Climate change, sea-level rise, and human development have contributed to the changing geomorphology of the San Francisco Bay - Delta (Bay-Delta) Estuary system. The need to predict scenarios of change led to the development of a new seamless, high-resolution digital elevation model (DEM) of the Bay – Delta that can be used by modelers attempting to understand potential future changes to the estuary system. This report details the three phases of the creation of this DEM. The first phase took a bathymetric-only DEM created in 2005 by the U.S. Geological Survey (USGS), refined it with additional data, and identified areas that would benefit from new surveys. The second phase began a USGS collaboration with the California Department of Water Resources (DWR) that updated a 2012 DWR seamless bathymetric/topographic DEM of the Bay-Delta with input from the USGS and modifications to fit the specific needs of USGS modelers. The third phase took the work from phase 2 and expanded the coverage area in the north to include the Yolo Bypass up to the Fremont Weir, the Sacramento River up to Knights Landing, and the American River up to the Nimbus Dam, and added back in the elevations for interior islands. The constant evolution of the Bay-Delta will require continuous updates to the DEM of the Delta, and there still are areas with older data that would benefit from modern surveys. As a result, DWR plans to continue updating the DEM.
Pacific Coastal and Marine Science Center
U.S. Geological Survey
2885 Mission St.
Santa Cruz, CA 95060
Molluscs possess a number of attributes that make them an excellent source of past environmental conditions in estuaries: they are common in estuarine environments; they typically have hard shells and are usually well preserved in sediments; they are relatively easy to detect in the environment; they have limited mobility as adults; they grow by incremental addition of layers to their shells; and they are found in all the major environments surrounding estuaries—terrestrial, freshwater, brackish, and marine waters. Analysis of molluscan assemblages can contribute information about past changes in sea level, climate, land use patterns, anthropogenic alterations, salinity, and other parameters of the benthic habitat and water chemistry within the estuary. High-resolution (from less than a day to annual) records of changes in environmental parameters can be obtained by analyzing the incremental growth layers in mollusc shells (sclerochronology). The shell layers retain information on changes in water temperature, salinity, seasonality, climate, river discharge, productivity, pollution and human activity. Isotopic analyses of mollusc shell growth layers can be problematic in estuaries where water temperatures and isotopic ratios can vary simultaneously; however, methods are being developed to overcome these problems. In addition to sclerochronology, molluscs are important to Holocene and Pleistocene estuarine palaeoenvironmental studies because of their use in the development of age models through radiocarbon dating, amino acid racemization, uranium-thorium series dating, and electron spin resonance (ESR) dating.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Applications of Paleoenvironmental Techniques in Estuarine Studies","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","publisherLocation":"Dordrecht","doi":"10.1007/978-94-024-0990-1_15","usgsCitation":"Wingard, G.L., and Surge, D., 2017, Application of molluscan analyses to the reconstruction of past environmental conditions in estuaries, chap. 15 of Applications of Paleoenvironmental Techniques in Estuarine Studies, v. 20, p. 357-387, https://doi.org/10.1007/978-94-024-0990-1_15.","productDescription":"31 p.","startPage":"357","endPage":"387","ipdsId":"IP-056056","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":342502,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-15","publicationStatus":"PW","scienceBaseUri":"59424b36e4b0764e6c65dc10","contributors":{"authors":[{"text":"Wingard, G. Lynn 0000-0002-3833-5207 lwingard@usgs.gov","orcid":"https://orcid.org/0000-0002-3833-5207","contributorId":605,"corporation":false,"usgs":true,"family":"Wingard","given":"G.","email":"lwingard@usgs.gov","middleInitial":"Lynn","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":698056,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Surge, Donna","contributorId":192887,"corporation":false,"usgs":false,"family":"Surge","given":"Donna","email":"","affiliations":[],"preferred":false,"id":698208,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70188488,"text":"70188488 - 2017 - The spatial distribution of earthquake stress rotations following large subduction zone earthquakes","interactions":[],"lastModifiedDate":"2017-06-14T08:56:36","indexId":"70188488","displayToPublicDate":"2017-06-14T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1430,"text":"Earth, Planets and Space","active":true,"publicationSubtype":{"id":10}},"title":"The spatial distribution of earthquake stress rotations following large subduction zone earthquakes","docAbstract":"Rotations of the principal stress axes due to great subduction zone earthquakes have been used to infer low differential stress and near-complete stress drop. The spatial distribution of coseismic and postseismic stress rotation as a function of depth and along-strike distance is explored for three recent M ≥ 8.8 subduction megathrust earthquakes. In the down-dip direction, the largest coseismic stress rotations are found just above the Moho depth of the overriding plate. This zone has been identified as hosting large patches of large slip in great earthquakes, based on the lack of high-frequency radiated energy. The large continuous slip patches may facilitate near-complete stress drop. There is seismological evidence for high fluid pressures in the subducted slab around the Moho depth of the overriding plate, suggesting low differential stress levels in this zone due to high fluid pressure, also facilitating stress rotations. The coseismic stress rotations have similar along-strike extent as the mainshock rupture. Postseismic stress rotations tend to occur in the same locations as the coseismic stress rotations, probably due to the very low remaining differential stress following the near-complete coseismic stress drop. The spatial complexity of the observed stress changes suggests that an analytical solution for finding the differential stress from the coseismic stress rotation may be overly simplistic, and that modeling of the full spatial distribution of the mainshock static stress changes is necessary.
","language":"English","publisher":"Springer","doi":"10.1186/s40623-017-0654-y","usgsCitation":"Hardebeck, J.L., 2017, The spatial distribution of earthquake stress rotations following large subduction zone earthquakes: Earth, Planets and Space, v. 69, no. 69, 11 p., https://doi.org/10.1186/s40623-017-0654-y.","productDescription":"11 p.","ipdsId":"IP-083499","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":469752,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40623-017-0654-y","text":"Publisher Index Page"},{"id":342461,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Chile, Indonesia, Japan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -221,\n 34.5\n ],\n [\n -216,\n 34.5\n ],\n [\n -216,\n 41.5\n ],\n [\n -221,\n 41.5\n ],\n [\n -221,\n 34.5\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.5,\n -32\n ],\n [\n -75.5,\n -39.5\n ],\n [\n -70,\n -39.5\n ],\n [\n -70,\n -32\n ],\n [\n -75.5,\n -32\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 90.5,\n -1\n ],\n [\n 100,\n -1\n ],\n [\n 100,\n 15\n ],\n [\n 90.5,\n 15\n ],\n [\n 90.5,\n -1\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"69","issue":"69","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-18","publicationStatus":"PW","scienceBaseUri":"59424b37e4b0764e6c65dc17","contributors":{"authors":[{"text":"Hardebeck, Jeanne L. 0000-0002-6737-7780 jhardebeck@usgs.gov","orcid":"https://orcid.org/0000-0002-6737-7780","contributorId":841,"corporation":false,"usgs":true,"family":"Hardebeck","given":"Jeanne","email":"jhardebeck@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":697976,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70188499,"text":"70188499 - 2017 - Soils as relative-age dating tools","interactions":[],"lastModifiedDate":"2017-06-14T14:08:17","indexId":"70188499","displayToPublicDate":"2017-06-14T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Soils as relative-age dating tools","docAbstract":"Soils develop at the earth's surface via multiple processes that act through time. Precluding burial or disturbance, soil genetic horizons form progressively and reflect the balance among formation processes, surface age, and original substrate composition. Soil morphology provides a key link between process and time (soil age), enabling soils to serve as both relative and numerical dating tools for geomorphic studies and landscape evolution. Five major factors define the contemporary state of all soils: climate, organisms, topography, parent material, and time. Soils developed on similar landforms and parent materials within a given landscape comprise what we term a soil/landform/substrate complex. Soils on such complexes that differ in development as a function of time represent a soil chronosequence. In a soil chronosequence, time constitutes the only independent formation factor; the other factors act through time. Time dictates the variations in soil development or properties (field or laboratory measured) on a soil/landform/substrate complex. Using a dataset within the chronosequence model, we can also formulate various soil development indices based upon one or a combination of soil properties, either for individual soil horizons or for an entire profile. When we evaluate soil data or soil indices mathematically, the resulting equation creates a chronofunction. Chronofunctions help quantify processes and mechanisms involved in soil development, and relate them mathematically to time. These rigorous kinds of comparisons among and within soil/landform complexes constitute an important tool for relative-age dating. After determining one or more absolute ages for a soil/landform complex, we can calculate quantitative soil formation, and or landform-development rates. Multiple dates for several complexes allow rate calculations for soil/landform-chronosequence development and soil-chronofunction calibration.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The International Encyclopedia of Geography","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"John Wiley & Sons, Ltd.","doi":"10.1002/9781118786352.wbieg0437","usgsCitation":"Markewich, H.W., Pavich, M.J., and Wysocki, D., 2017, Soils as relative-age dating tools, chap. of The International Encyclopedia of Geography, 14 p., https://doi.org/10.1002/9781118786352.wbieg0437.","productDescription":"14 p.","ipdsId":"IP-053464","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":342500,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-06","publicationStatus":"PW","scienceBaseUri":"59424b37e4b0764e6c65dc14","contributors":{"authors":[{"text":"Markewich, Helaine W. 0000-0001-9656-3243 helainem@usgs.gov","orcid":"https://orcid.org/0000-0001-9656-3243","contributorId":2008,"corporation":false,"usgs":true,"family":"Markewich","given":"Helaine","email":"helainem@usgs.gov","middleInitial":"W.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":698027,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pavich, Milan J. mpavich@usgs.gov","contributorId":2348,"corporation":false,"usgs":true,"family":"Pavich","given":"Milan","email":"mpavich@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":698028,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wysocki, Douglas A.","contributorId":61320,"corporation":false,"usgs":true,"family":"Wysocki","given":"Douglas A.","affiliations":[],"preferred":false,"id":698029,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70188465,"text":"70188465 - 2017 - Pulsed strain release on the Altyn Tagh fault, northwest China","interactions":[],"lastModifiedDate":"2018-10-24T16:43:47","indexId":"70188465","displayToPublicDate":"2017-06-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Pulsed strain release on the Altyn Tagh fault, northwest China","docAbstract":"Earthquake recurrence models assume that major surface-rupturing earthquakes are followed by periods of reduced rupture probability as stress rebuilds. Although purely periodic, time- or slip-predictable rupture models are known to be oversimplifications, a paucity of long records of fault slip clouds understanding of fault behavior and earthquake recurrence over multiple ruptures. Here, we report a 16 kyr history of fault slip—including a pulse of accelerated slip from 6.4 to 6.0 ka—determined using a Monte Carlo analysis of well-dated offset landforms along the central Altyn Tagh strike-slip fault (ATF) in northwest China. This pulse punctuates a median rate of 8.1+1.2/−0.9 mm/a and likely resulted from either a flurry of temporally clustered ∼Mw 7.5 ground-rupturing earthquakes or a single large >Mw 8.2 earthquake. The clustered earthquake scenario implies rapid re-rupture of a fault reach >195 km long and indicates decoupled rates of elastic strain energy accumulation versus dissipation, conceptualized as a crustal stress battery. If the pulse reflects a single event, slip-magnitude scaling implies that it ruptured much of the ATF with slip similar to, or exceeding, the largest documented historical ruptures. Both scenarios indicate fault rupture behavior that deviates from classic time- or slip-predictable models.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2016.11.024","usgsCitation":"Gold, R.D., Cowgill, E., Arrowsmith, J.R., and Friedrich, A.M., 2017, Pulsed strain release on the Altyn Tagh fault, northwest China: Earth and Planetary Science Letters, v. 459, p. 291-300, https://doi.org/10.1016/j.epsl.2016.11.024.","productDescription":"10 p.","startPage":"291","endPage":"300","ipdsId":"IP-081268","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":469832,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2016.11.024","text":"Publisher Index Page"},{"id":342419,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","otherGeospatial":"Altyn Tagh fault","volume":"459","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5940f9b1e4b0764e6c63eaa4","contributors":{"authors":[{"text":"Gold, Ryan D. 0000-0002-4464-6394 rgold@usgs.gov","orcid":"https://orcid.org/0000-0002-4464-6394","contributorId":3883,"corporation":false,"usgs":true,"family":"Gold","given":"Ryan","email":"rgold@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":697890,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cowgill, Eric","contributorId":192850,"corporation":false,"usgs":false,"family":"Cowgill","given":"Eric","affiliations":[],"preferred":false,"id":697891,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arrowsmith, J. Ramon","contributorId":80209,"corporation":false,"usgs":false,"family":"Arrowsmith","given":"J.","email":"","middleInitial":"Ramon","affiliations":[{"id":24511,"text":"Arizona State University, Tempe AZ USA 85287","active":true,"usgs":false}],"preferred":false,"id":697892,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Friedrich, Anke M.","contributorId":192852,"corporation":false,"usgs":false,"family":"Friedrich","given":"Anke","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":697916,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70188461,"text":"70188461 - 2017 - Expanding the North American Breeding Bird Survey analysis to include additional species and regions","interactions":[],"lastModifiedDate":"2017-06-13T09:56:47","indexId":"70188461","displayToPublicDate":"2017-06-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Expanding the North American Breeding Bird Survey analysis to include additional species and regions","docAbstract":"The North American Breeding Bird Survey (BBS) contains data for >700 bird species, but analyses often focus on a core group of ∼420 species. We analyzed data for 122 species of North American birds for which data exist in the North American Breeding Bird Survey (BBS) database but are not routinely analyzed on the BBS Summary and Analysis Website. Many of these species occur in the northern part of the continent, on routes that fall outside the core survey area presently analyzed in the United States and southern Canada. Other species not historically analyzed occur in the core survey area with very limited data but have large portions of their ranges in Mexico and south. A third group of species not historically analyzed included species thought to be poorly surveyed by the BBS, such as rare, coastal, or nocturnal species. For 56 species found primarily in regions north of the core survey area, we expanded the scope of the analysis, using data from 1993 to 2014 during which ≥3 survey routes had been sampled in 6 northern strata (Bird Conservation regions in Alaska, Yukon, and Newfoundland and Labrador) and fitting log-linear hierarchical models for an augmented BBS survey area that included both the new northern strata and the core survey area. We also applied this model to 168 species historically analyzed in the BBS that had data from these additional northern strata. For both groups of species we calculated survey-wide trends for the both core and augmented survey areas from 1993 to 2014; for species that did not occur in the newly defined strata, we computed trends from 1966 to 2014. We evaluated trend estimates in terms of established credibility criteria for BBS results, screening for imprecise trends, small samples, and low relative abundance. Inclusion of data from the northern strata permitted estimation of trend for 56 species not historically analyzed, but only 4 of these were reasonably monitored and an additional 13 were questionably monitored; 39 of these species were likely poorly monitored because of small numbers of samples or very imprecisely estimated trends. Only 4 of 66 “new” species found in the core survey area were reasonably monitored by the BBS; 20 were questionably monitored; and 42 were likely poorly monitored by the BBS because of inefficiency in precision, abundance, or sample size. The hierarchical analyses we present provide a means for reasonable inclusion of the additional species and strata in a common analysis with data from the core area, a critical step in the evolution of the BBS as a continent-scale survey. We recommend that results be presented both 1) from 1993 to the present using the expanded survey area, and 2) from 1966 to the present for the core survey area. Although most of the “new” species we analyzed were poorly monitored by the BBS during 1993–2014, continued expansion of the BBS will improve the quality of information in future analyses for these species and for the many other species presently monitored by the BBS.
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/102015-JFWM-109","usgsCitation":"Sauer, J.R., Niven, D., Pardieck, K.L., Ziolkowski, D., and Link, W.A., 2017, Expanding the North American Breeding Bird Survey analysis to include additional species and regions: Journal of Fish and Wildlife Management, v. 8, no. 1, p. 154-172, https://doi.org/10.3996/102015-JFWM-109.","productDescription":"19 p.","startPage":"154","endPage":"172","ipdsId":"IP-069657","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":486817,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/102015-jfwm-109","text":"Publisher Index Page"},{"id":342415,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-01","publicationStatus":"PW","scienceBaseUri":"5940f9b2e4b0764e6c63eab0","contributors":{"authors":[{"text":"Sauer, John R. 0000-0002-4557-3019 jrsauer@usgs.gov","orcid":"https://orcid.org/0000-0002-4557-3019","contributorId":146917,"corporation":false,"usgs":true,"family":"Sauer","given":"John","email":"jrsauer@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":697878,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Niven, Daniel 0000-0002-9527-0577 dniven@usgs.gov","orcid":"https://orcid.org/0000-0002-9527-0577","contributorId":179148,"corporation":false,"usgs":true,"family":"Niven","given":"Daniel","email":"dniven@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":697879,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pardieck, Keith L. 0000-0003-2779-4392 kpardieck@usgs.gov","orcid":"https://orcid.org/0000-0003-2779-4392","contributorId":4104,"corporation":false,"usgs":true,"family":"Pardieck","given":"Keith","email":"kpardieck@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":697880,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ziolkowski, David Jr. 0000-0002-2500-4417 dziolkowski@usgs.gov","orcid":"https://orcid.org/0000-0002-2500-4417","contributorId":179149,"corporation":false,"usgs":true,"family":"Ziolkowski","given":"David","suffix":"Jr.","email":"dziolkowski@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":697913,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Link, William A. 0000-0002-9913-0256 wlink@usgs.gov","orcid":"https://orcid.org/0000-0002-9913-0256","contributorId":146920,"corporation":false,"usgs":true,"family":"Link","given":"William","email":"wlink@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":697882,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70188462,"text":"ds1043 - 2017 - Transient electromagnetic soundings in the San Luis Valley, Colorado, near the Great Sand Dunes National Park and Preserve and the Alamosa National Wildlife Refuge (field seasons 2007, 2009, and 2011)","interactions":[],"lastModifiedDate":"2017-06-13T14:30:55","indexId":"ds1043","displayToPublicDate":"2017-06-13T00:00:00","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":"1043","title":"Transient electromagnetic soundings in the San Luis Valley, Colorado, near the Great Sand Dunes National Park and Preserve and the Alamosa National Wildlife Refuge (field seasons 2007, 2009, and 2011)","docAbstract":"Transient electromagnetic (TEM) soundings were made in the San Luis Valley, Colorado, to map the location of a blue clay unit as well as to investigate the presence of suspected faults. A total of 147 soundings were made near and in Great Sand Dunes National Park and Preserve, and an additional 6 soundings were made near Hansen Bluff on the eastern edge of the Alamosa National Wildlife Refuge. The blue clay is a significant hydrologic feature in the area that separates an unconfined surface aquifer from a deeper confined aquifer. Knowledge of its location is important to regional hydrological models. Previous analysis of well logs has shown that the blue clay has a resistivity of 10 ohm-meters or less, which is in contrast to the higher resistivity of sand, gravel, and other clay units found in the area, making it a very good target for TEM soundings. The top of the blue clay was found to have considerable relief, suggesting the possibility of deformation of the clay during or after deposition. Because of rift activity, deformation is to be expected. Of the TEM profiles made across faults identified by aeromagnetic data, some showed resistivity variations and (or) subsurface elevation relief of resistivity units, suggestive of faulting. Such patterns were not associated with all suspected faults. The Hansen Bluff profile showed variations in resistivity and depth to conductor that coincide with a scarp between the highlands to the east and the floodplain of the Rio Grande to the west.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1043","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Fitterman, D.V., 2017, Transient electromagnetic soundings in the San Luis Valley, Colorado, near the Great Sand Dunes National Park and Preserve and the Alamosa National Wildlife Refuge (field seasons 2007, 2009, and 2011): U.S. Geological Survey Data Series 1043, 39 p., https://doi.org/10.3133/ds1043.","productDescription":"Report: vii; 52 p.","startPage":"1","endPage":"39","numberOfPages":"52","onlineOnly":"Y","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":342428,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7D21VQ5","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Transient Electromagnetic Sounding Data Collected in the San Luis Valley, Colorado near the Great Sand Dunes National Park and Preserve and the Alamosa National Wildlife Refuge (Field Seasons 2007, 2009, and 2011)"},{"id":342407,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1043/coverthb.jpg"},{"id":342408,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1043/ds1043.pdf","text":"Report","size":"3.92 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1043"}],"country":"United States ","state":"Colorado","otherGeospatial":"San Luis Valley ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.11145019531249,\n 37.42906945530332\n ],\n [\n -105.56488037109375,\n 37.42906945530332\n ],\n [\n -105.56488037109375,\n 37.93444993515032\n ],\n [\n -106.11145019531249,\n 37.93444993515032\n ],\n [\n -106.11145019531249,\n 37.42906945530332\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Crustal Geophysics and Geochemistry Science Center
U.S. Geological Survey
Box 25046, MS 964
Denver, CO 80225
We examined data on white pine blister rust (blister rust) collected during the monitoring of whitebark pine trees in the Greater Yellowstone Ecosystem (from 2004-2015). Summaries of repeat observations performed by multiple independent observers are reviewed and discussed. These summaries show variability among observers and the potential for errors being made in blister rust status. Based on this assessment, we utilized occupancy models to analyze blister rust prevalence while explicitly accounting for imperfect detection. Available covariates were used to model both the probability of a tree being infected with blister rust and the probability of an observer detecting the infection. The fitted model provided strong evidence that the probability of blister rust infection increases as tree diameter increases and decreases as site elevation increases. Most importantly, we found evidence of heterogeneity in detection probabilities related to tree size and average slope of a transect. These results suggested that detecting the presence of blister rust was more difficult in larger trees. Also, there was evidence that blister rust was easier to detect on transects located on steeper slopes.
Our model accounted for potential impacts of observer experience on blister rust detection probabilities and also showed moderate variability among the different observers in their ability to detect blister rust. Based on these model results, we suggest that multiple observer sampling continue in future field seasons in order to allow blister rust prevalence estimates to be corrected for imperfect detection. We suggest that the multiple observer effort be spread out across many transects (instead of concentrated at a few each field season) while retaining the overall proportion of trees with multiple observers around 5-20%. Estimates of prevalence are confounded with detection unless it is explicitly accounted for in an analysis and we demonstrate how an occupancy model can be used to do account for this source of observation error.
","language":"English","publisher":"National Park Service","publisherLocation":"Fort Collins, CO","usgsCitation":"Wright, W.J., and Irvine, K.M., 2017, Assessment of imperfect detection of blister rust in whitebark pine within the Greater Yellowstone Ecosystem: Natural Resource Report 2017/1457, vi, 24 p.","productDescription":"vi, 24 p.","ipdsId":"IP-083274","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":342431,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":342427,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/DataStore/Reference/Profile/2240718"}],"country":"United States","state":"idaho, Montana, Utah, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.5,\n 41.918628865183045\n ],\n [\n -108.446044921875,\n 41.918628865183045\n ],\n [\n -108.446044921875,\n 45.75985868785574\n ],\n [\n -112.5,\n 45.75985868785574\n ],\n [\n -112.5,\n 41.918628865183045\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5940f9b0e4b0764e6c63ea9b","contributors":{"authors":[{"text":"Wright, Wilson J.","contributorId":192867,"corporation":false,"usgs":false,"family":"Wright","given":"Wilson","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":697959,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Irvine, Kathryn M. 0000-0002-6426-940X kirvine@usgs.gov","orcid":"https://orcid.org/0000-0002-6426-940X","contributorId":2218,"corporation":false,"usgs":true,"family":"Irvine","given":"Kathryn","email":"kirvine@usgs.gov","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":697958,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70188458,"text":"70188458 - 2017 - Synoptic sampling and principal components analysis to identify sources of water and metals to an acid mine drainage stream","interactions":[],"lastModifiedDate":"2017-07-12T10:23:19","indexId":"70188458","displayToPublicDate":"2017-06-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1564,"text":"Environmental Science and Pollution Research","active":true,"publicationSubtype":{"id":10}},"title":"Synoptic sampling and principal components analysis to identify sources of water and metals to an acid mine drainage stream","docAbstract":"Combining the synoptic mass balance approach with principal components analysis (PCA) can be an effective method for discretising the chemistry of inflows and source areas in watersheds where contamination is diffuse in nature and/or complicated by groundwater interactions. This paper presents a field-scale study in which synoptic sampling and PCA are employed in a mineralized watershed (Lion Creek, Colorado, USA) under low flow conditions to (i) quantify the impacts of mining activity on stream water quality; (ii) quantify the spatial pattern of constituent loading; and (iii) identify inflow sources most responsible for observed changes in stream chemistry and constituent loading. Several of the constituents investigated (Al, Cd, Cu, Fe, Mn, Zn) fail to meet chronic aquatic life standards along most of the study reach. The spatial pattern of constituent loading suggests four primary sources of contamination under low flow conditions. Three of these sources are associated with acidic (pH <3.1) seeps that enter along the left bank of Lion Creek. Investigation of inflow water (trace metal and major ion) chemistry using PCA suggests a hydraulic connection between many of the left bank inflows and mine water in the Minnesota Mine shaft located to the north-east of the river channel. In addition, water chemistry data during a rainfall-runoff event suggests the spatial pattern of constituent loading may be modified during rainfall due to dissolution of efflorescent salts or erosion of streamside tailings. These data point to the complexity of contaminant mobilisation processes and constituent loading in mining-affected watersheds but the combined synoptic sampling and PCA approach enables a conceptual model of contaminant dynamics to be developed to inform remediation.
","language":"English","publisher":"Springer","doi":"10.1007/s11356-017-9038-x","usgsCitation":"Byrne, P., Runkel, R.L., and Walton-Day, K., 2017, Synoptic sampling and principal components analysis to identify sources of water and metals to an acid mine drainage stream: Environmental Science and Pollution Research, v. 24, no. 20, p. 17220-17240, https://doi.org/10.1007/s11356-017-9038-x.","productDescription":"21 p.","startPage":"17220","endPage":"17240","ipdsId":"IP-080091","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":469759,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s11356-017-9038-x","text":"Publisher Index Page"},{"id":342403,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"24","issue":"20","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-06","publicationStatus":"PW","scienceBaseUri":"593fa830e4b0764e6c627943","contributors":{"authors":[{"text":"Byrne, Patrick","contributorId":192845,"corporation":false,"usgs":false,"family":"Byrne","given":"Patrick","affiliations":[],"preferred":false,"id":697867,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Runkel, Robert L. 0000-0003-3220-481X runkel@usgs.gov","orcid":"https://orcid.org/0000-0003-3220-481X","contributorId":685,"corporation":false,"usgs":true,"family":"Runkel","given":"Robert","email":"runkel@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":697866,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walton-Day, Katherine 0000-0002-9146-6193 kwaltond@usgs.gov","orcid":"https://orcid.org/0000-0002-9146-6193","contributorId":184043,"corporation":false,"usgs":true,"family":"Walton-Day","given":"Katherine","email":"kwaltond@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":697868,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70189502,"text":"70189502 - 2017 - Model-based approaches to deal with detectability: a comment on Hutto (2016)","interactions":[],"lastModifiedDate":"2017-07-14T10:17:33","indexId":"70189502","displayToPublicDate":"2017-06-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Model-based approaches to deal with detectability: a comment on Hutto (2016)","docAbstract":"In a recent paper, Hutto (2016a) challenges the need to account for detectability when interpreting data from point counts. A number of issues with model-based approaches to deal with detectability are presented, and an alternative suggested: surveying an area around each point over which detectability is assumed certain. The article contains a number of false claims and errors of logic, and we address these here. We provide suggestions about appropriate uses of distance sampling and occupancy modeling, arising from an intersection of design- and model-based inference.","language":"English","publisher":"Ecological Society of America ","doi":"10.1002/eap.1553","usgsCitation":"Marques, T.A., Thomas, L., Kery, M., Buckland, S.T., Borchers, D.L., Rexstad, E., Fewster, R.M., MacKenzie, D.I., Royle, A., Guillera-Arroita, G., Handel, C.M., Pavlacky, D., and Camp, R., 2017, Model-based approaches to deal with detectability: a comment on Hutto (2016): Ecological Applications, v. 27, no. 5, p. 1694-1698, https://doi.org/10.1002/eap.1553.","productDescription":"5 p.","startPage":"1694","endPage":"1698","ipdsId":"IP-085010","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":461511,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.1553","text":"Publisher Index Page"},{"id":343836,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"5","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-12","publicationStatus":"PW","scienceBaseUri":"5969d829e4b0d1f9f060a17c","contributors":{"authors":[{"text":"Marques, Tiago A.","contributorId":194662,"corporation":false,"usgs":false,"family":"Marques","given":"Tiago","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":704936,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thomas, Len 0000-0002-7436-067X","orcid":"https://orcid.org/0000-0002-7436-067X","contributorId":194663,"corporation":false,"usgs":false,"family":"Thomas","given":"Len","email":"","affiliations":[],"preferred":false,"id":704937,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kery, Marc","contributorId":194664,"corporation":false,"usgs":false,"family":"Kery","given":"Marc","email":"","affiliations":[],"preferred":false,"id":704938,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Buckland, Steve T. 0000-0002-9939-709X","orcid":"https://orcid.org/0000-0002-9939-709X","contributorId":194665,"corporation":false,"usgs":false,"family":"Buckland","given":"Steve","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":704939,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Borchers, David L.","contributorId":194666,"corporation":false,"usgs":false,"family":"Borchers","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":704940,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rexstad, Eric","contributorId":194667,"corporation":false,"usgs":false,"family":"Rexstad","given":"Eric","affiliations":[],"preferred":false,"id":704941,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fewster, Rachel M.","contributorId":194668,"corporation":false,"usgs":false,"family":"Fewster","given":"Rachel","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":704942,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"MacKenzie, Darryl I.","contributorId":194669,"corporation":false,"usgs":false,"family":"MacKenzie","given":"Darryl","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":704943,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":704934,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Guillera-Arroita, Gurutzeta","contributorId":149296,"corporation":false,"usgs":false,"family":"Guillera-Arroita","given":"Gurutzeta","email":"","affiliations":[{"id":13336,"text":"University of Melbourne","active":true,"usgs":false}],"preferred":false,"id":704944,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Handel, Colleen M. 0000-0002-0267-7408 cmhandel@usgs.gov","orcid":"https://orcid.org/0000-0002-0267-7408","contributorId":3067,"corporation":false,"usgs":true,"family":"Handel","given":"Colleen","email":"cmhandel@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":704935,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Pavlacky, David C. Jr","contributorId":194670,"corporation":false,"usgs":false,"family":"Pavlacky","given":"David C. ","suffix":"Jr","affiliations":[],"preferred":false,"id":704945,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Camp, Richard J.","contributorId":194671,"corporation":false,"usgs":false,"family":"Camp","given":"Richard J.","affiliations":[],"preferred":false,"id":704946,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70193465,"text":"70193465 - 2017 - Influence of trap modifications and environmental predictors on capture success of southern flying squirrels","interactions":[],"lastModifiedDate":"2017-11-02T13:11:40","indexId":"70193465","displayToPublicDate":"2017-06-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Influence of trap modifications and environmental predictors on capture success of southern flying squirrels","docAbstract":"Sherman traps are the most commonly used live traps in studies of small mammals and have been successfully used in the capture of arboreal species such as the southern flying squirrel (Glaucomys volans). However, southern flying squirrels spend proportionately less time foraging on the ground, which necessitates above-ground trapping methods and modifications of capture protocols. Further, quantitative estimates of the factors affecting capture success of flying squirrel populations have focused solely on effects of trapping methodologies. We developed and evaluated the efficacy of a portable Sherman trap design for capturing southern flying squirrels during 2015–2016 at the Alice L. Kibbe Field Station, Illinois, USA. Additionally, we used logistic regression to quantify potential effects of time-dependent (e.g., weather) and time-independent (e.g., habitat, extrinsic) factors on capture success of southern flying squirrels. We recorded 165 capture events (119 F, 44 M, 2 unknown) using our modified Sherman trap design. Probability of capture success decreased 0.10/1° C increase in daily maximum temperature and by 0.09/unit increase (km/hr) in wind speed. Conversely, probability of capture success increased by 1.2/1° C increase in daily minimum temperature. The probability of capturing flying squirrels was negatively associated with trap orientation. When tree-mounted traps are required, our modified trap design is a safe, efficient, and cost-effective method of capturing animals when moderate weather (temp and wind speed) conditions prevail. Further, we believe that strategic placement of traps (e.g., northeast side of tree) and quantitative information on site-specific (e.g., trap location) characteristics (e.g., topographical features, slope, aspect, climatologic factors) could increase southern flying squirrel capture success. © 2017 The Wildlife Society.
","language":"English","publisher":"Wiley","doi":"10.1002/wsb.769","usgsCitation":"Jacques, C.N., Zweep, J.S., Scheihing, M.E., Rechkemmer, W.T., Jenkins, S.E., Klaver, R.W., and Dubay, S.A., 2017, Influence of trap modifications and environmental predictors on capture success of southern flying squirrels: Wildlife Society Bulletin, v. 41, no. 2, p. 313-321, https://doi.org/10.1002/wsb.769.","productDescription":"9 p.","startPage":"313","endPage":"321","ipdsId":"IP-078961","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":469757,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doaj.org/article/7c2cd54ecd554011aca5558f735f007e","text":"Publisher Index Page"},{"id":348085,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois","county":"Hancock","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.52435302734375,\n 40.02130468739707\n ],\n [\n -90.50537109375,\n 40.02130468739707\n ],\n [\n -90.50537109375,\n 40.701463603604594\n ],\n [\n -91.52435302734375,\n 40.701463603604594\n ],\n [\n -91.52435302734375,\n 40.02130468739707\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-14","publicationStatus":"PW","scienceBaseUri":"59fc2ea4e4b0531197b27f81","contributors":{"authors":[{"text":"Jacques, Christopher N.","contributorId":15521,"corporation":false,"usgs":true,"family":"Jacques","given":"Christopher","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":719677,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zweep, James S.","contributorId":199664,"corporation":false,"usgs":false,"family":"Zweep","given":"James","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":719678,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scheihing, Mary E.","contributorId":199665,"corporation":false,"usgs":false,"family":"Scheihing","given":"Mary","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":719679,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rechkemmer, Will T.","contributorId":196304,"corporation":false,"usgs":false,"family":"Rechkemmer","given":"Will","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":719680,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jenkins, Sean E.","contributorId":199666,"corporation":false,"usgs":false,"family":"Jenkins","given":"Sean","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":719681,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Klaver, Robert W. 0000-0002-3263-9701 bklaver@usgs.gov","orcid":"https://orcid.org/0000-0002-3263-9701","contributorId":3285,"corporation":false,"usgs":true,"family":"Klaver","given":"Robert","email":"bklaver@usgs.gov","middleInitial":"W.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":719145,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dubay, Shelli A.","contributorId":171437,"corporation":false,"usgs":false,"family":"Dubay","given":"Shelli","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":719682,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70189897,"text":"70189897 - 2017 - A geochemical examination of humidity cell tests","interactions":[],"lastModifiedDate":"2017-11-08T19:26:08","indexId":"70189897","displayToPublicDate":"2017-06-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"A geochemical examination of humidity cell tests","docAbstract":"Humidity cell tests (HCTs) are long-term (20 to >300 weeks) leach tests that are considered by some to be the among the most reliable geochemical characterization methods for estimating the leachate quality of mined materials. A number of modifications have been added to the original HCT method, but the interpretation of test results varies widely. We suggest that the HCTs represent an underutilized source of geochemical data, with a year-long test generating approximately 2500 individual chemical data points. The HCT concentration peaks and valleys can be thought of as a “chromatogram” of reactions that may occur in the field, whereby peaks in concentrations are associated with different geochemical processes, including sulfate salt dissolution, sulfide oxidation, and dissolution of rock-forming minerals, some of which can neutralize acid. Some of these reactions occur simultaneously, some do not, and geochemical modeling can be used to help distinguish the dominant processes. Our detailed examination, including speciation and inverse modeling, of HCTs from three projects with different geology and mineralization shows that rapid sulfide oxidation dominates over a limited period of time that starts between 40 and 200 weeks of testing. The applicability of laboratory tests results to predicting field leachate concentrations, loads, or rates of reaction has not been adequately demonstrated, although early flush releases and rapid sulfide oxidation rates in HCTs should have some relevance to field conditions. Knowledge of possible maximum solute concentrations is needed to design effective treatment and mitigation approaches. Early flush and maximum sulfide oxidation results from HCTs should be retained and used in environmental models. Factors that complicate the use of HCTs include: sample representation, time for microbial oxidizers to grow, sample storage before testing, geochemical reactions that add or remove constituents, and the HCT results chosen for use in modeling the environmental performance at mine sites. Improved guidance is needed for more consistent interpretation and use of HCT results that rely on identifying: the geochemical processes; the mineralogy, including secondary mineralogy; the available surface area for reactions; and the influence of hydrologic processes on leachate concentrations in runoff, streams, and groundwater.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2017.03.016","usgsCitation":"Maest, A., and Nordstrom, D.K., 2017, A geochemical examination of humidity cell tests: Applied Geochemistry, v. 81, p. 109-131, https://doi.org/10.1016/j.apgeochem.2017.03.016.","productDescription":"23 p.","startPage":"109","endPage":"131","ipdsId":"IP-085397","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":469758,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2017.03.016","text":"Publisher Index Page"},{"id":344491,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"81","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59819315e4b0e2f5d463b79b","contributors":{"authors":[{"text":"Maest, Ann","contributorId":195266,"corporation":false,"usgs":false,"family":"Maest","given":"Ann","affiliations":[],"preferred":false,"id":706653,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nordstrom, D. Kirk 0000-0003-3283-5136 dkn@usgs.gov","orcid":"https://orcid.org/0000-0003-3283-5136","contributorId":749,"corporation":false,"usgs":true,"family":"Nordstrom","given":"D.","email":"dkn@usgs.gov","middleInitial":"Kirk","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":706652,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70187444,"text":"sir20175032 - 2017 - Groundwater quality in the Western San Joaquin Valley study unit, 2010: California GAMA Priority Basin Project","interactions":[],"lastModifiedDate":"2019-12-30T14:45:28","indexId":"sir20175032","displayToPublicDate":"2017-06-09T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5032","title":"Groundwater quality in the Western San Joaquin Valley study unit, 2010: California GAMA Priority Basin Project","docAbstract":"Water quality in groundwater resources used for public drinking-water supply in the Western San Joaquin Valley (WSJV) was investigated by the USGS in cooperation with the California State Water Resources Control Board (SWRCB) as part of its Groundwater Ambient Monitoring and Assessment (GAMA) Program Priority Basin Project. The WSJV includes two study areas: the Delta–Mendota and Westside subbasins of the San Joaquin Valley groundwater basin. Study objectives for the WSJV study unit included two assessment types: (1) a status assessment yielding quantitative estimates of the current (2010) status of groundwater quality in the groundwater resources used for public drinking water, and (2) an evaluation of natural and anthropogenic factors that could be affecting the groundwater quality. The assessments characterized the quality of untreated groundwater, not the quality of treated drinking water delivered to consumers by water distributors.
The status assessment was based on data collected from 43 wells sampled by the U.S. Geological Survey for the GAMA Priority Basin Project (USGS-GAMA) in 2010 and data compiled in the SWRCB Division of Drinking Water (SWRCB-DDW) database for 74 additional public-supply wells sampled for regulatory compliance purposes between 2007 and 2010. To provide context, concentrations of constituents measured in groundwater were compared to U.S. Environmental Protection Agency (EPA) and SWRCB-DDW regulatory and non-regulatory benchmarks for drinking-water quality. The status assessment used a spatially weighted, grid-based method to estimate the proportion of the groundwater resources used for public drinking water that has concentrations for particular constituents or class of constituents approaching or above benchmark concentrations. This method provides statistically unbiased results at the study-area scale within the WSJV study unit, and permits comparison of the two study areas to other areas assessed by the GAMA Priority Basin Project statewide.
Groundwater resources used for public drinking water in the WSJV study unit are among the most saline and most affected by high concentrations of inorganic constituents of all groundwater resources used for public drinking water that have been assessed by the GAMA Priority Basin Project statewide. Among the 82 GAMA Priority Basin Project study areas statewide, the Delta–Mendota study area ranked above the 90th percentile for aquifer-scale proportions of groundwater resources having concentrations of total dissolved solids (TDS), sulfate, chloride, manganese, boron, chromium(VI), selenium, and strontium above benchmarks, and the Westside study area ranked above the 90th percentile for TDS, sulfate, manganese, and boron.
In the WSJV study unit as a whole, one or more inorganic constituents with regulatory or non-regulatory, health-based benchmarks were present at concentrations above benchmarks in about 53 percent of the groundwater resources used for public drinking water, and one or more organic constituents with regulatory health-based benchmarks were detected at concentrations above benchmarks in about 3 percent of the resource. Individual constituents present at concentrations greater than health-based benchmarks in greater than 2 percent of groundwater resources used for public drinking water included: boron (51 percent, SWRCB-DDW notification level), chromium(VI) (25 percent, SWRCB-DDW maximum contaminant level (MCL)), arsenic (10 percent, EPA MCL), strontium (5.1 percent, EPA Lifetime health advisory level (HAL)), nitrate (3.9 percent, EPA MCL), molybdenum (3.8 percent, EPA HAL), selenium (2.6 percent, EPA MCL), and benzene (2.6 percent, SWRCB-DDW MCL). In addition, 50 percent of the resource had TDS concentrations greater than non-regulatory, aesthetic-based SWRCB-DDW upper secondary maximum contaminant level (SMCL), and 44 percent had manganese concentrations greater than the SWRCB-DDW SMCL.
Natural and anthropogenic factors that could affect the groundwater quality were evaluated by using results from statistical testing of associations between constituent concentrations and values of potential explanatory factors, inferences from geochemical and age-dating tracer results, and by considering the water-quality results in the context of the hydrogeologic setting of the WSJV study unit.
Natural factors, particularly the lithologies of the source areas for groundwater recharge and of the aquifers, were the dominant factors affecting groundwater quality in most of the WSJV study unit. However, where groundwater resources used for public supply included groundwater recharged in the modern era, mobilization of constituents by recharge of water used for irrigation also affected groundwater quality. Public-supply wells in the Westside study area had a median depth of 305 m and primarily tapped groundwater recharged hundreds to thousands of years ago, whereas public-supply wells in the Delta–Mendota study area had a median depth of 85 m and primarily tapped either groundwater recharged within the last 60 years or groundwater consisting of mixtures of this modern recharge and older recharge.
Public-supply wells in the WSJV study unit are screened in the Tulare Formation and zones above and below the Corcoran Clay Member are used. The Tulare Formation primarily consists of alluvial sediments derived from the Coast Ranges to the west, except along the valley trough at the eastern margin of the WSJV study unit where the Tulare Formation consists of fluvial sands derived from the Sierra Nevada to the east. Groundwater from wells screened in the Sierra Nevada sands had manganese-reducing or manganese- and iron-reducing oxidation-reduction (redox) conditions. These redox conditions commonly were associated with elevated arsenic or molybdenum concentrations, and the dominance of arsenic(III) in the dissolved arsenic supports reductive dissolution of iron and manganese oxyhydroxides as the mechanism. In addition, groundwater from many wells screened in Sierra Nevada sands contained low concentrations of nitrite or ammonium, indicating reduction of nitrate by denitrification or dissimilatory processes, respectively.
Geology of the Coast Ranges westward of the study unit strongly affects groundwater quality in the WSJV. Elevated concentrations of TDS, sulfate, boron, selenium and strontium in groundwater were primarily associated with aquifer sediments and recharge derived from areas of the Coast Ranges dominated by Cretaceous-to-Miocene age, organic-rich, reduced marine shales, known as the source of selenium in WSJV soils, surface water, and groundwater. Low sulfur-isotopic values (δ34S) of dissolved sulfate indicate that the sulfate was largely derived from oxidation of biogenic pyrite from the shales, and correlations with trace element concentrations, geologic setting, and groundwater geochemical modeling indicated that distributions of sulfate, strontium, and selenium in groundwater were controlled by dissolution of secondary sulfate minerals in soils and sediments.
Elevated concentrations of chromium(VI) were primarily associated with aquifer sediments and recharge derived from areas of the Coast Ranges dominated by the Franciscan Complex and ultramafic rocks. The Franciscan Complex also has boron-rich, sodium-chloride dominated hydrothermal fluids that contribute to elevated concentrations of boron and TDS.
Groundwater from wells screened in Coast Ranges alluvium was primarily oxic and relatively alkaline (median pH value of 7.55) in the Delta–Mendota study area, and primarily nitrate-reducing or suboxic and alkaline (median pH value of 8.4) in the Westside study area. Many groundwater samples from those wells have elevated concentrations of arsenic(V), molybdenum, selenium, or chromium(VI), consistent with desorption of metal oxyanions from mineral surfaces under those geochemical conditions.
High concentrations of benzene were associated with deep wells located in the vicinity of petroleum deposits at the southern end of the Westside study area. Groundwater from these wells had premodern age and anoxic geochemical conditions, and the ratios among concentrations of hydrocarbon constituents were different from ratios found in fuels and combustion products, which is consistent with a geogenic source for the benzene rather than contamination from anthropogenic sources.
Water stable-isotope compositions, groundwater recharge temperatures, and groundwater ages were used to infer four types of groundwater: (1) groundwater derived from natural recharge of water from major rivers draining the Sierra Nevada; (2) groundwater primarily derived from natural recharge of water from Coast Ranges runoff; (3) groundwater derived from recharge of pumped groundwater applied to the land surface for irrigation; and (4) groundwater derived from recharge during a period of much cooler paleoclimate. Water previously used for irrigation was found both above and below the Corcoran Clay, supporting earlier inferences that this clay member is no longer a robust confining unit.
Recharge of water used for irrigation has direct and indirect effects on groundwater quality. Elevated nitrate concentrations and detections of herbicides and fumigants in the Delta–Mendota study area generally were associated with greater agricultural land use near the well and with water recharged during the last 60 years. However, the extent of the groundwater resource affected by agricultural sources of nitrate was limited by groundwater redox conditions sufficient to reduce nitrate. The detection frequency of perchlorate in Delta–Mendota groundwater was greater than expected for natural conditions. Perchlorate, nitrate, selenium, and strontium concentrations were correlated with one another and were greater in groundwater inferred to be recharge of previously pumped groundwater used for irrigation. The source of the perchlorate, selenium, and strontium appears to be salts deposited in the soils and sediments of the arid WSJV that are dissolved and flushed into groundwater by the increased amount of recharge caused by irrigation. In the Delta–Mendota study area, the groundwater with elevated concentrations of selenium was found deeper in the aquifer system than it was reported by a previous study 25 years earlier, suggesting that this transient front of groundwater with elevated concentrations of constituents derived from dissolution of soil salts by irrigation recharge is moving down through the aquifer system and is now reaching the depth zone used for public drinking water supply.
California Water Science Center
California GAMA
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
We know economic and social policy has implications for ecosystems at large, but the consequences for a given geographic area or specific wildlife population are more difficult to conceptualize and communicate. Species distribution models, which extrapolate species-habitat relationships across ecological scales, are capable of predicting population changes in distribution and abundance in response to management and policy, and thus, are an ideal means for facilitating proactive management within a larger policy framework. To illustrate the capabilities of species distribution modeling in scenario planning for wildlife populations, we projected an existing distribution model for ring-necked pheasants (Phasianus colchicus) onto a series of alternative future landscape scenarios for Nebraska, USA. Based on our scenarios, we qualitatively and quantitatively estimated the effects of agricultural policy decisions on pheasant populations across Nebraska, in specific management regions, and at wildlife management areas.
","language":"English","publisher":"Wildlife Society","doi":"10.1002/wsb.763","usgsCitation":"Fontaine, J.J., Jorgensen, C., Stuber, E.F., Gruber, L.F., Bishop, A.A., Lusk, J.J., Zach, E.S., and Decker, K.L., 2017, Species distributions models in wildlife planning: agricultural policy and wildlife management in the great plains: Wildlife Society Bulletin, v. 41, no. 2, p. 194-204, https://doi.org/10.1002/wsb.763.","productDescription":"11 p.","startPage":"194","endPage":"204","ipdsId":"IP-074173","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500009,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/96c855f789ed430aa033cce5d08fd393","text":"External Repository"},{"id":347513,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","volume":"41","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-09","publicationStatus":"PW","scienceBaseUri":"59f83a35e4b063d5d30980d6","contributors":{"authors":[{"text":"Fontaine, Joseph J. 0000-0002-7639-9156 jfontaine@usgs.gov","orcid":"https://orcid.org/0000-0002-7639-9156","contributorId":3820,"corporation":false,"usgs":true,"family":"Fontaine","given":"Joseph","email":"jfontaine@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":716477,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jorgensen, Christopher","contributorId":198580,"corporation":false,"usgs":false,"family":"Jorgensen","given":"Christopher","affiliations":[],"preferred":false,"id":716478,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stuber, Erica F.","contributorId":198581,"corporation":false,"usgs":false,"family":"Stuber","given":"Erica","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":716479,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gruber, Lutz F.","contributorId":198582,"corporation":false,"usgs":false,"family":"Gruber","given":"Lutz","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":716480,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bishop, Andrew A.","contributorId":93323,"corporation":false,"usgs":true,"family":"Bishop","given":"Andrew","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":716481,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lusk, Jeffrey J.","contributorId":198584,"corporation":false,"usgs":false,"family":"Lusk","given":"Jeffrey","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":716482,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zach, Eric S.","contributorId":198585,"corporation":false,"usgs":false,"family":"Zach","given":"Eric","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":716483,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Decker, Karie L.","contributorId":51094,"corporation":false,"usgs":true,"family":"Decker","given":"Karie","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":716484,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70187352,"text":"sir20175036 - 2017 - Performance measures for a Mississippi River reintroduction into the forested wetlands of Maurepas Swamp","interactions":[],"lastModifiedDate":"2017-06-09T09:28:31","indexId":"sir20175036","displayToPublicDate":"2017-06-09T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5036","title":"Performance measures for a Mississippi River reintroduction into the forested wetlands of Maurepas Swamp","docAbstract":"The use of freshwater diversions (river reintroductions) from the Mississippi River as a restoration tool to rehabilitate Louisiana coastal wetlands has been promoted widely since the first such diversion at Caernarvon became operational in the early 1990s. To date, aside from the Bonnet Carré Spillway (which is designed and operated for flood control), there are only four operational Mississippi River freshwater diversions (two gated structures and two siphons) in coastal Louisiana, and they all target salinity intrusion, shellfish management, and (or) the enhancement of the integrity of marsh habitat. River reintroductions carry small sediment loads for various design reasons, but they can be effective in delivering freshwater to combat saltwater intrusion and increase the delivery of nutrients and suspended fine-grained sediments to receiving wetlands. River reintroductions may be an ideal restoration tool for targeting coastal swamp forest habitat; much of the area of swamp forest habitat in coastal Louisiana is undergoing saltwater intrusion, high rates of submergence, and lack of riverine flow leading to reduced concentrations of important nutrients and suspended sediments, which sustain growth and regeneration, help to aerate swamp soils, and remove toxic compounds from the rhizosphere.
The State of Louisiana Coastal Protection and Restoration Authority (CPRA) has made it a priority to establish a small freshwater river diversion into a coastal swamp forest located between Baton Rouge and New Orleans, Louisiana, to reintroduce Mississippi River water to Maurepas Swamp. While a full understanding of how a coastal swamp forest will respond to new freshwater loading through a Mississippi River reintroduction is unknown, this report provides guidance based on the available literature for establishing performance measures that can be used for evaluating the effectiveness of a Mississippi River reintroduction into the forested wetlands of Maurepas Swamp (project PO-29 of the Coastal Wetlands Planning, Protection and Restoration Act) and aid in adaptive management of the project. PO-29 is a small river reintroduction in scope, and through its operation, it will provide information about the feasibility and reasonable expectations for future river reintroduction projects targeting coastal swamp forests in Louisiana.
Located near Garyville, Louisiana, the Mississippi River reintroduction into Maurepas Swamp project is being designed to deliver a maximum flow of 57 cubic meters per second (m3/s) (or about 2,000 cubic feet per second [ft3/s]) directly from the river, but with a maximum flow through the outflow channel of 42 m3/s (or 1,500 ft3/s) available for at least half of the year. The river reintroduction will divert Mississippi River water through channelized flow and surface water to impact approximately 16,583 hectares (ha) of wetland habitat, much of which is swamp forest and swamp forest transitioning into marsh habitat. The Mississippi River reintroduction into Maurepas Swamp and associated outfall management features collectively should facilitate connectivity of water between the Mississippi River and the entire project area.
At any given location, hydrologic connectivity should occur at intervals between twice yearly and once per decade, and hydrologic management must allow the potential for water drawdowns to foster tree regeneration every 3–13 years. The river reintroduction is also anticipated to maintain salinity in swamp forests dominated by Taxodium distichum (baldcypress) to less than 1.3 practical salinity units (psu) and maintain salinity in mixed baldcypress and Nyssa aquatica (water tupelo) swamp forests to less than 0.8 psu. The river reintroduction should promote soil surface elevation gains of 8–9 millimeters per year (mm/yr) (range, 4.9–12.1 mm/yr) to offset relative sea-level rise and keep total river water nitrate (NO3-) loading into Maurepas Swamp to about 11.25 grams (g) of nitrogen (N) per square meter per year (m-2 yr-1 ) (range, 7.1–15.4 g N m-2 yr-1) to promote near complete uptake of NO3- by the vegetation in the receiving wetlands and reduce impacts to water quality in adjacent and connected water ways (for example, Blind River) and Lake Maurepas. With these performance measures maintained over time, we further expect swamp forest stands to realize improvements in stand density index of as much as 30–45 percent of maximum values for the stand type while maintaining an overstory leaf area index of 2.0–2.9 square meters per square meter or higher as swamp forests recover from decades of low flow, saltwater intrusion, reduced nutrients, and surface elevation deficits associated with isolation from the Mississippi River.
Associated with these performance measures are two major uncertainties: (1) an assumption that we can rely on existing data, literature, and modeling from coastal swamp forests to establish these performance measures and (2) an unknown time frame for evaluating these performance measures. Some performance measures can be assessed quickly, such as those associated with hydrology and nutrient uptake. Some performance measures, such as changes in soil surface elevation and forest structural integrity, could take longer to assess. Once performance measures are assessed across different time scales, however, adjustments to operations of the Mississippi River reintroduction into Maurepas Swamp can be swift. The proposed performance measures are ideal targets, mostly without specific consideration of practical, operational constraints. The measures are intended to be the basis by which adaptive management of the diversion structures can be evaluated. The measures are defined without regard to current conditions so that project success can be evaluated on net outcomes rather than specific change from existing conditions. We expect that the Mississippi River reintroduction into Maurepas Swamp will slow degradation and extend the life of the swamp for decades to centuries.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175036","collaboration":"Prepared in cooperation with the Coastal Protection and Restoration Authority (CPRA) of Louisiana","usgsCitation":"Krauss, K.W., Shaffer, G.P., Keim, R.F., Chambers, J.L., Wood, W.B., and Hartley, S.B., 2017, Performance measures for a Mississippi River reintroduction into the forested wetlands of Maurepas Swamp: U.S. Geological Survey Scientific Investigations Report 2017–5036, 56 p., https://doi.org/10.3133/sir20175036.","productDescription":"vii, 56 p.","numberOfPages":"68","onlineOnly":"Y","ipdsId":"IP-076437","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":342283,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5036/coverthb.jpg"},{"id":342284,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5036/sir20175036.pdf","text":"Report","size":"4.92 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5036"}],"country":"United States","state":"Louisiana","otherGeospatial":"Maurepas Swamp","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.71496963500977,\n 30.130430010985794\n ],\n [\n -90.70793151855469,\n 30.127757562686426\n ],\n [\n -90.6976318359375,\n 30.12538199235671\n ],\n [\n -90.68424224853516,\n 30.123006364871873\n ],\n [\n -90.68183898925781,\n 30.123451799378774\n ],\n [\n -90.68355560302734,\n 30.11587913951386\n ],\n [\n -90.68441390991211,\n 30.104444807954295\n ],\n [\n -90.68424224853516,\n 30.099841002166382\n ],\n [\n -90.68510055541992,\n 30.093157676702447\n ],\n [\n -90.67153930664062,\n 30.093900290733625\n ],\n [\n -90.65969467163086,\n 30.09523698193298\n ],\n [\n -90.64424514770508,\n 30.0964251367153\n ],\n [\n -90.626220703125,\n 30.097167726202468\n ],\n [\n -90.59738159179686,\n 30.096573655059025\n ],\n [\n -90.5877685546875,\n 30.097167726202468\n ],\n [\n -90.58176040649414,\n 30.097167726202468\n ],\n [\n -90.58176040649414,\n 30.10132612423917\n ],\n [\n -90.58382034301758,\n 30.10592986084689\n ],\n [\n -90.58691024780273,\n 30.109642395437696\n ],\n [\n -90.59154510498047,\n 30.114988200180996\n ],\n [\n -90.57283401489258,\n 30.113651776114697\n ],\n [\n -90.54639816284178,\n 30.111127370215993\n ],\n [\n -90.54759979248047,\n 30.132953923508076\n ],\n [\n -90.53352355957031,\n 30.133993162848824\n ],\n [\n -90.5192756652832,\n 30.133250850150496\n ],\n [\n -90.51017761230469,\n 30.132508531869735\n ],\n [\n -90.49713134765625,\n 30.13280545985193\n ],\n [\n -90.48768997192383,\n 30.133696238439384\n ],\n [\n -90.48906326293945,\n 30.14349427231131\n ],\n [\n -90.49163818359375,\n 30.150025754414877\n ],\n [\n -90.49610137939452,\n 30.15240073160066\n ],\n [\n -90.50090789794922,\n 30.158189498907962\n ],\n [\n -90.5024528503418,\n 30.163384257179096\n ],\n [\n -90.50176620483398,\n 30.16768827811798\n ],\n [\n -90.49936294555663,\n 30.172140515818256\n ],\n [\n -90.50485610961914,\n 30.171546895744946\n ],\n [\n -90.50897598266602,\n 30.170953272096156\n ],\n [\n -90.51034927368164,\n 30.17139849016794\n ],\n [\n -90.51292419433594,\n 30.17228892027792\n ],\n [\n -90.51721572875977,\n 30.171250084367482\n ],\n [\n -90.52167892456055,\n 30.17050805201317\n ],\n [\n -90.52906036376953,\n 30.17050805201317\n ],\n [\n -90.54107666015625,\n 30.169766014072298\n ],\n [\n -90.55103302001953,\n 30.16961760581373\n ],\n [\n -90.56098937988281,\n 30.171101678343547\n ],\n [\n -90.57334899902342,\n 30.174811761900497\n ],\n [\n -90.58399200439453,\n 30.181637950691677\n ],\n [\n -90.58982849121092,\n 30.188760426055236\n ],\n [\n -90.59394836425781,\n 30.196772595195785\n ],\n [\n -90.59463500976562,\n 30.202262038402417\n ],\n [\n -90.5958366394043,\n 30.211756568810145\n ],\n [\n -90.5961799621582,\n 30.21368503337007\n ],\n [\n -90.59858322143555,\n 30.216948502671475\n ],\n [\n -90.6039047241211,\n 30.216948502671475\n ],\n [\n -90.60785293579102,\n 30.215613460132406\n ],\n [\n -90.61162948608398,\n 30.21413005828547\n ],\n [\n -90.61437606811523,\n 30.21620681460864\n ],\n [\n -90.61609268188477,\n 30.218283527093387\n ],\n [\n -90.61969757080078,\n 30.219321866895765\n ],\n [\n -90.62467575073241,\n 30.219618533397615\n ],\n [\n -90.62965393066406,\n 30.220805190457803\n ],\n [\n -90.63411712646484,\n 30.222436820540278\n ],\n [\n -90.63549041748047,\n 30.227776511561217\n ],\n [\n -90.64115524291992,\n 30.229111389015017\n ],\n [\n -90.6456184387207,\n 30.23133614450099\n ],\n [\n -90.64836502075195,\n 30.233115912645207\n ],\n [\n -90.65128326416014,\n 30.230594564932193\n ],\n [\n -90.65385818481445,\n 30.22822147272596\n ],\n [\n -90.66003799438477,\n 30.226293293137275\n ],\n [\n -90.66278457641602,\n 30.22169517385814\n ],\n [\n -90.66364288330078,\n 30.218580196726734\n ],\n [\n -90.66261291503906,\n 30.21546512095419\n ],\n [\n -90.66158294677734,\n 30.212794977500614\n ],\n [\n -90.66312789916991,\n 30.21220160244795\n ],\n [\n -90.66673278808594,\n 30.214871762004673\n ],\n [\n -90.66930770874023,\n 30.21546512095419\n ],\n [\n -90.67205429077148,\n 30.21383337523219\n ],\n [\n -90.67617416381836,\n 30.2105698026023\n ],\n [\n -90.67874908447266,\n 30.207157770028097\n ],\n [\n -90.67651748657227,\n 30.20285547338714\n ],\n [\n -90.67342758178711,\n 30.197662795968995\n ],\n [\n -90.67462921142577,\n 30.19692096255026\n ],\n [\n -90.67737579345703,\n 30.19573401745418\n ],\n [\n -90.67720413208008,\n 30.192914965504624\n ],\n [\n -90.67840576171875,\n 30.1909860939853\n ],\n [\n -90.68098068237305,\n 30.190095832849106\n ],\n [\n -90.68235397338867,\n 30.186386324824365\n ],\n [\n -90.68389892578125,\n 30.18208312048974\n ],\n [\n -90.6866455078125,\n 30.179560465036428\n ],\n [\n -90.68870544433594,\n 30.177186142075502\n ],\n [\n -90.69231033325195,\n 30.17510856255117\n ],\n [\n -90.69454193115234,\n 30.174514960355882\n ],\n [\n -90.69437026977538,\n 30.17303093922411\n ],\n [\n -90.69282531738281,\n 30.171101678343547\n ],\n [\n -90.692138671875,\n 30.168875561169088\n ],\n [\n -90.69402694702148,\n 30.167094631229592\n ],\n [\n -90.69711685180664,\n 30.166797806444716\n ],\n [\n -90.70003509521484,\n 30.166352567591545\n ],\n [\n -90.7034683227539,\n 30.165016838966146\n ],\n [\n -90.70672988891602,\n 30.164126343161097\n ],\n [\n -90.70672988891602,\n 30.162048488335433\n ],\n [\n -90.70398330688477,\n 30.160564279505948\n ],\n [\n -90.70140838623047,\n 30.159228472457105\n ],\n [\n -90.70003509521484,\n 30.15774422117864\n ],\n [\n -90.70123672485352,\n 30.156705231991012\n ],\n [\n -90.70484161376953,\n 30.155369372664897\n ],\n [\n -90.70758819580078,\n 30.154478789727992\n ],\n [\n -90.70758819580078,\n 30.152994466961903\n ],\n [\n -90.70518493652344,\n 30.14928356231718\n ],\n [\n -90.70535659790039,\n 30.147799161369214\n ],\n [\n -90.70930480957031,\n 30.148096043345703\n ],\n [\n -90.71102142333984,\n 30.147799161369214\n ],\n [\n -90.71033477783203,\n 30.14616629452818\n ],\n [\n -90.7089614868164,\n 30.143642719888483\n ],\n [\n -90.70999145507812,\n 30.14171288396483\n ],\n [\n -90.7115364074707,\n 30.139486103306538\n ],\n [\n -90.70964813232422,\n 30.136516984265466\n ],\n [\n -90.70810317993164,\n 30.133696238439384\n ],\n [\n -90.7082748413086,\n 30.131320811009267\n ],\n [\n -90.71102142333984,\n 30.131320811009267\n ],\n [\n -90.71376800537108,\n 30.13102387856127\n ],\n [\n -90.71496963500977,\n 30.130430010985794\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
700 Cajundome Blvd.
Lafayette, LA 70506
Persistent motion of the south flank of Kīlauea Volcano, Hawai'i, has been known for several decades, but has only recently been identified at other large basaltic volcanoes—namely Piton de la Fournaise (La Réunion) and Etna (Sicily)—thanks to the advent of space geodetic techniques. Nevertheless, understanding of long-term flank instability is based largely on the example of Kīlauea, despite the large differences in the manifestations and mechanisms of the process when viewed through a comparative lens. For example, the rate of flank motion at Kīlauea is several times that of Etna and Piton de la Fournaise and is accommodated on a slip plane several km deeper than is probably present at the other two volcanoes. Gravitational spreading also appears to be the dominant driving force at Kīlauea, given the long-term steady motion of the volcano's south flank regardless of eruptive/intrusive activity, whereas magmatic activity plays a larger role in flank deformation at Etna and Piton de la Fournaise. Kīlauea and Etna, however, are both characterized by heavily faulted flanks, while Piton de la Fournaise shows little evidence for flank faulting. A helpful means of understanding the spectrum of persistent flank motion at large basaltic edifices may be through a framework defined on one hand by magmatic activity (which encompasses both magma supply and edifice size), and on the other hand by the structural setting of the volcano (especially the characteristics of the subvolcanic basement or subhorizontal intravolcanic weak zones). A volcano's size and magmatic activity will dictate the extent to which gravitational and magmatic forces can drive motion of an unstable flank (and possibly the level of faulting of that flank), while the volcano's structural setting governs whether or not a plane of weakness exists beneath or within the edifice and can facilitate flank slip. Considering persistent flank instability using this conceptual model is an alternative to using a single volcano as a “type example”—especially given that the example is usually Kīlauea, which defines an extreme end of the spectrum—and can provide a basis for understanding why flank motion may or may not exist on other large basaltic volcanoes worldwide.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2017.05.004","usgsCitation":"Poland, M.P., Peltier, A., Bonaforte, A., and Puglisi, G., 2017, The spectrum of persistent volcanic flank instability: A review and proposed framework based on Kīlauea, Piton de la Fournaise, and Etna: Journal of Volcanology and Geothermal Research, v. 339, p. 63-80, https://doi.org/10.1016/j.jvolgeores.2017.05.004.","productDescription":"18 p.","startPage":"63","endPage":"80","ipdsId":"IP-083995","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":469761,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://insu.hal.science/insu-03748853","text":"Publisher Index Page"},{"id":342321,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"France, Italy, United States","otherGeospatial":"Etna, Kīlauea Volcano, Piton de la Fournaise","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -154.883333,\n 19.55\n ],\n [\n -155.5,\n 19.55\n ],\n [\n -155.5,\n 19.116667\n ],\n [\n -154.883333,\n 19.116667\n ],\n [\n -154.883333,\n 19.55\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 55.666667,\n -21.152778\n ],\n [\n 55.666667,\n -21.319444\n ],\n [\n 55.836111,\n -21.319444\n ],\n [\n 55.836111,\n -21.152778\n ],\n [\n 55.666667,\n -21.152778\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 14.766667,\n 37.916667\n ],\n [\n 15.233333,\n 37.916667\n ],\n [\n 15.233333,\n 37.483333\n ],\n [\n 14.766667,\n 37.483333\n ],\n [\n 14.766667,\n 37.916667\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"339","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"593ad6dee4b0764e6c602139","contributors":{"authors":[{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":146118,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":697683,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peltier, Aline","contributorId":149410,"corporation":false,"usgs":false,"family":"Peltier","given":"Aline","email":"","affiliations":[],"preferred":false,"id":697684,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bonaforte, Alessandro","contributorId":192762,"corporation":false,"usgs":false,"family":"Bonaforte","given":"Alessandro","email":"","affiliations":[],"preferred":false,"id":697685,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Puglisi, Giuseppe","contributorId":192763,"corporation":false,"usgs":false,"family":"Puglisi","given":"Giuseppe","email":"","affiliations":[],"preferred":false,"id":697686,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70188425,"text":"70188425 - 2017 - The added value of time-variable microgravimetry to the understanding of how volcanoes work","interactions":[],"lastModifiedDate":"2018-10-25T16:02:45","indexId":"70188425","displayToPublicDate":"2017-06-09T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1431,"text":"Earth-Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"The added value of time-variable microgravimetry to the understanding of how volcanoes work","docAbstract":"During the past few decades, time-variable volcano gravimetry has shown great potential for imaging subsurface processes at active volcanoes (including some processes that might otherwise remain “hidden”), especially when combined with other methods (e.g., ground deformation, seismicity, and gas emissions). By supplying information on changes in the distribution of bulk mass over time, gravimetry can provide information regarding processes such as magma accumulation in void space, gas segregation at shallow depths, and mechanisms driving volcanic uplift and subsidence.\n\nDespite its potential, time-variable volcano gravimetry is an underexploited method, not widely adopted by volcano researchers or observatories. The cost of instrumentation and the difficulty in using it under harsh environmental conditions is a significant impediment to the exploitation of gravimetry at many volcanoes. In addition, retrieving useful information from gravity changes in noisy volcanic environments is a major challenge. While these difficulties are not trivial, neither are they insurmountable; indeed, creative efforts in a variety of volcanic settings highlight the value of time-variable gravimetry for understanding hazards as well as revealing fundamental insights into how volcanoes work.\n\nBuilding on previous work, we provide a comprehensive review of time-variable volcano gravimetry, including discussions of instrumentation, modeling and analysis techniques, and case studies that emphasize what can be learned from campaign, continuous, and hybrid gravity observations. We are hopeful that this exploration of time-variable volcano gravimetry will excite more scientists about the potential of the method, spurring further application, development, and innovation.","language":"English","publisher":"Elsevier","doi":"10.1016/j.earscirev.2017.04.014","usgsCitation":"Carbone, D., Poland, M.P., Greco, F., and Diament, M., 2017, The added value of time-variable microgravimetry to the understanding of how volcanoes work: Earth-Science Reviews, v. 169, p. 146-179, https://doi.org/10.1016/j.earscirev.2017.04.014.","productDescription":"34 p. ","startPage":"146","endPage":"179","ipdsId":"IP-079219","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":342326,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Earth","volume":"169","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"593ad6dfe4b0764e6c60213b","contributors":{"authors":[{"text":"Carbone, Daniele","contributorId":124561,"corporation":false,"usgs":false,"family":"Carbone","given":"Daniele","email":"","affiliations":[{"id":5113,"text":"INGV","active":true,"usgs":false}],"preferred":false,"id":697680,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":146118,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":697679,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Greco, Filippo","contributorId":192761,"corporation":false,"usgs":false,"family":"Greco","given":"Filippo","email":"","affiliations":[],"preferred":false,"id":697681,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Diament, Michel","contributorId":190642,"corporation":false,"usgs":false,"family":"Diament","given":"Michel","email":"","affiliations":[],"preferred":false,"id":697682,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70188416,"text":"70188416 - 2017 - Frictional strength of wet and dry montmorillonite","interactions":[],"lastModifiedDate":"2017-06-14T11:55:32","indexId":"70188416","displayToPublicDate":"2017-06-08T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Frictional strength of wet and dry montmorillonite","docAbstract":"Montmorillonite is a common mineral in fault zones, and its low strength relative to other common gouge minerals is important in many models of fault rheology. However, the coefficient of friction, μ, varies with degree of saturation and is not well constrained in the literature due to the difficulty of establishing fully drained or fully dried states in the laboratory. We measured μ of both saturated and oven-dried montmorillonite at normal stresses up to 700 MPa. Care was taken to shear saturated samples slowly enough to avoid pore fluid overpressure. For saturated samples, μ increased from 0.10 to 0.28 with applied effective normal stress, while for dry samples μ decreased from 0.78 to 0.45. The steady state rate dependence of friction, (a − b), was positive, promoting stable sliding. The wide disparity in reported frictional strengths can be attributed to experimental procedures that promote differing degrees of partial saturation or overpressured pore fluid conditions.
","language":"English","publisher":"AGU","doi":"10.1002/2016JB013658","usgsCitation":"Morrow, C.A., Moore, D.E., and Lockner, D.A., 2017, Frictional strength of wet and dry montmorillonite: Journal of Geophysical Research, v. 122, no. 5, p. 3392-3409, https://doi.org/10.1002/2016JB013658.","productDescription":"18 p.","startPage":"3392","endPage":"3409","ipdsId":"IP-079028","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":342317,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"122","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-06","publicationStatus":"PW","scienceBaseUri":"593ad6e1e4b0764e6c602145","contributors":{"authors":[{"text":"Morrow, Carolyn A. 0000-0003-3500-6181 cmorrow@usgs.gov","orcid":"https://orcid.org/0000-0003-3500-6181","contributorId":3206,"corporation":false,"usgs":true,"family":"Morrow","given":"Carolyn","email":"cmorrow@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":697651,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moore, Diane E. 0000-0002-8641-1075 dmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-8641-1075","contributorId":2704,"corporation":false,"usgs":true,"family":"Moore","given":"Diane","email":"dmoore@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":697653,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lockner, David A. 0000-0001-8630-6833 dlockner@usgs.gov","orcid":"https://orcid.org/0000-0001-8630-6833","contributorId":567,"corporation":false,"usgs":true,"family":"Lockner","given":"David","email":"dlockner@usgs.gov","middleInitial":"A.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":697652,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70188400,"text":"70188400 - 2017 - An updated geospatial liquefaction model for global application","interactions":[],"lastModifiedDate":"2017-06-08T10:30:00","indexId":"70188400","displayToPublicDate":"2017-06-08T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"An updated geospatial liquefaction model for global application","docAbstract":"We present an updated geospatial approach to estimation of earthquake-induced liquefaction from globally available geospatial proxies. Our previous iteration of the geospatial liquefaction model was based on mapped liquefaction surface effects from four earthquakes in Christchurch, New Zealand, and Kobe, Japan, paired with geospatial explanatory variables including slope-derived VS30, compound topographic index, and magnitude-adjusted peak ground acceleration from ShakeMap. The updated geospatial liquefaction model presented herein improves the performance and the generality of the model. The updates include (1) expanding the liquefaction database to 27 earthquake events across 6 countries, (2) addressing the sampling of nonliquefaction for incomplete liquefaction inventories, (3) testing interaction effects between explanatory variables, and (4) overall improving model performance. While we test 14 geospatial proxies for soil density and soil saturation, the most promising geospatial parameters are slope-derived VS30, modeled water table depth, distance to coast, distance to river, distance to closest water body, and precipitation. We found that peak ground velocity (PGV) performs better than peak ground acceleration (PGA) as the shaking intensity parameter. We present two models which offer improved performance over prior models. We evaluate model performance using the area under the curve under the Receiver Operating Characteristic (ROC) curve (AUC) and the Brier score. The best-performing model in a coastal setting uses distance to coast but is problematic for regions away from the coast. The second best model, using PGV, VS30, water table depth, distance to closest water body, and precipitation, performs better in noncoastal regions and thus is the model we recommend for global implementation.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120160198","usgsCitation":"Zhu, J., Baise, L.G., and Thompson, E.M., 2017, An updated geospatial liquefaction model for global application: Bulletin of the Seismological Society of America, v. 107, no. 3, p. 1365-1385, https://doi.org/10.1785/0120160198.","productDescription":"21 p. ","startPage":"1365","endPage":"1385","ipdsId":"IP-081714","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":342287,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Japan, New Zealand","city":"Christchurch, Kobe","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 172.8053283691406,\n -43.57939602461447\n ],\n [\n 172.73529052734375,\n -43.39007990915452\n ],\n [\n 172.65289306640625,\n -43.40205426790564\n ],\n [\n 172.5457763671875,\n -43.4509250075837\n ],\n [\n 172.51007080078122,\n -43.500752435690394\n ],\n [\n 172.4798583984375,\n -43.5515340832395\n ],\n [\n 172.48809814453125,\n -43.593322162687436\n ],\n [\n 172.52105712890625,\n -43.62712937016884\n ],\n [\n 172.58834838867188,\n -43.65098183989868\n ],\n [\n 172.628173828125,\n -43.659924074789096\n ],\n [\n 172.8053283691406,\n -43.57939602461447\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 135.10025024414062,\n 34.64394177616416\n ],\n [\n 135.1318359375,\n 34.6241677899049\n ],\n [\n 135.1819610595703,\n 34.61456158160819\n ],\n [\n 135.24032592773438,\n 34.61456158160819\n ],\n [\n 135.30555725097653,\n 34.62699293367839\n ],\n [\n 135.3206634521484,\n 34.64733112904415\n ],\n [\n 135.3289031982422,\n 34.68573411017608\n ],\n [\n 135.31997680664062,\n 34.722426197808446\n ],\n [\n 135.31173706054688,\n 34.74894726028228\n ],\n [\n 135.2849578857422,\n 34.75853788866992\n ],\n [\n 135.24238586425778,\n 34.75458894128615\n ],\n [\n 135.1922607421875,\n 34.742740966060076\n ],\n [\n 135.14076232910156,\n 34.72355492704221\n ],\n [\n 135.10025024414062,\n 34.64394177616416\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"107","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-02","publicationStatus":"PW","scienceBaseUri":"593ad6e1e4b0764e6c602149","contributors":{"authors":[{"text":"Zhu, Jing","contributorId":152048,"corporation":false,"usgs":false,"family":"Zhu","given":"Jing","email":"","affiliations":[{"id":6936,"text":"Tufts University","active":true,"usgs":false}],"preferred":false,"id":697589,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baise, Laurie G.","contributorId":127395,"corporation":false,"usgs":false,"family":"Baise","given":"Laurie","email":"","middleInitial":"G.","affiliations":[{"id":6936,"text":"Tufts University","active":true,"usgs":false}],"preferred":false,"id":697590,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":146592,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":697591,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70188407,"text":"70188407 - 2017 - Collecting a better water-quality sample: Reducing vertical stratification bias in open and closed channels","interactions":[],"lastModifiedDate":"2017-06-08T15:03:15","indexId":"70188407","displayToPublicDate":"2017-06-08T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Collecting a better water-quality sample: Reducing vertical stratification bias in open and closed channels","docAbstract":"Collection of water-quality samples that accurately characterize average particle concentrations and distributions in channels can be complicated by large sources of variability. The U.S. Geological Survey (USGS) developed a fully automated Depth-Integrated Sample Arm (DISA) as a way to reduce bias and improve accuracy in water-quality concentration data. The DISA was designed to integrate with existing autosampler configurations commonly used for the collection of water-quality samples in vertical profile thereby providing a better representation of average suspended sediment and sediment-associated pollutant concentrations and distributions than traditional fixed-point samplers. In controlled laboratory experiments, known concentrations of suspended sediment ranging from 596 to 1,189 mg/L were injected into a 3 foot diameter closed channel (circular pipe) with regulated flows ranging from 1.4 to 27.8 ft3 /s. Median suspended sediment concentrations in water-quality samples collected using the DISA were within 7 percent of the known, injected value compared to 96 percent for traditional fixed-point samplers. Field evaluation of this technology in open channel fluvial systems showed median differences between paired DISA and fixed-point samples to be within 3 percent. The range of particle size measured in the open channel was generally that of clay and silt. Differences between the concentration and distribution measured between the two sampler configurations could potentially be much larger in open channels that transport larger particles, such as sand.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 5th Federal Interagency Hydrologic Modeling Conference and the 10th Federal Interagency Sedimentation Conference","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Joint Federal Interagency Conference 2015","conferenceDate":"April 19-23, 2015","conferenceLocation":"Reno, NV","language":"English","publisher":"Department of Interior","publisherLocation":"Reston, VA","usgsCitation":"Selbig, W.R., 2017, Collecting a better water-quality sample: Reducing vertical stratification bias in open and closed channels, in Proceedings of the 5th Federal Interagency Hydrologic Modeling Conference and the 10th Federal Interagency Sedimentation Conference, Reno, NV, April 19-23, 2015, 11 p.","productDescription":"11 p.","ipdsId":"IP-060694","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":342312,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":342311,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://acwi.gov/sos/pubs/3rdJFIC/"}],"publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"593ad6e1e4b0764e6c602147","contributors":{"authors":[{"text":"Selbig, William R. 0000-0003-1403-8280 wrselbig@usgs.gov","orcid":"https://orcid.org/0000-0003-1403-8280","contributorId":877,"corporation":false,"usgs":true,"family":"Selbig","given":"William","email":"wrselbig@usgs.gov","middleInitial":"R.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":697626,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70187489,"text":"sir20175041 - 2017 - Hydrogeologic framework and hydrologic conditions of the Piney Point aquifer in Virginia","interactions":[],"lastModifiedDate":"2017-06-07T14:28:18","indexId":"sir20175041","displayToPublicDate":"2017-06-07T14:15:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5041","title":"Hydrogeologic framework and hydrologic conditions of the Piney Point aquifer in Virginia","docAbstract":"The Piney Point aquifer in Virginia is newly described and delineated as being composed of six geologic units, in a study conducted by the U.S. Geological Survey in cooperation with the Virginia Department of Environmental Quality (VA DEQ). The eastward-dipping geologic units include, in stratigraphically ascending order, the
Identification of geologic units is based on typical sediment lithologies of geologic formations. Fine-grained sediments that compose confining units positioned immediately above and below the Piney Point aquifer are also described.
The Piney Point aquifer is one of several confined aquifers within the Virginia Coastal Plain and includes a highly porous and solution-channeled indurated limestone within the Piney Point Formation from which withdrawals are made. The limestone is relatively continuous laterally across central parts of the Northern Neck, Middle Peninsula, and York-James Peninsula. Other geologic units are of variable extent. The configurations of most of the geologic units are further affected by newly identified faults that are aligned radially from the Chesapeake Bay impact crater and create constrictions or barriers to groundwater flow. Some geologic units are also truncated beneath the lower Rappahannock River by a resurge channel associated with the impact crater.
Groundwater withdrawals from the Piney Point aquifer increased from approximately 1 million gallons per day (Mgal/d) during 1900 to 7.35 Mgal/d during 2004. As a result, a water-level cone of depression in James City and northern York Counties was estimated to be as low as 70 feet (ft) below the National Geodetic Vertical Datum of 1929 (NGVD 29) by 2005. Withdrawals decreased to 5.01 Mgal/d by 2009 as withdrawals were shifted toward other sources, and by 2015 water levels had recovered to approximately 50 ft below NGVD 29.
The mean estimated transmissivity of the Piney Point aquifer in York and James City Counties is 16,300 feet squared per day (ft2/d), but farther north it is only 925 ft2/d. The mean well specific capacity in York and James City Counties is 11.4 gallons per minute per foot (gal/min/ft). Farther north in Virginia, mean specific capacity is only 2.26 gal/min/ft, and in Maryland it is 0.99 gal/min/ft. The northward decrease in specific capacity probably reflects the northward decrease in transmissivity, which results from poor development of the solution-channeled limestone.
An aquifer test in northern York County induced vertical leakage to the solution-channeled limestone from overlying silty sand and a change in response of the aquifer to pumping from a single layer to two layers. Transmissivity of the limestone of approximately 19,800 ft2/d was distinguished from the silty sand of approximately 2,500 ft2/d.
Most of the water in the Piney Point aquifer is slightly alkaline with moderate concentrations primarily of sodium and bicarbonate that are slightly undersaturated with respect to calcite. Iron concentrations are generally less than 0.3 milligrams per liter (mg/L). Mixing of freshwater with seawater has elevated chloride concentrations to the southeast to as much as 7,120 mg/L.
Information on the Piney Point aquifer can benefit water-resource management in siting production wells, predicting likely well yield, and anticipating water-level response to withdrawals. Models that vertically discretize individual geologic units can potentially be used to evaluate groundwater flow in greater detail by representing lateral flow and vertical leakage among the geologic units.
Because groundwater withdrawals are made primarily from the limestone and sand of the Piney Point Formation, the VA DEQ has considered regarding the limestone and sand singly as a regulated aquifer apart from the other geologic units. Under current policy in Virginia, if only the limestone and sand were regarded as a regulated aquifer, a greater amount of drawdown would be allowed than is allowed for the Piney Point aquifer consisting of six geologic units. Some production wells intercept multiple geologic units, and the units can undergo water-level decline and vertical leakage induced by pumping from the limestone and sand. Whether the other geologic units are to be regarded as regulated aquifers is an additional consideration for the VA DEQ.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175041","collaboration":"Prepared in cooperation with the Virginia Department of Environmental Quality","usgsCitation":"McFarland, E.R., 2017, Hydrogeologic framework and hydrologic conditions of the Piney Point aquifer in Virginia: U.S. Geological Survey Scientific Investigations Report 2017–5041, 63 p., 2 pl., and CD-ROM, https://doi.org/10.3133/sir20175041.","productDescription":"Report: vii, 62 p.; 2 Plates: 24 x 36 inches and 36 x 24 inches; Appendixes 1-2; Data Release; Read Me","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-075864","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":342072,"rank":7,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sir/2017/5041/readme.txt","size":"1.27 KB","linkFileType":{"id":2,"text":"txt"}},{"id":342068,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5041/sir20175041_appendix1.xlsx","text":"Appendix 1","size":"36.2 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Borehole Geologic-Unit Top-Surface Altitudes, Piney Point Aquifer, Virginia"},{"id":342066,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5041/coverthb.jpg"},{"id":342069,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5041/sir20175041_appendix2.xlsx","text":"Appendix 2 ","size":"23.1 MB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Aquifer-Component Test data, Piney Point Aquifer, Virginia"},{"id":342071,"rank":6,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5041/sir20175041_plate2.pdf","text":"Plate 2 ","size":"397 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Hydrogeologic Sections A–A’, B–B’, and C–C’ of the Piney Point Aquifer in Virginia"},{"id":342076,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7BV7DV5","text":"USGS data release","description":"USGS data release","linkHelpText":"Hydrogeologic Framework and Hydrologic Conditions of the Piney Point Aquifer in Virginia"},{"id":342067,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5041/sir20175041.pdf","text":"Report","size":"8.09 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5041"},{"id":342070,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5041/sir20175041_plate1.pdf","text":"Plate 1 ","size":"444 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Locations of Boreholes and Extent of Productive Limestone in the Piney Point Aquifer in Virginia"}],"country":"United States","state":"Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.291667,\n 38.291667\n ],\n [\n -76.208333,\n 38.291667\n ],\n [\n -76.208333,\n 37.125\n ],\n [\n -77.291667,\n 37.125\n ],\n [\n -77.291667,\n 38.291667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
Richmond, VA 23228
Drylands occur world-wide and are particularly vulnerable to climate change since dryland ecosystems depend directly on soil water availability that may become increasingly limited as temperatures rise. Climate change will both directly impact soil water availability, and also change plant biomass, with resulting indirect feedbacks on soil moisture. Thus, the net impact of direct and indirect climate change effects on soil moisture requires better understanding.
We used the ecohydrological simulation model SOILWAT at sites from temperate dryland ecosystems around the globe to disentangle the contributions of direct climate change effects and of additional indirect, climate change-induced changes in vegetation on soil water availability. We simulated current and future climate conditions projected by 16 GCMs under RCP 4.5 and RCP 8.5 for the end of the century. We determined shifts in water availability due to climate change alone and due to combined changes of climate and the growth form and biomass of vegetation.
Vegetation change will mostly exacerbate low soil water availability in regions already expected to suffer from negative direct impacts of climate change (with the two RCP scenarios giving us qualitatively similar effects). By contrast, in regions that will likely experience increased water availability due to climate change alone, vegetation changes will counteract these increases due to increased water losses by interception. In only a small minority of locations, climate change induced vegetation changes may lead to a net increase in water availability. These results suggest that changes in vegetation in response to climate change may exacerbate drought conditions and may dampen the effects of increased precipitation, i.e. leading to more ecological droughts despite higher precipitation in some regions. Our results underscore the value of considering indirect effects of climate change on vegetation when assessing future soil moisture conditions in water-limited ecosystems.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.13598","usgsCitation":"Tietjen, B., Schlaepfer, D., Bradford, J.B., Laurenroth, W.K., Hall, S.A., Duniway, M.C., Hochstrasser, T., Jia, G., Munson, S.M., Pyke, D.A., and Wilson, S.D., 2017, Climate change-induced vegetation shifts lead to more ecological droughts despite projected rainfall increases in many global temperate drylands: Global Change Biology, v. 23, no. 7, p. 2743-2754, https://doi.org/10.1111/gcb.13598.","productDescription":"12 p.","startPage":"2743","endPage":"2754","ipdsId":"IP-079913","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":335892,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","issue":"7","noUsgsAuthors":false,"publicationDate":"2017-03-06","publicationStatus":"PW","scienceBaseUri":"58ad5fc2e4b01ccd54f8b521","chorus":{"doi":"10.1111/gcb.13598","url":"http://dx.doi.org/10.1111/gcb.13598","publisher":"Wiley-Blackwell","authors":"Tietjen Britta, Schlaepfer Daniel R., Bradford John B., Lauenroth William K., Hall Sonia A., Duniway Michael C., Hochstrasser Tamara, Jia Gensuo, Munson Seth M., Pyke David A., Wilson Scott D.","journalName":"Global Change Biology","publicationDate":"3/2017","publiclyAccessibleDate":"3/6/2017"},"contributors":{"authors":[{"text":"Tietjen, Britta","contributorId":181517,"corporation":false,"usgs":false,"family":"Tietjen","given":"Britta","email":"","affiliations":[],"preferred":false,"id":670060,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schlaepfer, Daniel R.","contributorId":105189,"corporation":false,"usgs":false,"family":"Schlaepfer","given":"Daniel R.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":670061,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":670062,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Laurenroth, William K.","contributorId":175203,"corporation":false,"usgs":false,"family":"Laurenroth","given":"William","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":670063,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hall, Sonia A.","contributorId":181518,"corporation":false,"usgs":false,"family":"Hall","given":"Sonia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":670064,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":670065,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hochstrasser, Tamara","contributorId":181931,"corporation":false,"usgs":false,"family":"Hochstrasser","given":"Tamara","email":"","affiliations":[{"id":18091,"text":"University College Dublin","active":true,"usgs":false}],"preferred":false,"id":670066,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jia, Gensuo","contributorId":181520,"corporation":false,"usgs":false,"family":"Jia","given":"Gensuo","email":"","affiliations":[],"preferred":false,"id":670067,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":670068,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Pyke, David A. 0000-0002-4578-8335 david_a_pyke@usgs.gov","orcid":"https://orcid.org/0000-0002-4578-8335","contributorId":3118,"corporation":false,"usgs":true,"family":"Pyke","given":"David","email":"david_a_pyke@usgs.gov","middleInitial":"A.","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":670069,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Wilson, Scott D.","contributorId":181519,"corporation":false,"usgs":false,"family":"Wilson","given":"Scott","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":670070,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70188372,"text":"70188372 - 2017 - Nest-site selection and nest success of an Arctic-breeding passerine, Smith's Longspur, in a changing climate","interactions":[],"lastModifiedDate":"2017-06-07T13:52:08","indexId":"70188372","displayToPublicDate":"2017-06-07T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3551,"text":"The Condor","active":true,"publicationSubtype":{"id":10}},"title":"Nest-site selection and nest success of an Arctic-breeding passerine, Smith's Longspur, in a changing climate","docAbstract":"Despite changes in shrub cover and weather patterns associated with climate change in the Arctic, little is known about the breeding requirements of most passerines tied to northern regions. We investigated the nesting biology and nest habitat characteristics of Smith's Longspurs (Calcarius pictus) in 2 study areas in the Brooks Range of Alaska, USA. First, we examined variation in nesting phenology in relation to local temperatures. We then characterized nesting habitat and analyzed nest-site selection for a subset of nests (n = 86) in comparison with paired random points. Finally, we estimated the daily survival rate of 257 nests found in 2007–2013 with respect to both habitat characteristics and weather variables. Nest initiation was delayed in years with snow events, heavy rain, and freezing temperatures early in the breeding season. Nests were typically found in open, low-shrub tundra, and never among tall shrubs (mean shrub height at nests = 26.8 ± 6.7 cm). We observed weak nest-site selection patterns. Considering the similarity between nest sites and paired random points, coupled with the unique social mating system of Smith's Longspurs, we suggest that habitat selection may occur at the neighborhood scale and not at the nest-site scale. The best approximating model explaining nest survival suggested a positive relationship with the numbers of days above 21°C that an individual nest experienced; there was little support for models containing habitat variables. The daily nest survival rate was high (0.972–0.982) compared with that of most passerines in forested or grassland habitats, but similar to that of passerines nesting on tundra. Considering their high nesting success and ability to delay nest initiation during inclement weather, Smith's Longspurs may be resilient to predicted changes in weather regimes on the breeding grounds. Thus, the greatest threat to breeding Smith's Longspurs associated with climate change may be the loss of low-shrub habitat types, which could significantly change the characteristics of breeding areas.
","language":"English","publisher":"American Ornithological Society","doi":"10.1650/CONDOR-16-87.1","usgsCitation":"McFarland, H.R., Kendall, S.J., and Powell, A., 2017, Nest-site selection and nest success of an Arctic-breeding passerine, Smith's Longspur, in a changing climate: The Condor, v. 119, no. 1, p. 85-97, https://doi.org/10.1650/CONDOR-16-87.1.","productDescription":"13 p.","startPage":"85","endPage":"97","ipdsId":"IP-066082","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":469763,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1650/condor-16-87.1","text":"Publisher Index Page"},{"id":342247,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Atigun Gorge, Slope Mountain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -149.42779541015625,\n 68.38754917350626\n ],\n [\n -149.32411193847656,\n 68.38754917350626\n ],\n [\n -149.32411193847656,\n 68.42621140720802\n ],\n [\n -149.42779541015625,\n 68.42621140720802\n ],\n [\n -149.42779541015625,\n 68.38754917350626\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -149.26025390624997,\n 68.24954858146121\n ],\n [\n -149.15725708007812,\n 68.24954858146121\n ],\n [\n -149.15725708007812,\n 68.28895380229444\n ],\n [\n -149.26025390624997,\n 68.28895380229444\n ],\n [\n -149.26025390624997,\n 68.24954858146121\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"119","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"593910a9e4b0764e6c5e8846","contributors":{"authors":[{"text":"McFarland, Heather R.","contributorId":192723,"corporation":false,"usgs":false,"family":"McFarland","given":"Heather","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":697503,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kendall, Steve J. 0000-0002-9290-5629","orcid":"https://orcid.org/0000-0002-9290-5629","contributorId":169663,"corporation":false,"usgs":false,"family":"Kendall","given":"Steve","email":"","middleInitial":"J.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":697504,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Powell, Abby 0000-0002-9783-134X abby_powell@usgs.gov","orcid":"https://orcid.org/0000-0002-9783-134X","contributorId":176843,"corporation":false,"usgs":true,"family":"Powell","given":"Abby","email":"abby_powell@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":697441,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70189162,"text":"70189162 - 2017 - Synthesis centers as critical research infrastructure","interactions":[],"lastModifiedDate":"2018-02-13T14:43:53","indexId":"70189162","displayToPublicDate":"2017-06-07T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":997,"text":"BioScience","active":true,"publicationSubtype":{"id":10}},"title":"Synthesis centers as critical research infrastructure","docAbstract":"Demand for the opportunity to participate in a synthesis-center activity has increased in the years since the US National Science Foundation (NSF)–funded National Center for Ecological Analysis and Synthesis (NCEAS) opened its doors in 1995 and as more scientists across a diversity of scientific disciplines have become aware of what synthesis centers provide. The NSF has funded four synthesis centers, and more than a dozen new synthesis centers have been established around the world, some following the NSF model and others following different models suited to their national funding environment (http://synthesis-consortium.org).
Scientific synthesis integrates diverse data and knowledge to increase the scope and applicability of results and yield novel insights or explanations within and across disciplines (Pickett et al. 2007, Carpenter et al. 2009). The demand for synthesis comes from the pressing societal need to address grand challenges related to global change and other issues that cut across multiple societal sectors and disciplines and from recognition that substantial added scientific value can be achieved through the synthesis-based analysis of existing data. Demand also comes from groups of scientists who see exciting opportunities to generate new knowledge from interdisciplinary and transdisciplinary collaboration, often capitalizing on the increasingly large volume and variety of available data (Kelling et al. 2009, Bishop et al. 2014, Specht et al. 2015b). The ever-changing nature of societal challenges and the availability of data with which to address them suggest there will be an expanding need for synthesis.
However, we are now entering a phase in which government support for some existing synthesis centers has ended or will be ending soon, forcing those centers to close or develop new operational models, approaches, and funding streams. We argue here that synthesis centers play such a unique role in science that continued long-term public investment to maximize benefits to science and society is justified. In particular, we argue that synthesis centers represent community infrastructure more akin to research vessels than to term-funded centers of science and technology (e.g., NSF Science and Technology Centers). Through our experience running synthesis centers and, in some cases, developing postfederal funding models, we offer our perspective on the purpose and value of synthesis centers. We present case studies of different outcomes of transition plans and argue for a fundamental shift in the conception of synthesis science and the strategic funding of these centers by government funding agencies.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/biosci/bix053","usgsCitation":"Baron, J., Specht, A., Garnier, E., Bishop, P., Campbell, C.A., Davis, F., Fady, B., Field, D., Gross, L.J., Guru, S.M., Halpern, B., Hampton, S.E., Leavitt, P.R., Meagher, T.R., Ometto, J., Parker, J.N., Price, R., Rawson, C.H., Rodrigo, A., Sheble, L.A., and Winter, M., 2017, Synthesis centers as critical research infrastructure: BioScience, v. 67, no. 8, p. 750-759, https://doi.org/10.1093/biosci/bix053.","productDescription":"10 p. ","startPage":"750","endPage":"759","ipdsId":"IP-084553","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":469767,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/biosci/bix053","text":"Publisher Index Page"},{"id":343281,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"67","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-07","publicationStatus":"PW","scienceBaseUri":"595ca913e4b0d1f9f054ca12","contributors":{"authors":[{"text":"Baron, Jill 0000-0002-5902-6251 jill_baron@usgs.gov","orcid":"https://orcid.org/0000-0002-5902-6251","contributorId":194124,"corporation":false,"usgs":true,"family":"Baron","given":"Jill","email":"jill_baron@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":703286,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Specht, Alison","contributorId":178726,"corporation":false,"usgs":false,"family":"Specht","given":"Alison","email":"","affiliations":[],"preferred":false,"id":703299,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Garnier, Eric","contributorId":194148,"corporation":false,"usgs":false,"family":"Garnier","given":"Eric","email":"","affiliations":[],"preferred":false,"id":703300,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bishop, Pamela","contributorId":178724,"corporation":false,"usgs":false,"family":"Bishop","given":"Pamela","email":"","affiliations":[],"preferred":false,"id":703301,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Campbell, C. Andrew","contributorId":194149,"corporation":false,"usgs":false,"family":"Campbell","given":"C.","email":"","middleInitial":"Andrew","affiliations":[],"preferred":false,"id":703302,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Davis, Frank W.","contributorId":70273,"corporation":false,"usgs":true,"family":"Davis","given":"Frank W.","affiliations":[],"preferred":false,"id":703303,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fady, Bruno","contributorId":194150,"corporation":false,"usgs":false,"family":"Fady","given":"Bruno","email":"","affiliations":[],"preferred":false,"id":703304,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Field, Dawn","contributorId":194151,"corporation":false,"usgs":false,"family":"Field","given":"Dawn","email":"","affiliations":[],"preferred":false,"id":703305,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gross, Louis J.","contributorId":56705,"corporation":false,"usgs":true,"family":"Gross","given":"Louis","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":703306,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Guru, Siddeswara M.","contributorId":194152,"corporation":false,"usgs":false,"family":"Guru","given":"Siddeswara","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":703307,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Halpern, Benjamin S","contributorId":178719,"corporation":false,"usgs":false,"family":"Halpern","given":"Benjamin S","affiliations":[],"preferred":false,"id":703308,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Hampton, Stephanie E.","contributorId":178718,"corporation":false,"usgs":false,"family":"Hampton","given":"Stephanie","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":703309,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Leavitt, Peter R.","contributorId":173070,"corporation":false,"usgs":false,"family":"Leavitt","given":"Peter","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":703310,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Meagher, Thomas R.","contributorId":178725,"corporation":false,"usgs":false,"family":"Meagher","given":"Thomas","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":703311,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Ometto, Jean","contributorId":194154,"corporation":false,"usgs":false,"family":"Ometto","given":"Jean","affiliations":[],"preferred":false,"id":703312,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Parker, John N.","contributorId":178722,"corporation":false,"usgs":false,"family":"Parker","given":"John","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":703313,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Price, Richard","contributorId":194155,"corporation":false,"usgs":false,"family":"Price","given":"Richard","email":"","affiliations":[],"preferred":false,"id":703314,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Rawson, Casey H.","contributorId":194156,"corporation":false,"usgs":false,"family":"Rawson","given":"Casey","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":703315,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Rodrigo, Allen","contributorId":194157,"corporation":false,"usgs":false,"family":"Rodrigo","given":"Allen","email":"","affiliations":[],"preferred":false,"id":703316,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Sheble, Laura A.","contributorId":194158,"corporation":false,"usgs":false,"family":"Sheble","given":"Laura","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":703317,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Winter, Marten","contributorId":178720,"corporation":false,"usgs":false,"family":"Winter","given":"Marten","email":"","affiliations":[],"preferred":false,"id":703318,"contributorType":{"id":1,"text":"Authors"},"rank":21}]}} ,{"id":70188355,"text":"70188355 - 2017 - Perturbational and nonperturbational inversion of Rayleigh-wave velocities","interactions":[],"lastModifiedDate":"2017-06-07T08:33:59","indexId":"70188355","displayToPublicDate":"2017-06-07T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1808,"text":"Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Perturbational and nonperturbational inversion of Rayleigh-wave velocities","docAbstract":"The inversion of Rayleigh-wave dispersion curves is a classic geophysical inverse problem. We have developed a set of MATLAB codes that performs forward modeling and inversion of Rayleigh-wave phase or group velocity measurements. We describe two different methods of inversion: a perturbational method based on finite elements and a nonperturbational method based on the recently developed Dix-type relation for Rayleigh waves. In practice, the nonperturbational method can be used to provide a good starting model that can be iteratively improved with the perturbational method. Although the perturbational method is well-known, we solve the forward problem using an eigenvalue/eigenvector solver instead of the conventional approach of root finding. Features of the codes include the ability to handle any mix of phase or group velocity measurements, combinations of modes of any order, the presence of a surface water layer, computation of partial derivatives due to changes in material properties and layer boundaries, and the implementation of an automatic grid of layers that is optimally suited for the depth sensitivity of Rayleigh waves.