family":"Risley","given":"John","affiliations":[],"preferred":false,"id":346880,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moradkhani, Hamid","contributorId":42344,"corporation":false,"usgs":true,"family":"Moradkhani","given":"Hamid","email":"","affiliations":[],"preferred":false,"id":346881,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hay, Lauren E. 0000-0003-3763-4595 lhay@usgs.gov","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":1287,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","email":"lhay@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":346882,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Markstrom, Steve","contributorId":23682,"corporation":false,"usgs":true,"family":"Markstrom","given":"Steve","affiliations":[],"preferred":false,"id":346879,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70004524,"text":"sir20115069 - 2011 - Geologic framework and hydrogeologic characteristics in the southern part of the Rancho Diana Natural Area, northern Bexar County, Texas, 2008-10","interactions":[],"lastModifiedDate":"2017-03-29T16:07:20","indexId":"sir20115069","displayToPublicDate":"2011-05-31T10:01:04","publicationYear":"2011","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":"2011-5069","title":"Geologic framework and hydrogeologic characteristics in the southern part of the Rancho Diana Natural Area, northern Bexar County, Texas, 2008-10","docAbstract":"The area designated by the city of San Antonio as the Rancho Diana Natural Area is in northern Bexar County, near San Antonio, Texas. During 2008-10, the U.S. Geological Survey, in cooperation with the city of San Antonio, documented the geologic framework and mapped the hydrogeologic characteristics for the southern part of the Rancho Diana Natural Area. The geologic framework of the study area and its hydrogeologic characteristics were documented using field observations and information from previously published reports. Many of the geologic and hydrogeologic features were found by making field observations through the dense vegetation along gridlines spaced approximately 25 feet apart and documenting the features as they were located. Surface geologic features were identified and hydrogeologic features such as caves, sinkholes, and areas of solutionally enlarged porosity were located using hand-held Global Positioning System units. The location data were used to create a map of the hydrogeologic subdivisions and the location of karst features. The outcrops of the Edwards and Trinity aquifer recharge zones were mapped by using hydrogeologic subdivisions modified from previous reports. All rocks exposed within the study area are of sedimentary origin and Lower Cretaceous in age. The valley floor is formed in the cavernous member of the upper Glen Rose Limestone of the Trinity Group. The hills are composed of the basal nodular member, dolomitic member, Kirschberg evaporite member, and grainstone member of the Kainer Formation of the Edwards Group. Field observations made during this study of the exposed formations and members indicate that the formations and members typically are composed of mudstones, wackestones, packstones, grainstones, and argillaceous limestones, along with marls. The upper Glen Rose Limestone is approximately 410 to 450 feet thick but only the upper 70 feet is exposed in the study area. The Kainer Formation is approximately 255 feet thick in the study area and is composed of, in ascending order, the basal nodular member, dolomitic member, Kirschberg evaporite member, and grainstone member. The Edwards and Trinity aquifers contain a combination of fabric-selective and not-fabric-selective porosities. Porosity types observed in the study area that can increase the effective porosity and increase permeability include solutionally enlarged caves, sinkholes, fractures, bedding planes, channels, molds and vugs. Caves found during hydrogeologic mapping might have been spring discharge points, but sufficient downcutting over geologic time in the rocks has occurred so that springs discharge at lower elevations near the creek channel. The mapped caves, sinkholes, and other areas of solutionally enlarged porosity might facilitate recharge during large storm events when runoff occurs on the hillsides; additional areally distributed recharge in the study area occurs as a result of infiltration.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115069","collaboration":"In cooperation with the City of San Antonio","usgsCitation":"Clark, A.K., and Morris, R., 2011, Geologic framework and hydrogeologic characteristics in the southern part of the Rancho Diana Natural Area, northern Bexar County, Texas, 2008-10: U.S. Geological Survey Scientific Investigations Report 2011-5069, v, 19 p., https://doi.org/10.3133/sir20115069.","productDescription":"v, 19 p.","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2008-01-01","temporalEnd":"2010-12-31","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":116841,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5069.jpg"},{"id":21820,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5069/","linkFileType":{"id":5,"text":"html"}},{"id":338706,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2011/5069/pdf/sir2011-5069.pdf","text":"Report","size":"20 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Texas","county":"Bexar","otherGeospatial":"Rancho Diana Natural Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.67679595947266,\n 29.61763959537609\n ],\n [\n -98.68091583251953,\n 29.61465489947712\n ],\n [\n -98.68640899658203,\n 29.608685242542364\n ],\n [\n -98.68881225585938,\n 29.59883453582689\n ],\n [\n -98.68331909179688,\n 29.59077415103838\n ],\n [\n -98.67610931396484,\n 29.585997322833492\n ],\n [\n -98.66546630859375,\n 29.58629588122112\n ],\n [\n -98.65585327148438,\n 29.5922668634766\n ],\n [\n -98.6517333984375,\n 29.602118211647333\n ],\n [\n -98.64212036132812,\n 29.612267079123548\n ],\n [\n -98.64280700683592,\n 29.622713375554916\n ],\n [\n -98.64967346191406,\n 29.626891590943814\n ],\n [\n -98.65791320800781,\n 29.62629471363916\n ],\n [\n -98.66752624511719,\n 29.62539939105201\n ],\n [\n -98.67233276367188,\n 29.622414924968727\n ],\n [\n -98.67679595947266,\n 29.61763959537609\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b15e4b07f02db6a4819","contributors":{"authors":[{"text":"Clark, Allan K. 0000-0003-0099-1521 akclark@usgs.gov","orcid":"https://orcid.org/0000-0003-0099-1521","contributorId":1279,"corporation":false,"usgs":true,"family":"Clark","given":"Allan","email":"akclark@usgs.gov","middleInitial":"K.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":350563,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morris, Robert R. 0000-0001-7504-3732","orcid":"https://orcid.org/0000-0001-7504-3732","contributorId":106213,"corporation":false,"usgs":true,"family":"Morris","given":"Robert R.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":350564,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70173876,"text":"70173876 - 2011 - Interrelationships between fish tissue mercury concentrations and water quality for South Dakota natural lakes and impoundments","interactions":[],"lastModifiedDate":"2018-02-13T10:31:39","indexId":"70173876","displayToPublicDate":"2011-05-27T10:30:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3728,"text":"Water, Air, & Soil Pollution","onlineIssn":"1573-2932","printIssn":"0049-6979","active":true,"publicationSubtype":{"id":10}},"title":"Interrelationships between fish tissue mercury concentrations and water quality for South Dakota natural lakes and impoundments","docAbstract":"The purpose of this study was to determine whether water quality parameters commonly associated with primary productivity may be used to predict the susceptibility of a specific water body to exceed proposed fish consumption advisory limitation of 0.3 mg kg−1. South Dakota currently has nine lakes and impoundments that exceed fish tissue mercury advisory limits of 1.0 mg kg−1 total mercury, far exceeding US Environmental Protection Agency and Food and Drug Administration 0.3 mg kg−1 consumption criteria. Previous studies suggest that increased aquatic productivity may mitigate the effects of biological production and subsequent uptake of methyl mercury through bio-dilution; however, it is uncertain whether these trends may exist within highly alkaline and highly productive aquatic conditions common to South Dakota lakes and impoundments. Water quality parameters and fish tissue mercury data for northern pike and walleye were collected and assessed using existing South Dakota Department of Environment and Natural Resources and Game Fish and Parks data. The data was initially screened using both parametric linear regression and non-parametric Mann–Whitney rank sum comparisons and further assessed using binary logistic regression and stepwise logistic regression methodology. Three separate phosphorus measurements (total, total dissolved, and Trophic State Index) and pH were determined to significantly correlate with increased mercury concentrations for the northern pike-in-impoundments model. However, phosphorus surprisingly was not a strong predictor for the remaining scenarios modeled. For the northern pike-in-natural lakes models, alkalinity was the most significant water quality parameter predicting increased mercury concentrations. Mercury concentrations for the walleye-in-natural lakes models were further influenced by pH and alkalinity. The water quality and fish tissue mercury interrelationships determined within this study suggest aquatic productivity, and consequential eutrophication processes appear to be reasonable indicators of fish tissue mercury susceptibility for aquatic conditions common to South Dakota and highlight the continuing need to minimize eutrophication through effective watershed management strategies.
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optimal selection of sampling sites for monitoring networks","docAbstract":"Environmental monitoring programs must efficiently describe state shifts. We propose using maximum entropy modeling to select dissimilar sampling sites to capture environmental variability at low cost, and demonstrate a specific application: sample site selection for the Central Plains domain (453,490 km2) of the National Ecological Observatory Network (NEON). We relied on four environmental factors: mean annual temperature and precipitation, elevation, and vegetation type. A “sample site” was defined as a 20 km × 20 km area (equal to NEON’s airborne observation platform [AOP] footprint), within which each 1 km2 cell was evaluated for each environmental factor. After each model run, the most environmentally dissimilar site was selected from all potential sample sites. The iterative selection of eight sites captured approximately 80% of the environmental envelope of the domain, an improvement over stratified random sampling and simple random designs for sample site selection. 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To better understand the groundwater availability in the valley, the U.S. Geological Survey (USGS) developed the Central Valley hydrologic model (CVHM). Because of recent water-level declines and renewed subsidence, the CVHM is being updated to better simulate the geohydrologic system. The CVHM updates and refinements can be grouped into two general categories: (1) model code changes and (2) data updates. The CVHM updates and refinements will require that the model be recalibrated. The updated CVHM will provide a detailed transient analysis of changes in groundwater availability and flow paths in relation to climatic variability, urbanization, stream flow, and changes in irrigated agricultural practices and crops. The updated CVHM is particularly focused on more accurately simulating the locations and magnitudes of land subsidence. The intent of the updated CVHM is to help scientists better understand the availability and sustainability of water resources and the interaction of groundwater levels with land subsidence.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"World environmental and water resources congress 2011: Bearing knowledge for sustainability","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"World Environmental and Water Resources Congress 2011","conferenceDate":"May 22-26 2011","conferenceLocation":"Palm Springs, California","language":"English","publisher":"American Society of Civil Engineers","doi":"10.1061/41173(414)88","usgsCitation":"Faunt, C., Hanson, R.T., Martin, P., and Schmid, W., 2011, Planned updates and refinements to the Central Valley hydrologic model with an emphasis on improving the simulation of land subsidence in the San Joaquin Valley, in World environmental and water resources congress 2011: Bearing knowledge for sustainability, Palm Springs, California, May 22-26 2011, p. 864-870, https://doi.org/10.1061/41173(414)88.","productDescription":"7 p.","startPage":"864","endPage":"870","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-026942","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":308612,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Joaquin Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.11376953125,\n 35.17380831799959\n ],\n [\n -118.47656249999999,\n 36.35052700542763\n ],\n [\n -120.76171875,\n 38.87392853923629\n ],\n [\n -121.728515625,\n 40.17887331434696\n ],\n [\n -122.32177734375,\n 40.48038142908172\n ],\n [\n -122.56347656249999,\n 39.57182223734374\n ],\n [\n -121.6845703125,\n 37.94419750075404\n ],\n [\n -120.10253906249999,\n 36.01356058518153\n ],\n [\n -119.11376953125,\n 35.17380831799959\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2012-04-26","publicationStatus":"PW","scienceBaseUri":"56067036e4b058f706e51945","contributors":{"authors":[{"text":"Faunt, Claudia C. 0000-0001-5659-7529 ccfaunt@usgs.gov","orcid":"https://orcid.org/0000-0001-5659-7529","contributorId":1491,"corporation":false,"usgs":true,"family":"Faunt","given":"Claudia C.","email":"ccfaunt@usgs.gov","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":573555,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hanson, Randall T. 0000-0002-9819-7141 rthanson@usgs.gov","orcid":"https://orcid.org/0000-0002-9819-7141","contributorId":801,"corporation":false,"usgs":true,"family":"Hanson","given":"Randall","email":"rthanson@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":573556,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martin, Peter pmmartin@usgs.gov","contributorId":799,"corporation":false,"usgs":true,"family":"Martin","given":"Peter","email":"pmmartin@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":573557,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schmid, Wolfgang","contributorId":84020,"corporation":false,"usgs":false,"family":"Schmid","given":"Wolfgang","affiliations":[{"id":13040,"text":"Department of Hydrology and Water Resources, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":573558,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70005228,"text":"70005228 - 2011 - Estimating occupancy dynamics in an anuran assemblage from Louisiana, USA","interactions":[],"lastModifiedDate":"2020-01-28T09:35:43","indexId":"70005228","displayToPublicDate":"2011-05-25T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Estimating occupancy dynamics in an anuran assemblage from Louisiana, USA","docAbstract":"Effective monitoring programs are designed to track changes in the distribution, occurrence, and abundance of species. We developed an extension of Royle and Kéry's (2007) single species model to estimate simultaneously temporal changes in probabilities of detection, occupancy, colonization, extinction, and species turnover using data on calling anuran amphibians, collected from 2002 to 2006 in the Lower Mississippi Alluvial Valley of Louisiana, USA. During our 5-year study, estimates of occurrence probabilities declined for all 12 species detected. These declines occurred primarily in conjunction with variation in estimates of local extinction probabilities (cajun chorus frog [Pseudacris fouquettei], spring peeper [P. crucifer], northern cricket frog [Acris crepitans], Cope's gray treefrog [Hyla chrysoscelis], green treefrog [H. cinerea], squirrel treefrog [H. squirella], southern leopard frog [Lithobates sphenocephalus], bronze frog [L. clamitans], American bullfrog [L. catesbeianus], and Fowler's toad [Anaxyrus fowleri]). For 2 species (eastern narrowmouthed toad [Gastrophryne carolinensis] and Gulf Coast toad [Incilius nebulifer]), declines in occupancy appeared to be a consequence of both increased local extinction and decreased colonization events. The eastern narrow-mouthed toad experienced a 2.5-fold increase in estimates of occupancy in 2004, possibly because of the high amount of rainfall received during that year, along with a decrease in extinction and increase in colonization of new sites between 2003 and 2004. Our model can be incorporated into monitoring programs to estimate simultaneously the occupancy dynamics for multiple species that show similar responses to ecological conditions. It will likely be an important asset for those monitoring programs that employ the same methods to sample assemblages of ecologically similar species, including those that are rare. By combining information from multiple species to decrease the variance on estimates of individual species, our results are advantageous compared to single-species models. This feature enables managers and researchers to use an entire community, rather than just one species, as an ecological indicator in monitoring programs.","language":"English","publisher":"Wildlife Society","doi":"10.1002/jwmg.97","usgsCitation":"Walls, S., Waddle, J., and Dorazio, R.M., 2011, Estimating occupancy dynamics in an anuran assemblage from Louisiana, USA: Journal of Wildlife Management, v. 75, no. 4, p. 751-761, https://doi.org/10.1002/jwmg.97.","productDescription":"11 p.","startPage":"751","endPage":"761","temporalStart":"2002-01-01","temporalEnd":"2006-12-31","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":204251,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Atchafalaya Basin, Lower Mississippi Alluvial Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.8731689453125,\n 29.89304338543419\n ],\n [\n -91.8731689453125,\n 30.576450026618076\n ],\n [\n -91.373291015625,\n 30.576450026618076\n ],\n [\n -91.373291015625,\n 29.89304338543419\n ],\n [\n -91.8731689453125,\n 29.89304338543419\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"75","issue":"4","noUsgsAuthors":false,"publicationDate":"2011-05-25","publicationStatus":"PW","scienceBaseUri":"4f4e4a0ce4b07f02db5fc9db","contributors":{"authors":[{"text":"Walls, Susan C. 0000-0001-7391-9155","orcid":"https://orcid.org/0000-0001-7391-9155","contributorId":52284,"corporation":false,"usgs":true,"family":"Walls","given":"Susan C.","affiliations":[],"preferred":false,"id":352105,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waddle, J. Hardin 0000-0003-1940-2133","orcid":"https://orcid.org/0000-0003-1940-2133","contributorId":89982,"corporation":false,"usgs":true,"family":"Waddle","given":"J. Hardin","affiliations":[],"preferred":false,"id":352106,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dorazio, Robert M. 0000-0003-2663-0468 bob_dorazio@usgs.gov","orcid":"https://orcid.org/0000-0003-2663-0468","contributorId":1668,"corporation":false,"usgs":true,"family":"Dorazio","given":"Robert","email":"bob_dorazio@usgs.gov","middleInitial":"M.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":352104,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":99284,"text":"ofr20111125 - 2011 - Threats of habitat and water-quality degradation to mussel diversity in the Meramec River Basin, Missouri, USA","interactions":[],"lastModifiedDate":"2019-07-09T15:47:36","indexId":"ofr20111125","displayToPublicDate":"2011-05-25T00:00:00","publicationYear":"2011","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":"2011-1125","title":"Threats of habitat and water-quality degradation to mussel diversity in the Meramec River Basin, Missouri, USA","docAbstract":"The Meramec River Basin in east-central Missouri is an important stronghold for native freshwater mussels (Order: Unionoida) in the United States. Whereas the basin supports more than 40 mussel species, previous studies indicate that the abundance and distribution of most species are declining. Therefore, resource managers have identified the need to prioritize threats to native mussel populations in the basin and to design a mussel monitoring program. The objective of this study was to identify threats of habitat and water-quality degradation to mussel diversity in the basin. Affected habitat parameters considered as the main threats to mussel conservation included excess sedimentation, altered stream geomorphology and flow, effects on riparian vegetation and condition, impoundments, and invasive non-native species. Evaluating water-quality parameters for conserving mussels was a main focus of this study. Mussel toxicity data for chemical contaminants were compared to national water quality criteria (NWQC) and Missouri water quality standards (MWQS). However, NWQC and MWQS have not been developed for many chemical contaminants and some MWQS may not be protective of native mussel populations. Toxicity data indicated that mussels are sensitive to ammonia, copper, temperature, certain pesticides, pharmaceuticals, and personal care products; these compounds were identified as the priority water-quality parameters for mussel conservation in the basin. Measures to conserve mussel diversity in the basin include expanding the species and life stages of mussels and the list of chemical contaminants that have been assessed, establishing a long term mussel monitoring program that measures physical and chemical parameters of high priority, conducting landscape scale modeling to predict mussel distributions, determining sublethal effects of primary contaminants of concern, deriving risk-based guidance values for mussel conservation, and assessing the effects of wastewater treatment plants and non-point source pollution on mussels. A critical next step to further prioritize these needs is to conduct a watershed risk assessment using local data (for example, land use, flow) when available.\r\n","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111125","collaboration":"A report to the Missouri Department of Conservation","usgsCitation":"Hinck, J.E., Ingersoll, C.G., Wang, N., Augspurger, T., Barnhart, M., McMurray, S., Roberts, A.D., and Schrader, L., 2011, Threats of habitat and water-quality degradation to mussel diversity in the Meramec River Basin, Missouri, USA: U.S. Geological Survey Open-File Report 2011-1125, vi, 18 p., https://doi.org/10.3133/ofr20111125.","productDescription":"vi, 18 p.","additionalOnlineFiles":"N","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":116647,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1125.jpg"},{"id":204783,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1125/","linkFileType":{"id":5,"text":"html"}},{"id":334505,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2011/1125/pdf/of2011_1125.pdf","size":"529 kB","linkFileType":{"id":1,"text":"pdf"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92,37.25 ], [ -92,38.75 ], [ -90,38.75 ], [ -90,37.25 ], [ -92,37.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a54e4b07f02db62bc58","contributors":{"authors":[{"text":"Hinck, Jo Ellen 0000-0002-4912-5766","orcid":"https://orcid.org/0000-0002-4912-5766","contributorId":38507,"corporation":false,"usgs":true,"family":"Hinck","given":"Jo","email":"","middleInitial":"Ellen","affiliations":[],"preferred":false,"id":307998,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ingersoll, Christopher G. 0000-0003-4531-5949 cingersoll@usgs.gov","orcid":"https://orcid.org/0000-0003-4531-5949","contributorId":2071,"corporation":false,"usgs":true,"family":"Ingersoll","given":"Christopher","email":"cingersoll@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":307995,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Ning 0000-0002-2846-3352 nwang@usgs.gov","orcid":"https://orcid.org/0000-0002-2846-3352","contributorId":2818,"corporation":false,"usgs":true,"family":"Wang","given":"Ning","email":"nwang@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":307996,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Augspurger, Tom","contributorId":63921,"corporation":false,"usgs":true,"family":"Augspurger","given":"Tom","affiliations":[],"preferred":false,"id":308001,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barnhart, M. Christopher","contributorId":78061,"corporation":false,"usgs":true,"family":"Barnhart","given":"M. Christopher","affiliations":[],"preferred":false,"id":308002,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McMurray, Stephen E.","contributorId":38687,"corporation":false,"usgs":true,"family":"McMurray","given":"Stephen E.","affiliations":[],"preferred":false,"id":307999,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Roberts, Andrew D.","contributorId":52304,"corporation":false,"usgs":true,"family":"Roberts","given":"Andrew","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":308000,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schrader, Lynn","contributorId":14551,"corporation":false,"usgs":true,"family":"Schrader","given":"Lynn","email":"","affiliations":[],"preferred":false,"id":307997,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":99283,"text":"sim3121 - 2011 - Geologic map of the Ganiki Planitia quadrangle (V-14), Venus","interactions":[],"lastModifiedDate":"2023-03-16T10:55:03.655596","indexId":"sim3121","displayToPublicDate":"2011-05-24T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3121","title":"Geologic map of the Ganiki Planitia quadrangle (V-14), Venus","docAbstract":"The Ganiki Planitia (V-14) quadrangle on Venus, which extends from 25° N. to 50° N. and from 180° E. to 210° E., derives its name from the extensive suite of plains that dominates the geology of the northern part of the region. With a surface area of nearly 6.5 x 106 km2 (roughly two-thirds that of the United States), the quadrangle is located northwest of the Beta-Atla-Themis volcanic zone and southeast of the Atalanta Planitia lowlands, areas proposed to be the result of large scale mantle upwelling and downwelling, respectively. The region immediately south of Ganiki Planitia is dominated by Atla Regio, a major volcanic rise beneath which localized upwelling appears to be ongoing, whereas the area just to the north is dominated by the orderly system of north-trending deformation belts that characterize Vinmara Planitia. The Ganiki Planitia quadrangle thus lies at the intersection between several physiographic regions where extensive mantle flow-induced tectonic and volcanic processes are thought to have occurred.\r\nThe geology of the V-14 quadrangle is characterized by a complex array of volcanic, tectonic, and impact-derived features. There are eleven impact craters with diameters from 4 to 64 km, as well as four diffuse 'splotch' features interpreted to be the product of near-surface bolide explosions. Tectonic activity has produced heavily deformed tesserae, belts of complex deformation and rifts as well as a distributed system of fractures and wrinkle ridges. Volcanic activity has produced extensive regional plains deposits, and in the northwest corner of the quadrangle these plains host the initial (or terminal) 700 km of the Baltis Vallis canali, an enigmatic volcanic feature with a net length of ~7,000 km that is the longest channel on Venus. Major volcanic centers in V-14 include eight large volcanoes and eight coronae; all but one of these sixteen features was noted during a previous global survey. The V-14 quadrangle contains an abundance of minor volcanic features including individual shield volcanoes and localized fissure eruptions as well as many small annular structures and domes, which often serve as the source for local lava flows.\r\nThe topographic and geophysical characteristics of the Ganiki Planitia quadrangle are less complex than the surface geology, but they yield equally valuable information about the region’s formation and evolution. Referenced to the mean planetary radius of 6051.84 km, the average elevation in the quadrangle is -0.26±0.86 km (2σ) with a full range of -2.58 km to 1.85 km. The highest 2.5 percent of elevations in the quadrangle (above 0.60 km) are associated primarily with the major tessera blocks and the peaks of a few volcanic edifices, whereas the lowest 2.5 percent (below -1.12 km) mostly occur within corona interiors and in the northwest corner of the quadrangle where the plains begin to merge into the Atalanta Planitia lowlands. At the ~4.6 km/pixel scale of the topography data, the mean point-to-point topographic slope is 0.63° and topographic slopes greater than 2° cover less than 5 percent of the region. Overall, the topography of the Ganiki Planitia quadrangle can be characterized as flat, low lying, and nearly devoid of abrupt topographic variation. Complementing this gentle topography, the geoid anomaly has a generally linear gradient that decreases north-northwest from a high of ~20 m at the southern edge of the quadrangle (the northern border of the Atla Regio anomaly) to a low of -30 to -40 m along the northern edge (Konopliv and others, 1999). The vertical component of the gravity anomaly varies from ~50 mGal to -40 mGal, and integrated analysis of the gravity and topography data indicates that dynamically supported regions and areas of thickened crust are both present within the quadrangle.\r\nBecause the Ganiki Planitia quadrangle is a plains-dominated lowland area that lies between several major physiographic provinces (namely, Atla Regio, Atalanta Planitia, and Vinmara Planitia), a geologic map of the region may yield insight into a wide array of important problems in Venusian geology. The current mapping effort and analysis complements previous efforts to characterize aspects of the region’s geology, for example stratigraphy near parabolic halo crater sites, volcanic plains emplacement, wrinkle ridges, volcanic feature distribution, volcano deformation, coronae characteristics, lithospheric flexure, and various features along a 30±7.58° N. geotraverse. Our current research focuses on addressing four specific questions. Has the dominant style of volcanic expression within the quadrangle varied in a systematic fashion over time? Does the tectonic deformation within the quadrangle record significant regional patterns that vary spatially or temporally, and if so what are the scales, orientations and sources of the stress fields driving this deformation? If mantle upwelling and downwelling have played a significant role in the formation of Atla Regio and Atalanta Planitia as has been proposed, does the geology of Ganiki Planitia record evidence of northwest-directed lateral mantle flow connecting the two sites? Finally, can integration of the tectonic and volcanic histories preserved within the quadrangle help constrain competing resurfacing models for Venus?","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/sim3121","collaboration":"Prepared for the National Aeronautics and Space Administration","usgsCitation":"Grosfils, E.B., Long, S.M., Venechuk, E.M., Hurwitz, D.M., Richards, J.W., Drury, D.E., and Hardin, J., 2011, Geologic map of the Ganiki Planitia quadrangle (V-14), Venus: U.S. Geological Survey Scientific Investigations Map 3121, Map: 43.86 inches x 36.87 inches; Pamphlet: ii, 30 p., https://doi.org/10.3133/sim3121.","productDescription":"Map: 43.86 inches x 36.87 inches; Pamphlet: ii, 30 p.","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":116211,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim_3121.jpg"},{"id":204782,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3121/","linkFileType":{"id":5,"text":"html"}},{"id":414265,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://doi.org/10.5066/P9NSC8UY","text":"Interactive map","linkHelpText":"- Geologic Map of the Ganiki Planitia Quadrangle (V-14) of Venus, 1:5M. Grosfils and others (2011)"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4afee4b07f02db697873","contributors":{"authors":[{"text":"Grosfils, Eric B.","contributorId":27752,"corporation":false,"usgs":true,"family":"Grosfils","given":"Eric","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":307989,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Long, Sylvan M.","contributorId":14699,"corporation":false,"usgs":true,"family":"Long","given":"Sylvan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":307988,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Venechuk, Elizabeth M.","contributorId":50053,"corporation":false,"usgs":true,"family":"Venechuk","given":"Elizabeth","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":307991,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hurwitz, Debra M.","contributorId":43614,"corporation":false,"usgs":true,"family":"Hurwitz","given":"Debra","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":307990,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Richards, Joseph W.","contributorId":94926,"corporation":false,"usgs":true,"family":"Richards","given":"Joseph","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":307994,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Drury, Dorothy E.","contributorId":69425,"corporation":false,"usgs":true,"family":"Drury","given":"Dorothy","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":307993,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hardin, Johanna","contributorId":58151,"corporation":false,"usgs":true,"family":"Hardin","given":"Johanna","email":"","affiliations":[],"preferred":false,"id":307992,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70035058,"text":"70035058 - 2011 - Modelling the distribution of domestic ducks in Monsoon Asia","interactions":[],"lastModifiedDate":"2024-10-01T13:29:18.617101","indexId":"70035058","displayToPublicDate":"2011-05-24T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":682,"text":"Agriculture, Ecosystems and Environment","active":true,"publicationSubtype":{"id":10}},"title":"Modelling the distribution of domestic ducks in Monsoon Asia","docAbstract":"Domestic ducks are considered to be an important reservoir of highly pathogenic avian influenza (HPAI), as shown by a number of geospatial studies in which they have been identified as a significant risk factor associated with disease presence. Despite their importance in HPAI epidemiology, their large-scale distribution in Monsoon Asia is poorly understood. In this study, we created a spatial database of domestic duck census data in Asia and used it to train statistical distribution models for domestic duck distributions at a spatial resolution of 1 km. The method was based on a modelling framework used by the Food and Agriculture Organisation to produce the Gridded Livestock of the World (GLW) database, and relies on stratified regression models between domestic duck densities and a set of agro-ecological explanatory variables. We evaluated different ways of stratifying the analysis and of combining the prediction to optimize the goodness of fit of the predictions. We found that domestic duck density could be predicted with reasonable accuracy (mean RMSE and correlation coefficient between log-transformed observed and predicted densities being 0.58 and 0.80, respectively), using a stratification based on livestock production systems. We tested the use of artificially degraded data on duck distributions in Thailand and Vietnam as training data, and compared the modelled outputs with the original high-resolution data. This showed, for these two countries at least, that these approaches could be used to accurately disaggregate provincial level (administrative level 1) statistical data to provide high resolution model distributions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.agee.2011.04.013","issn":"01678809","usgsCitation":"Van Boeckel, T., Prosser, D.J., Franceschini, G., Biradar, C., Wint, W., Robinson, T., and Gilbert, M., 2011, Modelling the distribution of domestic ducks in Monsoon Asia: Agriculture, Ecosystems and Environment, v. 141, no. 3-4, p. 373-380, https://doi.org/10.1016/j.agee.2011.04.013.","productDescription":"8 p.","startPage":"373","endPage":"380","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":475001,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/3148691","text":"External Repository"},{"id":381244,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"141","issue":"3-4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a5c77e4b0c8380cd6fcff","contributors":{"authors":[{"text":"Van Boeckel, T.P.","contributorId":97342,"corporation":false,"usgs":false,"family":"Van Boeckel","given":"T.P.","affiliations":[],"preferred":false,"id":449081,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Prosser, Diann J. 0000-0002-5251-1799 dprosser@usgs.gov","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":2389,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","email":"dprosser@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":449075,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Franceschini, G.","contributorId":73030,"corporation":false,"usgs":true,"family":"Franceschini","given":"G.","email":"","affiliations":[],"preferred":false,"id":449080,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Biradar, C.","contributorId":44377,"corporation":false,"usgs":true,"family":"Biradar","given":"C.","email":"","affiliations":[],"preferred":false,"id":449078,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wint, W.","contributorId":24588,"corporation":false,"usgs":true,"family":"Wint","given":"W.","affiliations":[],"preferred":false,"id":449076,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Robinson, T.","contributorId":26154,"corporation":false,"usgs":true,"family":"Robinson","given":"T.","affiliations":[],"preferred":false,"id":449077,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gilbert, M.","contributorId":57810,"corporation":false,"usgs":true,"family":"Gilbert","given":"M.","affiliations":[],"preferred":false,"id":449079,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70004491,"text":"sir20105213 - 2011 - Use of multidimensional modeling to evaluate a channel restoration design for the Kootenai River, Idaho","interactions":[],"lastModifiedDate":"2017-06-17T12:57:00","indexId":"sir20105213","displayToPublicDate":"2011-05-23T18:24:07","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-5213","title":"Use of multidimensional modeling to evaluate a channel restoration design for the Kootenai River, Idaho","docAbstract":"River channel construction projects aimed at restoring or improving degraded waterways have become common but have been variously successful. In this report a methodology is proposed to evaluate channel designs before channels are built by using multidimensional modeling and analysis. This approach allows detailed analysis of water-surface profiles, sediment transport, and aquatic habitat that may result if the design is implemented. The method presented here addresses the need to model a range of potential stream-discharge and channel-roughness conditions to best assess the function of the design channel for a suite of possible conditions. This methodology is demonstrated by using a preliminary channel-restoration design proposed for a part of the Kootenai River in northern Idaho designated as critical habitat for the endangered white sturgeon (Acipenser transmontanus) and evaluating the design on the basis of simulations with the Flow and Sediment Transport with Morphologic Evolution of Channels (FaSTMECH) model. This evaluation indicated substantial problems with the preliminary design because boundary conditions used in the design were inconsistent with best estimates of future conditions. As a result, simulated water-surface levels did not meet target levels that corresponded to the designed bankfull surfaces; therefore, the flood plain would not function as intended. Sediment-transport analyses indicated that both the current channel of the Kootenai River and the design channel are largely unable to move the bed material through the reach at bankfull discharge. Therefore, sediment delivered to the design channel would likely be deposited within the reach instead of passing through it as planned. Consequently, the design channel geometry would adjust through time. Despite these issues, the design channel would provide more aquatic habitat suitable for spawning white sturgeon (Acipenser transmontanus) at lower discharges than is currently available in the Kootenai River. The evaluation methodology identified potential problems with the design channel that can be addressed through design modifications to better meet project objectives before channel construction.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20105213","usgsCitation":"Logan, B., McDonald, R.R., Nelson, J.M., Kinzel, P., and Barton, G.J., 2011, Use of multidimensional modeling to evaluate a channel restoration design for the Kootenai River, Idaho: U.S. Geological Survey Scientific Investigations Report 2010-5213, vi, 30 p.; Appendices, https://doi.org/10.3133/sir20105213.","productDescription":"vi, 30 p.; Appendices","startPage":"i","endPage":"68","numberOfPages":"74","costCenters":[{"id":145,"text":"Branch of Regional Research-Central Region","active":false,"usgs":true}],"links":[{"id":116227,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2010_5213.png"},{"id":21813,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5213/","size":"106","linkFileType":{"id":5,"text":"html"}}],"scale":"100000","projection":"Albers Equal-Area projection","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -118,47.916666666666664 ], [ -118,50 ], [ -114.5,50 ], [ -114.5,47.916666666666664 ], [ -118,47.916666666666664 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4adae4b07f02db685887","contributors":{"authors":[{"text":"Logan, B.L.","contributorId":17349,"corporation":false,"usgs":true,"family":"Logan","given":"B.L.","email":"","affiliations":[],"preferred":false,"id":350493,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McDonald, R. R.","contributorId":72810,"corporation":false,"usgs":true,"family":"McDonald","given":"R.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":350497,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nelson, J. M.","contributorId":68687,"corporation":false,"usgs":true,"family":"Nelson","given":"J.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":350496,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kinzel, P.J.","contributorId":27834,"corporation":false,"usgs":true,"family":"Kinzel","given":"P.J.","affiliations":[],"preferred":false,"id":350494,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barton, G. J.","contributorId":58660,"corporation":false,"usgs":true,"family":"Barton","given":"G.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":350495,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":99281,"text":"sir20115039 - 2011 - Estimated probabilities and volumes of postwildfire debris flows, a prewildfire evaluation for the upper Blue River watershed, Summit County, Colorado","interactions":[],"lastModifiedDate":"2012-02-10T00:11:58","indexId":"sir20115039","displayToPublicDate":"2011-05-23T00:00:00","publicationYear":"2011","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":"2011-5039","title":"Estimated probabilities and volumes of postwildfire debris flows, a prewildfire evaluation for the upper Blue River watershed, Summit County, Colorado","docAbstract":"Debris flows resulting from rainfall on recently burned, rugged, forested areas create potential hazards to life, property, infrastructure, and water resources. The location, extent, and severity of wildfire and the subsequent rainfall intensity and duration cannot be known in advance. However, hypothetical scenarios based on empirical debris-flow models are useful planning tools for conceptualizing potential postwildfire effects. A prewildfire study to determine the potential for postwildfire debris flows in the upper Blue River watershed in Summit County, Colorado, was conducted in 2009 by the U.S. Geological Survey, in cooperation with the Town of Breckenridge, to provide Breckenridge with a relative measure of which subwatersheds might constitute the most serious debris-flow hazards. \nPotential postwildfire debris-flow probabilities and volumes for nine primary watersheds tributary to the upper Blue River and 50 subwatersheds located within and adjacent to the primary watersheds were estimated by using empirical debris-flow models. An assumption in the debris-flow models was that a moderate to severe wildfire affected 100 percent of the forest and shrub stands within the area. Three postwildfire precipitation scenarios were used to represent a range of likely precipitation scenarios that could occur shortly after a wildfire: a 2-year recurrence, 1-hour-duration rainfall; a 10-year recurrence, 1-hour-duration rainfall; and a 25-year recurrence, 1-hour-duration rainfall. All of these precipitation scenarios resulted in debris flows from the hypothetically burned watersheds. \nSubwatersheds with the lowest postwildfire debris-flow probabilities tended to have large areas of alpine and subalpine vegetation or sparse forest cover that would be minimally affected by wildfire. Subwatersheds with the highest probabilities tended to be steep, heavily forested, and relatively small in drainage area. Subwatersheds with the smallest estimated postwildfire debris-flow volumes tended to have small drainage areas, relatively little forest cover, less rugged topography, or were located in alpine and subalpine areas. Subwatersheds with the highest estimated debris-flow volumes were those with the largest drainage areas.\nThe subwatersheds with the greatest potential postwildfire and postprecipitation hazards are those with both high probabilities of debris-flow occurrence and large estimated volumes of debris-flow material. The high probabilities of postwildfire debris flows, the associated large estimated debris-flow volumes, and the densely populated areas along the creeks and near the outlets of the primary watersheds indicate that Indiana, Pennsylvania, and Spruce Creeks are associated with a relatively high combined debris-flow hazard.","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/sir20115039","collaboration":"Prepared in cooperation with the Town of Breckenridge, Colorado","usgsCitation":"Elliott, J.G., Flynn, J.L., Bossong, C.R., and Char, S.J., 2011, Estimated probabilities and volumes of postwildfire debris flows, a prewildfire evaluation for the upper Blue River watershed, Summit County, Colorado: U.S. Geological Survey Scientific Investigations Report 2011-5039, iv, 22 p., https://doi.org/10.3133/sir20115039.","productDescription":"iv, 22 p.","onlineOnly":"Y","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":116602,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5039.bmp"},{"id":14681,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5039/","linkFileType":{"id":5,"text":"html"}}],"scale":"100000","projection":"Universal Transverse Mercator Projection","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -106.11777777777777,39.38333333333333 ], [ -106.11777777777777,39.35 ], [ -105.5,39.35 ], [ -105.5,39.38333333333333 ], [ -106.11777777777777,39.38333333333333 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a0ce4b07f02db5fcd48","contributors":{"authors":[{"text":"Elliott, John G. jelliott@usgs.gov","contributorId":832,"corporation":false,"usgs":true,"family":"Elliott","given":"John","email":"jelliott@usgs.gov","middleInitial":"G.","affiliations":[],"preferred":true,"id":307983,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flynn, Jennifer L.","contributorId":66298,"corporation":false,"usgs":true,"family":"Flynn","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":307985,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bossong, Clifford R.","contributorId":83183,"corporation":false,"usgs":true,"family":"Bossong","given":"Clifford","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":307986,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Char, Stephen J. sjchar@usgs.gov","contributorId":3982,"corporation":false,"usgs":true,"family":"Char","given":"Stephen","email":"sjchar@usgs.gov","middleInitial":"J.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":307984,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":99279,"text":"ofr20111026 - 2011 - Tectonic and metallogenic model for northeast Asia","interactions":[],"lastModifiedDate":"2012-02-10T00:11:58","indexId":"ofr20111026","displayToPublicDate":"2011-05-23T00:00:00","publicationYear":"2011","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":"2011-1026","title":"Tectonic and metallogenic model for northeast Asia","docAbstract":"This document describes the digital files in this report that contains a tectonic and metallogenic model for Northeast Asia. The report also contains background materials. This tectonic and metallogenic model and other materials on this report are derived from (1) an extensive USGS Professional Paper, 1765, on the metallogenesis and tectonics of Northeast Asia that is available on the Internet at http://pubs.usgs.gov/pp/1765/; and (2) the Russian Far East parts of an extensive USGS Professional Paper, 1697, on the metallogenesis and tectonics of the Russian Far East, Alaska, and the Canadian Cordillera that is available on the Internet at http://pubs.usgs.gov/pp/pp1697/. The major purpose of the tectonic and metallogenic model is to provide, in movie format, a colorful summary of the complex geology, tectonics, and metallogenesis of the region. To accomplish this goal four steps were taken: (1) 13 time-stage diagrams, from the late Neoproterozoic (850 Ma) through the present (0 Ma), were adapted, generalized, and transformed into color static time-stage diagrams; (2) the 13 time-stage diagrams were placed in a computer morphing program to produce the model; (3) the model was examined and each diagram was successively adapted to preceding and subsequent diagrams to match the size and surface expression of major geologic units; and (4) the final version of the model was produced in successive iterations of steps 2 and 3. The tectonic and metallogenic model and associated materials in this report are derived from a project on the major mineral deposits, metallogenesis, and tectonics of the Northeast Asia and from a preceding project on the metallogenesis and tectonics of the Russian Far East, Alaska, and the Canadian Cordillera. Both projects provide critical information on bedrock geology and geophysics, tectonics, major metalliferous mineral resources, metallogenic patterns, and crustal origin and evolution of mineralizing systems for this region. The major scientific goals and benefits of the projects are to: (1) provide a comprehensive international data base on the mineral resources of the region that is the first extensive knowledge available in English; (2) provide major new interpretations of the origin and crustal evolution of mineralizing systems and their host rocks, thereby enabling enhanced, broad-scale tectonic reconstructions and interpretations; and (3) promote trade and scientific and technical exchanges between North America and eastern Asia. ","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20111026","collaboration":"In cooperation with Jilin University, Changchun, People's Republic of China; Mongolian Academy of Sciences, Ulaanbaatar, Mongolia; Mongolian University of Science and Technology, Ulaanbaatar, Mongolia; Russian Academy of Sciences, Irkutsk, Russia; Russian Academy of Sciences, Khabarovsk, Russia; Russian Academy of Sciences, Magadan, Russia; Russian Academy of Sciences, Novosibirsk, Russia; Russian Academy of Sciences; Vladivostok, Russia; Russian Academy of Sciences, Yakutsk, Russia; and University of Texas, Arlington, Texas","usgsCitation":"Parfenov, L.M., Nokleberg, W.J., Berzin, N.A., Badarch, G., Dril, S.I., Gerel, O., Goryachev, N., Khanchuk, A.I., Kuz’min, M.I., Prokopiev, A.V., Ratkin, V.V., Rodionov, S.M., Scotese, C.R., Shpikerman, V.I., Timofeev, V.F., Tomurtogoo, O., and Yan, H., 2011, Tectonic and metallogenic model for northeast Asia: U.S. Geological Survey Open-File Report 2011-1026, 9 p.; Model file; Model-Figures folder; CD-ROM, https://doi.org/10.3133/ofr20111026.","productDescription":"9 p.; Model file; Model-Figures folder; CD-ROM","onlineOnly":"N","costCenters":[{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":116603,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1026.gif"},{"id":14680,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1026/","linkFileType":{"id":5,"text":"html"}}],"state":"Colorado","county":"Summit","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4882e4b07f02db516c22","contributors":{"editors":[{"text":"Nokleberg, Warren J. 0000-0002-1574-8869 wnokleberg@usgs.gov","orcid":"https://orcid.org/0000-0002-1574-8869","contributorId":2077,"corporation":false,"usgs":true,"family":"Nokleberg","given":"Warren","email":"wnokleberg@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":505758,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Parfenov, Leonid M.","contributorId":59112,"corporation":false,"usgs":true,"family":"Parfenov","given":"Leonid","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":307974,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nokleberg, Warren J. 0000-0002-1574-8869 wnokleberg@usgs.gov","orcid":"https://orcid.org/0000-0002-1574-8869","contributorId":2077,"corporation":false,"usgs":true,"family":"Nokleberg","given":"Warren","email":"wnokleberg@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":307964,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Berzin, Nikolai A.","contributorId":33793,"corporation":false,"usgs":true,"family":"Berzin","given":"Nikolai","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":307971,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Badarch, Gombosuren","contributorId":6940,"corporation":false,"usgs":true,"family":"Badarch","given":"Gombosuren","email":"","affiliations":[],"preferred":false,"id":307965,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dril, Sergy I.","contributorId":66823,"corporation":false,"usgs":true,"family":"Dril","given":"Sergy","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":307977,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gerel, Ochir","contributorId":41520,"corporation":false,"usgs":true,"family":"Gerel","given":"Ochir","email":"","affiliations":[],"preferred":false,"id":307973,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Goryachev, Nikolai A.","contributorId":7318,"corporation":false,"usgs":true,"family":"Goryachev","given":"Nikolai A.","affiliations":[],"preferred":false,"id":307966,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Khanchuk, Alexander I.","contributorId":19585,"corporation":false,"usgs":true,"family":"Khanchuk","given":"Alexander","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":307967,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kuz’min, Mikhail I. Obolenskiy Obolenskiy, Alexander A.","contributorId":28717,"corporation":false,"usgs":true,"family":"Kuz’min","given":"Mikhail","suffix":"Obolenskiy, Alexander A.","email":"","middleInitial":"I. Obolenskiy","affiliations":[],"preferred":false,"id":307969,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Prokopiev, Andrei V.","contributorId":20825,"corporation":false,"usgs":true,"family":"Prokopiev","given":"Andrei","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":307968,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ratkin, Vladimir V.","contributorId":79924,"corporation":false,"usgs":true,"family":"Ratkin","given":"Vladimir","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":307978,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Rodionov, Sergey M.","contributorId":64726,"corporation":false,"usgs":true,"family":"Rodionov","given":"Sergey","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":307975,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Scotese, Christopher R.","contributorId":66357,"corporation":false,"usgs":true,"family":"Scotese","given":"Christopher","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":307976,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Shpikerman, Vladimir I.","contributorId":35766,"corporation":false,"usgs":true,"family":"Shpikerman","given":"Vladimir","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":307972,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Timofeev, Vladimir F.","contributorId":90385,"corporation":false,"usgs":true,"family":"Timofeev","given":"Vladimir","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":307980,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Tomurtogoo, Onongin","contributorId":29932,"corporation":false,"usgs":true,"family":"Tomurtogoo","given":"Onongin","email":"","affiliations":[],"preferred":false,"id":307970,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Yan, Hongquan","contributorId":81559,"corporation":false,"usgs":true,"family":"Yan","given":"Hongquan","email":"","affiliations":[],"preferred":false,"id":307979,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":99273,"text":"ti2H1 - 2011 - Computational considerations for collecting and using data in the equidistant cylindrical map projection and the bounds of sampling geographic data at progressively higher resolution","interactions":[],"lastModifiedDate":"2012-02-02T00:05:16","indexId":"ti2H1","displayToPublicDate":"2011-05-20T00:00:00","publicationYear":"2011","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":"2-H1","title":"Computational considerations for collecting and using data in the equidistant cylindrical map projection and the bounds of sampling geographic data at progressively higher resolution","docAbstract":"The Equidistant Cylindrical Map projection is popular with digital modelers and others for storing and processing worldwide data sets because of the simple association of latitude and longitude to cell values or pixels in the resulting grid. This projection does not accurately display area, and the diminished geographic area represented by cells at high latitudes is not often carefully considered. A simple mathematical analysis quantifies the discrepancy in area sampled by cells at different latitudes. The presence of this discrepancy indicates that the use of this projection can induce bias in data sets when both sampling and reporting data. It is demonstrated that as the resolution requirements of input data for models increase, the necessity of providing data to accurately describe smaller cells, particularly at high latitude, will be a challenge. ","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ti2H1","usgsCitation":"Foley, K.M., 2011, Computational considerations for collecting and using data in the equidistant cylindrical map projection and the bounds of sampling geographic data at progressively higher resolution: U.S. Geological Survey Techniques and Methods 2-H1, iii, 5 p., https://doi.org/10.3133/ti2H1.","productDescription":"iii, 5 p.","costCenters":[{"id":308,"text":"Geology and Environmental Change Science Center","active":false,"usgs":true}],"links":[{"id":116909,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm_2_h1.gif"},{"id":204775,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/tm2h1/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a6be4b07f02db63d86f","contributors":{"authors":[{"text":"Foley, Kevin M. 0000-0003-1013-462X kfoley@usgs.gov","orcid":"https://orcid.org/0000-0003-1013-462X","contributorId":2543,"corporation":false,"usgs":true,"family":"Foley","given":"Kevin","email":"kfoley@usgs.gov","middleInitial":"M.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":307952,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":99271,"text":"ofr20111073 - 2011 - Global multi-resolution terrain elevation data 2010 (GMTED2010)","interactions":[],"lastModifiedDate":"2012-02-10T00:11:58","indexId":"ofr20111073","displayToPublicDate":"2011-05-20T00:00:00","publicationYear":"2011","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":"2011-1073","title":"Global multi-resolution terrain elevation data 2010 (GMTED2010)","docAbstract":"In 1996, the U.S. Geological Survey (USGS) developed a global topographic elevation model designated as GTOPO30 at a horizontal resolution of 30 arc-seconds for the entire Earth. Because no single source of topographic information covered the entire land surface, GTOPO30 was derived from eight raster and vector sources that included a substantial amount of U.S. Defense Mapping Agency data. The quality of the elevation data in GTOPO30 varies widely; there are no spatially-referenced metadata, and the major topographic features such as ridgelines and valleys are not well represented. Despite its coarse resolution and limited attributes, GTOPO30 has been widely used for a variety of hydrological, climatological, and geomorphological applications as well as military applications, where a regional, continental, or global scale topographic model is required. These applications have ranged from delineating drainage networks and watersheds to using digital elevation data for the extraction of topographic structure and three-dimensional (3D) visualization exercises (Jenson and Domingue, 1988; Verdin and Greenlee, 1996; Lehner and others, 2008). Many of the fundamental geophysical processes active at the Earth's surface are controlled or strongly influenced by topography, thus the critical need for high-quality terrain data (Gesch, 1994). U.S. Department of Defense requirements for mission planning, geographic registration of remotely sensed imagery, terrain visualization, and map production are similarly dependent on global topographic data.\r\n\r\nSince the time GTOPO30 was completed, the availability of higher-quality elevation data over large geographic areas has improved markedly. New data sources include global Digital Terrain Elevation Data (DTEDRegistered) from the Shuttle Radar Topography Mission (SRTM), Canadian elevation data, and data from the Ice, Cloud, and land Elevation Satellite (ICESat). Given the widespread use of GTOPO30 and the equivalent 30-arc-second DTEDRegistered level 0, the USGS and the National Geospatial-Intelligence Agency (NGA) have collaborated to produce an enhanced replacement for GTOPO30, the Global Land One-km Base Elevation (GLOBE) model and other comparable 30-arc-second-resolution global models, using the best available data. The new model is called the Global Multi-resolution Terrain Elevation Data 2010, or GMTED2010 for short. This suite of products at three different resolutions (approximately 1,000, 500, and 250 meters) is designed to support many applications directly by providing users with generic products (for example, maximum, minimum, and median elevations) that have been derived directly from the raw input data that would not be available to the general user or would be very costly and time-consuming to produce for individual applications. The source of all the elevation data is captured in metadata for reference purposes. It is also hoped that as better data become available in the future, the GMTED2010 model will be updated.","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20111073","usgsCitation":"Danielson, J.J., and Gesch, D.B., 2011, Global multi-resolution terrain elevation data 2010 (GMTED2010): U.S. Geological Survey Open-File Report 2011-1073, iv, 23 p.; Appendix, https://doi.org/10.3133/ofr20111073.","productDescription":"iv, 23 p.; Appendix","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":116894,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1073.jpg"},{"id":204774,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1073/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4abee4b07f02db674b19","contributors":{"authors":[{"text":"Danielson, Jeffrey J. 0000-0003-0907-034X daniels@usgs.gov","orcid":"https://orcid.org/0000-0003-0907-034X","contributorId":3996,"corporation":false,"usgs":true,"family":"Danielson","given":"Jeffrey","email":"daniels@usgs.gov","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":307951,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gesch, Dean B. 0000-0002-8992-4933 gesch@usgs.gov","orcid":"https://orcid.org/0000-0002-8992-4933","contributorId":2956,"corporation":false,"usgs":true,"family":"Gesch","given":"Dean","email":"gesch@usgs.gov","middleInitial":"B.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":307950,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":99274,"text":"ofr20111116 - 2011 - Rapid estimation of the economic consequences of global earthquakes","interactions":[],"lastModifiedDate":"2022-11-29T20:24:57.519343","indexId":"ofr20111116","displayToPublicDate":"2011-05-20T00:00:00","publicationYear":"2011","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":"2011-1116","title":"Rapid estimation of the economic consequences of global earthquakes","docAbstract":"The U.S. Geological Survey's (USGS) Prompt Assessment of Global Earthquakes for Response (PAGER) system, operational since mid 2007, rapidly estimates the most affected locations and the population exposure at different levels of shaking intensities. The PAGER system has significantly improved the way aid agencies determine the scale of response needed in the aftermath of an earthquake. For example, the PAGER exposure estimates provided reasonably accurate assessments of the scale and spatial extent of the damage and losses following the 2008 Wenchuan earthquake (Mw 7.9) in China, the 2009 L'Aquila earthquake (Mw 6.3) in Italy, the 2010 Haiti earthquake (Mw 7.0), and the 2010 Chile earthquake (Mw 8.8).\r\n\r\nNevertheless, some engineering and seismological expertise is often required to digest PAGER's exposure estimate and turn it into estimated fatalities and economic losses. This has been the focus of PAGER's most recent development.\r\n\r\nWith the new loss-estimation component of the PAGER system it is now possible to produce rapid estimation of expected fatalities for global earthquakes (Jaiswal and others, 2009). While an estimate of earthquake fatalities is a fundamental indicator of potential human consequences in developing countries (for example, Iran, Pakistan, Haiti, Peru, and many others), economic consequences often drive the responses in much of the developed world (for example, New Zealand, the United States, and Chile), where the improved structural behavior of seismically resistant buildings significantly reduces earthquake casualties.\r\n\r\nRapid availability of estimates of both fatalities and economic losses can be a valuable resource. The total time needed to determine the actual scope of an earthquake disaster and to respond effectively varies from country to country. It can take days or sometimes weeks before the damage and consequences of a disaster can be understood both socially and economically. The objective of the U.S. Geological Survey's PAGER system is to reduce this time gap to more rapidly and effectively mobilize response.\r\n\r\nWe present here a procedure to rapidly and approximately ascertain the economic impact immediately following a large earthquake anywhere in the world. In principle, the approach presented is similar to the empirical fatality estimation methodology proposed and implemented by Jaiswal and others (2009). In order to estimate economic losses, we need an assessment of the economic exposure at various levels of shaking intensity. The economic value of all the physical assets exposed at different locations in a given area is generally not known and extremely difficult to compile at a global scale. In the absence of such a dataset, we first estimate the total Gross Domestic Product (GDP) exposed at each shaking intensity by multiplying the per-capita GDP of the country by the total population exposed at that shaking intensity level. We then scale the total GDP estimated at each intensity by an exposure correction factor, which is a multiplying factor to account for the disparity between wealth and/or economic assets to the annual GDP. The economic exposure obtained using this procedure is thus a proxy estimate for the economic value of the actual inventory that is exposed to the earthquake. The economic loss ratio, defined in terms of a country-specific lognormal cumulative distribution function of shaking intensity, is derived and calibrated against the losses from past earthquakes. This report describes the development of a country or region-specific economic loss ratio model using economic loss data available for global earthquakes from 1980 to 2007. The proposed model is a potential candidate for directly estimating economic losses within the currently-operating PAGER system. PAGER's other loss models use indirect methods that require substantially more data (such as building/asset inventories, vulnerabilities, and the asset values exposed at the time of earthquake) to implement on a global basis and will thus take more time to develop and implement within the PAGER system.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20111116","usgsCitation":"Jaiswal, K., and Wald, D.J., 2011, Rapid estimation of the economic consequences of global earthquakes: U.S. Geological Survey Open-File Report 2011-1116, iv, 47 p.; 2 Appendixes, https://doi.org/10.3133/ofr20111116.","productDescription":"iv, 47 p.; 2 Appendixes","costCenters":[{"id":301,"text":"Geologic Hazards Team","active":false,"usgs":true}],"links":[{"id":116906,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1116.png"},{"id":204776,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1116/","linkFileType":{"id":5,"text":"html"}},{"id":409813,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_95202.htm","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a80e4b07f02db649616","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":307954,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":307953,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":99264,"text":"fs20113014 - 2011 - Using models for the optimization of hydrologic monitoring","interactions":[],"lastModifiedDate":"2012-03-08T17:16:13","indexId":"fs20113014","displayToPublicDate":"2011-05-17T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2011-3014","title":"Using models for the optimization of hydrologic monitoring","docAbstract":"Hydrologists are often asked what kind of monitoring network can most effectively support science-based water-resources management decisions. Currently (2011), hydrologic monitoring locations often are selected by addressing observation gaps in the existing network or non-science issues such as site access. A model might then be calibrated to available data and applied to a prediction of interest (regardless of how well-suited that model is for the prediction). However, modeling tools are available that can inform which locations and types of data provide the most 'bang for the buck' for a specified prediction. Put another way, the hydrologist can determine which observation data most reduce the model uncertainty around a specified prediction.\r\n\r\nAn advantage of such an approach is the maximization of limited monitoring resources because it focuses on the difference in prediction uncertainty with or without additional collection of field data. Data worth can be calculated either through the addition of new data or subtraction of existing information by reducing monitoring efforts (Beven, 1993). The latter generally is not widely requested as there is explicit recognition that the worth calculated is fundamentally dependent on the prediction specified. If a water manager needs a new prediction, the benefits of reducing the scope of a monitoring effort, based on an old prediction, may be erased by the loss of information important for the new prediction.\r\n\r\nThis fact sheet focuses on the worth or value of new data collection by quantifying the reduction in prediction uncertainty achieved be adding a monitoring observation. This calculation of worth can be performed for multiple potential locations (and types) of observations, which then can be ranked for their effectiveness for reducing uncertainty around the specified prediction. This is implemented using a Bayesian approach with the PREDUNC utility in the parameter estimation software suite PEST (Doherty, 2010).\r\n\r\nThe techniques briefly described earlier are described in detail in a U.S. Geological Survey Scientific Investigations Report available on the Internet (Fienen and others, 2010; http://pubs.usgs.gov/sir/2010/5159/). This fact sheet presents a synopsis of the techniques as applied to a synthetic model based on a model constructed using properties from the Lake Michigan Basin (Hoard, 2010).","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/fs20113014","collaboration":"National Water Availability and Use Pilot Program","usgsCitation":"Fienen, M., Hunt, R.J., Doherty, J.E., and Reeves, H.W., 2011, Using models for the optimization of hydrologic monitoring: U.S. Geological Survey Fact Sheet 2011-3014, 6 p., https://doi.org/10.3133/fs20113014.","productDescription":"6 p.","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":116954,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2011_3014.jpg"},{"id":204768,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2011/3014/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a14e4b07f02db602eb1","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":307929,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":307930,"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":307932,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reeves, Howard W. 0000-0001-8057-2081 hwreeves@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-2081","contributorId":2307,"corporation":false,"usgs":true,"family":"Reeves","given":"Howard","email":"hwreeves@usgs.gov","middleInitial":"W.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":307931,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}