This field-trip guide outlines the glacial history of the upper Arkansas River valley, Colorado, and builds on a previous GSA field trip to the area in 2010. The following will be presented: (1) new cosmogenic 10Be exposure ages of moraine boulders from the Pinedale and Bull Lake glaciations (Marine Isotope Stages 2 and 6, respectively) located adjacent to the Twin Lakes Reservoir, (2) numerical modeling of glaciers during the Pinedale glaciation in major tributaries draining into the upper Arkansas River, (3) discharge estimates for glacial-lake outburst floods in the upper Arkansas River valley, and (4) 10Be ages on flood boulders deposited downvalley from the moraine sequences. This research was stimulated by a new geologic map of the Granite 7.5′ quadrangle, in which the mapping of surficial deposits was revised based in part on the interpretation of newly acquired LiDAR data and field investigations. The new 10Be ages of the Pinedale terminal moraine at Twin Lakes average 21.8 ± 0.7 ka (n = 14), which adds to nearby Pinedale terminal moraine ages of 23.6 ± 1.4 ka (n = 5), 20.5 ± 0.2 ka (n = 3), and 16.6 ± 1.0 ka (n = 7), and downvalley outburst flood terraces that date to 20.9 ± 0.9 ka (n = 4) and 19.0 ± 0.6 ka (n = 4). This growing chronology leads to improved understanding of the controls and timing of glaciation in the western United States, the modeling of glacial-lake outburst flooding, and the reconstruction of paleotemperature through glacier modeling.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Unfolding the Geology of the West","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2016.0044(14)","usgsCitation":"Schweinsberg, A.D., Briner, J.P., Shroba, R.R., Licciardi, J.M., Leonard, E.M., Brugger, K.A., and Russell, C.M., 2016, Pinedale glacial history of the upper Arkansas River valley: New moraine chronologies, modeling results, and geologic mapping, chap. of Unfolding the Geology of the West: Geological Society of America Field Guides, v. 44, p. 335-353, https://doi.org/10.1130/2016.0044(14).","productDescription":"19 p.","startPage":"335","endPage":"353","ipdsId":"IP-076090","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":488635,"rank":3,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.morris.umn.edu/geol_facpubs/13","text":"External Repository"},{"id":340698,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":364811,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.geoscienceworld.org/books/book/1995/chapter/16277561/Pinedale-glacial-history-of-the-upper-Arkansas","linkFileType":{"id":5,"text":"html"}}],"country":"United States","otherGeospatial":"Arkansas River valley","volume":"44","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59084928e4b0fc4e448ffd52","contributors":{"authors":[{"text":"Schweinsberg, Avriel D.","contributorId":191619,"corporation":false,"usgs":false,"family":"Schweinsberg","given":"Avriel","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":693639,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Briner, Jason P.","contributorId":191620,"corporation":false,"usgs":false,"family":"Briner","given":"Jason","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":693640,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shroba, Ralph R. 0000-0002-2664-1813 rshroba@usgs.gov","orcid":"https://orcid.org/0000-0002-2664-1813","contributorId":1266,"corporation":false,"usgs":true,"family":"Shroba","given":"Ralph","email":"rshroba@usgs.gov","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":693638,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Licciardi, Joseph M.","contributorId":9759,"corporation":false,"usgs":false,"family":"Licciardi","given":"Joseph","email":"","middleInitial":"M.","affiliations":[{"id":12667,"text":"University of New Hampshire","active":true,"usgs":false}],"preferred":false,"id":693641,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Leonard, Eric M.","contributorId":127415,"corporation":false,"usgs":false,"family":"Leonard","given":"Eric","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":693642,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brugger, Keith A. 0000-0003-0869-920X","orcid":"https://orcid.org/0000-0003-0869-920X","contributorId":191621,"corporation":false,"usgs":false,"family":"Brugger","given":"Keith","email":"","middleInitial":"A.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":693643,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Russell, Charles M.","contributorId":191622,"corporation":false,"usgs":false,"family":"Russell","given":"Charles","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":693644,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70186879,"text":"70186879 - 2016 - CDMetaPOP: An individual-based, eco-evolutionary model for spatially explicit simulation of landscape demogenetics","interactions":[],"lastModifiedDate":"2017-11-22T17:38:20","indexId":"70186879","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"CDMetaPOP: An individual-based, eco-evolutionary model for spatially explicit simulation of landscape demogenetics","docAbstract":"1. Combining landscape demographic and genetics models offers powerful methods for addressing questions for eco-evolutionary applications.
2. Using two illustrative examples, we present Cost–Distance Meta-POPulation, a program to simulate changes in neutral and/or selection-driven genotypes through time as a function of individual-based movement, complex spatial population dynamics, and multiple and changing landscape drivers.
3. Cost–Distance Meta-POPulation provides a novel tool for questions in landscape genetics by incorporating population viability analysis, while linking directly to conservation applications.
Tectonic, geologic, geochemical, geochronologic, and ore deposit data from the U.S. Geological Survey-led assessment of 26 porphyry belts identified in the central Tethys region of Turkey, the Caucasus, Iran, western Pakistan, and southern Afghanistan relate porphyry mineralization to the tectonomagmatic evolution of the region and associated subduction and postsubduction processes. However, uplift, erosion, subsidence, and burial of porphyry systems, as well as post-mineral deformation, also played an essential role in shaping the observed metallogenic patterns.
We present a methodology that systematically evaluates the relationship between the level of erosion, the extent of cover, and the number of known porphyry occurrences in porphyry belts. Porphyry belts that exhibit coeval volcanic-to-plutonic rock aerial ratios between 33 and 66 and limited cover contain numerous identified porphyry occurrences. These belts are relatively well explored because porphyry systems are not eroded or buried. Porphyry belts with volcanic-to-plutonic ratios that are greater than 66, but are modestly covered, contain fewer identified porphyry occurrences. Current exploration in these belts is increasingly identifying porphyry systems under associated epithermal deposits. Porphyry belts that show volcanic-to-plutonic ratios that are greater than 66, but are extensively covered, contain few identified porphyry occurrences. These belts have not been extensively explored but have potential for discoveries under cover. Deformed porphyry belts exhibit variable volcanic-to-plutonic ratios that are typically below 33, but can be as high as 60. Commonly, these deformed belts are extensively covered. Exploration efforts for porphyry deposits in these variably exhumed belts have been limited.
Exploration has resulted in the identification of 62.7 million tonnes (Mt) of copper, 2.0 Mt of molybdenum, and 4.200 t of gold in the 45 porphyry deposits contained in the 26 porphyry belts of the region: (1) 54.7 Mt of copper (87% of total), 1.74 Mt of molybdenum (87%), and 3,370 t of gold (80%) occur in the 25 deposits of the four porphyry belts that exhibit coeval volcanic-to-plutonic ratios between 33 and 66 and limited cover; (2) 5.44 Mt of copper (9%), 0.148 Mt of molybdenum (7%), and 581 t of gold (14%) are contained in the 11 deposits of the 11 porphyry belts that display volcanic-to-plutonic ratios greater than 66 and modest cover; (3) 2.08 Mt of copper (3%), 0.110 Mt of molybdenum (6%), and 244 t of gold (6%) occur in the seven deposits of the three porphyry belts that have volcanic-to-plutonic ratios that are greater than 66 and extensive cover; and (4) 0.388 Mt of copper (1%), 0.006 Mt of molybdenum (<<1%), and 6 t of gold (<<1%) are contained in the two deposits of the eight deformed and covered porphyry belts with variable but typically low volcanic-to-plutonic ratios.
The central Tethys region is receiving considerable exploration attention. It hosts the Kadjaran (4.6 Mt Cu), Sungun (5.1 Mt Cu), Sar Cheshmeh (8.9 Mt Cu), and Reko Diq (23.0 Mt Cu) world-class porphyry deposits. Continued exploration for porphyry deposits in the region will likely lead to new discoveries in known porphyry belts, particularly under cover and below high- and intermediate-sulfidation epithermal systems.
The United States Geological Survey uses water-level (or stage) measurements to compute streamflow at over 8000 stream gaging stations located throughout the United States (waterwatch.usgs.gov, 2016). Streamflow (or discharge) is computed at five minute to hourly intervals from a relationship between water level and discharge that is uniquely determined for each station. The discharges are posted hourly to WaterWatch (waterwatch. usgs.gov) and are used by water managers to issue flood warnings and manage water supply and by other users of water information to make decisions. The accuracy of the water-level measurement is vital to the accuracy of the computed discharge. Because of the importance of water-level measurements, USGS has an accuracy policy of 0.02 ft or 0.2 percent of reading (whichever is larger) (Sauer and Turnipseed, 2010). Older technologies, such as float and shaft-encoder systems, bubbler systems and submersible pressure sensors, provide the needed accuracy but often require extensive construction to install and are prone to malfunctioning and damage from floating debris and sediment. No stilling wells or orifice lines need to be constructed for radar installations. During the last decade testing by the USGS Hydrologic Instrumentation Facility(HIF) found that radar water-level sensors can provide the needed accuracy for water-level measurements and because the sensor can be easily attached to bridges, reduce the construction required for installation. Additionally, the non-contact sensing of water level minimizes or eliminates damage and fouling from floating debris and sediment. This article is a brief summary of the testing efforts by the USGS HIF and field experiences with models of radar water-level sensors in streamflow measurement applications. Any use of trade names in this article is for descriptive purposes only and does not imply endorsement by the U.S. Government.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Manual on sea level: Measurement and interpretation Volume V: Radar gauges","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"United Nations Educational, Scientific and Cultural Organization","usgsCitation":"Fulford, J.M., 2016, Testing and use of radar water level sensors by the U.S. Geological Survey, 4 p.","productDescription":"4 p.","startPage":"121","endPage":"124","ipdsId":"IP-072695","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":352083,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":346989,"type":{"id":15,"text":"Index Page"},"url":"https://unesdoc.unesco.org/images/0024/002469/246981E.pdf"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afeea4ce4b0da30c1bfc5eb","contributors":{"authors":[{"text":"Fulford, Janice M. jfulford@usgs.gov","contributorId":991,"corporation":false,"usgs":true,"family":"Fulford","given":"Janice","email":"jfulford@usgs.gov","middleInitial":"M.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":714093,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70194448,"text":"70194448 - 2016 - LakeMetabolizer: An R package for estimating lake metabolism from free-water oxygen using diverse statistical models","interactions":[],"lastModifiedDate":"2018-01-24T16:05:13","indexId":"70194448","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1999,"text":"Inland Waters","active":true,"publicationSubtype":{"id":10}},"title":"LakeMetabolizer: An R package for estimating lake metabolism from free-water oxygen using diverse statistical models","docAbstract":"Metabolism is a fundamental process in ecosystems that crosses multiple scales of organization from individual organisms to whole ecosystems. To improve sharing and reuse of published metabolism models, we developed LakeMetabolizer, an R package for estimating lake metabolism from in situ time series of dissolved oxygen, water temperature, and, optionally, additional environmental variables. LakeMetabolizer implements 5 different metabolism models with diverse statistical underpinnings: bookkeeping, ordinary least squares, maximum likelihood, Kalman filter, and Bayesian. Each of these 5 metabolism models can be combined with 1 of 7 models for computing the coefficient of gas exchange across the air–water interface (k). LakeMetabolizer also features a variety of supporting functions that compute conversions and implement calculations commonly applied to raw data prior to estimating metabolism (e.g., oxygen saturation and optical conversion models). These tools have been organized into an R package that contains example data, example use-cases, and function documentation. The release package version is available on the Comprehensive R Archive Network (CRAN), and the full open-source GPL-licensed code is freely available for examination and extension online. With this unified, open-source, and freely available package, we hope to improve access and facilitate the application of metabolism in studies and management of lentic ecosystems.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/IW-6.4.883","usgsCitation":"Winslow, L., Zwart, J., Batt, R., Dugan, H., Woolway, R., Corman, J., Hanson, P.C., and Read, J.S., 2016, LakeMetabolizer: An R package for estimating lake metabolism from free-water oxygen using diverse statistical models: Inland Waters, v. 6, no. 4, p. 622-636, https://doi.org/10.1080/IW-6.4.883.","productDescription":"15 p.","startPage":"622","endPage":"636","ipdsId":"IP-065534","costCenters":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"links":[{"id":349534,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-02","publicationStatus":"PW","scienceBaseUri":"5a60fd87e4b06e28e9c24fa5","contributors":{"authors":[{"text":"Winslow, Luke 0000-0002-8602-5510 lwinslow@usgs.gov","orcid":"https://orcid.org/0000-0002-8602-5510","contributorId":168947,"corporation":false,"usgs":true,"family":"Winslow","given":"Luke","email":"lwinslow@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"preferred":true,"id":723877,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zwart, Jacob A.","contributorId":173345,"corporation":false,"usgs":false,"family":"Zwart","given":"Jacob A.","affiliations":[{"id":16905,"text":"University of Notre Dame, Dept. of Biological Sciences, Notre Dame, IN, 46556, USA","active":true,"usgs":false}],"preferred":false,"id":723878,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Batt, Ryan D.","contributorId":168948,"corporation":false,"usgs":false,"family":"Batt","given":"Ryan D.","affiliations":[{"id":25393,"text":"Department of Ecology, Evolution, and Natural Resources, Rutgers University, New Brunswick, New Jersey, USA 08901","active":true,"usgs":false}],"preferred":false,"id":723879,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dugan, Hilary","contributorId":150191,"corporation":false,"usgs":false,"family":"Dugan","given":"Hilary","affiliations":[{"id":17938,"text":"Center for Limnology University of Wisconsin, Madison, WI 53706, US","active":true,"usgs":false}],"preferred":false,"id":723880,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Woolway, R. Iestyn","contributorId":150345,"corporation":false,"usgs":false,"family":"Woolway","given":"R. Iestyn","affiliations":[{"id":18007,"text":"Lake Ecosystems Group, Centre for Ecology & Hydrology, Lancaster Environment Centre, Library Avenue, Bailrigg, Lancaster, LA1 4AP, UK.","active":true,"usgs":false}],"preferred":false,"id":723881,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Corman, Jessica","contributorId":194469,"corporation":false,"usgs":false,"family":"Corman","given":"Jessica","affiliations":[],"preferred":false,"id":723882,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hanson, Paul C.","contributorId":35634,"corporation":false,"usgs":false,"family":"Hanson","given":"Paul","email":"","middleInitial":"C.","affiliations":[{"id":12951,"text":"Center for Limnology, University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":723883,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Read, Jordan S. 0000-0002-3888-6631 jread@usgs.gov","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":4453,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","email":"jread@usgs.gov","middleInitial":"S.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":723884,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70192760,"text":"70192760 - 2016 - Recent and possible future variations in the North American Monsoon","interactions":[],"lastModifiedDate":"2017-12-20T11:09:39","indexId":"70192760","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Recent and possible future variations in the North American Monsoon","docAbstract":"The dynamics and recent and possible future changes of the June–September rainfall associated with the North American Monsoon (NAM) are reviewed in this chapter. Our analysis as well as previous analyses of the trend in June–September precipitation from 1948 until 2010 indicate significant precipitation increases over New Mexico and the core NAM region, and significant precipitation decreases over southwest Mexico. The trends in June–September precipitation have been forced by anomalous cyclonic circulation centered at 15°N latitude over the eastern Pacific Ocean. The anomalous cyclonic circulation is responsible for changes in the flux of moisture and the divergence of moisture flux within the core NAM region. Future climate projections using the Coupled Model Intercomparison Project Phase 5 (CMIP5) models, as part of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5), support the observed analyses of a later shift in the monsoon season in the presence of increased greenhouse gas concentrations in the atmosphere under the RCP8.5 scenario. The CMIP5 models under the RCP8.5 scenario predict significant NAM-related rainfall decreases during June and July and predict significant NAM-related rainfall increases during September and October.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The monsoons and climate change","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-319-21650-8_7","isbn":"978-3-319-21649-2","usgsCitation":"Hoell, A., Funk, C., Barlow, M., and Shukla, S., 2016, Recent and possible future variations in the North American Monsoon, chap. of The monsoons and climate change, p. 149-162, https://doi.org/10.1007/978-3-319-21650-8_7.","productDescription":"14 p.","startPage":"149","endPage":"162","ipdsId":"IP-062073","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":350130,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-21","publicationStatus":"PW","scienceBaseUri":"5a60fd88e4b06e28e9c24fd2","contributors":{"authors":[{"text":"Hoell, Andrew","contributorId":145805,"corporation":false,"usgs":false,"family":"Hoell","given":"Andrew","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":716847,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Funk, Chris 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":167070,"corporation":false,"usgs":true,"family":"Funk","given":"Chris","email":"cfunk@usgs.gov","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":716846,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barlow, Mathew","contributorId":145834,"corporation":false,"usgs":false,"family":"Barlow","given":"Mathew","affiliations":[{"id":16250,"text":"University of Massechusetts, Lowell","active":true,"usgs":false}],"preferred":false,"id":716849,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shukla, Shraddhanand","contributorId":140735,"corporation":false,"usgs":false,"family":"Shukla","given":"Shraddhanand","email":"","affiliations":[{"id":13549,"text":"UC Santa Barbara Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":716848,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70187721,"text":"70187721 - 2016 - An evaluation of behavior inferences from Bayesian state-space models: A case study with the Pacific walrus","interactions":[],"lastModifiedDate":"2018-06-16T17:49:28","indexId":"70187721","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2671,"text":"Marine Mammal Science","active":true,"publicationSubtype":{"id":10}},"title":"An evaluation of behavior inferences from Bayesian state-space models: A case study with the Pacific walrus","docAbstract":"State-space models offer researchers an objective approach to modeling complex animal location data sets, and state-space model behavior classifications are often assumed to have a link to animal behavior. In this study, we evaluated the behavioral classification accuracy of a Bayesian state-space model in Pacific walruses using Argos satellite tags with sensors to detect animal behavior in real time. We fit a two-state discrete-time continuous-space Bayesian state-space model to data from 306 Pacific walruses tagged in the Chukchi Sea. We matched predicted locations and behaviors from the state-space model (resident, transient behavior) to true animal behavior (foraging, swimming, hauled out) and evaluated classification accuracy with kappa statistics (κ) and root mean square error (RMSE). In addition, we compared biased random bridge utilization distributions generated with resident behavior locations to true foraging behavior locations to evaluate differences in space use patterns. Results indicated that the two-state model fairly classified true animal behavior (0.06 ≤ κ ≤ 0.26, 0.49 ≤ RMSE ≤ 0.59). Kernel overlap metrics indicated utilization distributions generated with resident behavior locations were generally smaller than utilization distributions generated with true foraging behavior locations. Consequently, we encourage researchers to carefully examine parameters and priors associated with behaviors in state-space models, and reconcile these parameters with the study species and its expected behaviors.
","language":"English","publisher":"Wiley","doi":"10.1111/mms.12332","usgsCitation":"Beatty, W.S., Jay, C.V., and Fischbach, A.S., 2016, An evaluation of behavior inferences from Bayesian state-space models: A case study with the Pacific walrus: Marine Mammal Science, v. 32, no. 4, p. 1299-1318, https://doi.org/10.1111/mms.12332.","productDescription":"20 p.","startPage":"1299","endPage":"1318","ipdsId":"IP-069772","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":438647,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77M060G","text":"USGS data release","linkHelpText":"Walrus Bayesian State-space Model Output from the Bering Sea and Chukchi Sea, 2008-2012"},{"id":341325,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-11","publicationStatus":"PW","scienceBaseUri":"591abe36e4b0a7fdb43c8bf5","contributors":{"authors":[{"text":"Beatty, William S. 0000-0003-0013-3113 wbeatty@usgs.gov","orcid":"https://orcid.org/0000-0003-0013-3113","contributorId":173946,"corporation":false,"usgs":true,"family":"Beatty","given":"William","email":"wbeatty@usgs.gov","middleInitial":"S.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":695273,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jay, Chadwick V. 0000-0002-9559-2189 cjay@usgs.gov","orcid":"https://orcid.org/0000-0002-9559-2189","contributorId":192736,"corporation":false,"usgs":true,"family":"Jay","given":"Chadwick","email":"cjay@usgs.gov","middleInitial":"V.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":695274,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fischbach, Anthony S. 0000-0002-6555-865X afischbach@usgs.gov","orcid":"https://orcid.org/0000-0002-6555-865X","contributorId":2865,"corporation":false,"usgs":true,"family":"Fischbach","given":"Anthony","email":"afischbach@usgs.gov","middleInitial":"S.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":695275,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70190332,"text":"70190332 - 2016 - Fire in the Earth System: Bridging data and modeling research","interactions":[],"lastModifiedDate":"2017-08-26T17:20:10","indexId":"70190332","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1112,"text":"Bulletin of the American Meteorological Society","onlineIssn":"1520-0477","printIssn":"0003-0007","active":true,"publicationSubtype":{"id":10}},"title":"Fire in the Earth System: Bridging data and modeling research","docAbstract":"Significant changes in wildfire occurrence, extent, and severity in areas such as western North America and Indonesia in 2015 have made the issue of fire increasingly salient in both the public and scientific spheres. Biomass combustion rapidly transforms land cover, smoke pours into the atmosphere, radiative heat from fires initiates dramatic pyrocumulus clouds, and the repeated ecological and atmospheric effects of fire can even impact regional and global climate. Furthermore, fires have a significant impact on human health, livelihoods, and social and economic systems.
Modeling and databased methods to understand fire have rapidly coevolved over the past decade. Satellite and ground-based data about present-day fire are widely available for applications in research and fire management. Fire modeling has developed in part because of the evolution in vegetation and Earth system modeling efforts, but parameterizations and validation are largely focused on the present day because of the availability of satellite data. Charcoal deposits in sediment cores have emerged as a powerful method to evaluate trends in biomass burning extending back to the Last Glacial Maximum and beyond, and these records provide a context for present-day fire. The Global Charcoal Database version 3 compiled about 700 charcoal records and more than 1,000 records are expected for the future version 4. Together, these advances offer a pathway to explore how the strengths of fire data and fire modeling could address the weaknesses in the overall understanding of human-climate–fire linkages.
A community of researchers studying fire in the Earth system with individual expertise that included paleoecology, paleoclimatology, modern ecology, archaeology, climate, and Earth system modeling, statistics, geography, biogeochemistry, and atmospheric science met at an intensive workshop in Massachusetts to explore new research directions and initiate new collaborations. Research themes, which emerged from the workshop participants via preworkshop surveys, focused on addressing the following questions: What are the climatic, ecological, and human drivers of fire regimes, both past and future? What is the role of humans in shaping historical fire regimes? How does fire ecology affect land cover changes, biodiversity, carbon storage, and human land uses? What are the historical fire trends and their impacts across biomes? Are their impacts local and/or regional? Are the fire trends in the last two decades unprecedented from a historical perspective? The workshop1 aimed to develop testable hypotheses about fire, climate, vegetation, and human interactions by leveraging the confluence of proxy, observational, and model data related to decadal- to millennial-scale fire activity on our planet. New research directions focused on broad interdisciplinary approaches to highlight how knowledge about past fire activity could provide a more complete understanding of the predictive capacity of fire models and inform fire policy in the face of our changing climate.
","largerWorkTitle":"Bulletin of the American Meteorological Society (BAMS)","language":"English","publisher":"American Meteorological Society","doi":"10.1175/BAMS-D-15-00319.1","usgsCitation":"Hantson, S., Kloster, S., Coughlan, M., Daniau, A., Vanniere, B., Bruecher, T., Kehrwald, N.M., and Magi, B.I., 2016, Fire in the Earth System: Bridging data and modeling research: Bulletin of the American Meteorological Society, v. 97, no. 6, p. 1069-1072, https://doi.org/10.1175/BAMS-D-15-00319.1.","productDescription":"4 p.","startPage":"1069","endPage":"1072","ipdsId":"IP-071531","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":471389,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/bams-d-15-00319.1","text":"Publisher Index Page"},{"id":345161,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"97","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-08","publicationStatus":"PW","scienceBaseUri":"59a288c9e4b077f0056692b1","contributors":{"authors":[{"text":"Hantson, Srijn","contributorId":195866,"corporation":false,"usgs":false,"family":"Hantson","given":"Srijn","affiliations":[{"id":34430,"text":"Karlsruhe Institute of Technology, Garmisch-Partenkirchen, Germany","active":true,"usgs":false}],"preferred":false,"id":708480,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kloster, Silvia","contributorId":195867,"corporation":false,"usgs":false,"family":"Kloster","given":"Silvia","email":"","affiliations":[{"id":32387,"text":"Max Planck Institute for Meteorology, Hamburg, Germany","active":true,"usgs":false}],"preferred":false,"id":708481,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coughlan, Michael","contributorId":168920,"corporation":false,"usgs":false,"family":"Coughlan","given":"Michael","email":"","affiliations":[{"id":25390,"text":"Department of Anthropology, University of Georgia, Athens, Georgia, USA","active":true,"usgs":false}],"preferred":false,"id":708482,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Daniau, Anne-Laure","contributorId":195869,"corporation":false,"usgs":false,"family":"Daniau","given":"Anne-Laure","email":"","affiliations":[{"id":34431,"text":"Université de Bordeaux, Talence, France","active":true,"usgs":false}],"preferred":false,"id":708483,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vanniere, Boris","contributorId":195870,"corporation":false,"usgs":false,"family":"Vanniere","given":"Boris","affiliations":[{"id":34432,"text":"Université Bourgogne Franche-Comté, Besançon, France","active":true,"usgs":false}],"preferred":false,"id":708484,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bruecher, Tim","contributorId":195871,"corporation":false,"usgs":false,"family":"Bruecher","given":"Tim","email":"","affiliations":[{"id":34427,"text":"GEOMAR, Helmholtz Centre for Ocean Research","active":true,"usgs":false}],"preferred":false,"id":708485,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kehrwald, Natalie M. 0000-0002-9160-2239 nkehrwald@usgs.gov","orcid":"https://orcid.org/0000-0002-9160-2239","contributorId":168918,"corporation":false,"usgs":true,"family":"Kehrwald","given":"Natalie","email":"nkehrwald@usgs.gov","middleInitial":"M.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":708479,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Magi, Brian I.","contributorId":168923,"corporation":false,"usgs":false,"family":"Magi","given":"Brian","email":"","middleInitial":"I.","affiliations":[{"id":25392,"text":"Department of Geography and Earth Science, University of North Carolina at Charlotte, North Carolina, USA","active":true,"usgs":false}],"preferred":false,"id":708486,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70193146,"text":"70193146 - 2016 - Establishing a baseline of estuarine submerged aquatic vegetation resources across salinity zones within coastal areas of the northern Gulf of Mexico","interactions":[],"lastModifiedDate":"2017-11-21T13:00:59","indexId":"70193146","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3909,"text":"Journal of the Southeastern Association of Fish and Wildlife Agencies","active":true,"publicationSubtype":{"id":10}},"title":"Establishing a baseline of estuarine submerged aquatic vegetation resources across salinity zones within coastal areas of the northern Gulf of Mexico","docAbstract":"Coastal ecosystems are dynamic and productive areas that are vulnerable to effects of global climate change. Despite their potentially limited spatial extent, submerged aquatic vegetation (SAV) beds function in coastal ecosystems as foundation species, and perform important ecological services. However, limited understanding of the factors controlling SAV distribution and abundance across multiple salinity zones (fresh, intermediate, brackish, and saline) in the northern Gulf of Mexico restricts the ability of models to accurately predict resource availability. We sampled 384 potential coastal SAV sites across the northern Gulf of Mexico in 2013 and 2014, and examined community and species-specific SAV distribution and biomass in relation to year, salinity, turbidity, and water depth. After two years of sampling, 14 species of SAV were documented, with three species (coontail [Ceratophyllum demersum], Eurasian watermilfoil [Myriophyllum spicatum], and widgeon grass [Ruppia maritima]) accounting for 54% of above-ground biomass collected. Salinity and water depth were dominant drivers of species assemblages but had little effect on SAV biomass. Predicted changes in salinity and water depths along the northern Gulf of Mexico coast will likely alter SAV production and species assemblages, shifting to more saline and depth-tolerant assemblages, which in turn may affect habitat and food resources for associated faunal species.
","language":"English","publisher":"Southeastern Association of Fish and Wildlife Agencies","usgsCitation":"Hillmann, E.R., DeMarco, K., and LaPeyre, M.K., 2016, Establishing a baseline of estuarine submerged aquatic vegetation resources across salinity zones within coastal areas of the northern Gulf of Mexico: Journal of the Southeastern Association of Fish and Wildlife Agencies, v. 3, p. 25-32.","productDescription":"8 p.","startPage":"25","endPage":"32","ipdsId":"IP-066781","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":349204,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.5478515625,\n 28\n ],\n [\n -87.099609375,\n 28\n ],\n [\n -87.099609375,\n 31\n ],\n [\n -96.5478515625,\n 31\n ],\n [\n -96.5478515625,\n 28\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"3","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fd88e4b06e28e9c24fb7","contributors":{"authors":[{"text":"Hillmann, Eva R.","contributorId":200686,"corporation":false,"usgs":false,"family":"Hillmann","given":"Eva","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":723053,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeMarco, Kristin","contributorId":200003,"corporation":false,"usgs":false,"family":"DeMarco","given":"Kristin","email":"","affiliations":[],"preferred":false,"id":723054,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"LaPeyre, Megan K. 0000-0001-9936-2252 mlapeyre@usgs.gov","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":585,"corporation":false,"usgs":true,"family":"LaPeyre","given":"Megan","email":"mlapeyre@usgs.gov","middleInitial":"K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":718094,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70191522,"text":"70191522 - 2016 - Estimating abundance: Chapter 27","interactions":[],"lastModifiedDate":"2017-11-30T12:58:43","indexId":"70191522","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Estimating abundance: Chapter 27","docAbstract":"This chapter provides a non-technical overview of ‘closed population capture–recapture’ models, a class of well-established models that are widely applied in ecology, such as removal sampling, covariate models, and distance sampling. These methods are regularly adopted for studies of reptiles, in order to estimate abundance from counts of marked individuals while accounting for imperfect detection. Thus, the chapter describes some classic closed population models for estimating abundance, with considerations for some recent extensions that provide a spatial context for the estimation of abundance, and therefore density. Finally, the chapter suggests some software for use in data analysis, such as the Windows-based program MARK, and provides an example of estimating abundance and density of reptiles using an artificial cover object survey of Slow Worms (Anguis fragilis).
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Reptile ecology and conservation: A handbook of techniques","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Oxford University Press","doi":"10.1093/acprof:oso/9780198726135.003.0027","usgsCitation":"Royle, J., 2016, Estimating abundance: Chapter 27, chap. of Reptile ecology and conservation: A handbook of techniques, p. 388-401, https://doi.org/10.1093/acprof:oso/9780198726135.003.0027.","productDescription":"14 p.","startPage":"388","endPage":"401","ipdsId":"IP-066002","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":349590,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fd88e4b06e28e9c24fdf","contributors":{"authors":[{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":138865,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":712610,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70187207,"text":"70187207 - 2016 - Age, growth and fall diet of channel catfish in Cheat Lake, West Virginia","interactions":[],"lastModifiedDate":"2017-04-26T12:41:20","indexId":"70187207","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","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":"Age, growth and fall diet of channel catfish in Cheat Lake, West Virginia","docAbstract":"Acidification has historically impaired Cheat Lake's fish community, but recent mitigation efforts within the Cheat River watershed have improved water quality and species richness. Presently, channel catfish Ictalurus punctatus are abundant and attain desirable sizes for anglers. We evaluated the age, growth, and fall diet of the population. We collected a sample of 155 channel catfish from Cheat Lake from 5 August to 4 December 2014, a subset of which we aged (n = 148) using lapillus otoliths. We fit four growth models (von Bertalanffy, logistic, Gompertz, and power) to length-at-age data and compared models using an information theoretic approach. We collected fall diets from 55 fish sampled from 13 October to 4 December 2014. Total lengths of individuals in the sample ranged from 154 to 721 mm and ages ranged from 2 to 19 y. We AICc-selected the von Bertalanffy growth model as the best approximating model, and the power and Gompertz models also had considerable support. Diets were numerically dominated by Diptera larvae, specifically Chironomidae and Chaoboridae, while 39% of stomachs contained terrestrial food items. This study provides baseline data for management of Cheat Lake's channel catfish population. Further, this study fills a knowledge gap in the scientific literature on channel catfish, because few previously published studies have examined the population ecology of channel catfish in the Central Appalachian region.
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/092015-JFWM-091","usgsCitation":"Hilling, C., Welsh, S.A., and Smith, D.M., 2016, Age, growth and fall diet of channel catfish in Cheat Lake, West Virginia: Journal of Fish and Wildlife Management, v. 7, no. 2, p. 304-314, https://doi.org/10.3996/092015-JFWM-091.","productDescription":"11 p.","startPage":"304","endPage":"314","ipdsId":"IP-074154","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":471372,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/092015-jfwm-091","text":"Publisher Index Page"},{"id":340456,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","otherGeospatial":"Cheat Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": 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studies","interactions":[],"lastModifiedDate":"2017-06-29T15:02:55","indexId":"70189094","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1806,"text":"Geophysical Prospecting","active":true,"publicationSubtype":{"id":10}},"title":"A comparison of helicopter-borne electromagnetic systems for hydrogeologic studies","docAbstract":"The increased application of airborne electromagnetic surveys to hydrogeological studies is driving a demand for data that can consistently be inverted for accurate subsurface resistivity structure from the near surface to depths of several hundred metres. We present an evaluation of three commercial airborne electromagnetic systems over two test blocks in western Nebraska, USA. The selected test blocks are representative of shallow and deep alluvial aquifer systems with low groundwater salinity and an electrically conductive base of aquifer. The aquifer units show significant lithologic heterogeneity and include both modern and ancient river systems. We compared the various data sets to one another and inverted resistivity models to borehole lithology and to ground geophysical models. We find distinct differences among the airborne electromagnetic systems as regards the spatial resolution of models, the depth of investigation, and the ability to recover near-surface resistivity variations. We further identify systematic biases in some data sets, which we attribute to incomplete or inexact calibration or compensation procedures.
","language":"English","publisher":"Wiley","doi":"10.1111/1365-2478.12262","usgsCitation":"Bedrosian, P.A., Schamper, C., and Auken, E., 2016, A comparison of helicopter-borne electromagnetic systems for hydrogeologic studies: Geophysical Prospecting, v. 64, no. 1, p. 192-215, https://doi.org/10.1111/1365-2478.12262.","productDescription":"24 p.","startPage":"192","endPage":"215","ipdsId":"IP-049361","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":343162,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","volume":"64","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-29","publicationStatus":"PW","scienceBaseUri":"595611b7e4b0d1f9f0506768","contributors":{"authors":[{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":702837,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schamper, Cyril","contributorId":193990,"corporation":false,"usgs":false,"family":"Schamper","given":"Cyril","email":"","affiliations":[],"preferred":false,"id":702838,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Auken, Esben","contributorId":193991,"corporation":false,"usgs":false,"family":"Auken","given":"Esben","email":"","affiliations":[],"preferred":false,"id":702839,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70187368,"text":"70187368 - 2016 - Golden-winged Warbler nest-site habitat selection: Chapter 7","interactions":[],"lastModifiedDate":"2017-09-07T16:50:51","indexId":"70187368","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"seriesTitle":{"id":5103,"text":"Studies in Avian Biology","printIssn":"0197-9922","active":true,"publicationSubtype":{"id":24}},"chapter":"7","title":"Golden-winged Warbler nest-site habitat selection: Chapter 7","docAbstract":"Avian habitat selection occurs at multiple spatial scales to incorporate life history requirements. Breeding habitat of Golden-winged Warblers (Vermivora chrysoptera) is characterized by largely forested landscapes containing natural or anthropogenic disturbance elements that maintain forest patches in early stages of succession. Breeding habitat occurs in a variety of settings, including shrub and forest swamps, regenerating forests following timber harvest, grazed pastures, and reclaimed mined lands. We identified structural components of nest sites for Golden-winged Warblers by measuring habitat characteristics across five states (North Carolina, New York, Pennsylvania, Tennessee, and West Virginia) in the Appalachian breeding-distribution segment and two states (Minnesota and Wisconsin) in the Great Lakes breeding-distribution segment. We measured habitat characteristics at the nest-site scale with a series of nested plots characterizing herbaceous vegetation (grasses and forbs), woody shrubs and saplings, and overstory trees. We measured similar variables at paired random plots located 25–50 m from the nest within the same territory to evaluate selection. We used conditional logistical regression to identify which parameters were important in habitat selection and Simple Saddlepoint Approximation (SSA) to aid in management interpretation of identified parameters for each study site. Study site was an important determinant for which parameters were significant in nest-site selection, although selection for some parameters was consistent across sites. The amount of woody cover at the nest-site scale was consistently present in the top nest-site selection models across sites, although the direction of the relationship was not the same across all sites. We also identified grass, forb, woody cover, and vegetation density as important components of Golden-winged Warbler nest-site selection. Based on SSA, we identified vegetation thresholds to aid in designing habitat management prescriptions to promote creation or restoration of Golden-winged Warbler nesting habitat across the eastern portion of their breeding distribution.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Golden-winged Warbler ecology, conservation, and habitat management (Studies in Avian Biology, volume 49)","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"CRC Press","publisherLocation":"Boca Raton, FL","isbn":"978-1-4822-4068-9","usgsCitation":"Terhune, T.M., Aldinger, K.R., Buehler, D.A., Flaspohler, D.J., Larkin, J.L., Loegering, J.P., Percy, K.L., Roth, A.M., Smalling, C.G., and Wood, P., 2016, Golden-winged Warbler nest-site habitat selection: Chapter 7, chap. 7 of Golden-winged Warbler ecology, conservation, and habitat management (Studies in Avian Biology, volume 49): Studies in Avian Biology, v. 49, p. 109-125.","productDescription":"17 p.","startPage":"109","endPage":"125","ipdsId":"IP-052635","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":340750,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":340749,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://hdl.handle.net/11299/189700"}],"volume":"49","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59099aaee4b0fc4e449157f0","contributors":{"authors":[{"text":"Terhune, Theron M. 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Indiana University of Pennsylvania","active":true,"usgs":false},{"id":17929,"text":"American Bird Conservancy","active":true,"usgs":false}],"preferred":false,"id":693994,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Loegering, John P.","contributorId":166933,"corporation":false,"usgs":false,"family":"Loegering","given":"John","email":"","middleInitial":"P.","affiliations":[{"id":33353,"text":"University of Minnesota, Crookston","active":true,"usgs":false}],"preferred":false,"id":693995,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Percy, Katie L.","contributorId":191722,"corporation":false,"usgs":false,"family":"Percy","given":"Katie","email":"","middleInitial":"L.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":693996,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Roth, Amber M.","contributorId":191723,"corporation":false,"usgs":false,"family":"Roth","given":"Amber","email":"","middleInitial":"M.","affiliations":[{"id":27866,"text":"University of Maine, Department of Wildlife, Fisheries, and Conservation Biology, Orono, ME","active":true,"usgs":false},{"id":25614,"text":"School of Forest Resources, University of Maine","active":true,"usgs":false},{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":693997,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Smalling, Curtis G.","contributorId":191724,"corporation":false,"usgs":false,"family":"Smalling","given":"Curtis","email":"","middleInitial":"G.","affiliations":[{"id":33352,"text":"Audubon North Carolina","active":true,"usgs":false}],"preferred":false,"id":693998,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wood, Petra pbwood@usgs.gov","contributorId":169812,"corporation":false,"usgs":true,"family":"Wood","given":"Petra","email":"pbwood@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":34541,"text":"West Virginia Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":693999,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70192005,"text":"70192005 - 2016 - Prioritizing landscapes for longleaf pine conservation","interactions":[],"lastModifiedDate":"2018-01-25T13:33:39","indexId":"70192005","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"FWS/CSS-119-2016","title":"Prioritizing landscapes for longleaf pine conservation","docAbstract":"We developed a spatially explicit model and map, as a decision support tool (DST), to aid conservation agencies creating or maintaining open pine ecosystems. The tool identified areas that are likely to provide the greatest benefit to focal bird populations based on a comprehensive landscape analysis. We used NLCD 2011, SSURGO, and SEGAP data to map the density of desired resources for open pine ecosystems and six focal species of birds and 2 reptiles within the historic range of longleaf pine east of the Mississippi River. Binary rasters were created of sites with desired characteristics such as land form, hydrology, land use and land cover, soils, potential habitat for focal species, and putative source populations of focal species. Each raster was smoothed using a kernel density estimator. Rasters were combined and scaled to map priority locations for the management of each focal species. Species’ rasters were combined and scaled to provide maps of overall priority for birds and for birds and reptiles. The spatial data can be used to identify high priority areas for conservation or to compare areas under consideration for maintenance or creation of open pine ecosystems.
","language":"English","publisher":"U.S. Fish and Wildlife Service","usgsCitation":"Grand, J.B., and Kleiner, K.J., 2016, Prioritizing landscapes for longleaf pine conservation: Cooperator Science Series FWS/CSS-119-2016, ii, 50 p.","productDescription":"ii, 50 p.","numberOfPages":"52","ipdsId":"IP-071312","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":350618,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":350617,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://digitalmedia.fws.gov/cdm/ref/collection/document/id/2131"}],"publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a6afac6e4b06e28e9c9a8ff","contributors":{"authors":[{"text":"Grand, J. Barry 0000-0002-3576-4567 barry_grand@usgs.gov","orcid":"https://orcid.org/0000-0002-3576-4567","contributorId":579,"corporation":false,"usgs":true,"family":"Grand","given":"J.","email":"barry_grand@usgs.gov","middleInitial":"Barry","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":713832,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kleiner, Kevin J.","contributorId":200004,"corporation":false,"usgs":false,"family":"Kleiner","given":"Kevin","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":725822,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70187351,"text":"70187351 - 2016 - Geomorphic evolution of the San Luis Basin and Rio Grande in southern Colorado and northern New Mexico","interactions":[],"lastModifiedDate":"2017-05-01T15:05:10","indexId":"70187351","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1724,"text":"GSA Field Guides","active":true,"publicationSubtype":{"id":10}},"title":"Geomorphic evolution of the San Luis Basin and Rio Grande in southern Colorado and northern New Mexico","docAbstract":"The San Luis Basin encompasses the largest structural and hydrologic basin of the Rio Grande rift. On this field trip, we will examine the timing of transition of the San Luis Basin from hydrologically closed, aggrading subbasins to a continuous fluvial system that eroded the basin, formed the Rio Grande gorge, and ultimately, integrated the Rio Grande from Colorado to the Gulf of Mexico. Waning Pleistocene neotectonic activity and onset of major glacial episodes, in particular Marine Isotope Stages 11–2 (~420–14 ka), induced basin fill, spillover, and erosion of the southern San Luis Basin. The combined use of new geologic mapping, fluvial geomorphology, reinterpreted surficial geology of the Taos Plateau, pedogenic relative dating studies, 3He surface exposure dating of basalts, and U-series dating of pedogenic carbonate supports a sequence of events wherein pluvial Lake Alamosa in the northern San Luis Basin overflowed, and began to drain to the south across the closed Sunshine Valley–Costilla Plain region ≤400 ka. By ~200 ka, erosion had cut through topographic highs at Ute Mountain and the Red River fault zone, and began deep-canyon incision across the southern San Luis Basin. Previous studies indicate that prior to 200 ka, the present Rio Grande terminated into a large bolson complex in the vicinity of El Paso, Texas, and systematic, headward erosional processes had subtly integrated discontinuously connected basins along the eastern flank of the Rio Grande rift and southern Rocky Mountains. We propose that the integration of the entire San Luis Basin into the Rio Grande drainage system (~400–200 ka) was the critical event in the formation of the modern Rio Grande, integrating hinterland basins of the Rio Grande rift from El Paso, Texas, north to the San Luis Basin with the Gulf of Mexico. This event dramatically affected basins southeast of El Paso, Texas, across the Chisos Mountains and southeastern Basin and Range province, including the Rio Conchos watershed and much of the Chihuahuan Desert, inducing broad regional landscape incision and exhumation.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/2016.0044(13)","usgsCitation":"Ruleman, C.A., Machette, M., Thompson, R.A., Miggins, D.M., Goehring, B.M., and Paces, J.B., 2016, Geomorphic evolution of the San Luis Basin and Rio Grande in southern Colorado and northern New Mexico: GSA Field Guides, v. 44, p. 291-333, https://doi.org/10.1130/2016.0044(13).","productDescription":"43 p.","startPage":"291","endPage":"333","ipdsId":"IP-076013","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":340697,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":" Colorado, New Mexico","otherGeospatial":"Rio Grande, San Luis Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105,\n 36.2\n ],\n [\n -106.5,\n 36.2\n ],\n [\n -106.5,\n 38.5\n ],\n [\n -105,\n 38.5\n ],\n [\n -105,\n 36.2\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"44","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59084929e4b0fc4e448ffd56","contributors":{"authors":[{"text":"Ruleman, Chester A. 0000-0002-1503-4591 cruleman@usgs.gov","orcid":"https://orcid.org/0000-0002-1503-4591","contributorId":1264,"corporation":false,"usgs":true,"family":"Ruleman","given":"Chester","email":"cruleman@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":693582,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Machette, Michael","contributorId":191604,"corporation":false,"usgs":false,"family":"Machette","given":"Michael","affiliations":[],"preferred":false,"id":693584,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Ren A. 0000-0002-3044-3043 rathomps@usgs.gov","orcid":"https://orcid.org/0000-0002-3044-3043","contributorId":1265,"corporation":false,"usgs":true,"family":"Thompson","given":"Ren","email":"rathomps@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":693583,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miggins, Dan M","contributorId":191605,"corporation":false,"usgs":false,"family":"Miggins","given":"Dan","email":"","middleInitial":"M","affiliations":[],"preferred":false,"id":693585,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goehring, Brent M","contributorId":191606,"corporation":false,"usgs":false,"family":"Goehring","given":"Brent","email":"","middleInitial":"M","affiliations":[],"preferred":false,"id":693586,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Paces, James B. 0000-0002-9809-8493 jbpaces@usgs.gov","orcid":"https://orcid.org/0000-0002-9809-8493","contributorId":2514,"corporation":false,"usgs":true,"family":"Paces","given":"James","email":"jbpaces@usgs.gov","middleInitial":"B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":693587,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70193166,"text":"70193166 - 2016 - A GIS model of habitat suitability for Solanum conocarpum (Solanaceae) in St. John, US Virgin Islands","interactions":[],"lastModifiedDate":"2017-11-20T15:42:39","indexId":"70193166","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5533,"text":"Caribbean Naturalist","onlineIssn":"2326-7119","active":true,"publicationSubtype":{"id":10}},"displayTitle":"A GIS model of habitat suitability for Solanum conocarpum (Solanaceae) in St. John, US Virgin Islands","title":"A GIS model of habitat suitability for Solanum conocarpum (Solanaceae) in St. John, US Virgin Islands","docAbstract":"Solanum conocarpum (Solanaceae) (Marron Bacora) is a rare, dry-forest shrub endemic to the island of St. John, US Virgin Islands, considered for listing under the Endangered Species Act. Given its status as a species of conservation concern, we incorporated environmental characteristics of 3 observed populations and 5 additional known locations into a geographic information system (GIS) analysis to create a habitat-suitability model for the species on the island of St. John. Our model identified 1929.87 ha of highly suitable and moderately suitable habitat. Of these, 1161.20 ha (60.2%) occurred within the boundaries of Virgin Islands National Park. Our model provides spatial information on potential locations for future surveys and restoration sites for this endemic species of the US Virgin Islands.
","language":"English","publisher":"Caribbean Naturalist","usgsCitation":"Palumbo, M.D., Fleming, J.P., Monsegur, O.A., and Vilella, F., 2016, A GIS model of habitat suitability for Solanum conocarpum (Solanaceae) in St. John, US Virgin Islands: Caribbean Naturalist, v. 36, p. 1-10.","productDescription":"10 p.","startPage":"1","endPage":"10","ipdsId":"IP-078831","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":349159,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fd88e4b06e28e9c24faf","contributors":{"authors":[{"text":"Palumbo, Matthew D.","contributorId":146265,"corporation":false,"usgs":false,"family":"Palumbo","given":"Matthew","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":722926,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fleming, Jonathan P.","contributorId":200629,"corporation":false,"usgs":false,"family":"Fleming","given":"Jonathan","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":722927,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Monsegur, Omar A.","contributorId":200630,"corporation":false,"usgs":false,"family":"Monsegur","given":"Omar","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":722928,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vilella, Francisco 0000-0003-1552-9989 fvilella@usgs.gov","orcid":"https://orcid.org/0000-0003-1552-9989","contributorId":171363,"corporation":false,"usgs":true,"family":"Vilella","given":"Francisco","email":"fvilella@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":718114,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70192838,"text":"70192838 - 2016 - Significance of beating observed in earthquake responses of buildings","interactions":[],"lastModifiedDate":"2018-02-02T15:10:33","indexId":"70192838","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Significance of beating observed in earthquake responses of buildings","docAbstract":"The beating phenomenon observed in the recorded responses of a tall building in Japan and another in the U.S. are examined in this paper. Beating is a periodic vibrational behavior caused by distinctive coupling between translational and torsional modes that typically have close frequencies. Beating is prominent in the prolonged resonant responses of lightly damped structures. Resonances caused by site effects also contribute to accentuating the beating effect. Spectral analyses and system identification techniques are used herein to quantify the periods and amplitudes of the beating effects from the strong motion recordings of the two buildings. Quantification of beating effects is a first step towards determining remedial actions to improve resilient building performance to strong earthquake induced shaking.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"16th U.S.-Japan-New Zealand Workshop on the Improvement of Structural Engineering and Resiliency","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Applied Technology Council","usgsCitation":"Çelebi, M., Ghahari, S.F., and Taciroglu, E., 2016, Significance of beating observed in earthquake responses of buildings, in 16th U.S.-Japan-New Zealand Workshop on the Improvement of Structural Engineering and Resiliency.","ipdsId":"IP-075048","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":350988,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a7586d9e4b00f54eb1d81fa","contributors":{"authors":[{"text":"Çelebi, Mehmet 0000-0002-4769-7357 celebi@usgs.gov","orcid":"https://orcid.org/0000-0002-4769-7357","contributorId":3205,"corporation":false,"usgs":true,"family":"Çelebi","given":"Mehmet","email":"celebi@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":717144,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ghahari, S. F.","contributorId":147707,"corporation":false,"usgs":false,"family":"Ghahari","given":"S.","email":"","middleInitial":"F.","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":717145,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Taciroglu, E.","contributorId":147710,"corporation":false,"usgs":false,"family":"Taciroglu","given":"E.","email":"","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":717146,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70189206,"text":"70189206 - 2016 - Implications of the methodological choices for hydrologic portrayals of climate change over the contiguous United States: Statistically downscaled forcing data and hydrologic models","interactions":[],"lastModifiedDate":"2017-07-05T16:25:03","indexId":"70189206","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2344,"text":"Journal of Hydrometeorology","active":true,"publicationSubtype":{"id":10}},"title":"Implications of the methodological choices for hydrologic portrayals of climate change over the contiguous United States: Statistically downscaled forcing data and hydrologic models","docAbstract":"Continental-domain assessments of climate change impacts on water resources typically rely on statistically downscaled climate model outputs to force hydrologic models at a finer spatial resolution. This study examines the effects of four statistical downscaling methods [bias-corrected constructed analog (BCCA), bias-corrected spatial disaggregation applied at daily (BCSDd) and monthly scales (BCSDm), and asynchronous regression (AR)] on retrospective hydrologic simulations using three hydrologic models with their default parameters (the Community Land Model, version 4.0; the Variable Infiltration Capacity model, version 4.1.2; and the Precipitation–Runoff Modeling System, version 3.0.4) over the contiguous United States (CONUS). Biases of hydrologic simulations forced by statistically downscaled climate data relative to the simulation with observation-based gridded data are presented. Each statistical downscaling method produces different meteorological portrayals including precipitation amount, wet-day frequency, and the energy input (i.e., shortwave radiation), and their interplay affects estimations of precipitation partitioning between evapotranspiration and runoff, extreme runoff, and hydrologic states (i.e., snow and soil moisture). The analyses show that BCCA underestimates annual precipitation by as much as −250 mm, leading to unreasonable hydrologic portrayals over the CONUS for all models. Although the other three statistical downscaling methods produce a comparable precipitation bias ranging from −10 to 8 mm across the CONUS, BCSDd severely overestimates the wet-day fraction by up to 0.25, leading to different precipitation partitioning compared to the simulations with other downscaled data. Overall, the choice of downscaling method contributes to less spread in runoff estimates (by a factor of 1.5–3) than the choice of hydrologic model with use of the default parameters if BCCA is excluded.
","language":"English","publisher":"American Meteorological Society","doi":"10.1175/JHM-D-14-0187.1","usgsCitation":"Mizukami, N., Clark, M.P., Gutmann, E.D., Mendoza, P.A., Newman, A.J., Nijssen, B., Livneh, B., Hay, L.E., Arnold, J.R., and Brekke, L.D., 2016, Implications of the methodological choices for hydrologic portrayals of climate change over the contiguous United States: Statistically downscaled forcing data and hydrologic models: Journal of Hydrometeorology, v. 17, p. 75-98, https://doi.org/10.1175/JHM-D-14-0187.1.","productDescription":"24 p.","startPage":"75","endPage":"98","ipdsId":"IP-064865","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":471387,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jhm-d-14-0187.1","text":"Publisher Index Page"},{"id":343367,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-17","publicationStatus":"PW","scienceBaseUri":"595dfab0e4b0d1f9f056a763","contributors":{"authors":[{"text":"Mizukami, Naoki","contributorId":178120,"corporation":false,"usgs":false,"family":"Mizukami","given":"Naoki","email":"","affiliations":[],"preferred":false,"id":703484,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clark, Martyn P.","contributorId":194183,"corporation":false,"usgs":false,"family":"Clark","given":"Martyn","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":703485,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gutmann, Ethan D.","contributorId":194227,"corporation":false,"usgs":false,"family":"Gutmann","given":"Ethan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":703486,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mendoza, Pablo A.","contributorId":194228,"corporation":false,"usgs":false,"family":"Mendoza","given":"Pablo","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":703487,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Newman, Andrew J.","contributorId":194229,"corporation":false,"usgs":false,"family":"Newman","given":"Andrew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":703488,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nijssen, Bart","contributorId":178123,"corporation":false,"usgs":false,"family":"Nijssen","given":"Bart","email":"","affiliations":[],"preferred":false,"id":703490,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Livneh, Ben","contributorId":145804,"corporation":false,"usgs":false,"family":"Livneh","given":"Ben","email":"","affiliations":[{"id":12641,"text":"NOAA NMFS","active":true,"usgs":false}],"preferred":false,"id":703491,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"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":703502,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Arnold, Jeffrey R.","contributorId":178125,"corporation":false,"usgs":false,"family":"Arnold","given":"Jeffrey","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":703492,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Brekke, Levi D.","contributorId":6776,"corporation":false,"usgs":true,"family":"Brekke","given":"Levi","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":703493,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70187144,"text":"70187144 - 2016 - Modelling with stakeholders - Next generation","interactions":[],"lastModifiedDate":"2017-04-25T11:02:04","indexId":"70187144","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Modelling with stakeholders - Next generation","docAbstract":"This paper updates and builds on ‘Modelling with Stakeholders’ Voinov and Bousquet, 2010 which demonstrated the importance of, and demand for, stakeholder participation in resource and environmental modelling. This position paper returns to the concepts of that publication and reviews the progress made since 2010. A new development is the wide introduction and acceptance of social media and web applications, which dramatically changes the context and scale of stakeholder interactions and participation. Technology advances make it easier to incorporate information in interactive formats via visualization and games to augment participatory experiences. Citizens as stakeholders are increasingly demanding to be engaged in planning decisions that affect them and their communities, at scales from local to global. How people interact with and access models and data is rapidly evolving. In turn, this requires changes in how models are built, packaged, and disseminated: citizens are less in awe of experts and external authorities, and they are increasingly aware of their own capabilities to provide inputs to planning processes, including models. The continued acceleration of environmental degradation and natural resource depletion accompanies these societal changes, even as there is a growing acceptance of the need to transition to alternative, possibly very different, life styles. Substantive transitions cannot occur without significant changes in human behaviour and perceptions. The important and diverse roles that models can play in guiding human behaviour, and in disseminating and increasing societal knowledge, are a feature of stakeholder processes today.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2015.11.016","usgsCitation":"Voinov, A., Kolagani, N., McCall, M.K., Glynn, P.D., Kragt, M.E., Ostermann, F.O., Pierce, S.A., and Ramu, P., 2016, Modelling with stakeholders - Next generation: Environmental Modelling and Software, v. 77, p. 196-220, https://doi.org/10.1016/j.envsoft.2015.11.016.","productDescription":"25 p.","startPage":"196","endPage":"220","ipdsId":"IP-070044","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":471361,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1016/j.envsoft.2015.11.016","text":"External Repository"},{"id":340246,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"77","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59006063e4b0e85db3a5dddb","contributors":{"authors":[{"text":"Voinov, Alexey","contributorId":191330,"corporation":false,"usgs":false,"family":"Voinov","given":"Alexey","affiliations":[],"preferred":false,"id":692736,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kolagani, Nagesh","contributorId":191331,"corporation":false,"usgs":false,"family":"Kolagani","given":"Nagesh","email":"","affiliations":[],"preferred":false,"id":692737,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCall, Michael K","contributorId":191332,"corporation":false,"usgs":false,"family":"McCall","given":"Michael","email":"","middleInitial":"K","affiliations":[],"preferred":false,"id":692738,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Glynn, Pierre D. 0000-0001-8804-7003 pglynn@usgs.gov","orcid":"https://orcid.org/0000-0001-8804-7003","contributorId":2141,"corporation":false,"usgs":true,"family":"Glynn","given":"Pierre","email":"pglynn@usgs.gov","middleInitial":"D.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":692735,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kragt, Marit E","contributorId":191333,"corporation":false,"usgs":false,"family":"Kragt","given":"Marit","email":"","middleInitial":"E","affiliations":[],"preferred":false,"id":692739,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ostermann, Frank O","contributorId":191334,"corporation":false,"usgs":false,"family":"Ostermann","given":"Frank","email":"","middleInitial":"O","affiliations":[],"preferred":false,"id":692740,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pierce, Suzanne A","contributorId":191335,"corporation":false,"usgs":false,"family":"Pierce","given":"Suzanne","email":"","middleInitial":"A","affiliations":[],"preferred":false,"id":692741,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ramu, Palaniappan","contributorId":191336,"corporation":false,"usgs":false,"family":"Ramu","given":"Palaniappan","email":"","affiliations":[],"preferred":false,"id":692742,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70186896,"text":"70186896 - 2016 - Feeding ecology of non-native Siberian prawns, Palaemon modestus (Heller, 1862) (Decapoda, Palaemonidae), in the lower Snake River, Washington, U.S.A.","interactions":[],"lastModifiedDate":"2017-04-13T14:56:16","indexId":"70186896","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1348,"text":"Crustaceana","active":true,"publicationSubtype":{"id":10}},"title":"Feeding ecology of non-native Siberian prawns, Palaemon modestus (Heller, 1862) (Decapoda, Palaemonidae), in the lower Snake River, Washington, U.S.A.","docAbstract":"We used both stomach content and stable isotope analyses to describe the feeding ecology of Siberian prawns Palaemon modestus (Heller, 1862), a non-native caridean shrimp that is a relatively recent invader of the lower Snake River. Based on identifiable prey in stomachs, the opossum shrimp Neomysis mercedis Holmes, 1896 comprised up to 34-55% (by weight) of diets of juvenile to adult P. modestus, which showed little seasonal variation. Other predominant items/taxa consumed included detritus, amphipods, dipteran larvae, and oligochaetes. Stable isotope analysis supported diet results and also suggested that much of the food consumed by P. modestus that was not identifiable came from benthic sources — predominantly invertebrates of lower trophic levels and detritus. Palaemon modestus consumption of N. mercedis may pose a competitive threat to juvenile salmon and resident fishes which also rely heavily on that prey.
","language":"English","publisher":"BRILL","doi":"10.1163/15685403-00003553","usgsCitation":"Tiffan, K.F., and Hurst, W., 2016, Feeding ecology of non-native Siberian prawns, Palaemon modestus (Heller, 1862) (Decapoda, Palaemonidae), in the lower Snake River, Washington, U.S.A.: Crustaceana, v. 89, no. 6-7, p. 721-736, https://doi.org/10.1163/15685403-00003553.","productDescription":"16 p.","startPage":"721","endPage":"736","ipdsId":"IP-073452","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":339703,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Snake River","volume":"89","issue":"6-7","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58f08e60e4b06911a29fa854","contributors":{"authors":[{"text":"Tiffan, Kenneth F. 0000-0002-5831-2846 ktiffan@usgs.gov","orcid":"https://orcid.org/0000-0002-5831-2846","contributorId":3200,"corporation":false,"usgs":true,"family":"Tiffan","given":"Kenneth","email":"ktiffan@usgs.gov","middleInitial":"F.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":690914,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hurst, William 0000-0001-5758-8210 whurst@usgs.gov","orcid":"https://orcid.org/0000-0001-5758-8210","contributorId":139838,"corporation":false,"usgs":true,"family":"Hurst","given":"William","email":"whurst@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":690915,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70048652,"text":"70048652 - 2016 - By-products of porphyry copper and molybdenum deposits","interactions":[],"lastModifiedDate":"2022-12-29T15:36:53.359262","indexId":"70048652","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"7","title":"By-products of porphyry copper and molybdenum deposits","docAbstract":"Porphyry Cu and porphyry Mo deposits are large to giant deposits ranging up to >20 and 1.6 Gt of ore, respectively, that supply about 60 and 95% of the world’s copper and molybdenum, as well as significant amounts of gold and silver. These deposits form from hydrothermal systems that affect 10s to >100 km3 of the upper crust and result in enormous mass redistribution and potential concentration of many elements.
Several critical elements, including Re, Se, and Te, which lack primary ores, are concentrated locally in some porphyry Cu deposits, and despite their low average concentrations in Cu-Mo-Au ores (100s of ppb to a few ppm), about 80% of the Re and nearly all of the Se and Te produced by mining is from porphyry Cu deposits.
Rhenium is concentrated in molybdenite, whose Re content varies from about 100 to 3,000 ppm in porphyry Cu deposits, ≤150 ppm in arc-related porphyry Mo deposits, and ≤35 ppm in alkali-feldspar rhyolite-granite (Climax-type) porphyry Mo deposits. Because of the relatively small size of porphyry Mo deposits compared to porphyry Cu deposits and the generally low Re contents of molybdenites in them, rhenium is not recovered from porphyry Mo deposits. The potential causes of the variation in Re content of molybdenites in porphyry deposits are numerous and complex, and this variation is likely the result of a combination of processes that may change between and within deposits. These processes range from variations in source and composition of parental magmas to physiochemical changes in the shallow hydrothermal environment. Because of the immense size of known and potential porphyry Cu resources, especially continental margin arc deposits, these deposits likely will provide most of the global supply of Re, Te, and Se for the foreseeable future.
Although Pd and lesser Pt are recovered from some deposits, platinum group metals are not strongly enriched in porphyry Cu deposits and PGM resources contained in known porphyry deposits are small. Because there are much larger known PGM resources in deposits in which PGMs are the primary commodities, it is unlikely that porphyry deposits will become a major source of PGMs.
Other critical commodities, such as In and Nb, may eventually be recovered from porphyry Cu and Mo deposits, but available data do not clearly define significant resources of these commodities in porphyry deposits. Although alkali-feldspar rhyolite-granite porphyry Mo deposits and their cogenetic intrusions are locally enriched in many rare metals (such as Li, Nb, Rb, Sn, Ta, and REEs) and minor amounts of REEs and Sn have been recovered from the Climax mine, these elements are generally found in uneconomic concentrations.
As global demand increases for critical elements that are essential for the modern world, porphyry deposits will play an increasingly important role as suppliers of some of these metals. The affinity of these metals and the larger size and greater number of porphyry Cu deposits suggest that they will remain more significant than porphyry Mo deposits in supplying many of these critical metals.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Rare earth and critical elements in ore deposits","largerWorkSubtype":{"id":15,"text":"Monograph"},"publisher":"Society of Economic Geologists","doi":"10.5382/Rev.18.07","usgsCitation":"John, D.A., and Taylor, R.D., 2016, By-products of porphyry copper and molybdenum deposits, chap. 7 of Rare earth and critical elements in ore deposits, v. 18, p. 137-164, https://doi.org/10.5382/Rev.18.07.","productDescription":"28 p.","startPage":"137","endPage":"164","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-050834","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":355932,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fca44e4b0f5d57878ec95","contributors":{"editors":[{"text":"Verplanck, Philip L. 0000-0002-3653-6419 plv@usgs.gov","orcid":"https://orcid.org/0000-0002-3653-6419","contributorId":728,"corporation":false,"usgs":true,"family":"Verplanck","given":"Philip","email":"plv@usgs.gov","middleInitial":"L.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":740796,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Hitzman, Murray W. 0000-0002-3876-0537 mhitzman@usgs.gov","orcid":"https://orcid.org/0000-0002-3876-0537","contributorId":200913,"corporation":false,"usgs":true,"family":"Hitzman","given":"Murray","email":"mhitzman@usgs.gov","middleInitial":"W.","affiliations":[],"preferred":false,"id":740797,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"John, David A. 0000-0001-7977-9106 djohn@usgs.gov","orcid":"https://orcid.org/0000-0001-7977-9106","contributorId":1748,"corporation":false,"usgs":true,"family":"John","given":"David","email":"djohn@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":518222,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taylor, Ryan D. 0000-0002-8845-5290 rtaylor@usgs.gov","orcid":"https://orcid.org/0000-0002-8845-5290","contributorId":3412,"corporation":false,"usgs":true,"family":"Taylor","given":"Ryan","email":"rtaylor@usgs.gov","middleInitial":"D.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":518223,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70162226,"text":"70162226 - 2016 - Earthquake probabilities for the Wasatch front region in Utah, Idaho, and Wyoming","interactions":[],"lastModifiedDate":"2019-08-06T10:00:31","indexId":"70162226","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Earthquake probabilities for the Wasatch front region in Utah, Idaho, and Wyoming","docAbstract":"In a letter to The Salt Lake Daily Tribune in September 1883, U.S. Geological Survey (USGS) geologist G.K. Gilbert warned local residents about the implications of observable fault scarps along the western base of the Wasatch Range. The scarps were evidence that large surface-rupturing earthquakes had occurred in the past and more would likely occur in the future. The main actor in this drama is the 350-km-long Wasatch fault zone (WFZ), which extends from central Utah to southernmost Idaho. The modern Wasatch Front urban corridor, which follows the valleys on the WFZ’s hanging wall between Brigham City and Nephi, is home to nearly 80% of Utah’s population of 3 million. Adding to this circumstance of “lots of eggs in one basket,” more than 75% of Utah’s economy is concentrated along the Wasatch Front in Utah’s four largest counties, literally astride the five central and most active segments of the WFZ.
","language":"English","publisher":"Utah Geological Survey ","usgsCitation":"Wong, I.G., Lund, W., DuRoss, C., Thomas, P., Arabasz, W., Crone, A.J., Hylland, M., Luco, N., Olig, S.S., Pechmann, J.C., Personius, S., Petersen, M.D., Schwartz, D.P., Smith, R.B., and Rowman, S., 2016, Earthquake probabilities for the Wasatch front region in Utah, Idaho, and Wyoming, Report: xiv., 164 p.; Appendixes A-E.","productDescription":"Report: xiv., 164 p.; Appendixes A-E","ipdsId":"IP-072108","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":336342,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":336340,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://quake.utah.edu/research/earthquake-probabilities-for-the-wasatch-front-region-in-utah-idaho-and-wyoming"}],"country":"United States","state":"Utah, Idaho, 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pathogen trait that can evolve in response to selection has led to a large body of virulence evolution theory developed in the 1980-1990s. Various aspects of this theory predict increased or decreased virulence in response to a complex array of selection pressures including mode of transmission, changes in host, mixed infection, vector-borne transmission, environmental changes, host vaccination, host resistance, and co-evolution of virus and host. A fundamental concept is prediction of trade-offs between the costs and benefits associated with higher virulence, leading to selection of optimal virulence levels. Through a combination of observational and experimental studies, including experimental evolution of viruses during serial passage, many of these predictions have now been explored in systems ranging from bacteriophage to viruses of plants, invertebrates, and vertebrate hosts. This chapter summarizes empirical studies of viral virulence evolution in numerous diverse systems, including the classic models myxomavirus in rabbits, Marek's disease virus in chickens, and HIV in humans. Collectively these studies support some aspects of virulence evolution theory, suggest modifications for other aspects, and show that predictions may apply in some virus:host interactions but not in others. Finally, we consider how virulence evolution theory applies to disease management in the field.
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","language":"English","publisher":"Canadian Center of Science and Education","doi":"10.5539/jgg.v8n1p28","usgsCitation":"Shoberg, T.G., 2016, Conflation and integration of archived geologic maps and associated uncertainties: Journal of Geography and Geology, v. 8, no. 1, p. 28-40, https://doi.org/10.5539/jgg.v8n1p28.","productDescription":"13 p.","startPage":"28","endPage":"40","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071720","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":471377,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5539/jgg.v8n1p28","text":"Publisher Index Page"},{"id":318407,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"1","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-24","publicationStatus":"PW","scienceBaseUri":"576913b5e4b07657d19feffa","contributors":{"authors":[{"text":"Shoberg, Thomas G. 0000-0003-0173-1246 tshoberg@usgs.gov","orcid":"https://orcid.org/0000-0003-0173-1246","contributorId":3764,"corporation":false,"usgs":true,"family":"Shoberg","given":"Thomas","email":"tshoberg@usgs.gov","middleInitial":"G.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":621442,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70168512,"text":"70168512 - 2016 - Does the stress-gradient hypothesis hold water? Disentangling spatial and temporal variation in plant effects on soil moisture in dryland systems","interactions":[],"lastModifiedDate":"2016-02-18T09:24:52","indexId":"70168512","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1711,"text":"Functional Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Does the stress-gradient hypothesis hold water? Disentangling spatial and temporal variation in plant effects on soil moisture in dryland systems","docAbstract":"