A theoretical basis and prototype numerical algorithm are provided that decompose regular time series of geomagnetic observations into three components: secular variation; solar quiet, and disturbance. Respectively, these three components correspond roughly to slow changes in the Earth’s internal magnetic field, periodic daily variations caused by quasi-stationary (with respect to the sun) electrical current systems in the Earth’s magnetosphere, and episodic perturbations to the geomagnetic baseline that are typically driven by fluctuations in a solar wind that interacts electromagnetically with the Earth’s magnetosphere. In contrast to similar algorithms applied to geomagnetic data in the past, this one addresses the issue of real time data acquisition directly by applying a time-causal, exponential smoother with “seasonal corrections” to the data as soon as they become available.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171037","usgsCitation":"Rigler, E.J., 2017, Time-causal decomposition of geomagnetic time series into secular variation, solar quiet, and disturbance signals: U.S. Geological Survey Open-File Report 2017–1037, 26 p., https://doi.org/10.3133/ofr20171037.","productDescription":"iv, 26 p.","numberOfPages":"31","onlineOnly":"Y","ipdsId":"IP-080216","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":340156,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1037/coverthb.jpg"},{"id":340157,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1037/ofr20171037.pdf","text":"Report","size":"3.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1037"}],"contact":"Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, MS–966
Denver, CO 80225-0046
https://www.usgs.gov/centers/geohazards/
","tableOfContents":"No abstract available.
Photogrammetry, a technique to obtain measurements from photographs, may be a valid method for measuring lengths of rare, threatened, or endangered species. Photogrammetric methods of measurement are nonintrusive and reduce the possibility of physical damage or physiological stress associated with the capture and handling of individuals. We evaluated precision and accuracy of photogrammetric length measurements relative to board measurements of Greenside Darters Etheostoma blennioides and Variegate Darters E. variatum in an aquarium and applied photogrammetry in a field study of the Diamond Darter Crystallaria cincotta, a federally listed endangered species. Digital photographs were taken of each individual using a waterproof camera equipped with two parallel lasers. Photogrammetric length measurements were digitized with ImageJ software. Agreement between board and photogrammetric measurements were high for Greenside and Variegate darters. The magnitude of differences was small between direct and photogrammetric measurements, ranging from 0.6% to 3.1%, depending on the species measured and the type of measurement taken. These results support photogrammetry as a useful method for obtaining length measurements of benthic stream fishes. Photogrammetric methods allowed for length measurements and an assessment of length frequency of 199 Diamond Darters, informative data for management that could not be collected with conventional measuring-board methods.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/02755947.2016.1235632","usgsCitation":"Rizzo, A.A., Welsh, S.A., and Thompson, P., 2017, A paired-laser photogrammetric method for in situ length measurement of benthic fishes: North American Journal of Fisheries Management, v. 37, no. 1, p. 16-22, https://doi.org/10.1080/02755947.2016.1235632.","productDescription":"7 p.","startPage":"16","endPage":"22","ipdsId":"IP-079166","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":340460,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-20","publicationStatus":"PW","scienceBaseUri":"5901b1b7e4b0c2e071a99b8a","contributors":{"authors":[{"text":"Rizzo, Austin A.","contributorId":191439,"corporation":false,"usgs":false,"family":"Rizzo","given":"Austin","email":"","middleInitial":"A.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":693048,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Welsh, Stuart A. 0000-0003-0362-054X swelsh@usgs.gov","orcid":"https://orcid.org/0000-0003-0362-054X","contributorId":1483,"corporation":false,"usgs":true,"family":"Welsh","given":"Stuart","email":"swelsh@usgs.gov","middleInitial":"A.","affiliations":[{"id":205,"text":"Cooperative Research Units","active":false,"usgs":true}],"preferred":false,"id":693013,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Patricia A. pathompson@usgs.gov","contributorId":5249,"corporation":false,"usgs":true,"family":"Thompson","given":"Patricia A.","email":"pathompson@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":693049,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70187208,"text":"70187208 - 2017 - Density estimates of monarch butterflies overwintering in central Mexico","interactions":[],"lastModifiedDate":"2020-09-01T20:37:19.913379","indexId":"70187208","displayToPublicDate":"2017-04-26T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3840,"text":"PeerJ","active":true,"publicationSubtype":{"id":10}},"title":"Density estimates of monarch butterflies overwintering in central Mexico","docAbstract":"Given the rapid population decline and recent petition for listing of the monarch butterfly (Danaus plexippus L.) under the Endangered Species Act, an accurate estimate of the Eastern, migratory population size is needed. Because of difficulty in counting individual monarchs, the number of hectares occupied by monarchs in the overwintering area is commonly used as a proxy for population size, which is then multiplied by the density of individuals per hectare to estimate population size. There is, however, considerable variation in published estimates of overwintering density, ranging from 6.9–60.9 million ha−1. We develop a probability distribution for overwinter density of monarch butterflies from six published density estimates. The mean density among the mixture of the six published estimates was ∼27.9 million butterflies ha−1 (95% CI [2.4–80.7] million ha−1); the mixture distribution is approximately log-normal, and as such is better represented by the median (21.1 million butterflies ha−1). Based upon assumptions regarding the number of milkweed needed to support monarchs, the amount of milkweed (Asclepias spp.) lost (0.86 billion stems) in the northern US plus the amount of milkweed remaining (1.34 billion stems), we estimate >1.8 billion stems is needed to return monarchs to an average population size of 6 ha. Considerable uncertainty exists in this required amount of milkweed because of the considerable uncertainty occurring in overwinter density estimates. Nevertheless, the estimate is on the same order as other published estimates. The studies included in our synthesis differ substantially by year, location, method, and measures of precision. A better understanding of the factors influencing overwintering density across space and time would be valuable for increasing the precision of conservation recommendations.
","language":"English","publisher":"PeerJ","doi":"10.7717/peerj.3221","usgsCitation":"Thogmartin, W.E., Diffendorfer, J., Lopez-Hoffman, L., Oberhauser, K., Pleasants, J., Semmens, B.X., Semmens, D.J., Taylor, O.R., and Wiederholt, R., 2017, Density estimates of monarch butterflies overwintering in central Mexico: PeerJ, v. 5, e3221, 18 p., https://doi.org/10.7717/peerj.3221.","productDescription":"e3221, 18 p.","ipdsId":"IP-072141","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":469903,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.3221","text":"Publisher Index Page"},{"id":340451,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico","volume":"5","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-26","publicationStatus":"PW","scienceBaseUri":"5901b1b7e4b0c2e071a99b88","contributors":{"authors":[{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":693025,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":693026,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lopez-Hoffman, Laura","contributorId":149127,"corporation":false,"usgs":false,"family":"Lopez-Hoffman","given":"Laura","affiliations":[{"id":17654,"text":"School of Natural Resources & the Environment and Udall Center for Studies in Public Policy, The University of Arizona, Tucson","active":true,"usgs":false}],"preferred":false,"id":693027,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oberhauser, Karen","contributorId":191431,"corporation":false,"usgs":false,"family":"Oberhauser","given":"Karen","affiliations":[],"preferred":false,"id":693028,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pleasants, John M.","contributorId":168616,"corporation":false,"usgs":false,"family":"Pleasants","given":"John M.","affiliations":[{"id":25341,"text":"Department of Ecology, Evolution, and Organismal Biology, Iowa State University","active":true,"usgs":false}],"preferred":false,"id":693029,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Semmens, Brice X.","contributorId":149775,"corporation":false,"usgs":false,"family":"Semmens","given":"Brice","email":"","middleInitial":"X.","affiliations":[{"id":17820,"text":"Scripps Institution of Oceanography, University of California, San Diego","active":true,"usgs":false}],"preferred":false,"id":693032,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Semmens, Darius J. 0000-0001-7924-6529 dsemmens@usgs.gov","orcid":"https://orcid.org/0000-0001-7924-6529","contributorId":1714,"corporation":false,"usgs":true,"family":"Semmens","given":"Darius","email":"dsemmens@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":693030,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Taylor, Orley R.","contributorId":191432,"corporation":false,"usgs":false,"family":"Taylor","given":"Orley","email":"","middleInitial":"R.","affiliations":[{"id":28093,"text":"Department of Ecology and Evolutionary Biology, University of Kansas, Lawrence, KS 66045, USA","active":true,"usgs":false}],"preferred":false,"id":693031,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wiederholt, Ruscena","contributorId":149125,"corporation":false,"usgs":false,"family":"Wiederholt","given":"Ruscena","affiliations":[{"id":17653,"text":"School of Natural Resources & the Environment, The University of Arizona, Tucson","active":true,"usgs":false}],"preferred":false,"id":693033,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70187158,"text":"70187158 - 2017 - Created mangrove wetlands store belowground carbon and surface elevation change enables them to adjust to sea-level rise","interactions":[],"lastModifiedDate":"2017-04-25T15:50:18","indexId":"70187158","displayToPublicDate":"2017-04-25T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Created mangrove wetlands store belowground carbon and surface elevation change enables them to adjust to sea-level rise","docAbstract":"Mangrove wetlands provide ecosystem services for millions of people, most prominently by providing storm protection, food and fodder. Mangrove wetlands are also valuable ecosystems for promoting carbon (C) sequestration and storage. However, loss of mangrove wetlands and these ecosystem services are a global concern, prompting the restoration and creation of mangrove wetlands as a potential solution. Here, we investigate soil surface elevation change, and its components, in created mangrove wetlands over a 25 year developmental gradient. All created mangrove wetlands were exceeding current relative sea-level rise rates (2.6 mm yr−1), with surface elevation change of 4.2–11.0 mm yr−1 compared with 1.5–7.2 mm yr−1 for nearby reference mangroves. While mangrove wetlands store C persistently in roots/soils, storage capacity is most valuable if maintained with future sea-level rise. Through empirical modeling, we discovered that properly designed creation projects may not only yield enhanced C storage, but also can facilitate wetland persistence perennially under current rates of sea-level rise and, for most sites, for over a century with projected medium accelerations in sea-level rise (IPCC RCP 6.0). Only the fastest projected accelerations in sea-level rise (IPCC RCP 8.5) led to widespread submergence and potential loss of stored C for created mangrove wetlands before 2100.
","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/s41598-017-01224-2","usgsCitation":"Krauss, K.W., Cormier, N., Osland, M.J., Kirwan, M.L., Stagg, C.L., Nestlerode, J.A., Russell, M.J., From, A., Spivak, A.C., Dantin, D.D., Harvey, J.E., and Almario, A.E., 2017, Created mangrove wetlands store belowground carbon and surface elevation change enables them to adjust to sea-level rise: Scientific Reports, v. 7, no. 1, Article 1030; 11 p., https://doi.org/10.1038/s41598-017-01224-2.","productDescription":"Article 1030; 11 p.","ipdsId":"IP-080501","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":469907,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-017-01224-2","text":"Publisher Index Page"},{"id":438360,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7RR1WC3","text":"USGS data release","linkHelpText":"Surface elevation change (VLMw) and vertical accretion data from created mangroves in Tampa Bay, Florida, USA (2011-2016)"},{"id":340411,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"1","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-21","publicationStatus":"PW","scienceBaseUri":"59006061e4b0e85db3a5ddc4","contributors":{"authors":[{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":692848,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cormier, Nicole 0000-0003-2453-9900 cormiern@usgs.gov","orcid":"https://orcid.org/0000-0003-2453-9900","contributorId":4262,"corporation":false,"usgs":true,"family":"Cormier","given":"Nicole","email":"cormiern@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":692849,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Osland, Michael J. 0000-0001-9902-8692 mosland@usgs.gov","orcid":"https://orcid.org/0000-0001-9902-8692","contributorId":3080,"corporation":false,"usgs":true,"family":"Osland","given":"Michael","email":"mosland@usgs.gov","middleInitial":"J.","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":692850,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kirwan, Matthew L.","contributorId":191373,"corporation":false,"usgs":false,"family":"Kirwan","given":"Matthew","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":692851,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stagg, Camille L. 0000-0002-1125-7253 staggc@usgs.gov","orcid":"https://orcid.org/0000-0002-1125-7253","contributorId":4111,"corporation":false,"usgs":true,"family":"Stagg","given":"Camille","email":"staggc@usgs.gov","middleInitial":"L.","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":692852,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nestlerode, Janet A.","contributorId":191374,"corporation":false,"usgs":false,"family":"Nestlerode","given":"Janet","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":692853,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Russell, Marc J.","contributorId":191375,"corporation":false,"usgs":false,"family":"Russell","given":"Marc","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":692854,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"From, Andrew 0000-0002-6543-2627 froma@usgs.gov","orcid":"https://orcid.org/0000-0002-6543-2627","contributorId":169668,"corporation":false,"usgs":true,"family":"From","given":"Andrew","email":"froma@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":692855,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Spivak, Amanda C.","contributorId":191376,"corporation":false,"usgs":false,"family":"Spivak","given":"Amanda","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":692856,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Dantin, Darrin D.","contributorId":191377,"corporation":false,"usgs":false,"family":"Dantin","given":"Darrin","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":692857,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Harvey, James E.","contributorId":191378,"corporation":false,"usgs":false,"family":"Harvey","given":"James","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":692858,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Almario, Alejandro E.","contributorId":191379,"corporation":false,"usgs":false,"family":"Almario","given":"Alejandro","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":692859,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70187126,"text":"70187126 - 2017 - Modeling the long-term effects of introduced herbivores on the spread of an invasive tree","interactions":[],"lastModifiedDate":"2017-05-18T10:59:39","indexId":"70187126","displayToPublicDate":"2017-04-25T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Modeling the long-term effects of introduced herbivores on the spread of an invasive tree","docAbstract":"Context
Melaleuca quinquenervia (Cav.) Blake (hereafter melaleuca) is an invasive tree from Australia that has spread over the freshwater ecosystems of southern Florida, displacing native vegetation, thus threatening native biodiversity. Suppression of melaleuca appears to be progressing through the introduction of insect species, the weevil, Oxiops vitiosa, and the psyllid, Boreioglycaspis melaleucae.
ObjectiveTo improve understanding of the possible effects of herbivory on the landscape dynamics of melaleuca in native southern Florida plant communities.
MethodsWe projected likely future changes in plant communities using the individual based modeling platform, JABOWA-II, by simulating successional processes occurring in two types of southern Florida habitat, cypress swamp and bay swamp, occupied by native species and melaleuca, with the impact of insect herbivores.
ResultsComputer simulations show melaleuca invasion leads to decreases in density and basal area of native species, but herbivory would effectively control melaleuca to low levels, resulting in a recovery of native species. When herbivory was modeled on pure melaleuca stands, it was more effective in stands with initially larger-sized melaleuca. Although the simulated herbivory did not eliminate melaleuca, it decreased its presence dramatically in all cases, supporting the long-term effectiveness of herbivory in controlling melaleuca invasion.
ConclusionsThe results provide three conclusions relevant to management: (1) The introduction of insect herbivory that has been applied to melaleuca appears sufficient to suppress melaleuca over the long term, (2) dominant native species may recover in about 50 years, and (3) regrowth of native species will further suppress melaleuca through competition.
In 2008, the U.S. Congress authorized the establishment of the National Climate Change and Wildlife Science Center (NCCWSC) within the U.S. Department of Interior (DOI). Housed administratively within the U.S. Geological Survey (USGS), NCCWSC is part of the DOI’s ongoing mission to meet the challenges of climate change and its effects on wildlife and aquatic resources. From 2010 through 2012, NCCWSC established eight regional DOI Climate Science Centers (CSCs). Each of these regional CSCs operated with the mission to “synthesize and integrate climate change impact data and develop tools that the Department’s managers and partners can use when managing the Department’s land, water, fish and wildlife, and cultural heritage resources” (Salazar 2009). The model developed by NCCWSC for the regional CSCs employed a dual approach of a federal USGS-staffed component and a parallel host-university component established competitively through a 5-year cooperative agreement with NCCWSC. At the conclusion of this 5-year agreement, a review of each CSC was undertaken, with the Southeast Climate Science Center (SE CSC) review in February 2016.
The SE CSC is hosted by North Carolina State University (NCSU) in Raleigh, North Carolina, and is physically housed within the NCSU Department of Applied Ecology along with the Center for Applied Aquatic Ecology, the North Carolina Cooperative Fish and Wildlife Research Unit (CFWRU), and the North Carolina Agromedicine Institute. The U.S. Department of Agriculture Southeast Regional Climate Hub is based at NCSU as is the National Oceanic and Atmospheric Administration (NOAA) Southeast Regional Climate Center, the North Carolina Institute for Climate Studies, the North Carolina Wildlife Resources Commission, the NOAA National Weather Service, the State Climate Office of North Carolina, and the U.S. Forest Service Eastern Forest Environmental Threat Assessment Center. This creates a strong core of organizations operating in close proximity focused on climate issues.
The geographic area covered by the SE CSC represents all or part of 16 states and the Caribbean Islands and has overlapping boundaries with seven Landscape Conservation Cooperatives (LCCs): Appalachian LCC, Eastern Tallgrass Prairie and Big Rivers LCC, Gulf Coast Prairie LCC, Gulf Coastal Plains and Ozarks LCC, Peninsular Florida LCC, South Atlantic LCC, and Caribbean LCC. The SE CSC region also encompasses 134 U.S. Fish and Wildlife Service refuges and 89 National Park Service (NPS) units and is home to 11 federally recognized and 54 state recognized tribes.
Dispersal can impact population dynamics and geographic variation, and thus, genetic approaches that can establish which landscape factors influence population connectivity have ecological and evolutionary importance. Mixed models that account for the error structure of pairwise datasets are increasingly used to compare models relating genetic differentiation to pairwise measures of landscape resistance. A model selection framework based on information criteria metrics or explained variance may help disentangle the ecological and landscape factors influencing genetic structure, yet there are currently no consensus for the best protocols. Here, we develop landscape-directed simulations and test a series of replicates that emulate independent empirical datasets of two species with different life history characteristics (greater sage-grouse; eastern foxsnake). We determined that in our simulated scenarios, AIC and BIC were the best model selection indices and that marginal R2 values were biased toward more complex models. The model coefficients for landscape variables generally reflected the underlying dispersal model with confidence intervals that did not overlap with zero across the entire model set. When we controlled for geographic distance, variables not in the underlying dispersal models (i.e., nontrue) typically overlapped zero. Our study helps establish methods for using linear mixed models to identify the features underlying patterns of dispersal across a variety of landscapes.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.2825","usgsCitation":"Row, J.R., Knick, S.T., Oyler-McCance, S.J., Lougheed, S.C., and Fedy, B.C., 2017, Developing approaches for linear mixed modeling in landscape genetics through landscape-directed dispersal simulations: Ecology and Evolution, v. 7, no. 11, p. 3751-3761, https://doi.org/10.1002/ece3.2825.","productDescription":"11 p.","startPage":"3751","endPage":"3761","ipdsId":"IP-064858","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":469904,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.2825","text":"Publisher Index Page"},{"id":340392,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"11","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-18","publicationStatus":"PW","scienceBaseUri":"59006062e4b0e85db3a5ddcb","contributors":{"authors":[{"text":"Row, Jeffery R.","contributorId":191345,"corporation":false,"usgs":false,"family":"Row","given":"Jeffery","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":692781,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knick, Steven T. 0000-0003-4025-1704 steve_knick@usgs.gov","orcid":"https://orcid.org/0000-0003-4025-1704","contributorId":159,"corporation":false,"usgs":true,"family":"Knick","given":"Steven","email":"steve_knick@usgs.gov","middleInitial":"T.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":692780,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":692782,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lougheed, Stephen C.","contributorId":191346,"corporation":false,"usgs":false,"family":"Lougheed","given":"Stephen","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":692783,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fedy, Bradley C.","contributorId":191347,"corporation":false,"usgs":false,"family":"Fedy","given":"Bradley","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":692784,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70187182,"text":"70187182 - 2017 - Post-fire interactions between soil water repellency, soil fertility and plant growth in soil collected from a burned piñon-juniper woodland","interactions":[],"lastModifiedDate":"2017-06-07T10:18:00","indexId":"70187182","displayToPublicDate":"2017-04-25T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2183,"text":"Journal of Arid Environments","active":true,"publicationSubtype":{"id":10}},"title":"Post-fire interactions between soil water repellency, soil fertility and plant growth in soil collected from a burned piñon-juniper woodland","docAbstract":"Woody plant encroachment can increase nutrient resources in the plant-mound zone. After a fire, this zone is often found to be water repellent. This study aimed to understand the effects of post-fire water repellency on soil water and inorganic nitrogen and their effects on plant growth of the introduced annual Bromus tectorum and native bunchgrass Pseudoroegneria spicata. Plots centered on burned Juniperus osteosperma trees were either left untreated or treated with surfactant to ameliorate water repellency. After two years, we excavated soil from the untreated and treated plots and placed it in zerotension lysimeter pots. In the greenhouse, half of the pots received an additional surfactant treatment. Pots were seeded separately with B. tectorum or P. spicata. Untreated soils had high runoff, decreased soilwater content, and elevated NO3eN in comparison to surfactant treated soils. The two plant species typically responded similar to the treatments. Above-ground biomass and microbial activity (estimated through soil CO2 gas emissions) was 16.8-fold and 9.5-fold higher in the surfactant-treated soils than repellent soils, respectably. This study demonstrates that water repellency can influence site recovery by decreasing soil water content, promoting inorganic N retention, and impairing plant growth and microbial activity.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jaridenv.2017.04.005","usgsCitation":"Fernelius, K.J., Madsen, M.D., Hopkins, B., Bansal, S., Anderson, V.J., Eggett, D.L., and Roundy, B.A., 2017, Post-fire interactions between soil water repellency, soil fertility and plant growth in soil collected from a burned piñon-juniper woodland: Journal of Arid Environments, v. 144, p. 98-109, https://doi.org/10.1016/j.jaridenv.2017.04.005.","productDescription":"12 p.","startPage":"98","endPage":"109","ipdsId":"IP-074353","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":469905,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jaridenv.2017.04.005","text":"Publisher Index Page"},{"id":340414,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","volume":"144","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59006060e4b0e85db3a5ddbf","contributors":{"authors":[{"text":"Fernelius, Kaitlynn J.","contributorId":191384,"corporation":false,"usgs":false,"family":"Fernelius","given":"Kaitlynn","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":692955,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Madsen, Matthew D.","contributorId":191385,"corporation":false,"usgs":false,"family":"Madsen","given":"Matthew","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":692956,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hopkins, Bryan 0000-0001-7313-055X","orcid":"https://orcid.org/0000-0001-7313-055X","contributorId":191386,"corporation":false,"usgs":false,"family":"Hopkins","given":"Bryan","email":"","affiliations":[{"id":6681,"text":"Brigham Young University","active":true,"usgs":false}],"preferred":false,"id":692957,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bansal, Sheel 0000-0003-1233-1707 sbansal@usgs.gov","orcid":"https://orcid.org/0000-0003-1233-1707","contributorId":167295,"corporation":false,"usgs":true,"family":"Bansal","given":"Sheel","email":"sbansal@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":692954,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anderson, Val J.","contributorId":191387,"corporation":false,"usgs":false,"family":"Anderson","given":"Val","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":692958,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Eggett, Dennis L.","contributorId":191388,"corporation":false,"usgs":false,"family":"Eggett","given":"Dennis","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":692959,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Roundy, Bruce A.","contributorId":178261,"corporation":false,"usgs":false,"family":"Roundy","given":"Bruce","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":692960,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70187152,"text":"70187152 - 2017 - Improved supervised classification of accelerometry data to distinguish behaviors of soaring birds","interactions":[],"lastModifiedDate":"2017-11-29T10:33:59","indexId":"70187152","displayToPublicDate":"2017-04-25T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Improved supervised classification of accelerometry data to distinguish behaviors of soaring birds","docAbstract":"Soaring birds can balance the energetic costs of movement by switching between flapping, soaring and gliding flight. Accelerometers can allow quantification of flight behavior and thus a context to interpret these energetic costs. However, models to interpret accelerometry data are still being developed, rarely trained with supervised datasets, and difficult to apply. We collected accelerometry data at 140Hz from a trained golden eagle (Aquila chrysaetos) whose flight we recorded with video that we used to characterize behavior. We applied two forms of supervised classifications, random forest (RF) models and K-nearest neighbor (KNN) models. The KNN model was substantially easier to implement than the RF approach but both were highly accurate in classifying basic behaviors such as flapping (85.5% and 83.6% accurate, respectively), soaring (92.8% and 87.6%) and sitting (84.1% and 88.9%) with overall accuracies of 86.6% and 92.3% respectively. More detailed classification schemes, with specific behaviors such as banking and straight flights were well classified only by the KNN model (91.24% accurate; RF = 61.64% accurate). The RF model maintained its accuracy of classifying basic behavior classification accuracy of basic behaviors at sampling frequencies as low as 10Hz, the KNN at sampling frequencies as low as 20Hz. Classification of accelerometer data collected from free ranging birds demonstrated a strong dependence of predicted behavior on the type of classification model used. Our analyses demonstrate the consequence of different approaches to classification of accelerometry data, the potential to optimize classification algorithms with validated flight behaviors to improve classification accuracy, ideal sampling frequencies for different classification algorithms, and a number of ways to improve commonly used analytical techniques and best practices for classification of accelerometry data.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0174785","usgsCitation":"Sur, M., Suffredini, T., Wessells, S.M., Bloom, P.H., Lanzone, M., Blackshire, S., Sridhar, S., and Katzner, T., 2017, Improved supervised classification of accelerometry data to distinguish behaviors of soaring birds: PLoS ONE, v. 12, no. 4, e0174785; 19 p., https://doi.org/10.1371/journal.pone.0174785.","productDescription":"e0174785; 19 p.","ipdsId":"IP-081662","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":469906,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0174785","text":"Publisher Index Page"},{"id":340410,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-12","publicationStatus":"PW","scienceBaseUri":"59006062e4b0e85db3a5ddc9","contributors":{"authors":[{"text":"Sur, Maitreyi","contributorId":191354,"corporation":false,"usgs":false,"family":"Sur","given":"Maitreyi","email":"","affiliations":[],"preferred":false,"id":692796,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Suffredini, Tony","contributorId":191355,"corporation":false,"usgs":false,"family":"Suffredini","given":"Tony","email":"","affiliations":[],"preferred":false,"id":692797,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wessells, Stephen M. 0000-0002-1895-4553 smwess@usgs.gov","orcid":"https://orcid.org/0000-0002-1895-4553","contributorId":2235,"corporation":false,"usgs":true,"family":"Wessells","given":"Stephen","email":"smwess@usgs.gov","middleInitial":"M.","affiliations":[{"id":5072,"text":"Office of Communication and Publishing","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":692798,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bloom, Peter H.","contributorId":191356,"corporation":false,"usgs":false,"family":"Bloom","given":"Peter","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":692799,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lanzone, Michael J.","contributorId":140128,"corporation":false,"usgs":false,"family":"Lanzone","given":"Michael J.","affiliations":[{"id":13392,"text":"Cellular Tracking Technologies","active":true,"usgs":false}],"preferred":false,"id":692800,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blackshire, Sheldon","contributorId":191357,"corporation":false,"usgs":false,"family":"Blackshire","given":"Sheldon","email":"","affiliations":[],"preferred":false,"id":692801,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sridhar, Srisarguru","contributorId":191358,"corporation":false,"usgs":false,"family":"Sridhar","given":"Srisarguru","email":"","affiliations":[],"preferred":false,"id":692802,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":692795,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70187153,"text":"70187153 - 2017 - Effect of hydraulic hysteresis on the stability of infinite slopes under steady infiltration","interactions":[],"lastModifiedDate":"2017-05-08T16:07:12","indexId":"70187153","displayToPublicDate":"2017-04-25T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2327,"text":"Journal of Geotechnical and Geoenvironmental Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Effect of hydraulic hysteresis on the stability of infinite slopes under steady infiltration","docAbstract":"Hydraulic hysteresis, including capillary soil water retention (SWR), air entrapment SWR, and hydraulic conductivity, is a common phenomenon in unsaturated soils. However, the influence of hydraulic hysteresis on suction stress, and subsequently slope stability, is generally ignored. This paper examines the influence of each of these three types of hysteresis on slope stability using an infinite slope stability analysis under steady infiltration conditions. First, hypothetical slopes for representative silty and sandy soils are examined. Then a monitored hillslope in the San Francisco Bay Area, California is assessed, using observed rainfall conditions and measured hydraulic and geotechnical properties of the colluvial soil. Results show that profiles of suction stress and the corresponding factor of safety are generally strongly affected by hydraulic hysteresis. Results suggest that each of the three types of hydraulic hysteresis may play a major role in the occurrence of slope failure, indicating that ignoring hydraulic hysteresis will likely lead to underestimates of failure potential and hence to inaccurate slope stability analysis.
The U.S. Geological Survey conducted a study, in cooperation with the Georgia Environmental Protection Division, to define the hydrologic properties of the Claiborne aquifer and evaluate its connection with the Upper Floridan aquifer in southwest Georgia. The effort involved collecting and compiling hydrologic data from the aquifer in subarea 4 of southwestern Georgia. Data collected for this study include borehole geophysical logs in 7 wells, and two 72-hour aquifer tests to determine aquifer properties.
The top of the Claiborne aquifer extends from an altitude of about 200 feet above the North American Vertical Datum of 1988 (NAVD 88) in Terrell County to 402 feet below NAVD 88 in Decatur County, Georgia. The base of the aquifer extends from an altitude of about 60 feet above NAVD 88 in eastern Sumter County to about 750 feet below NAVD 88 in Decatur County. Aquifer thickness ranges from about 70 feet in eastern Early County to 400 feet in Decatur County.
The transmissivity of the Claiborne aquifer, determined from two 72-hour aquifer tests, was estimated to be 1,500 and 700 feet squared per day in Mitchell and Early Counties, respectively. The storage coefficient was estimated to be 0.0006 and 0.0004 for the same sites, respectively. Aquifer test data from Mitchell County indicate a small amount of leakage occurred during the test. Groundwater-flow models suggest that the source of the leakage was the underlying Clayton aquifer, which produced about 2.5 feet of drawdown in response to pumping in the Claiborne aquifer. The vertical hydraulic conductivity of the confining unit between the Claiborne and Clayton aquifers was simulated to be about 0.02 foot per day.
Results from the 72-hour aquifer tests run for this study indicated no interconnection between the Claiborne and overlying Upper Floridan aquifers at the two test sites. Additional data are needed to monitor the effects that increased withdrawals from the Claiborne aquifer may have on future water resources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175017","collaboration":"Prepared in cooperation with the Georgia Environmental Protection Division","usgsCitation":"Gordon, D.W., and Gonthier, Gerald, 2017, Hydrology of the Claiborne aquifer and interconnection with the Upper Floridan aquifer in southwest Georgia: U.S. Geological Survey Scientific Investigations Report 2017–5017, 49 p., https://doi.org/10.3133/sir20175017.","productDescription":"x, 49 p.","numberOfPages":"64","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-076880","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":339811,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5017/sir20175017.pdf","text":"Report","size":"8.60 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5017"},{"id":339810,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5017/coverthb.jpg"},{"id":339835,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7B8569W","text":"USGS data release","description":"USGS data release","linkHelpText":"Data collected for Claiborne aquifer study in southwestern Georgia during 2015 to 2016"}],"country":"United States","state":"Georgia","otherGeospatial":"Claiborne Aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.1495361328125,\n 30.60482195075795\n ],\n [\n -83.748779296875,\n 30.60482195075795\n ],\n [\n -83.748779296875,\n 32.57459172113418\n ],\n [\n -85.1495361328125,\n 32.57459172113418\n ],\n [\n -85.1495361328125,\n 30.60482195075795\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
http://www.usgs.gov/water/southatlantic/
The HayWired scenario is a hypothetical earthquake sequence that is being used to better understand hazards for the San Francisco Bay region during and after an earthquake of magnitude 7 on the Hayward Fault. The 2014 Working Group on California Earthquake Probabilities calculated that there is a 33-percent likelihood of a large (magnitude 6.7 or greater) earthquake occurring on the Hayward Fault within three decades. A large Hayward Fault earthquake will produce strong ground shaking, permanent displacement of the Earth’s surface, landslides, liquefaction (soils becoming liquid-like during shaking), and subsequent fault slip, known as afterslip, and earthquakes, known as aftershocks.
The most recent large earthquake on the Hayward Fault occurred on October 21, 1868, and it ruptured the southern part of the fault. The 1868 magnitude-6.8 earthquake occurred when the San Francisco Bay region had far fewer people, buildings, and infrastructure (roads, communication lines, and utilities) than it does today, yet the strong ground shaking from the earthquake still caused significant building damage and loss of life. The next large Hayward Fault earthquake is anticipated to affect thousands of structures and disrupt the lives of millions of people. Earthquake risk in the San Francisco Bay region has been greatly reduced as a result of previous concerted efforts; for example, tens of billions of dollars of investment in strengthening infrastructure was motivated in large part by the 1989 magnitude 6.9 Loma Prieta earthquake. To build on efforts to reduce earthquake risk in the San Francisco Bay region, the HayWired earthquake scenario comprehensively examines the earthquake hazards to help provide the crucial scientific information that the San Francisco Bay region can use to prepare for the next large earthquake, The HayWired Earthquake Scenario—Earthquake Hazards volume describes the strong ground shaking modeled in the scenario and the hazardous movements of the Earth’s surface that the fault rupture and shaking will activate.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"The HayWired earthquake scenario","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175013v1","collaboration":"Prepared in cooperation with the California Geological Survey","usgsCitation":"Detweiler, S.T., and Wein, A.M., eds., 2017, The HayWired earthquake scenario—Earthquake hazards (ver. 1.2, December 2018): U.S. Geological Survey Scientific Investigations Report 2017–5013–A–H, 126 p., https://doi.org/10.3133/sir20175013v1.","productDescription":"xii, 126 p.","numberOfPages":"143","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":340004,"rank":1,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5013/sir20175013f_appendix2.zip","text":"Chapter F appendix 2","size":"74 KB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2017-5013 Chapter F appendix 2"},{"id":368413,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175013v2","text":"Scientific Investigations Report 2017-5013 Volume 2","description":"SIR 2017-5013 Volume 2","linkHelpText":"– The HayWired Earthquake Scenario—Engineering Implications"},{"id":368414,"rank":9,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175013V3","text":"Scientific Investigations Report 2017-5013 Volume 3","description":"SIR 2017-5013 Volume 3","linkHelpText":"– The HayWired Earthquake Scenario—Societal Consequences"},{"id":392902,"rank":10,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20183016","text":"Fact Sheet 2018-3016","linkHelpText":"– The HayWired Earthquake Scenario—We Can Outsmart Disaster"},{"id":392903,"rank":11,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20213054","text":"Fact Sheet 2021-3054","linkHelpText":"– The HayWired Earthquake Scenario—Societal Consequences"},{"id":353257,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7RN363Z","text":"USGS data release","description":"USGS data release","linkHelpText":"Data from earthquake-induced landslide hazards for a M7.0 scenario earthquake on the Hayward Fault"},{"id":352272,"rank":6,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2017/5013/versionHist_.txt","size":"1 KB","description":"SIR 2017-5013"},{"id":340063,"rank":5,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5013/sir20175013ah_v1.2.pdf","text":"Report","size":"55 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5013 Chapters A–H Version 1.1"},{"id":340049,"rank":4,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5013/coverthbah.jpg"},{"id":340006,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F76H4FPH","text":"USGS data release","description":"USGS data release","linkHelpText":"Point locations for earthquakes M2.5 and greater in a two-year aftershock sequence resulting from the HayWired scenario earthquake mainshock (4/18/2018) in the San Francisco Bay area, California"},{"id":340005,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F74X5610","text":"USGS data release","description":"USGS data release","linkHelpText":"Liquefaction potential as a result of HayWired earthquake scenario mainshock (April 18, 2018) shaking in Alameda and Santa Clara Counties, San Francisco Bay area, California"}],"country":"United States","state":"California","otherGeospatial":"Hayward Fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123,\n 37\n ],\n [\n -121,\n 37\n ],\n [\n -121,\n 38.65\n ],\n [\n -123,\n 38.65\n ],\n [\n -123,\n 37\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: April 2017; Version 1.1: March 2018; Version 1.2: December 2018","contact":"Contact Information, Menlo Park, Calif.
Office—Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025
https://earthquake.usgs.gov/
The role of parasites in trophic ecology is poorly understood in marine ecosystems. Stable isotope analyses (SIA) have been widely used in studies of trophic ecology, but have rarely been applied to study the role of parasites. Considering that some parasites are associated with altered host foraging patterns, SIA can help elucidate whether parasitism influences host trophic interactions. French grunt (Haemulon flavolineatum), an abundant Caribbean coral reef fish, contributes greatly to trophic connectivity. They typically depart the reef at dusk, feed overnight in seagrass beds, and return to the reef at dawn. The large parasitic isopod Anilocra haemuli commonly infects French grunt, and infected fish are less likely to complete their diel migration, and are in poorer condition than uninfected conspecifics. Brown chromis (Chromis multilineata) are diurnally feeding planktivores and infection by Anilocra chromis does not influence host condition. To determine if Anilocra infection influences host diet and foraging locality, we conducted stable carbon and nitrogen isotope analyses on scale, muscle, heart and gill tissues of infected and uninfected French grunt and brown chromis. We determined that all French grunt had δ13C values representative of seagrass habitats, but infected French grunt were significantly enriched in 13C and 15N compared to uninfected conspecifics. This suggests that compared to uninfected conspecifics, infected French grunt forage in seagrass, but on isotopically enriched prey, and/or are in poorer condition, which can elevate δ13C and δ15N values. For brown chromis, infection did not significantly influence any δ13C and δ15N values; hence they all foraged in the same environment and on similar prey. This is the first study to use SIA to examine differences in resource use by Caribbean coral reef fishes associated with parasitism and to evaluate how closely related parasites might have host-dependent effects on host trophic ecology.
","language":"English","publisher":"Wiley","doi":"10.1111/maec.12413","usgsCitation":"Welicky, R., Demopoulos, A., and Sikkel, P.C., 2017, Host-dependent differences in resource use associated with Anilocra spp. parasitism in two coral reef fishes, as revealed by stable carbon and nitrogen isotope analyses: Marine Ecology, v. 38, no. 2, Article e12413, https://doi.org/10.1111/maec.12413.","productDescription":"Article e12413","ipdsId":"IP-073021","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":340178,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","issue":"2","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-17","publicationStatus":"PW","scienceBaseUri":"58ff0e9ae4b006455f2d61ae","contributors":{"authors":[{"text":"Welicky, Rachel","contributorId":191260,"corporation":false,"usgs":false,"family":"Welicky","given":"Rachel","email":"","affiliations":[],"preferred":false,"id":692516,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Demopoulos, Amanda W.J. 0000-0003-2096-4694 ademopoulos@usgs.gov","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":371,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda W.J.","email":"ademopoulos@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":692514,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sikkel, Paul C.","contributorId":140403,"corporation":false,"usgs":false,"family":"Sikkel","given":"Paul","email":"","middleInitial":"C.","affiliations":[{"id":13476,"text":"Arkansas State University, State University, AR","active":true,"usgs":false}],"preferred":false,"id":692515,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70187129,"text":"70187129 - 2017 - When mechanism matters: Bayesian forecasting using models of ecological diffusion","interactions":[],"lastModifiedDate":"2017-04-24T14:27:01","indexId":"70187129","displayToPublicDate":"2017-04-24T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1466,"text":"Ecology Letters","active":true,"publicationSubtype":{"id":10}},"title":"When mechanism matters: Bayesian forecasting using models of ecological diffusion","docAbstract":"Ecological diffusion is a theory that can be used to understand and forecast spatio-temporal processes such as dispersal, invasion, and the spread of disease. Hierarchical Bayesian modelling provides a framework to make statistical inference and probabilistic forecasts, using mechanistic ecological models. To illustrate, we show how hierarchical Bayesian models of ecological diffusion can be implemented for large data sets that are distributed densely across space and time. The hierarchical Bayesian approach is used to understand and forecast the growth and geographic spread in the prevalence of chronic wasting disease in white-tailed deer (Odocoileus virginianus). We compare statistical inference and forecasts from our hierarchical Bayesian model to phenomenological regression-based methods that are commonly used to analyse spatial occurrence data. The mechanistic statistical model based on ecological diffusion led to important ecological insights, obviated a commonly ignored type of collinearity, and was the most accurate method for forecasting.
","language":"English","publisher":"Wiley","doi":"10.1111/ele.12763","usgsCitation":"Hefley, T.J., Hooten, M., Russell, R.E., Walsh, D.P., and Powell, J.A., 2017, When mechanism matters: Bayesian forecasting using models of ecological diffusion: Ecology Letters, v. 20, no. 5, p. 640-650, https://doi.org/10.1111/ele.12763.","productDescription":"11 p.","startPage":"640","endPage":"650","ipdsId":"IP-074169","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":340206,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-31","publicationStatus":"PW","scienceBaseUri":"58ff0e99e4b006455f2d61a4","contributors":{"authors":[{"text":"Hefley, Trevor J.","contributorId":147146,"corporation":false,"usgs":false,"family":"Hefley","given":"Trevor","email":"","middleInitial":"J.","affiliations":[{"id":16796,"text":"Dept Fish, Wildlife & Cons Biol, Colorado St Univ, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":692661,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":692658,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":692659,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walsh, Daniel P. 0000-0002-7772-2445 dwalsh@usgs.gov","orcid":"https://orcid.org/0000-0002-7772-2445","contributorId":4758,"corporation":false,"usgs":true,"family":"Walsh","given":"Daniel","email":"dwalsh@usgs.gov","middleInitial":"P.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":692660,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Powell, James A.","contributorId":190683,"corporation":false,"usgs":false,"family":"Powell","given":"James","email":"","middleInitial":"A.","affiliations":[{"id":12682,"text":"Utah State University, Logan, UT","active":true,"usgs":false}],"preferred":false,"id":692662,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70187128,"text":"70187128 - 2017 - Clearing the waters: Evaluating the need for site-specific field fluorescence corrections based on turbidity measurements","interactions":[],"lastModifiedDate":"2017-05-02T15:23:05","indexId":"70187128","displayToPublicDate":"2017-04-24T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2622,"text":"Limnology and Oceanography: Methods","active":true,"publicationSubtype":{"id":10}},"title":"Clearing the waters: Evaluating the need for site-specific field fluorescence corrections based on turbidity measurements","docAbstract":"In situ fluorescent dissolved organic matter (fDOM) measurements have gained increasing popularity as a proxy for dissolved organic carbon (DOC) concentrations in streams. One challenge to accurate fDOM measurements in many streams is light attenuation due to suspended particles. Downing et al. (2012) evaluated the need for corrections to compensate for particle interference on fDOM measurements using a single sediment standard in a laboratory study. The application of those results to a large river improved unfiltered field fDOM accuracy. We tested the same correction equation in a headwater tropical stream and found that it overcompensated fDOM when turbidity exceeded ∼300 formazin nephelometric units (FNU). Therefore, we developed a site-specific, field-based fDOM correction equation through paired in situ fDOM measurements of filtered and unfiltered streamwater. The site-specific correction increased fDOM accuracy up to a turbidity as high as 700 FNU, the maximum observed in this study. The difference in performance between the laboratory-based correction equation of Downing et al. (2012) and our site-specific, field-based correction equation likely arises from differences in particle size distribution between the sediment standard used in the lab (silt) and that observed in our study (fine to medium sand), particularly during high flows. Therefore, a particle interference correction equation based on a single sediment type may not be ideal when field sediment size is significantly different. Given that field fDOM corrections for particle interference under turbid conditions are a critical component in generating accurate DOC estimates, we describe a way to develop site-specific corrections.
","language":"English","publisher":"ASLO","doi":"10.1002/lom3.10175","usgsCitation":"Saraceno, J.F., Shanley, J.B., Downing, B.D., and Pellerin, B.A., 2017, Clearing the waters: Evaluating the need for site-specific field fluorescence corrections based on turbidity measurements: Limnology and Oceanography: Methods, v. 15, no. 4, p. 408-416, https://doi.org/10.1002/lom3.10175.","productDescription":"9 p.","startPage":"408","endPage":"416","ipdsId":"IP-075294","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":469909,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lom3.10175","text":"Publisher Index Page"},{"id":340207,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"4","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-25","publicationStatus":"PW","scienceBaseUri":"58ff0e9ae4b006455f2d61a6","contributors":{"authors":[{"text":"Saraceno, John Franco 0000-0003-0064-1820 saraceno@usgs.gov","orcid":"https://orcid.org/0000-0003-0064-1820","contributorId":2328,"corporation":false,"usgs":true,"family":"Saraceno","given":"John","email":"saraceno@usgs.gov","middleInitial":"Franco","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":692654,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shanley, James B. 0000-0002-4234-3437 jshanley@usgs.gov","orcid":"https://orcid.org/0000-0002-4234-3437","contributorId":1953,"corporation":false,"usgs":true,"family":"Shanley","given":"James","email":"jshanley@usgs.gov","middleInitial":"B.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":692655,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Downing, Bryan D. 0000-0002-2007-5304 bdowning@usgs.gov","orcid":"https://orcid.org/0000-0002-2007-5304","contributorId":1449,"corporation":false,"usgs":true,"family":"Downing","given":"Bryan","email":"bdowning@usgs.gov","middleInitial":"D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":692656,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pellerin, Brian A. bpeller@usgs.gov","contributorId":1451,"corporation":false,"usgs":true,"family":"Pellerin","given":"Brian","email":"bpeller@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":692657,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70187109,"text":"70187109 - 2017 - Confirmation of cisco spawning in Chaumont Bay, Lake Ontario using an egg pumping device","interactions":[],"lastModifiedDate":"2017-05-24T10:17:09","indexId":"70187109","displayToPublicDate":"2017-04-24T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Confirmation of cisco spawning in Chaumont Bay, Lake Ontario using an egg pumping device","docAbstract":"Cisco Coregonus artedi, a historically abundant and commercially important fish in the Great Lakes, have declined drastically in the last century due to the impacts of invasive species, overfishing, and habitat degradation. Chaumont Bay, New York is believed to contain one of the last remaining spawning populations of cisco in Lake Ontario although direct evidence of spawning has remained elusive. We document cisco spawning in Chaumont Bay for the first time in decades through the use of an egg pumping device specifically developed to sample through lake ice. Forty-one eggs were identified as cisco using genetic barcoding of the mitochondrial cytochrome c oxidase I (COI) gene. Cisco eggs were associated with shallow, rocky shoals. Contemporary knowledge of spawning behavior is an important step toward the successful restoration of cisco in Lake Ontario and across the Great Lakes.
","language":"English","publisher":"International Association for Great Lakes Research","publisherLocation":"Ann Arbor, MI","doi":"10.1016/j.jglr.2017.03.024","usgsCitation":"George, E.M., Stott, W., Young, B., Karboski, C.T., Crabtree, D.L., Roseman, E.F., and Rudstam, L.G., 2017, Confirmation of cisco spawning in Chaumont Bay, Lake Ontario using an egg pumping device: Journal of Great Lakes Research, v. 43, no. 3, p. 204-208, https://doi.org/10.1016/j.jglr.2017.03.024.","productDescription":"5 p.","startPage":"204","endPage":"208","ipdsId":"IP-075750","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":469908,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2017.03.024","text":"Publisher Index Page"},{"id":340135,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Chaumont Bay, Lake Ontario","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.21035575866699,\n 44.02750723990718\n ],\n [\n -76.13448143005371,\n 44.02750723990718\n ],\n [\n -76.13448143005371,\n 44.064461679421605\n ],\n [\n -76.21035575866699,\n 44.064461679421605\n ],\n [\n -76.21035575866699,\n 44.02750723990718\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58ff0e9be4b006455f2d61b4","contributors":{"authors":[{"text":"George, Ellen M. egeorge@usgs.gov","contributorId":3941,"corporation":false,"usgs":true,"family":"George","given":"Ellen","email":"egeorge@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":692483,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stott, Wendylee wstott@usgs.gov","contributorId":3763,"corporation":false,"usgs":true,"family":"Stott","given":"Wendylee","email":"wstott@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":692484,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Young, Brian","contributorId":191250,"corporation":false,"usgs":false,"family":"Young","given":"Brian","email":"","affiliations":[],"preferred":false,"id":692489,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Karboski, Curtis T.","contributorId":191251,"corporation":false,"usgs":false,"family":"Karboski","given":"Curtis","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":692490,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Crabtree, Darran L.","contributorId":90628,"corporation":false,"usgs":true,"family":"Crabtree","given":"Darran","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":692487,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Roseman, Edward F. 0000-0002-5315-9838 eroseman@usgs.gov","orcid":"https://orcid.org/0000-0002-5315-9838","contributorId":168428,"corporation":false,"usgs":true,"family":"Roseman","given":"Edward","email":"eroseman@usgs.gov","middleInitial":"F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":692482,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rudstam, Lars G.","contributorId":56609,"corporation":false,"usgs":false,"family":"Rudstam","given":"Lars","email":"","middleInitial":"G.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":692488,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70187107,"text":"70187107 - 2017 - Spatial dependence of reduced sulfur in Everglades dissolved organic matter controlled by sulfate enrichment","interactions":[],"lastModifiedDate":"2018-04-02T16:48:09","indexId":"70187107","displayToPublicDate":"2017-04-24T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Spatial dependence of reduced sulfur in Everglades dissolved organic matter controlled by sulfate enrichment","docAbstract":"Sulfate inputs to the Florida Everglades stimulate sulfidic conditions in freshwater wetland sediments that affect ecological and biogeochemical processes. An unexplored implication of sulfate enrichment is alteration of the content and speciation of sulfur in dissolved organic matter (DOM), which influences the reactivity of DOM with trace metals. Here, we describe the vertical and lateral spatial dependence of sulfur chemistry in the hydrophobic organic acid fraction of DOM from unimpacted and sulfate-impacted Everglades wetlands using X-ray absorption spectroscopy and ultrahigh-resolution mass spectrometry. Spatial variation in DOM sulfur content and speciation reflects the degree of sulfate enrichment and resulting sulfide concentrations in sediment pore waters. Sulfur is incorporated into DOM predominantly as highly reduced species in sulfidic pore waters. Sulfur-enriched DOM in sediment pore waters exchanges with overlying surface waters and the sulfur likely undergoes oxidative transformations in the water column. Across all wetland sites and depths, the total sulfur content of DOM correlated with the relative abundance of highly reduced sulfur functionality. The results identify sulfate input as a primary determinant on DOM sulfur chemistry to be considered in the context of wetland restoration and sulfur and trace metal cycling.
","language":"English","publisher":"American Chemical Society","publisherLocation":"Washington, D.C.","doi":"10.1021/acs.est.6b04142","usgsCitation":"Poulin, B.A., Ryan, J.N., Nagy, K.L., Stubbins, A., Dittmar, T., Orem, W.H., Krabbenhoft, D.P., and Aiken, G.R., 2017, Spatial dependence of reduced sulfur in Everglades dissolved organic matter controlled by sulfate enrichment: Environmental Science & Technology, v. 51, no. 7, p. 3630-3639, https://doi.org/10.1021/acs.est.6b04142.","productDescription":"10 p.","startPage":"3630","endPage":"3639","ipdsId":"IP-080060","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":469910,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1351336","text":"Publisher Index Page"},{"id":340139,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.37597656249999,\n 26.681821407205977\n ],\n [\n -80.4473876953125,\n 26.592211259271505\n ],\n [\n -80.4473876953125,\n 26.475490196773805\n ],\n [\n -80.53802490234375,\n 26.337729970839195\n ],\n [\n -80.83053588867188,\n 26.330345320410842\n ],\n [\n -80.826416015625,\n 26.154205294151907\n ],\n [\n -80.82916259765625,\n 26.13571361317392\n ],\n [\n -80.8319091796875,\n 26.098721466341463\n ],\n [\n -80.83740234375,\n 26.06788573671561\n ],\n [\n -80.83465576171875,\n 26.02717014049738\n ],\n [\n -80.83465576171875,\n 26.011126781744576\n ],\n [\n -80.8319091796875,\n 25.98150251402977\n ],\n [\n -80.826416015625,\n 25.91482062206972\n ],\n [\n -80.83465576171875,\n 25.897526562523137\n ],\n [\n -80.84701538085938,\n 25.78505344378837\n ],\n [\n -80.81954956054688,\n 25.761556561592343\n ],\n [\n -80.48858642578125,\n 25.761556561592343\n ],\n [\n -80.48309326171875,\n 25.897526562523137\n ],\n [\n -80.44052124023438,\n 25.939522021945148\n ],\n [\n -80.44052124023438,\n 25.951870779973\n ],\n [\n -80.43502807617188,\n 26.013595133509128\n ],\n [\n -80.43502807617188,\n 26.061717616104055\n ],\n [\n -80.43502807617188,\n 26.09748819315666\n ],\n [\n -80.43228149414062,\n 26.113519730139508\n ],\n [\n -80.43365478515625,\n 26.13941218371873\n ],\n [\n -80.36773681640625,\n 26.125850185680356\n ],\n [\n -80.29769897460938,\n 26.18625059891685\n ],\n [\n -80.29495239257812,\n 26.350036674507894\n ],\n [\n -80.27847290039062,\n 26.366033431992303\n ],\n [\n -80.25375366210938,\n 26.366033431992303\n ],\n [\n -80.23727416992188,\n 26.386948928734135\n ],\n [\n -80.23452758789062,\n 26.415240336985207\n ],\n [\n -80.22766113281249,\n 26.436146919246013\n ],\n [\n -80.21942138671875,\n 26.468114356372276\n ],\n [\n -80.22079467773438,\n 26.512362303867505\n ],\n [\n -80.22903442382812,\n 26.53570851865494\n ],\n [\n -80.2496337890625,\n 26.5737895138798\n ],\n [\n -80.27572631835938,\n 26.602034978080944\n ],\n [\n -80.321044921875,\n 26.62781822639305\n ],\n [\n -80.343017578125,\n 26.64745870265938\n ],\n [\n -80.35537719726562,\n 26.66341410252066\n ],\n [\n -80.36361694335938,\n 26.6855025116156\n ],\n [\n -80.37597656249999,\n 26.681821407205977\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"51","issue":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-15","publicationStatus":"PW","scienceBaseUri":"58ff0e9ce4b006455f2d61b6","contributors":{"authors":[{"text":"Poulin, Brett A. 0000-0002-5555-7733 bpoulin@usgs.gov","orcid":"https://orcid.org/0000-0002-5555-7733","contributorId":4360,"corporation":false,"usgs":true,"family":"Poulin","given":"Brett","email":"bpoulin@usgs.gov","middleInitial":"A.","affiliations":[{"id":5044,"text":"National Research Program - 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However, in addition to having an elevated mean concentration of ∼525 mg/L (as N), NO3− in the coastal sabkhas of Abu Dhabi is enriched in 15N (mean δ15N ∼17‰), which is an enigma. A NO3− solute mass balance analysis of the sabkha aquifer system suggests that more than 90% of the nitrogen is from local atmospheric deposition and the remainder from ascending brine. In contrast, isotopic mass balances based on Δ17O, δ15N, and δ18O data suggest approximately 80 to 90% of the NO3− could be from ascending brine. As the sabkha has essentially no soil, no vegetation, and no anthropogenic land or water use, we propose to resolve this apparent contradiction with a density-driven free-convection transport model. In this conceptual model, the density of rain is increased by solution of surface salts, transporting near-surface oxygenated NO3− bearing water downward where it encounters reducing conditions and mixes with oxygen-free ascending geologic brines. In this environment, NO3− is partially reduced to nitrogen gas (N2), thus enriching the remaining NO3− in heavy isotopes. The isotopically fractionated NO3− and nitrogen gas return to the near-surface oxidizing environment on the upward displacement leg of the free-convection cycle, where the nitrogen gas is released to the atmosphere and new NO3− is added to the system from atmospheric deposition. This recharge/recycling process has operated over many cycles in the 8000-year history of the shallow aquifer, progressively concentrating and isotopically fractionating the NO3−.
","language":"English","publisher":"Wiley","doi":"10.1111/gwat.12463","usgsCitation":"Wood, W., and Bohlke, J., 2017, Density-driven free-convection model for isotopically fractionated geogenic nitrate in sabkha brine: Groundwater, v. 55, no. 2, p. 199-207, https://doi.org/10.1111/gwat.12463.","productDescription":"9 p.","startPage":"199","endPage":"207","ipdsId":"IP-075480","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":340170,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United Arab Emirates","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 51.92138671874999,\n 23.88081490545854\n ],\n [\n 54.84375,\n 23.88081490545854\n ],\n [\n 54.84375,\n 24.93127614538456\n ],\n [\n 51.92138671874999,\n 24.93127614538456\n ],\n [\n 51.92138671874999,\n 23.88081490545854\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"55","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-28","publicationStatus":"PW","scienceBaseUri":"58ff0e9ae4b006455f2d61ac","contributors":{"authors":[{"text":"Wood, Warren W.","contributorId":47770,"corporation":false,"usgs":false,"family":"Wood","given":"Warren W.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":692578,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bohlke, J.K. 0000-0001-5693-6455 jkbohlke@usgs.gov","orcid":"https://orcid.org/0000-0001-5693-6455","contributorId":191103,"corporation":false,"usgs":true,"family":"Bohlke","given":"J.K.","email":"jkbohlke@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":692577,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70187122,"text":"70187122 - 2017 - Lyme disease ecology in a changing world: Consensus, uncertainty and critical gaps for improving control","interactions":[],"lastModifiedDate":"2017-05-02T15:36:30","indexId":"70187122","displayToPublicDate":"2017-04-24T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3048,"text":"Philosophical Transactions of the Royal Society B: Biological Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Lyme disease ecology in a changing world: Consensus, uncertainty and critical gaps for improving control","docAbstract":"Lyme disease is the most common tick-borne disease in temperate regions of North America, Europe and Asia, and the number of reported cases has increased in many regions as landscapes have been altered. Although there has been extensive work on the ecology and epidemiology of this disease in both Europe and North America, substantial uncertainty exists about fundamental aspects that determine spatial and temporal variation in both disease risk and human incidence, which hamper effective and efficient prevention and control. Here we describe areas of consensus that can be built on, identify areas of uncertainty and outline research needed to fill these gaps to facilitate predictive models of disease risk and the development of novel disease control strategies. Key areas of uncertainty include: (i) the precise influence of deer abundance on tick abundance, (ii) how tick populations are regulated, (iii) assembly of host communities and tick-feeding patterns across different habitats, (iv) reservoir competence of host species, and (v) pathogenicity for humans of different genotypes of Borrelia burgdorferi. Filling these knowledge gaps will improve Lyme disease prevention and control and provide general insights into the drivers and dynamics of this emblematic multi-host–vector-borne zoonotic disease.
","language":"English","publisher":"Royal Society of London","publisherLocation":"London","doi":"10.1098/rstb.2016.0117","usgsCitation":"Kilpatrick, A.M., Dobson, A.D., Levi, T., Salkeld, D.J., Swei, A., Ginsberg, H., Kjemtrup, A., Padgett, K.A., Jensen, P.A., Fish, D., Ogden, N.H., and Diuk-Wasser, M.A., 2017, Lyme disease ecology in a changing world: Consensus, uncertainty and critical gaps for improving control: Philosophical Transactions of the Royal Society B: Biological Sciences, v. 372, no. 1722, Article 20160117; 15 p., https://doi.org/10.1098/rstb.2016.0117.","productDescription":"Article 20160117; 15 p.","ipdsId":"IP-079486","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":461629,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rstb.2016.0117","text":"Publisher Index Page"},{"id":340195,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"372","issue":"1722","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-24","publicationStatus":"PW","scienceBaseUri":"58ff0e9ae4b006455f2d61aa","contributors":{"authors":[{"text":"Kilpatrick, A. Marm","contributorId":139721,"corporation":false,"usgs":false,"family":"Kilpatrick","given":"A.","email":"","middleInitial":"Marm","affiliations":[{"id":12892,"text":"Dept of Ecology & Evolutionary Biology, Univ of California","active":true,"usgs":false}],"preferred":false,"id":692608,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dobson, Andrew D.M.","contributorId":191294,"corporation":false,"usgs":false,"family":"Dobson","given":"Andrew","email":"","middleInitial":"D.M.","affiliations":[],"preferred":false,"id":692609,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Levi, Taal","contributorId":191295,"corporation":false,"usgs":false,"family":"Levi","given":"Taal","email":"","affiliations":[],"preferred":false,"id":692610,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Salkeld, Daniel J.","contributorId":191296,"corporation":false,"usgs":false,"family":"Salkeld","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":692611,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Swei, Andrea","contributorId":172648,"corporation":false,"usgs":false,"family":"Swei","given":"Andrea","email":"","affiliations":[],"preferred":false,"id":692612,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ginsberg, Howard S. 0000-0002-4933-2466 hginsberg@usgs.gov","orcid":"https://orcid.org/0000-0002-4933-2466","contributorId":147665,"corporation":false,"usgs":true,"family":"Ginsberg","given":"Howard S.","email":"hginsberg@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":692607,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kjemtrup, Anne","contributorId":191297,"corporation":false,"usgs":false,"family":"Kjemtrup","given":"Anne","email":"","affiliations":[],"preferred":false,"id":692613,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Padgett, Kerry A.","contributorId":191298,"corporation":false,"usgs":false,"family":"Padgett","given":"Kerry","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":692614,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Jensen, Per A.","contributorId":191299,"corporation":false,"usgs":false,"family":"Jensen","given":"Per","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":692615,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Fish, Durland","contributorId":191300,"corporation":false,"usgs":false,"family":"Fish","given":"Durland","email":"","affiliations":[],"preferred":false,"id":692616,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ogden, Nick H.","contributorId":191301,"corporation":false,"usgs":false,"family":"Ogden","given":"Nick","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":692617,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Diuk-Wasser, Maria A.","contributorId":148025,"corporation":false,"usgs":false,"family":"Diuk-Wasser","given":"Maria","email":"","middleInitial":"A.","affiliations":[{"id":7254,"text":"Columbia University - Lamont Doherty Earth Observatory","active":true,"usgs":false}],"preferred":false,"id":692624,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70187123,"text":"70187123 - 2017 - Planting richness affects the recovery of vegetation and soil processes in constructed wetlands following disturbance","interactions":[],"lastModifiedDate":"2017-04-24T13:18:57","indexId":"70187123","displayToPublicDate":"2017-04-24T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Planting richness affects the recovery of vegetation and soil processes in constructed wetlands following disturbance","docAbstract":"The resilience of constructed wetland ecosystems to severe disturbance, such as a mass herbivory eat-out or soil disturbance, remains poorly understood. In this study, we use a controlled mesocosm experiment to examine how original planting diversity affects the ability of constructed freshwater wetlands to recover structurally and functionally after a disturbance (i.e., aboveground harvesting and soil coring). We assessed if the planting richness of macrophyte species influences recovery of constructed wetlands one year after a disturbance. Mesocosms were planted in richness groups with various combinations of either 1, 2, 3, or 4 species (RG 1–4) to create a gradient of richness. Structural wetland traits measured include morphological regrowth of macrophytes, soil bulk density, soil moisture, soil %C, and soil %N. Functional wetland traits measured include above ground biomass production, soil potential denitrification, and soil potential microbial respiration. Total mesocosm cover increased along the gradient of plant richness (43.5% in RG 1 to 84.5% in RG 4) in the growing season after the disturbance, although not all planted individuals recovered. This was largely attributed to the dominance of the obligate annual species. The morphology of each species was affected negatively by the disturbance, producing shorter, and fewer stems than in the years prior to the disturbance, suggesting that the communities had not fully recovered one year after the disturbance. Soil characteristics were almost uniform across the planting richness gradient, but for a few exceptions (%C, C:N, and non-growing season soil moisture were higher slightly in RG 2). Denitrification potential (DEA) increased with increasing planting richness and was influenced by the abundance and quality of soil C. Increased open space in unplanted mesocosms and mesocosms with lower species richness increased labile C, leading to higher C mineralization rates.
","language":"English","publisher":"Elsevier","publisherLocation":"New York, NY","doi":"10.1016/j.scitotenv.2016.11.134","usgsCitation":"Means, M.M., Ahn, C., and Noe, G.E., 2017, Planting richness affects the recovery of vegetation and soil processes in constructed wetlands following disturbance: Science of the Total Environment, v. 579, p. 1366-1378, https://doi.org/10.1016/j.scitotenv.2016.11.134.","productDescription":"13 p.","startPage":"1366","endPage":"1378","ipdsId":"IP-081435","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":488607,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.11.134","text":"Publisher Index Page"},{"id":340192,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"579","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58ff0e9ae4b006455f2d61a8","contributors":{"authors":[{"text":"Means, Mary M.","contributorId":191302,"corporation":false,"usgs":false,"family":"Means","given":"Mary","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":692621,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ahn, Changwoo","contributorId":38047,"corporation":false,"usgs":true,"family":"Ahn","given":"Changwoo","affiliations":[],"preferred":false,"id":692622,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":692620,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70186762,"text":"ds1047 - 2017 - Digitized analog boomer seismic-reflection data collected during U.S. Geological Survey cruises Erda 90-1_HC, Erda 90-1_PBP, and Erda 91-3 in Mississippi Sound, June 1990 and September 1991","interactions":[],"lastModifiedDate":"2017-04-21T10:51:50","indexId":"ds1047","displayToPublicDate":"2017-04-21T09:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1047","title":"Digitized analog boomer seismic-reflection data collected during U.S. Geological Survey cruises Erda 90-1_HC, Erda 90-1_PBP, and Erda 91-3 in Mississippi Sound, June 1990 and September 1991","docAbstract":"The U.S. Geological Survey (USGS) Coastal and Marine Geology Program has actively collected geophysical and sedimentological data in the northern Gulf of Mexico for several decades, including shallow subsurface data in the form of high-resolution seismic-reflection profiles (HRSP). Prior to the mid-1990s most HRSP data were collected in analog format as paper rolls of continuous profiles up to 25 meters long. A large portion of this data resides in a single repository with minimal metadata. As part of the National Geological and Geophysical Data Preservation Program, scientists at the USGS St. Petersburg Coastal and Marine Science Center are converting the analog paper records to digital format using a large-format continuous scanner.
This report, along with the accompanying USGS data release (Bosse and others, 2017), serves as an archive of seismic profiles with headers, converted Society of Exploration Geophysicists Y format (SEG-Y) files, navigation data, and geographic information system data files for digitized boomer seismic-reflection data collected from the Research Vessel (R/V) Erda during two cruises in 1990 and 1991. The Erda 90-1 geophysical cruise was conducted in two legs. The first leg included seismic data collected from the Hancock County region of the Mississippi Sound (Erda 90-1_HC) from June 4 to June 6, 1990. The second leg included seismic data collected from the Petit Bois Pass area of Mississippi Sound (Erda 90-1_PBP) from June 8 to June 9, 1990. The Erda 91-3 cruise occurred between September 12 and September 23, 1991, and surveyed the Mississippi Sound region just west of Horn Island, Mississippi.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1047","usgsCitation":"Bosse, S.T., Flocks, J.G., and Forde, A.S., 2017, Digitized analog boomer seismic-reflection data collected during U.S. Geological Survey cruises Erda 90-1_HC, Erda 90-1_PBP, and Erda 91-3 in Mississippi Sound, June 1990 and September 1991: U.S. Geological Survey Data Series 1047, https://doi.org/10.3133/ds1047.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-081454","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":491684,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P14HK9XR","text":"USGS data release","linkHelpText":"Archive of Digitized Analog Boomer Seismic Reflection Data Collected Offshore of Mississippi, Alabama, and Florida in 1975: MAFLA 1975"},{"id":438366,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EFUAN3","text":"USGS data release","linkHelpText":"Archive of Digitized Analog Boomer Seismic Reflection Data Collected from the Northern Gulf of Mexico: Intersea 1980"},{"id":438365,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YA25SF","text":"USGS data release","linkHelpText":"Archive of Digitized Analog Boomer Seismic Reflection Data Collected from the Northern Gulf of Mexico: 1982, 1985, 1989, 1991, and 1992 "},{"id":438364,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9L3W3MX","text":"USGS data release","linkHelpText":"Archive of Digitized Analog Boomer Seismic Reflection Data Collected During USGS Cruise Kit Jones 92-1 Along the Florida Shelf, July 1992"},{"id":339824,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1047/coverthb.jpg"},{"id":339825,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1047/index.html","text":"Report HTML"},{"id":339828,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7BV7DRT","text":"USGS data release","description":"USGS data release","linkHelpText":"Archive of Digitized Analog Boomer Seismic-Reflection Data Collected During U.S. Geological Survey Cruises Erda 90-1_HC, Erda 90-1_PBP, and Erda 91-3 in Mississippi Sound, June 1990 and September 1991"}],"contact":"St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
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This study was undertaken to determine if the U.S. Geological Survey’s process for conducting mineral resource assessments on Earth can be applied to asteroids. Successful completion of the assessment, using water and iron resources to test the workflow, has resulted in identification of the minimal adjustments required to conduct full resource assessments beyond Earth. We also identify the types of future studies that would greatly reduce uncertainties in an actual future assessment. Whereas this is a feasibility study and does not include a complete and robust analysis of uncertainty, it is clear that the water and metal resources in near-Earth asteroids are sufficient to support humanity should it become a fully space-faring species.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171041","productDescription":"iii, 28 p.","onlineOnly":"Y","ipdsId":"IP-080222","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":340103,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1041/coverthb2.jpg"},{"id":340091,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1041/ofr20171041.pdf","text":"Report","size":"525 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1041"}],"contact":"Astrogeology Science Center
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The U.S. Geological Survey (USGS) has several strategic goals that focus its efforts on serving the American people. The USGS Ecosystems Mission Area has responsibility for the following objectives under the strategic goal of “Science to Manage and Sustain Resources for Thriving Economies and Healthy Ecosystems”:
This report provides abstracts of the majority of ongoing research investigations of the USGS Cooperative Fish and Wildlife Research Units program and is intended to complement the 2016 Cooperative Research Units Program Year in Review Circular 1424 (https://doi.org/10.3133/cir1424). The report is organized by the following major science themes that contribute to the objectives of the USGS:
Chief, Cooperative Fish and Wildlife Research Units Program
U.S. Geological Survey
12201 Sunrise Valley Drive
MS 303 National Center
Reston, VA 20192
https://www.coopunits.org/