Effective habitat conservation is predicated on maintaining high levels or increasing local persistence probability of the species it purports to protect. Thus, methodological approaches that improve the inferential value of local persistence are of utmost value to guide conservation planning as they inform area selection processes. Herein we used the painted bunting Passerina ciris, a species of conservation interest in North Carolina, as an illustrative case that combined single-season, single-species occupancy analyses and a threats and risk decision support tool to rank five areas of conservation interest in terms of local persistence probability. We used survey data from two seasons (2008–2009) grouped into 21 natal dispersal sampling units and land-cover data from 12 habitat classes to establish the relationship between local occupancy probability and habitat. Occupancy increased most strongly with increasing amount of maritime forest. Projections to year 2050, relative to year 2000, indicated that a potential loss of maritime forest of 200–1,300 ha, depending on the area of interest. Projected loss was lowest at Bald Head Island–Wilmington (2%) and highest at Camp Lejune (27%). Bald Head Island–Wilmington ranked highest in projected local persistence probability (0.91; 95% confidence interval [CI] = 0.53–0.99), whereas Top Sail–Hammocks Beach Park ranked lowest (0.28; 95% CI = 0.03–0.82). Estimates of local persistence offer decision-makers another criterion to prioritize areas for conservation and help guide efforts aimed at maintaining or enhancing local persistence. These include in situ habitat management, expanding or connecting existing areas of interest. In the future, we recommend the use of multiseason occupancy models, coupled with measures of uncertainty of land-cover projections, to strengthen inferences about local persistence, particularly useful in nonstationary landscapes driven by human activities.
","language":"English","publisher":"Allen Press","doi":"10.3996/112017-JFWM-089","usgsCitation":"Yirka, L., Collazo, J.A., Williams, S.G., and Cobb, D.T., 2018, Persistence-based area prioritization for conservation: Applying occupancy and habitat threats and risks analyses: Journal of Fish and Wildlife Management, v. 9, no. 2, p. 554-564, https://doi.org/10.3996/112017-JFWM-089.","productDescription":"11 p.","startPage":"554","endPage":"564","ipdsId":"IP-091420","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":468355,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/112017-jfwm-089","text":"Publisher Index Page"},{"id":395051,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.6126708984375,\n 33.80197351806589\n ],\n [\n -76.53350830078125,\n 33.80197351806589\n ],\n [\n -76.53350830078125,\n 34.87015842600913\n ],\n [\n -78.6126708984375,\n 34.87015842600913\n ],\n [\n -78.6126708984375,\n 33.80197351806589\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"2","noUsgsAuthors":false,"publicationDate":"2018-10-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Yirka, L. 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The effects of plague on prairie dogs and ferrets are mitigated using a deltamethrin pulicide dust that reduces the spread of plague by killing fleas, the vector for the plague bacterium. In portions of Conata Basin, Buffalo Gap National Grassland, and Badlands National Park, South Dakota, US, 0.05% deltamethrin has been infused into prairie dog burrows on an annual basis since 2005. We aimed to determine if fleas (Oropsylla hirsuta) in portions of the Conata Basin and Badlands National Park have evolved resistance to deltamethrin. We assessed flea prevalence, obtained by combing prairie dogs for fleas, as an indirect measure of resistance. Dusting was ineffective in two colonies treated with deltamethrin for >8 yr; flea prevalence rebounded within 1 mo of dusting. We used a bioassay that exposed fleas to deltamethrin to directly evaluate resistance. Fleas from colonies with >8 yr of exposure to deltamethrin exhibited survival rates that were 15% to 83% higher than fleas from sites that had never been dusted. All fleas were paralyzed or dead after 55 min. After removal from deltamethrin, 30% of fleas from the dusted colonies recovered, compared with 1% of fleas from the not-dusted sites. Thus, deltamethrin paralyzed fleas from colonies with long-term exposure to deltamethrin, but a substantial number of those fleas was resistant and recovered. Flea collections from live-trapped prairie dogs in Thunder Basin National Grassland, Wyoming, US, suggest that, in some cases, fleas might begin to develop a moderate level of resistance to deltamethrin after 5–6 yr of annual treatments. Restoration of black-footed ferrets and prairie dogs will rely on an adaptive, integrative approach to plague management, for instance involving the use of vaccines and rotating applications of insecticidal products with different active ingredients.
","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/2017-10-250","usgsCitation":"Eads, D.A., Biggins, D.E., Bowser, J., McAllister, J., Griebel, R., Childers, E., Livieri, T.M., Painter, C., Sterling Krank, L., and Bly, K., 2018, Resistance to deltamethrin in prairie dog (Cynomys ludovicianus) fleas in the field and in the laboratory: Journal of Wildlife Diseases, v. 54, no. 4, p. 745-754, https://doi.org/10.7589/2017-10-250.","productDescription":"10 p.","startPage":"745","endPage":"754","ipdsId":"IP-089457","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":460837,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6710209","text":"External Repository"},{"id":437732,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7PR7V5N","text":"USGS data release","linkHelpText":"Data on deltamethrin resistance in 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S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":835742,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sterling Krank, Lindsey","contributorId":279933,"corporation":false,"usgs":false,"family":"Sterling Krank","given":"Lindsey","email":"","affiliations":[{"id":57388,"text":"Humane Society of the United States","active":true,"usgs":false}],"preferred":false,"id":835743,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Bly, Kristy","contributorId":279935,"corporation":false,"usgs":false,"family":"Bly","given":"Kristy","email":"","affiliations":[{"id":37767,"text":"World Wildlife Fund","active":true,"usgs":false}],"preferred":false,"id":835744,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70216764,"text":"70216764 - 2018 - Development of the Wildlife Adaptation Menu for Resource Managers","interactions":[],"lastModifiedDate":"2020-12-14T17:48:28.022309","indexId":"70216764","displayToPublicDate":"2018-09-30T11:46:19","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"seriesTitle":{"id":7468,"text":"Final Report","active":true,"publicationSubtype":{"id":9}},"title":"Development of the Wildlife Adaptation Menu for Resource Managers","docAbstract":"The Climate Change Response Framework is an example of a collaborative, cross-boundary approach to create a set of tools, partnerships, and actions to support climate-informed conservation and land management. Historically, this effort has focused on the needs of forest managers and forestry professionals. In recent years, however, there has been increasing demand for science and tools to address climate change adaptation in wildlife management and conservation. Not only do wildlife and resource managers need the best available science, it must also be presented in a usable format with feasible options within the purview of an individual manager.
The research team is first completing a comprehensive review of peer-reviewed studies to summarize what wildlife-related management actions currently exist in climate change adaptation. They will then develop and test a “menu” of climate change adaptation actions that are suitable for wildlife management in terrestrial ecosystems. This Wildlife Adaptation Menu will be modeled off existing adaptation menus for Forestry and Urban Forestry, and it will be designed to be used in conjunction with the Adaptation Workbook. In addition to a menu of adaption strategies and approaches, the scientists will also identify site-level tactics and develop case studies demonstrating the use and implementation of the menu. To ensure that information and tools meet the needs of managers, the team is involving and integrating input from wildlife managers at every step of the process. Managers will be involved in scoping the project, testing the menu, and implementing the menu.
For millennia, wildfires have markedly influenced forests and non-forested landscapes of the western United States (US), and they are increasingly seen as having substantial impacts on society and nature. There is growing concern over what kinds and amounts of fire will achieve desirable outcomes and limit harmful effects on people and nature. Moreover, the increasing complexity surrounding cost and management of wildfires suggests that science should play a more prominent role in informing decisions about the need for fire in nature, and the need for society to adapt to the inevitable occurrence of different kinds and amounts of fire and smoke.
Scientists widely view the natural wildfire regime as essential to western US forest ecosystem functioning. However, debates continue over how much low-, moderate-, and high severity fire is “natural” or desirable in these forests. Ongoing disagreement centers on the characteristics and importance of historical proportions and patch size distributions of low-, moderate-, and high-severity fires of dry, moist, and cold forests, and on the ecological consequences of changing fire-patch patterns and relative abundances. Scientists also debate the relative importance of climate and extreme weather versus fuel as drivers of high-severity fire, as well as the effectiveness and value of fuel treatments for reducing risks of undesired fire effects.
Climate research shows that we should expect shifting future climates in all ecoregions. These expected changes make it difficult for scientists, land managers, and decision-makers to know the degree to which future forest management should be informed by historical conditions. There also is disagreement about how to make western forests more resilient to future disruptions in both climatic and fire regimes. To complicate matters, areas of scientific agreement -- the “common ground” shared by those in the research community -- are poorly articulated. Thus, the focus of the Fire Research Consensus (FRC) project has been to identify common ground among scientists, and provide a summary that can inform management. Land and fire managers are one audience for this report, as are stakeholders and the interested public.
Our analysis, which results from extensive scientific literature reviews and questionnaires sent to western fire scientists and land managers, is summarized in nine key
topics:
A. Fire history and fire ecology vary with geography.
B. Human impacts and management history vary with geography.
C. Fire is a keystone process, which occurs in almost all western US forest types.
D. Knowledge of historical range of variability (HRV) is useful but does not dictate land
management goals.
E. Forest structure, composition, and fuels have changed, affecting burn severity and
fire extent.
F. Climate and fuels both influence current fire sizes and their severities.
G. The role of changing climatic conditions is increasingly important.
H. Multiple fire ecology and fire history research approaches can be useful for
characterizing fire regimes.
I. Many existing fire management tools and strategies can be useful moving forward.
We found much common ground that will be useful to scientists, managers, citizens, and policy decision-makers. For example, there is wide agreement among scientists that fire is one of the most essential influences on western forests and that more fire is needed on most landscapes, but not all wildfire behavior or extent will do. Fires can produce more positive benefits and fewer negative impacts when they burn with an ecologically appropriate mix and pattern of low, moderate, and high severity. Managers will need assistance and funding to create landscape conditions that favor more desirable fire behavior at broad spatial scales. Note that much societal impact from western wildfires occurs in non-forested landscapes that are not covered in this report, where findings would differ from those reported here for forested landscapes. We summarize additional key points below.
","language":"English","publisher":"National Center for Ecological Analysis and Synthesis","usgsCitation":"Moritz, M.A., Topik, C., Allen, C.D., Hessburg, P.F., Morgan, P., Odion, D.C., Veblen, T.T., and McCullough, I.M., 2018, A statement of common ground regarding the role of wildfire in forested landscapes of the western United States: Final Report, 55 p.","productDescription":"55 p.","ipdsId":"IP-099757","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":382548,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":382533,"type":{"id":15,"text":"Index Page"},"url":"https://www.nceas.ucsb.edu/snapp/fire-research-consensus"}],"country":"United States","otherGeospatial":"Western United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.71679687499999,\n 31.952162238024975\n ],\n [\n -103.095703125,\n 31.952162238024975\n ],\n [\n -103.095703125,\n 48.69096039092549\n ],\n [\n -124.71679687499999,\n 48.69096039092549\n ],\n [\n -124.71679687499999,\n 31.952162238024975\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Moritz, Max A.","contributorId":182434,"corporation":false,"usgs":false,"family":"Moritz","given":"Max","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":808909,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Topik, Chris","contributorId":248342,"corporation":false,"usgs":false,"family":"Topik","given":"Chris","email":"","affiliations":[{"id":49864,"text":"The Nature Conservancy, North America Forest Restoration Program","active":true,"usgs":false}],"preferred":false,"id":808910,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, Craig D. 0000-0002-8777-5989 craig_allen@usgs.gov","orcid":"https://orcid.org/0000-0002-8777-5989","contributorId":2597,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"craig_allen@usgs.gov","middleInitial":"D.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":808911,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hessburg, Paul F.","contributorId":46481,"corporation":false,"usgs":false,"family":"Hessburg","given":"Paul","email":"","middleInitial":"F.","affiliations":[{"id":12647,"text":"U.S. Forest Service, Pacific Northwest Research Station","active":true,"usgs":false}],"preferred":false,"id":808912,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Morgan, Penelope","contributorId":127585,"corporation":false,"usgs":false,"family":"Morgan","given":"Penelope","email":"","affiliations":[],"preferred":false,"id":808913,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Odion, Dennis C.","contributorId":248343,"corporation":false,"usgs":false,"family":"Odion","given":"Dennis","email":"","middleInitial":"C.","affiliations":[{"id":28103,"text":"University of California - Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":808914,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Veblen, Thomas T.","contributorId":218196,"corporation":false,"usgs":false,"family":"Veblen","given":"Thomas","email":"","middleInitial":"T.","affiliations":[{"id":36627,"text":"University of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":808915,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McCullough, Ian M.","contributorId":149952,"corporation":false,"usgs":false,"family":"McCullough","given":"Ian","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":808916,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70199790,"text":"70199790 - 2018 - Time series of high-resolution images enhances efforts to monitor post-fire condition and recovery, Waldo Canyon fire, Colorado, USA","interactions":[],"lastModifiedDate":"2018-10-23T16:44:04","indexId":"70199790","displayToPublicDate":"2018-09-28T13:04:11","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2083,"text":"International Journal of Wildland Fire","active":true,"publicationSubtype":{"id":10}},"title":"Time series of high-resolution images enhances efforts to monitor post-fire condition and recovery, Waldo Canyon fire, Colorado, USA","docAbstract":"Interpretations of post-fire condition and rates of vegetation recovery can influence management priorities, actions and perception of latent risks from landslides and floods. In this study, we used the Waldo Canyon fire (2012, Colorado Springs, Colorado, USA) as a case study to explore how a time series (2011–2016) of high-resolution images can be used to delineate burn extent and severity, as well as quantify post-fire vegetation recovery. We applied an object-based approach to map burn severity and vegetation recovery using Worldview-2, Worldview-3 and QuickBird-2 imagery. The burned area was classified as 51% high, 20% moderate and 29% low burn-severity. Across the burn extent, the shrub cover class showed a rapid recovery, resprouting vigorously within 1 year, whereas 4 years post-fire, areas previously dominated by conifers were divided approximately equally between being classified as dominated by quaking aspen saplings with herbaceous species in the understorey or minimally recovered. Relative to using a pixel-based Normalised Difference Vegetation Index (NDVI), our object-based approach showed higher rates of revegetation. High-resolution imagery can provide an effective means to monitor post-fire site conditions and complement more prevalent efforts with moderate- and coarse-resolution sensors.
","language":"English","publisher":"CSIRO Publishing","doi":"10.1071/WF17177","usgsCitation":"Vanderhoof, M.K., Burt, C., and Hawbaker, T., 2018, Time series of high-resolution images enhances efforts to monitor post-fire condition and recovery, Waldo Canyon fire, Colorado, USA: International Journal of Wildland Fire, v. 27, no. 10, p. 699-713, https://doi.org/10.1071/WF17177.","productDescription":"15 p.","startPage":"699","endPage":"713","ipdsId":"IP-093249","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":437734,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NWJQJR","text":"USGS data release","linkHelpText":"Data release for Time series of high-resolution images enhances efforts to monitor post-fire condition and recovery, Waldo Canyon fire, Colorado, USA"},{"id":357904,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Waldo Canyon ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105,\n 38.8667\n ],\n [\n -104.8667,\n 38.8667\n ],\n [\n -104.8667,\n 39\n ],\n [\n -105,\n 39\n ],\n [\n -105,\n 38.8667\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"27","issue":"10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02f85e4b0fc368eb5387b","contributors":{"authors":[{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":746619,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burt, Clifton 0000-0001-5213-800X","orcid":"https://orcid.org/0000-0001-5213-800X","contributorId":208271,"corporation":false,"usgs":true,"family":"Burt","given":"Clifton","email":"","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":746620,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":568,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":746621,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70199794,"text":"70199794 - 2018 - Efficient delineation of nested depression hierarchy in digital elevation models for hydrological analysis using level-set method","interactions":[],"lastModifiedDate":"2019-05-29T09:31:14","indexId":"70199794","displayToPublicDate":"2018-09-28T12:54:22","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Efficient delineation of nested depression hierarchy in digital elevation models for hydrological analysis using level-set method","docAbstract":"In terrain analysis and hydrological modeling, surface depressions (or sinks) in a digital elevation model (DEM) are commonly treated as artifacts and thus filled and removed to create a depressionless DEM. Various algorithms have been developed to identify and fill depressions in DEMs during the past decades. However, few studies have attempted to delineate and quantify the nested hierarchy of actual depressions, which can provide crucial information for characterizing surface hydrologic connectivity and simulating the fill‐merge‐spill hydrological process. In this paper, we present an innovative and efficient algorithm for delineating and quantifying nested depressions in DEMs using the level‐set method based on graph theory. The proposed level‐set method emulates water level decreasing from the spill point along the depression boundary to the lowest point at the bottom of a depression. By tracing the dynamic topological changes (i.e., depression splitting/merging) within a compound depression, the level‐set method can construct topological graphs and derive geometric properties of the nested depressions. The experimental results of two fine‐resolution Light Detection and Ranging‐derived DEMs show that the raster‐based level‐set algorithm is much more efficient (~150 times faster) than the vector‐based contour tree method. The proposed level‐set algorithm has great potential for being applied to large‐scale ecohydrological analysis and watershed modeling.
","language":"English","publisher":"American Water Resources Association","doi":"10.1111/1752-1688.12689","usgsCitation":"Wu, Q., Lane, C., Wang, L., Vanderhoof, M.K., Christensen, J.R., and Liu, H., 2018, Efficient delineation of nested depression hierarchy in digital elevation models for hydrological analysis using level-set method: Journal of the American Water Resources Association, v. 55, no. 2, p. 354-368, https://doi.org/10.1111/1752-1688.12689.","productDescription":"15 p.","startPage":"354","endPage":"368","ipdsId":"IP-094162","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":468357,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7995241","text":"External Repository"},{"id":357902,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"55","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-28","publicationStatus":"PW","scienceBaseUri":"5bc02f86e4b0fc368eb5387f","contributors":{"authors":[{"text":"Wu, Qiusheng","contributorId":208272,"corporation":false,"usgs":false,"family":"Wu","given":"Qiusheng","email":"","affiliations":[{"id":37769,"text":"Binghamton University","active":true,"usgs":false}],"preferred":false,"id":746633,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lane, Charles R.","contributorId":138991,"corporation":false,"usgs":false,"family":"Lane","given":"Charles R.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":746634,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Lei","contributorId":193279,"corporation":false,"usgs":false,"family":"Wang","given":"Lei","email":"","affiliations":[],"preferred":false,"id":746635,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":746632,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Christensen, Jay R.","contributorId":179361,"corporation":false,"usgs":false,"family":"Christensen","given":"Jay","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":746636,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Liu, Hongxing","contributorId":38075,"corporation":false,"usgs":true,"family":"Liu","given":"Hongxing","email":"","affiliations":[],"preferred":false,"id":746665,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70199795,"text":"70199795 - 2018 - A spatially discrete, integral projection model and its application to invasive carp","interactions":[],"lastModifiedDate":"2018-09-28T12:51:25","indexId":"70199795","displayToPublicDate":"2018-09-28T12:51:17","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"A spatially discrete, integral projection model and its application to invasive carp","docAbstract":"Natural resource managers and ecologists often desire an understanding of spatial dynamics such as migration, dispersion, and meta-population dynamics. Network-node models can capture these salient features. Additionally, the state-variable used with many species may be appropriately modeled as a continuous variable (e.g., length) and management activities sometimes can only target individuals of certain sizes. Integral projection models (IPMs) can capture this life history characteristic and allow for the examination of size-specific management. We combined an IPM with a network-node model to capture both of these salient features. We then demonstrated how this model could be used to understand and manage populations of invasive species focusing on grass carp as an example. Grass carp disrupt ecosystems outside of their native range and have spread around much of the world, including North America. The impacts of grass carp include adversely changing aquatic plant communities, which in turn affect a wide range of endpoints ranging from water quality to waterfowl recruitment. We specifically examined two theoretical systems using parameters from the literature. First, we modeled a lake with two tributaries and examined how modified sterile males could be used as a control tool. We found that modified sterile males may be a feasible control tool to limit population growth. Second, we modeled a series of river pools and examined how harvest and deterrents could be used to decrease the risk of expanding grass carp's range within a river system. Within this system, we also compared the impacts of size specific harvest and uniform harvest across all sizes. We found that targeting the largest, spawning populations may be more important than targeting the populations close to the invasion front for reducing the risk of spreading grass carp. We also demonstrate that size of harvested fish was important for controlling populations.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2018.09.006","usgsCitation":"Erickson, R.A., Eager, E.E., Kocovsky, P., Glover, D.C., Kallis, J.L., and Long, K.R., 2018, A spatially discrete, integral projection model and its application to invasive carp: Ecological Modelling, v. 387, p. 163-171, https://doi.org/10.1016/j.ecolmodel.2018.09.006.","productDescription":"9 p.","startPage":"163","endPage":"171","ipdsId":"IP-094621","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":468358,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2018.09.006","text":"Publisher Index Page"},{"id":437736,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9T9J3JU","text":"USGS data release","linkHelpText":"Spatially explicit integral projection model"},{"id":357901,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"387","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02f86e4b0fc368eb53881","contributors":{"authors":[{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":746637,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eager, Eric E.","contributorId":208273,"corporation":false,"usgs":false,"family":"Eager","given":"Eric","email":"","middleInitial":"E.","affiliations":[{"id":37770,"text":"UWL","active":true,"usgs":false}],"preferred":false,"id":746638,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kocovsky, Patrick 0000-0003-4325-4265 pkocovsky@usgs.gov","orcid":"https://orcid.org/0000-0003-4325-4265","contributorId":150837,"corporation":false,"usgs":true,"family":"Kocovsky","given":"Patrick","email":"pkocovsky@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":746639,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Glover, David C.","contributorId":178006,"corporation":false,"usgs":false,"family":"Glover","given":"David","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":746640,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kallis, Jahn L.","contributorId":205603,"corporation":false,"usgs":false,"family":"Kallis","given":"Jahn","email":"","middleInitial":"L.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":746641,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Long, K. R.","contributorId":208274,"corporation":false,"usgs":false,"family":"Long","given":"K.","email":"","middleInitial":"R.","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":746642,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70198291,"text":"ofr20181115 - 2018 - Depth to basement and thickness of unconsolidated sediments for the western United States—Initial estimates for layers of the U.S. Geological Survey National Crustal Model","interactions":[],"lastModifiedDate":"2018-09-28T13:29:30","indexId":"ofr20181115","displayToPublicDate":"2018-09-28T12:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1115","title":"Depth to basement and thickness of unconsolidated sediments for the western United States—Initial estimates for layers of the U.S. Geological Survey National Crustal Model","docAbstract":"We present numeric grids containing estimates of the thickness of unconsolidated sediments and depth to the pre-Cenozoic
basement for the western United States. Values for these grids were combined and integrated from previous studies or derived
directly from gravity analyses. The grids are provided with 1-kilometer grid-node spacing in ScienceBase (https://www.sciencebase.gov).
These layers may be updated as results from new studies become available.
Director, Geology, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
Box 25046, MS 973
Denver, CO 80225
Little is known about populations of Stonecat Noturus flavus, especially in the northeastern United States, where they are at the edge of their range. In Lake Champlain tributaries, Stonecats are listed as endangered in Vermont but not in New York. Here we describe the growth of Stonecats in two tributaries to Lake Champlain, one in Vermont (LaPlatte River), which was our primary interest, and one in New York (Great Chazy River), with von Bertalanffy growth models fit to lengths at the times of marking and recapture and to observed length and age data. We also compared growth of Stonecats in these waters to results from other locations near the middle of their distribution. Stonecats in the Great Chazy River were larger at ages 1–3, but similar in size for ages 4 and 5, than Stonecats from the LaPlatte River. Stonecats in Lake Champlain tributaries were generally larger at age than those from the middle of their range, except for those from Lake Erie. From our mean length‐at‐age results and previous literature estimates of length at maturity for Stonecats, it appears that Stonecats in Lake Champlain reach maturity by age 3, though future research that directly estimates age at maturity would be more informative. These results will help managers assess the effect of various environmental and human stressors that Stonecats have experienced in the Lake Champlain basin in recent years. Furthermore, our results expand the literature, which lacks information about growth of this species. Finally, our mark–recapture approach to estimating growth of Stonecats can be applied to other species, especially where data are limited because of their status, and in other systems.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10230","usgsCitation":"Puchala, E., Parrish, D.L., and Ogle, D.H., 2018, Size and age of Stonecats in Lake Champlain; Estimating growth at the margin of their range to aid in population management: North American Journal of Fisheries Management, v. 38, no. 6, p. 1316-1323, https://doi.org/10.1002/nafm.10230.","productDescription":"8 p.","startPage":"1316","endPage":"1323","ipdsId":"IP-097102","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":380303,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York, Vermont","otherGeospatial":"Great Chazy River, La Platte River, Lake Champlain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n 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Understanding how anthropogenic and environmental stressors influence migratory movements is of critical importance because of their potential to cause a mismatch between the timing of animal movements and the emergence of high-quality forage. We measured stress hormones (fecal glucocorticoid metabolites; FGMs) to test hypotheses about the effects of high-quality forage tracking, human land use, and use of stopover sites on the physiological state of individuals along a migratory route. We collected and analyzed FGM concentrations from 399 mule deer (Odocoileus hemionus) samples obtained along a 241 km migratory route in western Wyoming, USA, during spring 2015 and 2016. In support of a fitness benefit hypothesis, individuals occupying areas closer to peak forage quality had decreased FGM levels. Specifically, for every 10-day interval closer to peak forage quality, we observed a 7% decrease in FGMs. Additionally, we observed support for both an additive anthropogenic stress hypothesis and a hypothesis that stopovers act as physiological refugia, wherein individuals sampled far from stopover sites exhibited 341% higher FGM levels if in areas of low landscape integrity compared to areas of high landscape integrity. Overall, our findings indicate that the physiological state of mule deer during migration is influenced by both anthropogenic disturbances and their ability to track high-quality forage. The availability of stopovers, however, modulates physiological responses to those stressors. Thus, our results support a recent call for the prioritization of stopover locations and connectivity between those locations in conservation planning for migratory large herbivores.","language":"English","publisher":"Oxford University Press","doi":"10.1093/conphys/coy054","usgsCitation":"Jachowski, D., Kauffman, M., Jesmer, B.R., Sawyer, H., and Millspaugh, J., 2018, Integrating physiological stress into the movement ecology of migratory ungulates: A spatial analysis with mule deer: Conservation Physiology, v. 6, no. 1, p. 1-12, https://doi.org/10.1093/conphys/coy054.","productDescription":"coy054, 12 p.","startPage":"1","endPage":"12","ipdsId":"IP-092704","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":468360,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/conphys/coy054","text":"Publisher Index Page"},{"id":395156,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Wyoming","otherGeospatial":"Big Sandy River, Finger Lakes, Fremont Lake, Green River Valley, Hoback Basin, Red Desert, Wind River Mountain Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.05303955078125,\n 41.66470503009207\n ],\n [\n -108.71520996093749,\n 41.693424216151314\n ],\n [\n -108.97338867187499,\n 42.52069952914966\n ],\n [\n -109.57489013671875,\n 42.85583308674893\n ],\n [\n -109.68475341796875,\n 42.93430692117159\n ],\n [\n -109.786376953125,\n 43.014689161895184\n ],\n [\n -109.88800048828125,\n 43.10298826174054\n ],\n [\n -109.84405517578125,\n 43.48680489735277\n ],\n [\n -110.830078125,\n 43.369119087738554\n ],\n [\n -110.78338623046875,\n 43.08694333811321\n ],\n [\n -110.093994140625,\n 42.97250158602597\n ],\n [\n -110.05279541015625,\n 42.81555136172695\n ],\n [\n -109.7039794921875,\n 42.75104599038353\n ],\n [\n -109.23431396484375,\n 42.18986405028881\n ],\n [\n -109.20135498046875,\n 41.68316883525891\n ],\n [\n -109.05303955078125,\n 41.66470503009207\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","issue":"1","noUsgsAuthors":false,"publicationDate":"2018-09-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Jachowski, David S.","contributorId":228814,"corporation":false,"usgs":false,"family":"Jachowski","given":"David S.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":832213,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":202921,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":832214,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jesmer, Brett R.","contributorId":200192,"corporation":false,"usgs":false,"family":"Jesmer","given":"Brett","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":832215,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sawyer, Hall","contributorId":39930,"corporation":false,"usgs":false,"family":"Sawyer","given":"Hall","affiliations":[],"preferred":false,"id":832216,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Millspaugh, Joshua J.","contributorId":11141,"corporation":false,"usgs":false,"family":"Millspaugh","given":"Joshua J.","affiliations":[],"preferred":false,"id":832217,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70199767,"text":"70199767 - 2018 - A new modeling approach to prioritize riparian restoration to reduce sediment loading in two Virginia river basins","interactions":[],"lastModifiedDate":"2018-09-27T14:26:04","indexId":"70199767","displayToPublicDate":"2018-09-27T14:26:01","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"A new modeling approach to prioritize riparian restoration to reduce sediment loading in two Virginia river basins","docAbstract":"Human impact, particularly land cover changes (e.g., agriculture, construction) increase erosion and sediment loading into streams. Benthic species are negatively affected by silt deposition that coats and embeds stream substrate. Given that riparian buffers are effective sediment filters, riparian restoration is increasingly implemented by conservation groups to protect stream habitats. Limited funding and a multitude of impaired streams warrant the need for cost-effective prioritization of potential restoration actions. We created a decision-support framework for conservation agencies and aquatic resource managers to prioritize riparian restoration efforts. Our framework integrates GIS data and field surveys into a statistical model to predict instream silt from estimates of upland soil loss and riparian filtration capacity. We focus specifically on prioritizing sites in upper sections of the Roanoke and Nottoway river basins (Virginia, US) based on observed records of Roanoke logperch (Percina rex), an imperiled sediment-sensitive species. Our statistical approach examines soil characteristics, land cover, precipitation, topography, and annual soil loss estimates from the empirically derived Revised Universal Soil Loss Equation, combined with land cover-based riparian filtration capacity as potential stream habitat predictors. We found riparian filtration capacity to be a significant predictor of silt cover, while precipitation was a significant predictor of embeddedness. Spatial scale was also a factor, in that spatial variance in silt cover and embeddedness was more accurately predicted at smaller spatial extents. Ultimately, our model can be used as a prioritization tool for mitigating high siltation areas, or for protecting low soil erosion areas.
","language":"English","publisher":"Springer","doi":"10.1007/s00267-018-1078-6","usgsCitation":"Scott, L.N., Villamagna, A.M., and Angermeier, P., 2018, A new modeling approach to prioritize riparian restoration to reduce sediment loading in two Virginia river basins: Environmental Management, v. 62, no. 4, p. 721-739, https://doi.org/10.1007/s00267-018-1078-6.","productDescription":"19 p.","startPage":"721","endPage":"739","ipdsId":"IP-090172","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468362,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10919/99269","text":"External Repository"},{"id":357850,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina, Virginia","volume":"62","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-16","publicationStatus":"PW","scienceBaseUri":"5bc02f87e4b0fc368eb5388b","contributors":{"authors":[{"text":"Scott, Lisa N.","contributorId":208250,"corporation":false,"usgs":false,"family":"Scott","given":"Lisa","email":"","middleInitial":"N.","affiliations":[{"id":35056,"text":"Plymouth State University","active":true,"usgs":false}],"preferred":false,"id":746534,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Villamagna, Amy M.","contributorId":201421,"corporation":false,"usgs":false,"family":"Villamagna","given":"Amy","email":"","middleInitial":"M.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":746535,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Angermeier, Paul L. 0000-0003-2864-170X","orcid":"https://orcid.org/0000-0003-2864-170X","contributorId":204519,"corporation":false,"usgs":true,"family":"Angermeier","given":"Paul L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":746533,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70199746,"text":"70199746 - 2018 - Effects of leg flags on nest survival of four species of Arctic‐breeding shorebirds","interactions":[],"lastModifiedDate":"2018-09-27T14:17:35","indexId":"70199746","displayToPublicDate":"2018-09-27T14:17:31","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2284,"text":"Journal of Field Ornithology","active":true,"publicationSubtype":{"id":10}},"title":"Effects of leg flags on nest survival of four species of Arctic‐breeding shorebirds","docAbstract":"Marking wild birds is an integral part of many field studies. However, if marks affect the vital rates or behavior of marked individuals, any conclusions reached by a study might be biased relative to the general population. Leg bands have rarely been found to have negative effects on birds and are frequently used to mark individuals. Leg flags, which are larger, heavier, and might produce more drag than bands, are commonly used on shorebirds and can help improve resighting rates. However, no one to date has assessed the possible effects of leg flags on the demographic performance of shorebirds. At seven sites in Arctic Alaska and western Canada, we marked individuals and monitored nest survival of four species of Arctic‐breeding shorebirds, including Semipalmated Sandpipers (Calidris pusilla), Western Sandpipers (C. mauri), Red‐necked Phalaropes (Phalaropus lobatus), and Red Phalaropes (P. fulicarius). We used a daily nest survival model in a Bayesian framework to test for effects of leg flags, relative to birds with only bands, on daily survival rates of 1952 nests. We found no evidence of a difference in nest survival between birds with flags and those with only bands. Our results suggest, therefore, that leg flags have little effect on the nest success of Arctic‐breeding sandpipers and phalaropes. Additional studies are needed, however, to evaluate the possible effects of flags on shorebirds that use other habitats and on survival rates of adults and chicks.
","language":"English","publisher":"Wiley","doi":"10.1111/jofo.12264","usgsCitation":"Weiser, E.L., Lanctot, R., Brown, S.C., Gates, H.R., Bentzen, R.L., Boldenow, M.L., Cunningham, J.A., Doll, A.C., Donnelly, T., English, W.B., Franks, S.E., Grond, K., Herzog, P., Hill, B.L., Kendall, S.J., Kwon, E., Lank, D.B., Liebezeit, J.R., Rausch, J., Saalfeld, S.T., Taylor, A.R., Ward, D.H., Wood, P., and Sandercock, B.K., 2018, Effects of leg flags on nest survival of four species of Arctic‐breeding shorebirds: Journal of Field Ornithology, v. 89, no. 3, p. 287-297, https://doi.org/10.1111/jofo.12264.","productDescription":"11 p.","startPage":"287","endPage":"297","ipdsId":"IP-098142","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":468364,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/jofo.12264","text":"External Repository"},{"id":357846,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"89","issue":"3","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-23","publicationStatus":"PW","scienceBaseUri":"5bc02f88e4b0fc368eb53891","contributors":{"authors":[{"text":"Weiser, Emily L. 0000-0003-1598-659X","orcid":"https://orcid.org/0000-0003-1598-659X","contributorId":206605,"corporation":false,"usgs":true,"family":"Weiser","given":"Emily","email":"","middleInitial":"L.","affiliations":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"preferred":true,"id":746438,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lanctot, Richard B.","contributorId":77879,"corporation":false,"usgs":false,"family":"Lanctot","given":"Richard B.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":746439,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Stephen C. 0000-0002-0421-1660","orcid":"https://orcid.org/0000-0002-0421-1660","contributorId":208214,"corporation":false,"usgs":false,"family":"Brown","given":"Stephen","email":"","middleInitial":"C.","affiliations":[{"id":37764,"text":"Shorebird Recovery Program","active":true,"usgs":false}],"preferred":false,"id":746440,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gates, H. 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0000-0002-9290-5629","orcid":"https://orcid.org/0000-0002-9290-5629","contributorId":169663,"corporation":false,"usgs":false,"family":"Kendall","given":"Steve","email":"","middleInitial":"J.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":746452,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Kwon, Eunbi","contributorId":169349,"corporation":false,"usgs":false,"family":"Kwon","given":"Eunbi","email":"","affiliations":[],"preferred":false,"id":746453,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Lank, David B.","contributorId":42533,"corporation":false,"usgs":false,"family":"Lank","given":"David","email":"","middleInitial":"B.","affiliations":[{"id":29801,"text":"Department of Biological Sciences, Simon Fraser University, Burnaby, BC","active":true,"usgs":false}],"preferred":false,"id":746454,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Liebezeit, Joseph 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iron‐enhanced sand filtration on Daphnia magna and Pimephales promelas","docAbstract":"Urban stormwater is an important but incompletely characterized contributor to surface‐water toxicity. The present study used 5 bioassays of 2 model organisms (Daphnia magnaand fathead minnow, Pimephales promelas) to investigate stormwater toxicity and mitigation by full‐scale iron‐enhanced sand filters (IESFs). Stormwater samples were collected from major stormwater conveyances and full‐scale IESFs during 4 seasonal events (winter snowmelt and spring, early summer, and late summer rainfalls) and analyzed for a diverse range of contaminants of emerging concern including pharmaceuticals, personal care products, industrial chemicals, and pesticides. Concurrently, stormwater samples were collected for toxicity testing. Seasonality appeared more influential and consistent than site type for most bioassays. Typically, biological consequences were least in early summer and greatest in late summer and winter. In contrast with the unimproved and occasionally reduced biological outcomes in IESF‐treated and late summer samples, water chemistry indicated that numbers and total concentrations of detected organic chemicals, metals, and nutrients were reduced in late summer and in IESF‐treated stormwater samples. Some potent toxicants showed more specific seasonality (e.g., high concentrations of polycyclic aromatic hydrocarbons and industrial compounds in winter, pesticides in early summer and spring, flame retardants in late summer), which may have influenced outcomes. Potential explanations for insignificant or unexpected stormwater treatment outcomes include confounding effects of complex stormwater matrices, IESF nutrient removal, and, less likely, unmonitored toxicants.
","language":"English","publisher":"Society of Environmental Toxicology and Chemistry","doi":"10.1002/etc.4227","usgsCitation":"Westerhoff, B.M., Fairbairn, D.J., Ferrey, M.L., Matilla, A., Kunkel, J., Elliott, S.M., Kiesling, R.L., Woodruff, D., and Schoenfuss, H.L., 2018, Effects of urban stormwater and iron‐enhanced sand filtration on Daphnia magna and Pimephales promelas: Environmental Toxicology and Chemistry, v. 37, no. 10, p. 2645-2659, https://doi.org/10.1002/etc.4227.","productDescription":"15 p.","startPage":"2645","endPage":"2659","ipdsId":"IP-095127","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":357842,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","issue":"10","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-05","publicationStatus":"PW","scienceBaseUri":"5bc02f88e4b0fc368eb53893","contributors":{"authors":[{"text":"Westerhoff, Benjamin M.","contributorId":208226,"corporation":false,"usgs":false,"family":"Westerhoff","given":"Benjamin","email":"","middleInitial":"M.","affiliations":[{"id":20306,"text":"St. Cloud State University","active":true,"usgs":false}],"preferred":false,"id":746463,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fairbairn, David J.","contributorId":207455,"corporation":false,"usgs":false,"family":"Fairbairn","given":"David","email":"","middleInitial":"J.","affiliations":[{"id":13330,"text":"Minnesota Pollution Control Agency","active":true,"usgs":false}],"preferred":false,"id":746464,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ferrey, Mark L.","contributorId":207457,"corporation":false,"usgs":false,"family":"Ferrey","given":"Mark","email":"","middleInitial":"L.","affiliations":[{"id":13330,"text":"Minnesota Pollution Control Agency","active":true,"usgs":false}],"preferred":false,"id":746465,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Matilla, Adriana","contributorId":208227,"corporation":false,"usgs":false,"family":"Matilla","given":"Adriana","email":"","affiliations":[{"id":20306,"text":"St. Cloud State University","active":true,"usgs":false}],"preferred":false,"id":746466,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kunkel, Jordan","contributorId":208228,"corporation":false,"usgs":false,"family":"Kunkel","given":"Jordan","email":"","affiliations":[{"id":20306,"text":"St. Cloud State University","active":true,"usgs":false}],"preferred":false,"id":746467,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Elliott, Sarah M. 0000-0002-1414-3024 selliott@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-3024","contributorId":1472,"corporation":false,"usgs":true,"family":"Elliott","given":"Sarah","email":"selliott@usgs.gov","middleInitial":"M.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":746462,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kiesling, Richard L. 0000-0002-3017-1826 kiesling@usgs.gov","orcid":"https://orcid.org/0000-0002-3017-1826","contributorId":1837,"corporation":false,"usgs":true,"family":"Kiesling","given":"Richard","email":"kiesling@usgs.gov","middleInitial":"L.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":746468,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Woodruff, Dustin","contributorId":208230,"corporation":false,"usgs":false,"family":"Woodruff","given":"Dustin","email":"","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":746469,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schoenfuss, Heiko L.","contributorId":76409,"corporation":false,"usgs":false,"family":"Schoenfuss","given":"Heiko","email":"","middleInitial":"L.","affiliations":[{"id":13317,"text":"Saint Cloud State University","active":true,"usgs":false}],"preferred":false,"id":746470,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70198847,"text":"fs20183046 - 2018 - Williston Basin groundwater availability, United States and Canada","interactions":[],"lastModifiedDate":"2018-09-27T16:45:41","indexId":"fs20183046","displayToPublicDate":"2018-09-27T12:55:52","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-3046","title":"Williston Basin groundwater availability, United States and Canada","docAbstract":"The Williston Basin contains important oil and gas resources for the Nation. Freshwater supplies are limited in this semiarid area, and oil and gas development can require large volumes of freshwater. Groundwater is the primary source of water for many water users in the Williston Basin, so to better understand these resources, the U.S. Geological Survey (USGS) assessed the groundwater availability in this area. The final phase of this assessment included a computer model that simulates how groundwater flows in the aquifer systems and simulates how changes in water use and natural conditions may affect the water resources. These results provide a tool for land and water-resource managers to determine how water can be used for multiple purposes in the Williston Basin. For additional information about this assessment and more in-depth descriptions and results, see Long and others (2018).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183046","collaboration":"Water Availability and Use Science Program","usgsCitation":"Thamke, J.N., Long, A.J., and Davis, K.W., 2018, Williston Basin groundwater availability, United States and Canada: U.S. Geological Survey Fact Sheet 2018-3046, 4 p., https://doi.org/10.3133/fs20183046.","productDescription":"Report: 4 p.; Data Releases","onlineOnly":"N","ipdsId":"IP-098105","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":357815,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3046/fs20183046.pdf","text":"Report","size":"3.40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018–3046"},{"id":357816,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78P5ZDV","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water use data for hydraulic fracturing treatments in the Williston Basin, United States, 2000–2015"},{"id":357814,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3046/coverthb.jpg"},{"id":357817,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/pp1841","text":"Professional Paper 1841","size":"18.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1841","linkHelpText":"Groundwater availability of the Williston Basin, United States and Canada"},{"id":357818,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FACTT3","text":"USGS data release","description":"USGS Data Release","linkHelpText":"MODFLOW-NWT model of predictive simulations of groundwater response to selected scenarios in the Williston Basin, United States and Canada"}],"country":"Canada, United States","otherGeospatial":"Williston Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108,\n 44\n ],\n [\n -98,\n 44\n ],\n [\n -98,\n 51\n ],\n [\n -108,\n 51\n ],\n [\n -108,\n 44\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director , Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, Montana 59601
Outbreaks of plague, a flea‐vectored bacterial disease, occur periodically in prairie dog populations in the western United States. In order to understand the conditions that are conducive to plague outbreaks and potentially predict spatial and temporal variations in risk, it is important to understand the factors associated with flea abundance and distribution that may lead to plague outbreaks. We collected and identified 20,041 fleas from 6,542 individual prairie dogs of four different species over a 4‐year period along a latitudinal gradient from Texas to Montana. We assessed local climate and other factors associated with flea prevalence and abundance, as well as the incidence of plague outbreaks. Oropsylla hirsuta, a prairie dog specialist flea, and Pulex simulans, a generalist flea species, were the most common fleas found on our pairs. High elevation pairs in Wyoming and Utah had distinct flea communities compared with the rest of the study pairs. The incidence of prairie dogs with Yersinia pestis detections in fleas was low (n = 64 prairie dogs with positive fleas out of 5,024 samples from 4,218 individual prairie dogs). The results of our regression models indicate that many factors are associated with the presence of fleas. In general, flea abundance (number of fleas on hosts) is higher during plague outbreaks, lower when prairie dogs are more abundant, and reaches peak levels when climate and weather variables are at intermediate levels. Changing climate conditions will likely affect aspects of both flea and host communities, including population densities and species composition, which may lead to changes in plague dynamics. Our results support the hypothesis that local conditions, including host, vector, and environmental factors, influence the likelihood of plague outbreaks, and that predicting changes to plague dynamics under climate change scenarios will have to consider both host and vector responses to local factors.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.4390","usgsCitation":"Russell, R.E., Abbott, R.C., Tripp, D.W., and Rocke, T.E., 2018, Local factors associated with on‐host flea distributions on prairie dog colonies: Ecology and Evolution, v. 8, no. 17, p. 8951-8972, https://doi.org/10.1002/ece3.4390.","productDescription":"22 p.; Data Release","startPage":"8951","endPage":"8972","ipdsId":"IP-098871","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":460839,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.4390","text":"Publisher Index Page"},{"id":357829,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418306,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TM79CK"}],"volume":"8","issue":"17","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-14","publicationStatus":"PW","scienceBaseUri":"5bc02f88e4b0fc368eb53899","contributors":{"authors":[{"text":"Russell, Robin E. 0000-0001-8726-7303 rerussell@usgs.gov","orcid":"https://orcid.org/0000-0001-8726-7303","contributorId":3998,"corporation":false,"usgs":true,"family":"Russell","given":"Robin","email":"rerussell@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":746471,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Abbott, Rachel C. 0000-0003-4820-9295 rabbott@usgs.gov","orcid":"https://orcid.org/0000-0003-4820-9295","contributorId":1183,"corporation":false,"usgs":true,"family":"Abbott","given":"Rachel","email":"rabbott@usgs.gov","middleInitial":"C.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":746472,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tripp, Daniel W.","contributorId":17910,"corporation":false,"usgs":false,"family":"Tripp","given":"Daniel","email":"","middleInitial":"W.","affiliations":[{"id":13449,"text":"Colorado Division of Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":746473,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rocke, Tonie E. 0000-0003-3933-1563 trocke@usgs.gov","orcid":"https://orcid.org/0000-0003-3933-1563","contributorId":2665,"corporation":false,"usgs":true,"family":"Rocke","given":"Tonie","email":"trocke@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":746474,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70199749,"text":"70199749 - 2018 - Temperature regimes, growth, and food consumption for female and male adult walleye in Lake Huron and Lake Erie: a bioenergetics analysis","interactions":[],"lastModifiedDate":"2018-09-27T12:14:07","indexId":"70199749","displayToPublicDate":"2018-09-27T12:14:04","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Temperature regimes, growth, and food consumption for female and male adult walleye in Lake Huron and Lake Erie: a bioenergetics analysis","docAbstract":"Bioenergetics modeling was used to assess the relative importance of food availability and water temperature in determining walleye (Sander vitreus) growth. Temperature regimes experienced by both female and male adult walleye in three basins of Lake Huron and in Lake Erie were determined by use of surgically implanted temperature loggers and acoustic telemetry. Temperatures experienced by walleye were higher in Lake Erie than in Lake Huron. Walleye from Lake Erie grew at nearly double the rate of walleye from Lake Huron, and mass at age for adult females averaged about 50% greater than that for adult males in both lakes. Food consumption rate for an average adult walleye in Lake Erie was nearly twice as high as that in Lake Huron. Interbasin and interlake variability in temperature regimes accounted for a moderate degree of variability in walleye growth. We concluded that the driver for faster growth in Lake Erie compared with Lake Huron was higher food availability in Lake Erie compared with Lake Huron. The sex difference in temperature regimes explained 15% of the sex difference in Lake Erie walleye growth.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2017-0280","usgsCitation":"Madenjian, C.P., Hayden, T., Peat, T.B., Vandergoot, C., Fielder, D.G., Gorman, A.M., Pothoven, S.A., Dettmers, J.M., Cooke, S., Zhao, Y., and Krueger, C., 2018, Temperature regimes, growth, and food consumption for female and male adult walleye in Lake Huron and Lake Erie: a bioenergetics analysis: Canadian Journal of Fisheries and Aquatic Sciences, v. 75, no. 10, p. 1573-1586, https://doi.org/10.1139/cjfas-2017-0280.","productDescription":"14 p.","startPage":"1573","endPage":"1586","ipdsId":"IP-081676","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":460841,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2017-0280","text":"External 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Marie","contributorId":145525,"corporation":false,"usgs":false,"family":"Gorman","given":"Ann","email":"","middleInitial":"Marie","affiliations":[],"preferred":false,"id":746478,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pothoven, Steven A.","contributorId":92998,"corporation":false,"usgs":false,"family":"Pothoven","given":"Steven","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":746479,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dettmers, John M.","contributorId":191256,"corporation":false,"usgs":false,"family":"Dettmers","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":746480,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cooke, Steven J.","contributorId":56132,"corporation":false,"usgs":false,"family":"Cooke","given":"Steven J.","affiliations":[{"id":36574,"text":"Carleton University, Ottawa, Ontario","active":true,"usgs":false}],"preferred":false,"id":746481,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Zhao, Yingming","contributorId":205147,"corporation":false,"usgs":false,"family":"Zhao","given":"Yingming","email":"","affiliations":[{"id":37034,"text":"Ontario Ministry of Natural Resources and Forestry, Aquatic Research and Monitoring Section","active":true,"usgs":false}],"preferred":false,"id":746482,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Krueger, Charles C.","contributorId":67821,"corporation":false,"usgs":false,"family":"Krueger","given":"Charles C.","affiliations":[{"id":7019,"text":"Great Lakes Fishery Commission","active":true,"usgs":false}],"preferred":false,"id":746483,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70198096,"text":"70198096 - 2018 - Variation in the vital rates of an Antarctic marine predator: the role of individual heterogeneity","interactions":[],"lastModifiedDate":"2018-10-04T13:09:02","indexId":"70198096","displayToPublicDate":"2018-09-26T12:31:33","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Variation in the vital rates of an Antarctic marine predator: the role of individual heterogeneity","docAbstract":"Variation in life‐history traits such as lifespan and lifetime reproductive output is thought to arise, in part, due to among‐individual differences in the underlying probabilities of survival and reproduction. However, the stochastic nature of demographic processes can also generate considerable variation in fitness‐related traits among otherwise‐identical individuals. An improved understanding of life‐history evolution and population dynamics therefore depends on evaluating the relative role of each of these processes. Here, we used a 33‐yr data set with reproductive histories for 1,274 female Weddell seals from Erebus Bay, Antarctica, to assess the strength of evidence for among‐individual heterogeneity in the probabilities of survival and reproduction, while accounting for multiple other sources of variation in vital rates. Our analysis used recent advances in Bayesian model selection techniques and diagnostics to directly compare model fit and predictive power between models that included individual effects on survival and reproduction to those that did not. We found strong evidence for costs of reproduction to both survival and future reproduction, with breeders having rates of survival and subsequent reproduction that were 3% and 6% lower than rates for non‐breeders. We detected age‐related changes in the rates of survival and reproduction, but the patterns differed for the two rates. Survival rates steadily declined from 0.92 at age 7 to 0.56 at the maximal age of 31 yr. In contrast, reproductive rates increased from 0.68 at age 7 to 0.79 at age 16 and then steadily declined to 0.37 for the oldest females. Models that included individual effects explained more variation in observed life histories and had better estimated predictive power than those that did not, indicating their importance in understanding sources of variation among individuals in life‐history traits. We found that among‐individual heterogeneity in survival was small relative to that for reproduction. Our study, which found patterns of variation in vital rates that are consistent with a series of predictions from life‐history theory, is the first to provide a thorough assessment of variation in important vital rates for a long‐lived, high‐latitude marine mammal while taking full advantage of recent developments in model evaluation.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.2481","usgsCitation":"Paterson, J.T., Rotella, J.J., Link, W.A., and Garrott, R.A., 2018, Variation in the vital rates of an Antarctic marine predator: the role of individual heterogeneity: Ecology, v. 99, no. 10, p. 2385-2396, https://doi.org/10.1002/ecy.2481.","productDescription":"12 p.","startPage":"2385","endPage":"2396","ipdsId":"IP-099409","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":460843,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecy.2481","text":"Publisher Index Page"},{"id":357774,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"99","issue":"10","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-12","publicationStatus":"PW","scienceBaseUri":"5bc02f8be4b0fc368eb538a9","contributors":{"authors":[{"text":"Paterson, J. Terrill","contributorId":206296,"corporation":false,"usgs":false,"family":"Paterson","given":"J.","email":"","middleInitial":"Terrill","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":740000,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rotella, Jay J.","contributorId":37271,"corporation":false,"usgs":false,"family":"Rotella","given":"Jay","email":"","middleInitial":"J.","affiliations":[{"id":5098,"text":"Department of Ecology, Montana State University","active":true,"usgs":false}],"preferred":false,"id":740001,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Link, William A. 0000-0002-9913-0256 wlink@usgs.gov","orcid":"https://orcid.org/0000-0002-9913-0256","contributorId":146920,"corporation":false,"usgs":true,"family":"Link","given":"William","email":"wlink@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":739999,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Garrott, Robert A.","contributorId":171537,"corporation":false,"usgs":false,"family":"Garrott","given":"Robert","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":740002,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70198476,"text":"70198476 - 2018 - Deciphering the dynamics of inorganic carbon export from intertidal salt marshes using high-frequency measurements","interactions":[],"lastModifiedDate":"2018-11-14T09:16:01","indexId":"70198476","displayToPublicDate":"2018-09-26T12:23:09","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2662,"text":"Marine Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Deciphering the dynamics of inorganic carbon export from intertidal salt marshes using high-frequency measurements","docAbstract":"The lateral export of carbon from coastal marshes via tidal exchange is a key component of the marsh carbon budget and coastal carbon cycles. However, the magnitude of this export has been difficult to accurately quantify due to complex tidal dynamics and seasonal cycling of carbon. In this study, we use in situ, high-frequency measurements of dissolved inorganic carbon (DIC) and water fluxes to estimate lateral DIC fluxes from a U.S. northeastern salt marsh. DIC was measured by a CHANnelized Optical Sensor (CHANOS) that provided an in situ concentration measurement at 15-min intervals, during periods in summer (July – August) and late fall (December). Seasonal changes in the marsh had strong effects on DIC concentrations, while tidally-driven water fluxes were the fundamental vehicle of marsh carbon export. Episodic events, such as groundwater discharge and mean sea water level changes, can impact DIC flux through altered DIC concentrations and water flow. Variability between individual tides within each season was comparable to mean variability between the two seasons. Estimated mean DIC fluxes based on a multiple linear regression (MLR) model of DIC concentrations and high-frequency water fluxes agreed reasonably well with those derived from CHANOS DIC measurements for both study periods, indicating that high-frequency, modeled DIC concentrations, coupled with continuous water flux measurements and a hydrodynamic model, provide a robust estimate of DIC flux. Additionally, an analysis of sampling strategies revealed that DIC fluxes calculated using conventional sampling frequencies (hourly to two-hourly) of a single tidal cycle are unlikely to capture a representative mean DIC flux compared to longer-term measurements across multiple tidal cycles with sampling frequency on the order of tens of minutes. This results from a disproportionately large amount of the net DIC flux occurring over a small number of tidal cycles, while most tides have a near-zero DIC export. Thus, high-frequency measurements (on the order of tens of minutes or better) over the time period of interest are necessary to accurately quantify tidal exports of carbon species from salt marshes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.marchem.2018.08.005","usgsCitation":"Chu, S.N., Wang, Z., Gonneea Eagle, M., Kroeger, K.D., and Ganju, N., 2018, Deciphering the dynamics of inorganic carbon export from intertidal salt marshes using high-frequency measurements: Marine Chemistry, v. 206, p. 7-18, https://doi.org/10.1016/j.marchem.2018.08.005.","productDescription":"12 p.","startPage":"7","endPage":"18","ipdsId":"IP-099810","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468365,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.marchem.2018.08.005","text":"Publisher Index Page"},{"id":357773,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"206","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02f8be4b0fc368eb538ab","contributors":{"authors":[{"text":"Chu, Sophie N.","contributorId":174603,"corporation":false,"usgs":false,"family":"Chu","given":"Sophie","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":741590,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wang, Zhaohui Aleck","contributorId":174589,"corporation":false,"usgs":false,"family":"Wang","given":"Zhaohui Aleck","affiliations":[{"id":13627,"text":"Woods Hole Oceanographic Institution, Woods Hole, MA","active":true,"usgs":false}],"preferred":false,"id":741591,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gonneea Eagle, Meagan 0000-0001-5072-2755 mgonneea@usgs.gov","orcid":"https://orcid.org/0000-0001-5072-2755","contributorId":174590,"corporation":false,"usgs":true,"family":"Gonneea Eagle","given":"Meagan","email":"mgonneea@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":741589,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kroeger, Kevin D. 0000-0002-4272-2349 kkroeger@usgs.gov","orcid":"https://orcid.org/0000-0002-4272-2349","contributorId":1603,"corporation":false,"usgs":true,"family":"Kroeger","given":"Kevin","email":"kkroeger@usgs.gov","middleInitial":"D.","affiliations":[{"id":41100,"text":"Coastal and Marine Hazards and Resources Program","active":true,"usgs":true}],"preferred":true,"id":741592,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":741593,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70199711,"text":"70199711 - 2018 - A causal partition of trait correlations: using graphical models to derive statistical models from theoretical language","interactions":[],"lastModifiedDate":"2018-09-26T11:05:12","indexId":"70199711","displayToPublicDate":"2018-09-26T11:05:04","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"A causal partition of trait correlations: using graphical models to derive statistical models from theoretical language","docAbstract":"Recent studies hypothesize various causes of species‐level trait covariation, namely size (e.g., metabolic theory of ecology and leaf economics spectrum), pace‐of‐life (e.g., slow‐to‐fast continuum; lifestyle continuum), evolutionary history (e.g., phylogenetic conservatism), and ecological conditions (e.g., stabilizing selection). Various methods have been used in attempts to partition trait correlation among these influences (e.g., univariate analysis, principal components analysis, and factor analysis). However, it is not clear that the implied causal structure assumed by these methods matches the hypothesized causal structure driving trait correlations, a situation that can potentially lead to biased estimates and incorrect partitioning among mechanisms. Here, we propose the application of graphical causal models (GCM) for across‐kingdom synthesis and to aid researchers in their selection of correct analytical strategies. Graphical causal models use causal diagrams (i.e., box‐and‐arrow graphs) to represent expert knowledge of the data‐generating processes to analytically investigate the possibility of identifying hypothesized causal associations. We developed a causal diagram that synthesizes prominent hypotheses of trait covariation. Using the causal diagram, we (1) derived a quantitative expression to partition trait covariance among its hypothesized causal elements (i.e., size, pace‐of‐life, evolutionary history, and ecological conditions) and (2) developed analytic strategies to attribute trait covariance among the hypothesized causal elements under real‐world data availability, namely unobserved variables (i.e., pace‐of‐life) and confounding variables (i.e., evolutionary history and ecological conditions). Finally, we tested each analytic strategy by simulating trait datasets and, after incorporating the data limitations, tested their ability to correctly partition trait covariance. The analytical strategies were able to correctly partition trait covariance into the hypothesized causal elements of size, pace‐of‐life, and the historical effects of evolutionary history and ecological conditions. We demonstrate the efficacy of these strategies by applying them to a widely used trait dataset. Overall, the application of GCM revealed that researchers have used inappropriate measures to represent their theoretical constructs and have relied on analytical strategies that violated their causal assumptions, likely resulting in biased estimates. We discuss how this mismatch between theoretical language and statistical methods is prevalent in species‐level, trait‐based research and call for future studies to address these limitations.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2422","usgsCitation":"Cronin, J.P., and Schoolmaster, D., 2018, A causal partition of trait correlations: using graphical models to derive statistical models from theoretical language: Ecosphere, v. 9, no. 9, p. 1-15, https://doi.org/10.1002/ecs2.2422.","productDescription":"e02422; 15 p.","startPage":"1","endPage":"15","ipdsId":"IP-066629","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":468366,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2422","text":"Publisher Index Page"},{"id":357754,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"9","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-17","publicationStatus":"PW","scienceBaseUri":"5bc02f8ce4b0fc368eb538b1","contributors":{"authors":[{"text":"Cronin, James P. 0000-0001-6791-5828 jcronin@usgs.gov","orcid":"https://orcid.org/0000-0001-6791-5828","contributorId":5834,"corporation":false,"usgs":true,"family":"Cronin","given":"James","email":"jcronin@usgs.gov","middleInitial":"P.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":746297,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schoolmaster, Donald 0000-0003-0910-4458 schoolmasterd@usgs.gov","orcid":"https://orcid.org/0000-0003-0910-4458","contributorId":156350,"corporation":false,"usgs":true,"family":"Schoolmaster","given":"Donald","email":"schoolmasterd@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":746298,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70259473,"text":"70259473 - 2018 - McGee Till—oldest glacial deposit in the Sierra Nevada, California— and Quaternary evolution of the rangefront escarpment","interactions":[],"lastModifiedDate":"2024-10-09T15:23:08.832201","indexId":"70259473","displayToPublicDate":"2018-09-26T10:16:53","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"McGee Till—oldest glacial deposit in the Sierra Nevada, California— and Quaternary evolution of the rangefront escarpment","docAbstract":"The McGee Till is an early Pleistocene glacial diamict as thick as 50 m, preserved over an area of 1.65 km2 on a relict low-relief Pliocene plateau that stands 900 m higher than mouths of its bounding canyons, on the rangefront of the Sierra Nevada. Although recognized 90 years ago as the oldest till in the Sierra, its age and relation to the next oldest Sierran till have remained uncertain, even controversial. This contribution seeks to clarify both. The McGee Till consists predominantly of grussy boulders and sandy-granular matrix derived largely from a distinctive Cretaceous granodiorite that walls McGee Creek canyon 4–8 km to the south. The till rests directly upon two different basaltic units that yield 40Ar/39Ar ages of 2.8 and 2.6 Ma and show little or no evidence of preglacial erosion. The basalts preserve a minimum of 165–255 m of relief on steep slopes that existed around the plateau margins at the time of their eruption. McGee Creek consists of two segments—a north-directed reach that confined the glacier that deposited the till and, now diverging at a right bend just upvalley from the till, a northeast-flowing reach that was incised later. The base of the McGee Till is at 3160 m elevation on the present-day rim of McGee Creek, 610 m above the bend. The base of the 130-ka Tahoe Till (MIS 6) is at 2550 m elevation directly downslope from the McGee Till and at 2300 m at the rangefront mouth of the canyon's northeast reach. The base of the 900–866 ka Sherwin Till (MIS 22) is at 2400 m at the nearby rangefront mouth of Rock Creek. As the canyons were cut to nearly modern depths before the Sherwin glaciation, the high-perched McGee Till is probably older than 2 Ma and possibly close in age to the 2.6 Ma basalt it overlies. Growth in rangefront relief since about 3.0–2.5 Ma owes to normal slip on the Hilton Creek and Round Valley Faults east of McGee Mountain as well as to the 767-ka collapse of Long Valley caldera to its north.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2018.08.008","usgsCitation":"Hildreth, W., Fierstein, J., and Calvert, A.T., 2018, McGee Till—oldest glacial deposit in the Sierra Nevada, California— and Quaternary evolution of the rangefront escarpment: Quaternary Science Reviews, v. 198, p. 242-265, https://doi.org/10.1016/j.quascirev.2018.08.008.","productDescription":"24 p.","startPage":"242","endPage":"265","ipdsId":"IP-097618","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":468367,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quascirev.2018.08.008","text":"Publisher Index Page"},{"id":462747,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"McGill Till","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.34178096223278,\n 37.90563417842898\n ],\n [\n -119.34178096223278,\n 37.462740515318\n ],\n [\n -118.32272088159911,\n 37.462740515318\n ],\n [\n -118.32272088159911,\n 37.90563417842898\n ],\n [\n -119.34178096223278,\n 37.90563417842898\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"198","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hildreth, Wes 0000-0002-7925-4251 hildreth@usgs.gov","orcid":"https://orcid.org/0000-0002-7925-4251","contributorId":2221,"corporation":false,"usgs":true,"family":"Hildreth","given":"Wes","email":"hildreth@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":915429,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fierstein, Judith E. 0000-0001-8024-1426","orcid":"https://orcid.org/0000-0001-8024-1426","contributorId":329988,"corporation":false,"usgs":true,"family":"Fierstein","given":"Judith E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":915430,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Calvert, Andrew T. 0000-0001-5237-2218 acalvert@usgs.gov","orcid":"https://orcid.org/0000-0001-5237-2218","contributorId":2694,"corporation":false,"usgs":true,"family":"Calvert","given":"Andrew","email":"acalvert@usgs.gov","middleInitial":"T.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":915431,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70199691,"text":"70199691 - 2018 - Burn severity controls on postfire Araucaria‐Nothofagus regeneration in the Andean Cordillera","interactions":[],"lastModifiedDate":"2018-11-14T09:17:48","indexId":"70199691","displayToPublicDate":"2018-09-25T16:29:25","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2193,"text":"Journal of Biogeography","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Burn severity controls on postfire Araucaria‐Nothofagus regeneration in the Andean Cordillera","title":"Burn severity controls on postfire Araucaria‐Nothofagus regeneration in the Andean Cordillera","docAbstract":"Aim
The aim of the study was to investigate postfire regeneration patterns of Araucaria‐Nothofagus forests on the west slope of the Andes; to evaluate the relationship between remotely sensed burn severity and forest mortality; and to assess controls of burn severity on forest response at local spatio‐temporal scales.
Location
Araucanía region in the western Andean Range of south‐central Chile where fire occurred during the 2001–2002 season.
Methods
Sampling of prefire stand structure and postfire vegetation response was performed along a burn severity gradient a decade after the fire. We evaluated the relationship between field‐measured tree mortality and satellite‐derived burn severity using a generalized linear model. We fit zero‐inflated mixture models to regeneration data of each genus to assess the importance of abiotic variables, stand characteristics, and biotic interactions.
Results
The relative version of the delta Normalized Burn Ratio explained 85% of the variability in canopy mortality. Nearly 12,000 hectares burned; the majority at high severity (67%). Regeneration densities of both genera were lower at higher levels of burn severity and higher with greater total basal area (live, dead, and down trees). The relative effect size of burn severity on regeneration was nearly twice as large for Nothofagus, which suggests information legacies of Araucaria have cascading effects on postdisturbance material legacies.
Main conclusions
Araucaria‐Nothofagus mortality from wildfire can be readily mapped using satellite‐derived burn severity. Although environmental site characteristics and biotic interactions mediate regeneration, basal area, and burn severity are the main mechanisms controlling regeneration. Forest refugia and postfire regeneration are vulnerable to recurrent fire. Therefore, we expect future fire (either increased severity or frequency), driven by landscape level changes, as a potential mechanism that can reduce local resilience of these forests as initial postfire material legacies (e.g., refugia and regeneration) are removed from the landscape. Our findings highlight an approach to quantify important attributes of forest disturbance and refugia, and identify areas for monitoring postdisturbance regeneration as the forests throughout south‐central Chile and Argentina face a multitude of potential change agents.
Low‐temperature thermochronometry is widely used to measure the timing and rate of slip on normal faults. Rates are often derived from suites of footwall thermochronometer samples, but regression of age vs. structural depth fails to account for the trajectories of samples during fault slip. We demonstrate that in rotating fault blocks, regression of age‐depth data is susceptible to significant errors (>10%) in the identification of the initiation and rate of faulting. Advection of heat and topographic growth influence the thermal histories of exhumed particles, but for a range of geologically reasonable fault geometries and rates these effects produce Apatite (U‐Th)/He ages comparable to those derived from rotation through fixed isotherms. We apply the fixed‐isotherm model to published data from the Pine Forest Range and the East Range, Nevada, by incorporating field and thermochronologic constraints into a Markov chain Monte Carlo model. Modeled parameters for the Pine Forest Range are described by narrow ranges of geologically reasonable values. Compared to slip rates of 0.3‐0.8 km/Myr and an inititation of faulting ca. 11‐12 Ma derived from visual inspection, the model predicts an average slip rate of ~1.1 km/Myr and an onset of faulting ca. 9‐10 Ma. For the East Range fault block the model suggests faulting begain ~17 Ma with an extension rate of ~3 km/Myr and slowed to an extension rate of ~0.5 km/Myr at ~14 Ma. The absence of a preserved partial retention zone in the East Range sample set limits how well the model can predict fault block geometry.
","language":"English","publisher":"AGU","doi":"10.1029/2018TC005207","usgsCitation":"Johnstone, S., and Colgan, J.P., 2018, Interpretation of low‐temperature thermochronometer ages from tilted normal fault blocks: Tectonics, v. 37, no. 10, p. 3647-3667, https://doi.org/10.1029/2018TC005207.","productDescription":"21 p.","startPage":"3647","endPage":"3667","ipdsId":"IP-099026","costCenters":[{"id":308,"text":"Geology and Environmental Change Science Center","active":false,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":468370,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://eartharxiv.org/an3fr/","text":"External Repository"},{"id":357721,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","issue":"10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-15","publicationStatus":"PW","scienceBaseUri":"5bc02f8ce4b0fc368eb538bb","contributors":{"authors":[{"text":"Johnstone, Samuel 0000-0002-3945-2499","orcid":"https://orcid.org/0000-0002-3945-2499","contributorId":207545,"corporation":false,"usgs":true,"family":"Johnstone","given":"Samuel","email":"","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":746229,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Colgan, Joseph P. 0000-0001-6671-1436 jcolgan@usgs.gov","orcid":"https://orcid.org/0000-0001-6671-1436","contributorId":1649,"corporation":false,"usgs":true,"family":"Colgan","given":"Joseph","email":"jcolgan@usgs.gov","middleInitial":"P.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":746230,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70199308,"text":"ofr20181149 - 2018 - 2018 report on incorporating sedimentary basin response into the design of tall buildings in Seattle, Washington","interactions":[],"lastModifiedDate":"2018-09-25T16:38:19","indexId":"ofr20181149","displayToPublicDate":"2018-09-25T09:22:44","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1149","title":"2018 report on incorporating sedimentary basin response into the design of tall buildings in Seattle, Washington","docAbstract":"On March 22, 2018, the Seattle Department of Construction and Inspections (SDCI) and the U.S. Geological Survey (USGS) convened a workshop of engineers and seismologists to provide guidance on incorporating sedimentary basin response into the design of tall buildings in Seattle. This workshop provided recommendations that build on those from a March 2013 workshop (Chang and others, 2014), primarily based on new results from 3-D simulations of magnitude (M) 9 Cascadia earthquakes (The M9 Project). Susan Chang, a geotechnical engineer with the Seattle Department of Construction and Inspections, organized and led the workshop; Art Frankel (USGS) assisted in constructing the agenda.
The workshop agenda and attendees are provided in the appendix. The attendees represented a wide range of expertise, including seismologists with expertise in ground motions and basin response, geotechnical engineers, and structural engineers. Their professional experience included working on local projects related to the design of long-period structures; peer reviewing ground motions for performance-based design of high-rises in Seattle; researching basin response in academic, government and industry settings; developing ground motion models; and representing local and national structural engineering organizations. In this report, we summarize the technical presentations, key discussion points, and recommendations from the workshop.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181149","usgsCitation":"Wirth, E.A., Chang, S.W., and Frankel, A.D., 2018, 2018 report on incorporating sedimentary basin response into the design of tall buildings in Seattle, Washington: U.S. Geological Survey Open-File Report 2018–1149, 19 p., https://doi.org/10.3133/ofr20181149.","productDescription":"iv, 19 p.","numberOfPages":"23","onlineOnly":"Y","ipdsId":"IP-099788","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":357679,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1149/ofr20181149.pdf","text":"Report","size":"3.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2018-1149"},{"id":357678,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1149/coverthb.jpg"}],"country":"United States","state":"Washington","city":"Seattle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.5,\n 47.5\n ],\n [\n -122.2,\n 47.5\n ],\n [\n -122.2,\n 47.8\n ],\n [\n -122.5,\n 47.8\n ],\n [\n -122.5,\n 47.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Earthquake Science Center, Seattle Field Office
U.S. Geological Survey
University of Washington, Dept. of Earth and Space Sciences
Box 351310
Seattle, WA 98195
A series of 11 digital flood-inundation maps was developed for a 5.5-mile reach of the lower Pawcatuck River in Westerly, Rhode Island, and Stonington and North Stonington, Connecticut, by the U.S. Geological Survey (USGS) in cooperation with the Town of Westerly, Rhode Island, and the Rhode Island Office of Housing and Community Development. The coverage of the maps extends from downstream from the Ashaway River inflow at the State Border between Hopkinton and Westerly, Rhode Island, and North Stonington, Connecticut, to about 500 feet (ft) downstream from the U.S. Route 1/Broad Street bridge on the State border between Westerly, Rhode Island, and Stonington, Connecticut. A one-dimensional step-backwater hydraulic model created and calibrated for an ongoing (2018) Federal Emergency Management Agency Flood-Insurance Study for New London County, Connecticut and Washington County, Rhode Island was updated for this study. The hydraulic model reflects the removal of the White Rock dam during 2015–16, and was calibrated using the stage-discharge relation at the USGS Pawcatuck River at Westerly, Rhode Island, streamgage (01118500) and documented high-water marks from the March 30, 2010, flood, which had a peak flow slightly greater than the estimated 0.2-percent annual exceedance probability floodflow.
The hydraulic model was used to compute water-surface profiles for 11 flood stages at 1-ft intervals referenced to the USGS Pawcatuck River at Westerly, Rhode Island, streamgage (01118500) and ranging from 6.0 ft (3.32 ft, North American Vertical Datum of 1988), which is the National Weather Service Advanced Hydrologic Prediction Service flood category “action stage,” to 16.0 ft (13.32 ft, North American Vertical Datum of 1988), which is the maximum stage of the stage-discharge relation at the streamgage and exceeds the National Weather Service Advanced Hydrologic Prediction Service flood category “major flood stage” of 11.0 ft. The simulated water-surface profiles were combined with a geographic information system digital elevation model derived from light detection and ranging (lidar) data with a 1.0-ft vertical accuracy to create flood-inundation maps. The flood-inundation maps depict estimates of the areal extent and depth of flooding corresponding to 11 selected flood stages at the streamgage. The flood-inundation maps depict only riverine flooding and do not depict any tidal backwater or coastal storm surge that could occur in the lower part of the river reach. The flood-inundation maps can be accessed through the USGS Flood Inundation Mapping Science website at https://water.usgs.gov/osw/flood_inundation. Near-real-time stages and discharges at the Pawcatuck River streamgage can be obtained from the USGS National Water Information System at https://waterdata.usgs.gov/. The National Weather Service Advanced Hydrologic Prediction Service provides flood forecast of stage for this site (WSTR1) at https://water.weather.gov/ahps/.
The availability of flood-inundation maps referenced to current and forecasted water levels at the USGS Pawcatuck River at Westerly, Rhode Island streamgage (01118500) can provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, and postflood recovery efforts. The flood-inundation maps are nonregulatory but provide Federal, State, and local agencies and the public with estimates of the potential extent of flooding during flood events.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185112","collaboration":"Prepared in cooperation with the Town of Westerly, Rhode Island, and the Rhode Island Office of Housing and Community Development","usgsCitation":"Bent, G.C., and Lombard, P.J., 2018, Flood-inundation maps for the lower Pawcatuck River in Westerly, Rhode Island, and Stonington and North Stonington, Connecticut: U.S. Geological Survey Scientific Investigations Report 2018–5112, 16 p., https://doi.org/10.3133/sir20185112.","productDescription":"Report: vii, 16 p.; Application Site; Data Release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-091691","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":357651,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7610Z80 ","text":"USGS data release","description":"USGS data release","linkHelpText":"Flood-Inundation Grids and Shapefiles for the Lower Pawcatuck River in Westerly, Rhode Island, and Stonington and North Stonington, Connecticut"},{"id":437742,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9G0N0TN","text":"USGS data release","linkHelpText":"River Channel Survey Data, Redwood Creek, California, 1953-2013"},{"id":437741,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7610Z80","text":"USGS data release","linkHelpText":"Flood-Inundation Grids and Shapefiles for the Lower Pawcatuck River in Westerly, Rhode Island, and Stonington and North Stonington, Connecticut"},{"id":357652,"rank":4,"type":{"id":4,"text":"Application Site"},"url":"https://wimcloud.usgs.gov/apps/FIM/FloodInundationMapper.html ","linkFileType":{"id":5,"text":"html"},"linkHelpText":"- Flood Inundation Mapper"},{"id":357649,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5112/coverthb.jpg"},{"id":357650,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5112/sir20185112.pdf","text":"Report","size":"1.21 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5112"}],"country":"United States","state":"Connecticut, Rhode Island","city":"North Stonington, Stonington, Westerly","otherGeospatial":"Lower Pawcatuck River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.85,\n 41.3667\n ],\n [\n -71.7833,\n 41.3667\n ],\n [\n -71.7833,\n 41.425\n ],\n [\n -71.85,\n 41.425\n ],\n [\n -71.85,\n 41.3667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532