Using data from six wild Mojave Desert Tortoise (Gopherus agassizii (Cooper, 1861)) populations, we quantified seasonal differences in immune system measurements and microbial load in the respiratory tract, pertinent to this species’ susceptibility to upper respiratory tract disease. We quantified bacteria-killing activity of blood plasma and differential leukocyte counts to detect trends in temporal variation in immune function. We used centered log-ratio (clr) transformations of leukocyte counts and stress that such transformations are necessary for compositional data. We tested animals for the potential pathogen Pasteurella testudinis Snipes and Biberstein, 1982 with a newly created quantitative polymerase chain reaction (qPCR) assay, as well as for the known respiratory pathogens Mycoplasma agassizii Brown et al., 2001 and Mycoplasma testudineum Brown et al., 2004. We found very little disease and suggest that P. testudinis is a prevalent, commensal microbe in these Mojave Desert Tortoise populations, and its quantification may be a tool to study natural fluctuations in microbe levels in Mojave Desert Tortoise respiratory tracts. Our analyses showed that both the potential for inflammatory responses and microbe levels are highest in the spring for healthy Mojave Desert Tortoises, when lymphocyte levels are lowest. The genetic and statistical tools that we used are easily applicable to other wildlife systems and provide the necessary data to quantify species-wide trends in health and test hypotheses pertinent to host–microbe dynamics.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjz-2018-0255","usgsCitation":"Sandmeier, F.C., Leonard, K.L., Tracy, C., Drake, K.K., Esque, T., Nussear, K.E., and Germano, J., 2019, Tools to understand seasonality in health: quantification of microbe loads and analyses of compositional ecoimmunological data reveal complex patterns in Mojave Desert Tortoise (Gopherus agassizii) populations: Canadian Journal of Zoology, v. 97, no. 9, p. 841-848, https://doi.org/10.1139/cjz-2018-0255.","productDescription":"8 p.","startPage":"841","endPage":"848","ipdsId":"IP-107373","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":501004,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/96565","text":"External Repository"},{"id":380189,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"97","issue":"9","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sandmeier, F. C.","contributorId":244500,"corporation":false,"usgs":false,"family":"Sandmeier","given":"F.","email":"","middleInitial":"C.","affiliations":[{"id":48921,"text":"Colorado State University-Pueblo","active":true,"usgs":false}],"preferred":false,"id":804067,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leonard, K. L.","contributorId":244501,"corporation":false,"usgs":false,"family":"Leonard","given":"K.","email":"","middleInitial":"L.","affiliations":[{"id":48921,"text":"Colorado State University-Pueblo","active":true,"usgs":false}],"preferred":false,"id":804068,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tracy, C. R.","contributorId":244502,"corporation":false,"usgs":false,"family":"Tracy","given":"C. R.","affiliations":[{"id":48922,"text":"University of Nevado, Reno","active":true,"usgs":false}],"preferred":false,"id":804069,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Drake, K. Kristina 0000-0003-0711-7634 kdrake@usgs.gov","orcid":"https://orcid.org/0000-0003-0711-7634","contributorId":3799,"corporation":false,"usgs":true,"family":"Drake","given":"K.","email":"kdrake@usgs.gov","middleInitial":"Kristina","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":804070,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Esque, Todd 0000-0002-4166-6234 tesque@usgs.gov","orcid":"https://orcid.org/0000-0002-4166-6234","contributorId":195896,"corporation":false,"usgs":true,"family":"Esque","given":"Todd","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":804071,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nussear, K. E.","contributorId":204375,"corporation":false,"usgs":false,"family":"Nussear","given":"K.","email":"","middleInitial":"E.","affiliations":[{"id":36924,"text":"Univerisity of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":804072,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Germano, J","contributorId":244503,"corporation":false,"usgs":false,"family":"Germano","given":"J","email":"","affiliations":[{"id":38703,"text":"New Zealand Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":804073,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70210266,"text":"70210266 - 2019 - Sampling the volatile-rich transition zone beneath Bermuda","interactions":[],"lastModifiedDate":"2020-05-27T13:47:43.535415","indexId":"70210266","displayToPublicDate":"2019-05-15T08:39:39","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2840,"text":"Nature","active":true,"publicationSubtype":{"id":10}},"title":"Sampling the volatile-rich transition zone beneath Bermuda","docAbstract":"Intraplate magmatic provinces found away from active plate boundaries, provide direct sampling of the Earth’s mantle composition and heterogeneity. Observed chemical heterogeneities in the mantle are commonly attributed to recycling during subduction1-3, which allows for the addition of volatiles and incompatible elements into the mantle. Although many intraplate volcanoes sample deep mantle reservoirs, possibly at the core-mantle boundary4,5, not all intraplate volcanoes are deep rooted6 and reservoirs in other shallower boundary layers likely participate in magma generation. Here we present new evidence that suggests that Bermuda sampled a previously unknown mantle domain, characterized by silica under-saturated melts that have significant enrichments in incompatible elements and volatiles, and a unique, extreme isotopic signature. Bermuda records the most radiogenic 206Pb/204Pb isotopes ever documented in an ocean basin (19.9-21.7), coupled with low 207Pb/204Pb (15.5-15.6) and relatively invariant Sr, Nd, and Hf isotopes, suggesting that this source must be <650 Ma. We interpret the Bermuda source as a new, transient mantle reservoir that resulted from recycling and storage of incompatible elements and volatiles7-10 in the transition zone, aided by the fractionation of Pb by minerals that are only stable in this boundary layer such as K-Hollandite11-12. Recent recycling and storage of material into the transition zone suggests that this reservoir can only be found in the Atlantic Ocean. Our geodynamic models suggest that this layer was sampled by disturbances related to mantle flow. Seismic studies have shown that recycled materials can be stored in the transition zone13. For the first time we show geochemical evidence that this storage is key in the generation of extreme isotopic domains previously thought to be related only to deep recycling.","language":"English","publisher":"Nature","doi":"10.1038/s41586-019-1183-6","usgsCitation":"Mazza, S.E., Gazel, E., Bizmis, M., Moucha, R., Beguelin, P., Johnson, E.A., McAleer, R.J., and Sobolev, A., 2019, Sampling the volatile-rich transition zone beneath Bermuda: Nature, v. 569, p. 398-403, https://doi.org/10.1038/s41586-019-1183-6.","productDescription":"6 p.","startPage":"398","endPage":"403","ipdsId":"IP-102271","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":375070,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Bermuda","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.673828125,\n 21.69826549685252\n ],\n [\n -59.94140624999999,\n 21.69826549685252\n ],\n [\n -59.94140624999999,\n 35.817813158696616\n ],\n [\n -75.673828125,\n 35.817813158696616\n ],\n [\n -75.673828125,\n 21.69826549685252\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"569","noUsgsAuthors":false,"publicationDate":"2019-05-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Mazza, Sarah E. 0000-0001-8091-1186","orcid":"https://orcid.org/0000-0001-8091-1186","contributorId":198664,"corporation":false,"usgs":false,"family":"Mazza","given":"Sarah","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":789847,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gazel, Esteban","contributorId":192876,"corporation":false,"usgs":false,"family":"Gazel","given":"Esteban","email":"","affiliations":[],"preferred":false,"id":789848,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bizmis, Michael 0000-0002-4611-6928","orcid":"https://orcid.org/0000-0002-4611-6928","contributorId":198666,"corporation":false,"usgs":false,"family":"Bizmis","given":"Michael","email":"","affiliations":[],"preferred":false,"id":789849,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moucha, Robert","contributorId":173102,"corporation":false,"usgs":false,"family":"Moucha","given":"Robert","email":"","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":789850,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beguelin, Paul 0000-0002-1525-2994","orcid":"https://orcid.org/0000-0002-1525-2994","contributorId":224977,"corporation":false,"usgs":false,"family":"Beguelin","given":"Paul","email":"","affiliations":[{"id":37804,"text":"University of South Carolina","active":true,"usgs":false}],"preferred":false,"id":789851,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Elizabeth A. 0000-0001-7244-6122","orcid":"https://orcid.org/0000-0001-7244-6122","contributorId":198665,"corporation":false,"usgs":false,"family":"Johnson","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":789852,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McAleer, Ryan J. 0000-0003-3801-7441 rmcaleer@usgs.gov","orcid":"https://orcid.org/0000-0003-3801-7441","contributorId":215498,"corporation":false,"usgs":true,"family":"McAleer","given":"Ryan","email":"rmcaleer@usgs.gov","middleInitial":"J.","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":789853,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sobolev, Alexander 0000-0002-1997-2032","orcid":"https://orcid.org/0000-0002-1997-2032","contributorId":224978,"corporation":false,"usgs":false,"family":"Sobolev","given":"Alexander","email":"","affiliations":[{"id":41013,"text":"Vernadsky Institute, Russian Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":789854,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70187345,"text":"pp1824G - 2019 - Geology and assessment of undiscovered oil and gas resources of the Northwest Canada Interior Basins Province, Arctic Canada","interactions":[{"subject":{"id":70187345,"text":"pp1824G - 2019 - Geology and assessment of undiscovered oil and gas resources of the Northwest Canada Interior Basins Province, Arctic Canada","indexId":"pp1824G","publicationYear":"2019","noYear":false,"chapter":"G","displayTitle":"Geology and Assessment of Undiscovered Oil and Gas Resources of the Northwest Canada Interior Basins Province, Arctic Canada, 2008","title":"Geology and assessment of undiscovered oil and gas resources of the Northwest Canada Interior Basins Province, Arctic Canada"},"predicate":"IS_PART_OF","object":{"id":70193865,"text":"pp1824 - 2017 - The 2008 Circum-Arctic Resource Appraisal ","indexId":"pp1824","publicationYear":"2017","noYear":false,"title":"The 2008 Circum-Arctic Resource Appraisal "},"id":1}],"isPartOf":{"id":70193865,"text":"pp1824 - 2017 - The 2008 Circum-Arctic Resource Appraisal ","indexId":"pp1824","publicationYear":"2017","noYear":false,"title":"The 2008 Circum-Arctic Resource Appraisal "},"lastModifiedDate":"2024-06-26T14:19:47.208944","indexId":"pp1824G","displayToPublicDate":"2019-05-15T08:24:32","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1824","chapter":"G","displayTitle":"Geology and Assessment of Undiscovered Oil and Gas Resources of the Northwest Canada Interior Basins Province, Arctic Canada, 2008","title":"Geology and assessment of undiscovered oil and gas resources of the Northwest Canada Interior Basins Province, Arctic Canada","docAbstract":"The Northwest Canada Interior Basins Province is bounded by the Mackenzie and Richardson Mountains on the southwest and west, by the Eskimo Lakes Arch on the northwest, and by the erosional limit of Paleozoic strata on the east. It lies within the far northwest part of the Paleozoic continent of Laurentia. During early Paleozoic time, it was part of a passive margin formed when the Neoproterozoic supercontinent Rodinia broke apart. A Cambrian marine transgressive sequence gave way to an evaporitic intrashelf basin, succeeded by a westward-building carbonate bank from Late Cambrian through Middle Devonian time. In Late Devonian and early Carboniferous time, the region was buried by a thick succession of south-prograding clastic strata derived from orogenic belts to the northeast and north. A subsequent period of inactivity and erosion persisted until sedimentation resumed as the opening of the Canada Basin initiated an Early Cretaceous marine transgression over much of the region. Later in Cretaceous time, clastic strata derived from Cordilleran uplifts to the southwest began to prograde north, ending with eventual Laramide uplift and deformation in latest Cretaceous and Paleogene time.
Two petroleum systems are known within the province. A petroleum system in Cambrian to Middle Devonian strata, sourced by alginitic Cambrian shales and sealed by Cambrian evaporites, is proven by modest gas discoveries in the Colville Hills; generation is attributed to burial under the Upper Devonian clastic wedge. An Upper Devonian petroleum system, proven by the presence of the 250-million-barrel Norman Wells field at the southern edge of the province, was sourced by organic-rich shale of the Canol Formation. Generation is similarly inferred to have been driven by burial beneath the Devonian clastic wedge, perhaps augmented locally by additional Cretaceous burial. Potential reservoirs include Devonian reefs and sandstones stratigraphically below and laterally equivalent to the source rocks, as well as overlying sandstones in the clastic wedge. Subordinate source rocks could include organic-rich shales within the clastic wedge.
Principal risks to the lower Paleozoic petroleum system include (1) inadequate reservoir volume for a field of the minimum size and (2) petroleum loss by remigration caused by Laramide deformation. One lower Paleozoic assessment unit (AU) was quantitatively assessed, with estimated resources of 0 to 117 million barrels of oil (MMBO), mean 23 MMBO; and 0 to 1,364 billion cubic feet of gas (BCFG), mean 310 BCFG. The principle risks to the Devonian petroleum system were considered to be (1) lack of preservation due to extensive erosion before the Cretaceous, and (2) inadequate reservoir volume, because the best potential reservoir strata, Devonian reefs, may be absent throughout most of the province owing to either lack of deposition or erosion. These risks were sufficiently high that the single AU defined in the Devonian petroleum system was not quantitatively assessed, because the chance of a field of the minimum size, 50 million barrels of oil equivalent, was estimated to be only 0.1.
Contact Information, Geology, Minerals, Energy, & Geophysics Science Center—Menlo Park
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
FAX 650-329-4936
Anthropogenic activities are changing landscapes and the context in which predator–prey dynamics evolved, thereby altering key ecological processes and community structure. Yet, the specific mechanisms underlying such changes are rarely understood. We tested whether a mesopredator release explained increased rodent density and concomitant predation of songbird nests near natural gas development. From 2015 to 2016, we surveyed apex predators (coyotes, badgers, raptors, and corvids) and measured apparent survival and perceived predation risk of deer mice (Peromyscus maniculatus; a primary nest predator), at 12 plots spanning a gradient of surface disturbance caused by energy development in Wyoming, USA. Additionally, we measured densities of three nest predators: deer mice, least chipmunks (Tamias minimus), and thirteen-lined ground squirrels (Ictidomys tridecemlineatus). Contrary to the mesopredator release hypothesis, counts of apex predators and perceived predation risk of deer mice increased with surface disturbance from energy development, whereas apparent survival of mice decreased. Densities of mice and ground squirrels, however, increased with surface disturbance, despite increased predation pressure. We therefore rejected the mesopredator release hypothesis as a potential mechanism underlying altered trophic dynamics near energy development. Our results suggest that apex predator control measures would not benefit declining songbirds on natural gas fields. Rather, apex predator abundance may be regulated from the bottom-up by rodents in this system. Our results corroborate a pattern showing weakened effects of mesopredator release in habitats modified by humans. Understanding how predator–prey dynamics may be altered in novel environments requires an understanding of how predators and prey alike respond to habitat change under different contexts.
The primary mission of the U.S. Geological Survey (USGS) Water Mission Area is to collect and disseminate reliable, impartial, and timely information needed to understand the water resources of the Nation, including data on streamflow, groundwater, water quality, water use, and availability. Management of data throughout the entire data lifecycle is necessary to meet the mission and maintain the USGS reputation of producing high-quality data as the Nation’s primary earth-science information agency. This document describes the data management procedures of the USGS Washington Water Science Center, including responsibilities of staff and workflow procedures.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191049","usgsCitation":"Conn, K.E., Mastin, M.C., Long, A.J., Dinicola, R.S., and Barton, C., 2019, Data management plan for the U.S. Geological Survey Washington Water Science Center : U.S. Geological Survey Open-File Report 2019-1049, 23 p., https://doi.org/10.3133/ofr20191049.","productDescription":"Report: iv, 23 p.","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-104277","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":363807,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1049/coverthb.jpg"},{"id":363808,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1049/ofr20191049.pdf","text":"Report","size":"573 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1049"}],"country":"United States","state":"Washington","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
Atoll islands’ alongshore sediment transport gradients depend on how island and reef morphology affect incident wave energy. It is unclear, though, how potential atoll morphologic configurations influence shoreline erosion and/or accretion patterns, and how these relationships will respond to future sea-level rise (SLR). Schematic atoll models with varying morphologies were used to evaluate the relative control of individual morphological parameters on alongshore transport gradients. Incident wave transformations were simulated using a physics-based numerical model and alongshore erosion and accretion was calculated using empirical formulae. The magnitude of the transport gradients increased with SLR: initial erosion or accretion patterns intensified. Modeled morphologic parameters that significantly influenced alongshore transport were the atoll diameter, reef flat width, reef flat depth, and island width. Modeled atolls with comparably small diameters, narrow and deep reef flats with narrow islands displayed greater magnitudes of erosion and/or accretion, especially with SLR. Windward island shorelines are projected to accrete toward the island’s longitudinal ends and lagoon due to SLR, whereas leeward islands erode along lagoon shorelines and extend toward the island ends. Oblique island, oriented parallel to the incident deepwater wave direction, shorelines are forecast to build out leeward along the reef rim and toward the lagoon while eroding along regions exposed to direct wave attack. These findings make it possible to evaluate the relative risk of alongshore erosion/accretion on atolls due to SLR in a rapid, first-order analysis.
Branch Chief, Hydrologic Networks Branch, Observing Systems Division
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 412
Reston, VA 20192
Choices in ecological research and natural resource management require balancing multiple, often competing objectives. Examples include maximizing species persistence in a wildlife conservation context, while minimizing cost, or balancing opposing stakeholder objectives when managing wildlife populations. Multiple-objective optimization (MOO) provides a unifying framework for solving multiple objective problems. Model selection is a critical component of ecological inference and prediction and requires balancing the competing objectives of model fit and model complexity. The tradeoff between model fit and model complexity provides a basis for describing the model-selection problem within the MOO framework. We discuss MOO and two strategies for solving the MOO problem; modeling preferences pre-optimization and post-optimization. Most conventional model selection methods can be formulated as solutions of MOO problems via specification of pre-optimization preferences. We reconcile model selection within the MOO framework. We also consider model selection using post-optimization specification of preferences. That is, by first identifying Pareto optimal solutions, and then selecting among them. We demonstrate concepts with an ecological application of model selection using avian species richness data in the continental United States.
Floral traits and rewards are important in mediating interactions between plants and pollinators. Agricultural management practices can affect abiotic factors known to influence floral traits; however, our understanding of the links between agricultural practices and floral trait expression is still poorly understood. Variation in floral morphological, nectar, and pollen traits of two important agricultural species, Coffea arabica and C. canephora, was assessed under different agricultural practices (sun and shade). Corolla diameter and corolla tube length were larger and pollen total nitrogen content greater in shade plantations of C. canephora than sun plantations. Corolla tube length and anther filament length were larger in shade plantations of C. arabica. No effect of agricultural practice was found on nectar volume, sugar or caffeine concentrations, or pollen production. Pollen total nitrogen content was lower in sun than shade plantations of C. canephora, but no difference was found between sun and shade for C. arabica. This study provides baseline data on the influence of agronomic practices on C. arabica and C. canephora floral traits and also helps fill a gap in knowledge about the effects of shade trees on floral traits, which can be pertinent to other agroforestry systems.
Understanding changes in wave attenuation by emergent vegetation as wetlands degrade or accrete over time is crucial for incorporation of wetlands into holistic coastal risk management. Linked SLAMM and XBeach models were used to investigate potential future changes in wave attenuation over a 50-year period in a degrading, subtropical wetland and a prograding, temperate wetland. These contrasting systems also have differing management contexts and were contrasted to demonstrate how the linked models can provide management-relevant insights. Morphological development of wetlands for different scenarios of sea-level rise and accretion was simulated with SLAMM and then coupled with different vegetation characteristics to predict the influence on future wave attenuation using XBeach. The geomorphological context, subsidence, and accretion resulted in large predicted reductions in the extent of vegetated land (e.g., wetland) and changes in wave height reduction potential across the wetland. These were exacerbated by increases in sea-level from +0.217 m to +0.386 m over a 50-year period, especially at the lowest accretion rates in the degrading wetland. Mangrove vegetation increased wave attenuation within the degrading, subtropical, saline wetland, while grazing reduced wave attenuation in the temperate, prograding wetland. Coastal management decisions and actions, related to coastal vegetation type and structure, have the potential to change future wave attenuation at a spatial scale relevant to coastal protection planning. Therefore, a coastal management approach that includes disaster risk reduction, biodiversity, and climate change, can be informed by coastal modeling tools, such as those demonstrated here for two contrasting case studies.
We investigated the morphology, biostratigraphy, shell stable isotope composition and paleogeography of the common Arctic benthic foraminifera, Cassidulina teretis (Tappan 1951) (sometimes assigned to Islandiella (Nørvang 1958), for application to Quaternary paleoceanography. Cassidulina teretis, which has been studied by several generations of Arctic foraminiferal specialists, is used in Arctic Ocean paleoceanographic reconstructions based on foraminiferal assemblages and, increasingly, isotope shell chemistry. Here we review its modern and fossil distribution including discussions of its taxonomy, ecology, biostratigraphy and shell chemistry. Cassidulina teretis Tappan 1951, originally described from the Gubik Formation, northern Alaska coastal plain, has variability in test size, apertural morphology and development of an umbilical boss representing intra- and inter-population differences across the Arctic and subarctic in modern, Quaternary and Pliocene assemblages. Nonetheless, our studies and those previously published lead us to conclude that populations from the Arctic Ocean represent a single species proposed by Tappan as Cassidulina teretis. Its modern distribution is mainly 200 to 1000 m water depth, often living within the core of the relatively warm Atlantic Layer. However, shallower occurrences suggest other factors, such as food supply, are also critical to its ecology. The Holocene distribution of Cassidulina teretis in the Beaufort Sea boundary indicate millennial-scale changes in relative abundance related to changing Atlantic Layer influence, sea-ice cover, surface productivity and food availability. There are extremely large changes in its abundance during the last deglacial interval on the Yermak Plateau, Barents Sea slope and the Laptev Sea reflecting rapid ocean changes during the Bølling-Allerød, Younger Dryas, and Preboreal. Similarly, C. teretis abundance changes during the last 300,000 years allow us to use it, at least regionally, as a useful biostratigraphic marker. The stable isotopic composition of Cassidulina teretis tests holds promise for establishing an isotope stratigraphy across the Arctic Ocean and perhaps also in the Nordic Seas, off Iceland and in the northern North Atlantic Ocean, once disequilibrium values and offsets from other Arctic benthic species are more firmly established.
","language":"English","publisher":"Micro Press","usgsCitation":"Cronin, T.M., Seidenstein, J., Keller, K., McDougall-Reid, K., Reufer, A., and Gemery, L., 2019, The benthic foraminifera cassidulina from the Arctic Ocean: Application to paleoceanography and biostratigraphy: Micropaleontology, v. 65, no. 2, p. 105-125.","productDescription":"21 p.","startPage":"105","endPage":"125","ipdsId":"IP-097014","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":385640,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":385617,"type":{"id":15,"text":"Index Page"},"url":"https://www.micropress.org/microaccess/micropaleontology/issue-347/article-2119"}],"volume":"65","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cronin, Thomas M. 0000-0002-2643-0979 tcronin@usgs.gov","orcid":"https://orcid.org/0000-0002-2643-0979","contributorId":2579,"corporation":false,"usgs":true,"family":"Cronin","given":"Thomas","email":"tcronin@usgs.gov","middleInitial":"M.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":815570,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Seidenstein, Julia","contributorId":243162,"corporation":false,"usgs":false,"family":"Seidenstein","given":"Julia","affiliations":[],"preferred":false,"id":815571,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keller, Katherine 0000-0001-6915-5455","orcid":"https://orcid.org/0000-0001-6915-5455","contributorId":218048,"corporation":false,"usgs":false,"family":"Keller","given":"Katherine","email":"","affiliations":[{"id":39732,"text":"Natural Systems Analysts, Harvard University","active":true,"usgs":false}],"preferred":false,"id":815572,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McDougall-Reid, Kristin 0000-0002-8788-3664","orcid":"https://orcid.org/0000-0002-8788-3664","contributorId":216211,"corporation":false,"usgs":true,"family":"McDougall-Reid","given":"Kristin","email":"","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":815573,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reufer, Ana","contributorId":258025,"corporation":false,"usgs":false,"family":"Reufer","given":"Ana","email":"","affiliations":[{"id":16809,"text":"James Madison University","active":true,"usgs":false}],"preferred":false,"id":815574,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gemery, Laura 0000-0003-1966-8732 lgemery@usgs.gov","orcid":"https://orcid.org/0000-0003-1966-8732","contributorId":5402,"corporation":false,"usgs":true,"family":"Gemery","given":"Laura","email":"lgemery@usgs.gov","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":815645,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70205082,"text":"70205082 - 2019 - GLASS3: A standalone multi-scale seismic detection associator","interactions":[],"lastModifiedDate":"2019-08-30T07:35:41","indexId":"70205082","displayToPublicDate":"2019-05-14T07:34:55","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":960,"text":"BSSA","active":true,"publicationSubtype":{"id":10}},"title":"GLASS3: A standalone multi-scale seismic detection associator","docAbstract":"The automated global real-time association of phase picks into seismic sources comes with unique challenges when simultaneously monitoring at local, regional and global scales. High spatial variability in seismic station density, transitory seismic data availability, and time-varying noise characteristics of individual stations must be considered in the design of an associator that is fast and accurate with a low false association rate. These challenges are particularly apparent at the U.S. Geological Survey (USGS) National Earthquake Information Center (NEIC), which monitors seismicity in near-real time on local, regional, and global scales using seismic data from roughly 2,100 real-time seismic stations. In order to fully leverage this large dataset, NEIC developed a stand-alone, self-configuring seismic phase associator, GLASS3 (GLobal ASSociator 3) that simultaneously processes variably scaled 3D association webs, each with a unique set of nucleation criteria (e.g., nucleation stack threshold). GLASS3 has many useful features for real-time monitoring including its computational efficiency, instantaneous pick processing, and on-the-fly configurability such as the creation and removal of targeted association webs and updates to supporting station metadata. GLASS3 runs both as part of a real-time event processing system, and as a configurable standalone associator that can be applied to a large variety of seismic problems. Here we describe the GLASS3 algorithm and demonstrate (including input data and configuration files) its use in associating phase-ambiguous picks on multiple scales.","language":"English","publisher":"GeoScienceWorld","doi":"10.1785/0120180308","usgsCitation":"Yeck, W.L., Patton, J., Johnson, C.E., Kragness, D., Benz, H.M., Earle, P.S., Guy, M.M., and Ambruz, N., 2019, GLASS3: A standalone multi-scale seismic detection associator: BSSA, v. 4, no. 109, p. 1469-1478, https://doi.org/10.1785/0120180308.","productDescription":"10 p.","startPage":"1469","endPage":"1478","ipdsId":"IP-106509","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":367107,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":367104,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.geoscienceworld.org/ssa/bssa/article/109/4/1469/570430/glass3-a-standalone-multiscale-seismic-detection"}],"volume":"4","issue":"109","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-05-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Yeck, William L. 0000-0002-2801-8873 wyeck@usgs.gov","orcid":"https://orcid.org/0000-0002-2801-8873","contributorId":147558,"corporation":false,"usgs":true,"family":"Yeck","given":"William","email":"wyeck@usgs.gov","middleInitial":"L.","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":769900,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Patton, John 0000-0003-0142-5118","orcid":"https://orcid.org/0000-0003-0142-5118","contributorId":218681,"corporation":false,"usgs":true,"family":"Patton","given":"John","email":"","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":769901,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Caryl E.","contributorId":218682,"corporation":false,"usgs":false,"family":"Johnson","given":"Caryl","email":"","middleInitial":"E.","affiliations":[{"id":39885,"text":"Introspective Systems LLC","active":true,"usgs":false}],"preferred":false,"id":769902,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kragness, David","contributorId":218683,"corporation":false,"usgs":false,"family":"Kragness","given":"David","affiliations":[{"id":39886,"text":"Katylyst Integration","active":true,"usgs":false}],"preferred":false,"id":769903,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Benz, Harley M. 0000-0002-6860-2134 benz@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-2134","contributorId":794,"corporation":false,"usgs":true,"family":"Benz","given":"Harley","email":"benz@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":769904,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Earle, Paul S. 0000-0002-3500-017X pearle@usgs.gov","orcid":"https://orcid.org/0000-0002-3500-017X","contributorId":173551,"corporation":false,"usgs":true,"family":"Earle","given":"Paul","email":"pearle@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":769905,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Guy, Michelle M. 0000-0003-3450-4656 mguy@usgs.gov","orcid":"https://orcid.org/0000-0003-3450-4656","contributorId":173432,"corporation":false,"usgs":true,"family":"Guy","given":"Michelle","email":"mguy@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":769906,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ambruz, Nicholas 0000-0002-3660-3546","orcid":"https://orcid.org/0000-0002-3660-3546","contributorId":218684,"corporation":false,"usgs":true,"family":"Ambruz","given":"Nicholas","email":"","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":769907,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70215924,"text":"70215924 - 2019 - Relaxation response of critically stressed macroscale surficial rock sheets","interactions":[],"lastModifiedDate":"2020-11-02T13:10:17.599535","indexId":"70215924","displayToPublicDate":"2019-05-14T07:08:19","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3306,"text":"Rock Mechanics and Rock Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Relaxation response of critically stressed macroscale surficial rock sheets","docAbstract":"Rock environments both underground and on Earth’s surface show indications of energetic macroscale fracture. In tunnels and excavations, these manifest as rockbursts—energetic explosions of rock that can damage engineering projects, and may pose ongoing financial and safety risk as rock stresses adjust during post-failure relaxation. In natural settings at the surface, evidence for rockbursts exist in the form of tent-like structures of ruptured exfoliation sheets, but few direct observations of such events exist, precluding the analysis of how natural rock formations may evolve after rupture. Here we investigate the post-failure evolution of a granitic rock dome following rapid fracture events (i.e., surficial rockbursts) that occurred in California, USA during 2014–2016. Building upon previous work that showed a thermal stress origin for the observed fracturing, we investigate the return to background stress conditions (i.e., stress relaxation) observed in both short- (week, month) and long-term (multi-year) rock deformation trends. Acoustic emissions, deformation, and environmental monitoring data indicate that partially detached rock sheets forming the surface of the dome undergo fracture aperture closing during cooling periods, concurrent with reduction of rock stress by the source of forcing (i.e., thermal stress). However, with sufficient critical and/or subcritical fracture, our observations also show that rock sheets can become decoupled from the source of stress, resulting in a long-term return to background stress conditions. Our results provide insight into the cyclic and likely ephemeral nature of rock fracture in surficial rock domes, as well as in underground rockburst environments.
Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean resources of 24 trillion cubic feet of gas in the Mesaverde Group and Wasatch Formation of the Uinta-Piceance Province in northeast Utah and northwest Colorado.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193027","usgsCitation":"Drake, R.M., II, Schenk, C.J., Mercier, T.J., Le, P.A., Finn, T.M., Johnson, R.C., Woodall, C.A., Gaswirth, S.B., Marra, K.R., Pitman, J.K., Leathers-Miller, H.M., Haines, S.S., and Tennyson, M.E., 2019, Assessment of undiscovered continuous tight-gas resources in the Mesaverde Group and Wasatch Formation, Uinta-Piceance Province, Utah and Colorado, 2018: U.S. Geological Survey Fact Sheet 2019–3027, 2 p., https://doi.org/10.3133/fs20193027.","productDescription":"Report: 2 p.; Data Release","numberOfPages":"2","onlineOnly":"N","ipdsId":"IP-105699","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":437464,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P935RLIG","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project - Piceance and Uinta Basins, Mesaverde Group Tight Gas Assessment Unit Boundaries and Assessment Input Data Forms"},{"id":363589,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3027/fs20193027.pdf","text":"Report","size":"804 kB ","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2019-3027"},{"id":363588,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3027/coverthb2.jpg"},{"id":369123,"rank":4,"type":{"id":30,"text":"Data Release"},"url":" https://doi.org/10.5066/P935RLIG ","text":"USGS data release","description":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project—Piceance and Uinta Basins, Mesaverde Group Tight Gas Assessment Unit Boundaries and Assessment Input Data Forms"},{"id":363952,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3027/fs20193027_corr-note.txt","text":"Correction Note","size":"1.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"FS 2019-3027 Correction Note"}],"country":"United States","state":"Colorado, Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.1044921875,\n 37.96152331396614\n ],\n [\n -105.897216796875,\n 37.95286091815649\n ],\n [\n -105.88623046874999,\n 41.0130657870063\n ],\n [\n -111.851806640625,\n 40.95501133048621\n ],\n [\n -112.1044921875,\n 37.96152331396614\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
Because natural ecosystems are complex, it is difficult to predict how their variability scales across space and levels of organization. The species‐insurance hypothesis predicts that asynchronous dynamics among species should reduce variability when biomass is aggregated either from local species populations to local multispecies communities, or from metapopulations to metacommunities. Similarly, the spatial‐insurance hypothesis predicts that asynchronous spatial dynamics among either local populations or local communities should stabilize metapopulation biomass and metacommunity biomass, respectively. In combination, both species and spatial insurance reduce variation in metacommunity biomass over time, yet these insurances are rarely considered together in natural systems. We partitioned the extent that species insurance and spatial insurance reduced the annual variation in macroalgal biomass in a southern California kelp forest. We quantified variability and synchrony at two levels of organization (population and community) and two spatial scales (local plots and region) and quantified the strength of species and spatial insurance by comparing observed variability and synchrony in aggregate biomass to null models of independent species or spatial dynamics based on cyclic‐shift permutation. Spatial insurance was weak, presumably because large‐scale oceanographic processes in the study region led to high spatial synchrony at both population‐ and community‐level biomass. Species insurance was stronger due to asynchronous dynamics among the metapopulations of a few common species. In particular, a regional decline in the dominant understory kelp species Pterygophora californica was compensated for by the rise of three subdominant species. These compensatory dynamics were associated with positive values of the Pacific Decadal Oscillation, indicating that differential species tolerances to warmer temperature and nutrient‐poor conditions may underlie species insurance in this system. Our results illustrate how species insurance can stabilize aggregate community properties in natural ecosystems where environmental conditions vary over broad spatial scales.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.2719","usgsCitation":"Lamy, T., Wang, S., Renard, D., Lafferty, K.D., Reed, D.C., and Miller, R.J., 2019, Species insurance trumps spatial insurance in stabilizing biomass of a marine macroalgal metacommunity: Ecology, v. 100, no. 2, e02719, 10 p., https://doi.org/10.1002/ecy.2719.","productDescription":"e02719, 10 p.","ipdsId":"IP-104448","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":364980,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"100","issue":"2","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2019-05-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Lamy, Thomas","contributorId":203605,"corporation":false,"usgs":false,"family":"Lamy","given":"Thomas","email":"","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":764934,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wang, Shaopeng","contributorId":216516,"corporation":false,"usgs":false,"family":"Wang","given":"Shaopeng","email":"","affiliations":[{"id":39466,"text":"Peking University, Beijing","active":true,"usgs":false}],"preferred":false,"id":764935,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Renard, Delphine","contributorId":216517,"corporation":false,"usgs":false,"family":"Renard","given":"Delphine","email":"","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":764936,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":764933,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reed, Daniel C.","contributorId":203607,"corporation":false,"usgs":false,"family":"Reed","given":"Daniel","email":"","middleInitial":"C.","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":764937,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miller, Robert J.","contributorId":176277,"corporation":false,"usgs":false,"family":"Miller","given":"Robert","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":764938,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70204006,"text":"70204006 - 2019 - Groundwater quality of a public supply aquifer in proximity to oil development, Fruitvale Oil Field, Bakersfield, California","interactions":[],"lastModifiedDate":"2019-06-26T16:03:51","indexId":"70204006","displayToPublicDate":"2019-05-13T15:51:24","publicationYear":"2019","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":"Groundwater quality of a public supply aquifer in proximity to oil development, Fruitvale Oil Field, Bakersfield, California","docAbstract":"Due to concerns over the effects of oil production activities on groundwater quality in California, chemical, isotopic, dissolved gas and age-dating tracers were analyzed in samples collected from public-supply wells and produced-water sites in the Fruitvale oil field (FVOF). A combination of newly collected and historical data was used to determine whether oil formation fluids have mixed with groundwater used for public supply and what the potential pathways for the migration of oil formation fluids into groundwater may be. Stable isotopes of water (δ2H and δ18O) and age dating (3H, 3Hetrit, SF6 and 14C) tracers in groundwater samples were consistent with the Kern River being the main source of recharge to aquifers. The distribution of major ion concentrations and pH with distance from the Kern River indicate that natural processes were the primary controls on groundwater salinity. Two of 14 groundwater samples had δ13C-DIC values (−2.4 to +1.9 per mil) consistent with mixtures of <1 to about 9 percent oil-field water. Concentrations of TDS in groundwater samples were generally much lower (129–1,200 milligrams per liter (mg/l), median 216 mg/l) than produced water samples (586–24,930 mg/l, median 2,717 mg/l), suggesting that any mixing of oil-field water with groundwater has not significantly affected groundwater salinity. Trace concentrations of thermogenic methane were detected in three groundwater samples that did not have dissolved inorganic or isotopic indicators consistent with mixing of oil-field water, suggesting that stray gases may have migrated from the subsurface via preferential pathways such as leaky well bores into groundwater aquifers. Low concentrations of petroleum hydrocarbons were detected in samples that also contained anthropogenic VOCs and components of post- and pre-1950s recharge, indicating that petroleum hydrocarbons could have come from subsurface and/or surface sources. Overall, the results of this study indicated that groundwater currently used for public supply in the FVOF was of good quality with little, if any, effects from oil production activities. This may be due in part to the relatively rapid flushing of the aquifer system by recharge from the Kern River.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2019.05.003","usgsCitation":"Wright, M., McMahon, P.B., Landon, M.K., and Kulongoski, J.T., 2019, Groundwater quality of a public supply aquifer in proximity to oil development, Fruitvale Oil Field, Bakersfield, California: Applied Geochemistry, v. 106, p. 82-95, https://doi.org/10.1016/j.apgeochem.2019.05.003.","productDescription":"14 p.","startPage":"82","endPage":"95","ipdsId":"IP-093942","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true}],"links":[{"id":467620,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2019.05.003","text":"Publisher Index Page"},{"id":365096,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Bakersfield","otherGeospatial":"Fruitvale Oil Field","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.57107543945311,\n 35.17493084974928\n ],\n [\n -119.57107543945311,\n 35.17493084974928\n ],\n [\n -119.57107543945311,\n 35.17493084974928\n ],\n [\n -119.57107543945311,\n 35.17493084974928\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.00115966796875,\n 35.48890875085949\n ],\n [\n -119.04373168945314,\n 35.48541438776276\n ],\n [\n -119.0478515625,\n 35.48275857019274\n ],\n [\n -119.04870986938477,\n 35.46808010116232\n ],\n [\n -119.04029846191405,\n 35.46108941215697\n ],\n [\n -119.02072906494142,\n 35.44724605551148\n ],\n [\n -119.02072906494142,\n 35.44221151715641\n ],\n [\n -119.01643753051758,\n 35.43941441533686\n ],\n [\n -119.01163101196289,\n 35.436617216330966\n ],\n [\n -119.00922775268555,\n 35.42878454211113\n ],\n [\n -119.01884078979492,\n 35.42374884923695\n ],\n [\n -119.01248931884766,\n 35.411018333025666\n ],\n [\n -119.00871276855467,\n 35.40682101870289\n ],\n [\n -118.98828506469725,\n 35.41003897923532\n ],\n [\n -118.96957397460938,\n 35.41269719754907\n ],\n [\n -118.96322250366211,\n 35.42290953648285\n ],\n [\n -118.94914627075195,\n 35.43395978725954\n ],\n [\n -118.9460563659668,\n 35.44235136969617\n ],\n [\n -118.95429611206056,\n 35.453259119161764\n ],\n [\n -118.9621925354004,\n 35.46808010116232\n ],\n [\n -118.97283554077148,\n 35.474930386870035\n ],\n [\n -118.99686813354491,\n 35.485833719356805\n ],\n [\n -119.00115966796875,\n 35.48890875085949\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"106","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wright, Michael 0000-0003-0653-6466 mtwright@usgs.gov","orcid":"https://orcid.org/0000-0003-0653-6466","contributorId":151031,"corporation":false,"usgs":true,"family":"Wright","given":"Michael","email":"mtwright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":765169,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McMahon, Peter B. 0000-0001-7452-2379 pmcmahon@usgs.gov","orcid":"https://orcid.org/0000-0001-7452-2379","contributorId":724,"corporation":false,"usgs":true,"family":"McMahon","given":"Peter","email":"pmcmahon@usgs.gov","middleInitial":"B.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":765170,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Landon, Matthew K. 0000-0002-5766-0494 landon@usgs.gov","orcid":"https://orcid.org/0000-0002-5766-0494","contributorId":392,"corporation":false,"usgs":true,"family":"Landon","given":"Matthew","email":"landon@usgs.gov","middleInitial":"K.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":765171,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kulongoski, Justin T. 0000-0002-3498-4154 kulongos@usgs.gov","orcid":"https://orcid.org/0000-0002-3498-4154","contributorId":173457,"corporation":false,"usgs":true,"family":"Kulongoski","given":"Justin","email":"kulongos@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":765172,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70202978,"text":"ofr20191037 - 2019 - Monitoring live vegetation in semiarid and arid rangeland environments with satellite remote sensing in northern Kenya","interactions":[],"lastModifiedDate":"2019-05-14T11:37:50","indexId":"ofr20191037","displayToPublicDate":"2019-05-13T11:49:01","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1037","displayTitle":"Monitoring Live Vegetation in Semiarid and Arid Rangeland Environments with Satellite Remote Sensing in Northern Kenya","title":"Monitoring live vegetation in semiarid and arid rangeland environments with satellite remote sensing in northern Kenya","docAbstract":"As part of the U.S. Department of the Interior’s (DOI) commitment to provide technical assistance to the Kenyan Northern Rangelands Trust (NRT), the U.S. Geological Survey, in collaboration with the DOI International Technical Assistance Program and the U.S. Agency for International Development’s regional mission in East Africa, created a high spatial and time-sensitive live vegetation monitoring system for NRT. The system built with advanced field and sensor technologies produced directly calibrated and highly accurate satellite mapping that is extendable both forward and backward in time. The maps are produced in a simple 0–100-percent representation of live vegetation status and change over time. The backbone of the mapping is the Sentinel satellite remote sensing systems with 5-day collection frequencies and ground spatial resolutions of 10 meters. The European Space Agency (ESA) offers free Sentinel satellite image data through conveniently accessed websites and free user-friendly image processing software downloadable directly onto a personal workstation. ESA provides free online software support. The mapping capability was extended from the forward mapping of Sentinel back in time with the Landsat satellite remote sensing system that has an available and free data archive back to 1983. Although Landsat has coarser spatial resolution, the Landsat to Sentinel live vegetation mapping comparison supports the use of Landsat to provide NRT the historical recreation of prominent live vegetation changes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191037","collaboration":"Prepared in cooperation with the U.S. Agency for International Development","usgsCitation":"Rangoonwala, Amina, and Ramsey, E.W., III, 2019, Monitoring live vegetation in semiarid and arid rangeland environments with satellite remote sensing in northern Kenya: U.S. Geological Survey Open-File Report 2019–1037, 83 p., https://doi.org/10.3133/ofr20191037.","productDescription":"Report: vii, 83 p.; 15 Figures","numberOfPages":"96","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-105119","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":363609,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1037/ofr20191037.pdf","text":"Report","size":"22.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 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"},{"id":363623,"rank":16,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2019/1037/ofr20191037_fig40b.tif","text":"Figure 40B—high resolution—","description":"OFR 2019–1037 Figure 40B","linkHelpText":"Live vegetation cover proportion for the core-Kenyan Northern Rangelands Trust conservancies in June 2018 "},{"id":363624,"rank":17,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2019/1037/ofr20191037_fig41.jpg","text":"Figure 41—high resolution—","description":"OFR 2019–1037 Figure 41","linkHelpText":"June 2018 synthetic aperture radar (SAR) vertical send and vertical receive (VV) and vertical send and horizontal receive (VH) images"}],"country":"Kenya","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 33.8818359375,\n -0.9667509997666298\n ],\n [\n 37.72705078125,\n -3.601142320158722\n ],\n [\n 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U.S. Geological Survey
700 Cajundome Blvd.
Lafayette, LA 70506
Topographical differencing and edge-matching analyses were used to evaluate agreement of the Coastal National Elevation Database Applications Project’s Northern Gulf of Mexico topobathymetric digital elevation model (TBDEM) with The National Map 3-Dimensional Elevation Program (3DEP) 1/3 arc-second digital elevation models (DEMs). In addition to topographic map products provided through the National Geospatial Program, the model integrates bathymetric and topobathymetric datasets for three-dimensional (3D) mapping of rivers, lakes, and bays in the upland and intertidal wetlands to offshore environments in coastal zones from the border between Texas and Louisiana to east of Mobile Bay, Alabama.
Contoured elevation differences between the Northern Gulf of Mexico TBDEM and the 3DEP 1/3 arc-second DEMs indicate that 85 percent of elevation data in the Northern Gulf of Mexico TBDEM agree (no difference for contoured elevations) between 95 and 100 percent with 3DEP 1/3 arc-second DEMs. Edge matching differences between adjacent Northern Gulf of Mexico TBDEM source projects or between the TBDEM and 3DEP DEMs indicate most seams between integrated and 3DEP DEMs are smooth. Where seams did not match, most differences were in the range of tenths to hundredths of a meter. Valid differences that are greater than plus or minus 2 meters in areas of bathymetric data are found in the Mississippi River, Atchafalaya River, Lower Atchafalaya River, Wax Lake Pass channel, the Vermilion Bay bathymetric datasets, and where topobathymetric datasets are integrated in the model. Areas with positive or negative outlier difference elevations seem to be a result of site conditions that affect light detection and ranging (lidar) waveform return signals, misclassification of surface features, or possibly because of interpolation required to develop a smooth elevation surface. Results of this analysis provide information to help understand model parameters and agreement of the Northern Gulf of Mexico TBDEM developed using different data types from different sources with The National Map 3DEP DEMs.
Inclusion of bathymetric and topobathymetric data types in the 3DEP aligns with the mission to respond to growing needs for a wide range of three-dimensional representations of the Nation and supports the U.S. Geological Survey strategy for developing a National Terrain Model to provide hydrographic and elevation data that extend the elevation surface below water bodies. The 3D Nation Requirements and Benefits Study sponsored by the U.S. Geological Survey and National Oceanic and Atmospheric Administration to assess local to regional Tribal, State, and Federal technical requirements, needs, and benefits for using topographic and bathymetric 3DEP elevation data will be used to help develop and refine future program alternatives for 3D elevation data that include a category for bathymetry and topobathymetry. At the time of this report (2019), 3DEP acquisition is specific to topographic lidar that meets lidar DEM specifications and which requires surface-water feature areas to be hydroflattened. Cataloging bathymetric and topobathymetric DEMs as part of the 3DEP will require new specifications for acoustic, lidar, merged acoustic and lidar, and possibly other bathymetric and topobathymetric survey data types.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191016","usgsCitation":"Miller-Corbett, C., 2019, Analysis for agreement of the Northern Gulf of Mexico topobathymetric digital elevation model with 3-Dimensional Elevation Program 1/3 arc-second digital elevation models: U.S. Geological Survey Open-File Report 2019–1016, 44 p., https://doi.org/10.3133/ofr20191016.","productDescription":"vi, 43 p.","numberOfPages":"54","onlineOnly":"Y","ipdsId":"IP-081383","costCenters":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"links":[{"id":363655,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1016/ofr20191016.pdf","text":"Report","size":"16.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1016"},{"id":363654,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1016/coverthb.jpg"}],"country":"United States","state":"Alabama, Florida, Louisiana, Mississippi, Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.48193359375,\n 28.43971381702788\n ],\n [\n -84.13330078125,\n 28.43971381702788\n ],\n [\n -84.13330078125,\n 31.39115752282472\n ],\n [\n -96.48193359375,\n 31.39115752282472\n ],\n [\n -96.48193359375,\n 28.43971381702788\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, National Geospatial Technical Operations Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
Human activity has altered 33–50% of Earth's surface, including temperate grasslands and sagebrush rangelands, resulting in a loss of biodiversity. By promoting habitat for sensitive or wide‐ranging species, less exigent species may be protected in an umbrella effect. The greater sage‐grouse (Centrocercus urophasianus; sage‐grouse) has been proposed as an umbrella for other sagebrush‐obligate species because it has an extensive range that overlaps with many other species, it is sensitive to anthropogenic activity, it requires resources over large landscapes, and its habitat needs are known. The efficacy of the umbrella concept, however, is often assumed and rarely tested. Therefore, we surveyed sage‐grouse pellet occurrence and sagebrush‐associated songbird abundance in northwest Colorado, USA, to determine the amount of habitat overlap between sage‐grouse and 4 songbirds (Brewer's sparrow [Spizella breweri], sage thrasher [Oreoscoptes montanus], sagebrush sparrow [Artemisiospiza nevadensis]), and green‐tailed towhee [Pipilo chlorurus]). During May and June 2013–2015, we conducted standard point count breeding surveys for songbirds and counted sage‐grouse pellets within 300 10‐m radius plots. We modeled songbird abundance and sage‐grouse pellet occurrence with multi‐scaled environmental features, such as sagebrush cover and bare ground. To evaluate sage‐grouse as an umbrella for sagebrush‐associated passerines, we determined the correlation between probability of sage‐grouse pellet occurrence and model‐predicted songbird densities per sampling plot. We then classified the sage‐grouse probability of occurrence as high (probability >0.5) and low (probability ≤0.5) and mapped model‐predicted surfaces for each species in our study area. We determined average songbird density in areas of high and low probability of sage‐grouse occurrence. Sagebrush cover at intermediate scales was an important predictor for all species, and ground cover was important for all species except sage thrashers. Areas with a higher probability of sage‐grouse occurrence also contained higher densities of Brewer's sparrows, green‐tailed towhees, and sage thrashers, but predicted sagebrush sparrow densities were lower in these areas. In northwest Colorado, sage‐grouse may be an effective umbrella for Brewer's sparrows, green‐tailed towhees, and sage thrashers, but sage‐grouse habitat does not appear to capture areas that support high sagebrush sparrow densities. A multi‐species focus may be the best management and conservation strategy for several species of concern, especially those with conflicting habitat requirements.
","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21663","usgsCitation":"Timmer, J.M., Aldridge, C.L., and Fernandez-Gimenez, M., 2019, Managing for multiple species: Greater sage‐grouse and sagebrush songbirds: Journal of Wildlife Management, v. 83, no. 5, p. 1043-1056, https://doi.org/10.1002/jwmg.21663.","productDescription":"14 p.","startPage":"1043","endPage":"1056","ipdsId":"IP-104297","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":380700,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","county":"Moffat County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-107.3181,41.0035],[-107.3178,40.9852],[-107.3177,40.9789],[-107.3175,40.9707],[-107.3171,40.9503],[-107.317,40.9412],[-107.3173,40.929],[-107.3171,40.9145],[-107.3167,40.8596],[-107.3166,40.856],[-107.3157,40.8378],[-107.3145,40.7748],[-107.3144,40.7716],[-107.3131,40.7013],[-107.3131,40.699],[-107.3128,40.6854],[-107.3126,40.6723],[-107.3121,40.6142],[-107.3119,40.5997],[-107.3688,40.5996],[-107.3683,40.5429],[-107.427,40.5427],[-107.427,40.5132],[-107.4276,40.4238],[-107.4294,40.3612],[-107.4297,40.3467],[-107.43,40.3322],[-107.4402,40.3321],[-107.4382,40.2618],[-107.4389,40.2235],[-107.4396,40.219],[-107.7614,40.2214],[-107.8192,40.2211],[-107.8758,40.2207],[-107.8945,40.2209],[-107.9144,40.221],[-107.9523,40.2213],[-107.9891,40.2217],[-108.0084,40.2218],[-108.0855,40.2224],[-108.1042,40.2225],[-108.1626,40.2225],[-108.1819,40.2226],[-108.2011,40.2227],[-108.218,40.2229],[-108.2367,40.2225],[-108.256,40.2226],[-108.2945,40.2224],[-108.3313,40.2222],[-108.3891,40.2225],[-108.4083,40.2221],[-108.4445,40.2223],[-108.5023,40.2221],[-108.5216,40.2217],[-108.5577,40.2219],[-108.5975,40.2215],[-108.6553,40.2212],[-108.6692,40.2214],[-109.051,40.2228],[-109.0514,40.2608],[-109.0514,40.2753],[-109.0514,40.2844],[-109.0513,40.292],[-109.0512,40.3206],[-109.0509,40.3583],[-109.0509,40.3874],[-109.0509,40.4041],[-109.0508,40.419],[-109.0507,40.4491],[-109.0508,40.4636],[-109.0508,40.4713],[-109.0508,40.4767],[-109.0505,40.4931],[-109.0503,40.5317],[-109.0501,40.5774],[-109.0501,40.5793],[-109.0501,40.5933],[-109.0501,40.6096],[-109.0501,40.6515],[-109.0501,40.6545],[-109.0499,40.666],[-109.0501,40.6949],[-109.0499,40.7516],[-109.0499,40.7693],[-109.0498,40.7834],[-109.0497,40.824],[-109.0493,40.8433],[-109.0493,40.8453],[-109.0492,40.8587],[-109.0488,40.8866],[-109.0489,40.9036],[-109.0487,40.9107],[-109.049,40.9268],[-109.0488,40.9479],[-109.049,41],[-108.9729,41.0002],[-108.9315,41.0001],[-108.912,41.0001],[-108.7655,41.0002],[-108.746,41.0002],[-108.6516,41.0005],[-108.6321,41.0005],[-108.5699,41.0003],[-108.3781,40.9997],[-108.3745,40.9997],[-108.3118,41],[-108.2923,41.0001],[-108.263,41.0003],[-108.2186,41.0007],[-108.1808,41.001],[-108.0007,41.0025],[-107.966,41.0028],[-107.9154,41.0029],[-107.888,41.0029],[-107.8801,41.0029],[-107.8521,41.0029],[-107.8391,41.0028],[-107.8326,41.0028],[-107.8206,41.0028],[-107.8131,41.0028],[-107.7845,41.0028],[-107.7078,41.0028],[-107.6767,41.0028],[-107.6049,41.0028],[-107.5288,41.0026],[-107.5136,41.0026],[-107.5093,41.0026],[-107.4947,41.0026],[-107.4575,41.0027],[-107.4137,41.0029],[-107.3948,41.003],[-107.3674,41.0032],[-107.3437,41.0033],[-107.3181,41.0035]]]},\"properties\":{\"name\":\"Moffat\",\"state\":\"CO\"}}]}","volume":"83","issue":"5","noUsgsAuthors":false,"publicationDate":"2019-05-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Timmer, Jennifer M.","contributorId":140717,"corporation":false,"usgs":false,"family":"Timmer","given":"Jennifer","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":805435,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":805436,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fernandez-Gimenez, Maria E","contributorId":245143,"corporation":false,"usgs":false,"family":"Fernandez-Gimenez","given":"Maria E","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":805437,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70205440,"text":"70205440 - 2019 - Seismological, geological, and geotechnical engineering aspects of the 2018 MW 6.6 Hokkaido Eastern Iburi earthquake","interactions":[],"lastModifiedDate":"2019-09-19T09:35:12","indexId":"70205440","displayToPublicDate":"2019-05-13T09:27:57","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Seismological, geological, and geotechnical engineering aspects of the 2018 MW 6.6 Hokkaido Eastern Iburi earthquake","docAbstract":"The 2018 Hokkaido Eastern Iburi MW6.6 earthquake struck the southern coast of the north island of Japan in the early morning (3:08 AM JST) on September 6, 2018. The event had a hypocentral depth of 35 km, centered beneath the port city of Tomakomai. Extremely strong shaking with peak ground acceleration in excess of 0.5 g was felt in the communities directly north of Tomakomai, in the districts of Abira and Atsuma. There, a very high density of landslides occurred in pumices soil that affected the majority of slopes in the region above the floodplain. These landslides were typically a thin veneer of 1 to 3 m of recent (<9000 ybp) volcanic pumice mantling older Kawabata marine sedimentary rocks. The source of the pumice layers are recent eruptions from Mt. Tarumae, south of Shikotsu-ko Caldera lake. Several block megaslides were observed in the Kawabata marine unit. A flow failure resulting from soil collapse or liquefaction was observed in fill deposits placed in a residential community district of Kiyota ward in Sapporo. The community, Satozuka-1 is situated on a natural steep ravine that was filled with pumice soil to level construction area to a gently sloping landscape for housing construction. The flow failure consisted of lateral migration of soil from the upper slope regions of the community onto the surface of the lower community. The upper community topographically deflated as large quantities of fluidized soil flooded the lower streets.
","language":"English","publisher":"Geotechnical Extreme Events Reconnaissance Association (GEER)","doi":"10.18118/G6CM1K","usgsCitation":"Kayen, R., Wham, B., Grant, A.R., Atsushi, M., Anderson, D., Zimmaro, P., Wang, P., Tsai, Y.T., Bachhuber, J., Madugo, C.L., Sun, J., Hitchcock, C.S., and Motto, M., 2019, Seismological, geological, and geotechnical engineering aspects of the 2018 MW 6.6 Hokkaido Eastern Iburi earthquake, 105 p., https://doi.org/10.18118/G6CM1K.","productDescription":"105 p.","ipdsId":"IP-105842","costCenters":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":367542,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Japan","otherGeospatial":"Hokkaido","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n 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Donald","contributorId":189872,"corporation":false,"usgs":false,"family":"Anderson","given":"Donald","affiliations":[],"preferred":false,"id":771190,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zimmaro, Paolo","contributorId":219068,"corporation":false,"usgs":false,"family":"Zimmaro","given":"Paolo","email":"","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":771191,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wang, Pengfei","contributorId":217351,"corporation":false,"usgs":false,"family":"Wang","given":"Pengfei","email":"","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":771192,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Tsai, Yi 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Joseph","contributorId":217368,"corporation":false,"usgs":false,"family":"Sun","given":"Joseph","affiliations":[{"id":39608,"text":"Pacific Gas & Electric Company","active":true,"usgs":false}],"preferred":false,"id":771196,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Hitchcock, Christopher S.","contributorId":173160,"corporation":false,"usgs":false,"family":"Hitchcock","given":"Christopher","email":"","middleInitial":"S.","affiliations":[{"id":27167,"text":"InfraTerra, Inc.","active":true,"usgs":false}],"preferred":false,"id":771197,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Motto, Matthew","contributorId":219071,"corporation":false,"usgs":false,"family":"Motto","given":"Matthew","email":"","affiliations":[{"id":39956,"text":"Infraterra","active":true,"usgs":false}],"preferred":false,"id":771198,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70205447,"text":"70205447 - 2019 - A comparative analysis of common methods to identify waterbird hotspots","interactions":[],"lastModifiedDate":"2019-09-18T18:19:42","indexId":"70205447","displayToPublicDate":"2019-05-11T18:13:33","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"A comparative analysis of common methods to identify waterbird hotspots","docAbstract":"1. Hotspot analysis is a commonly used method in ecology and conservation to identify areas of high biodiversity or conservation concern. However, delineating and mapping hotspots is subjective and various approaches can lead to different conclusions with regard to the classification of particular areas as hotspots, complicating long-term conservation planning and implementation efforts.
2. We present a comparative analysis of recent approaches for identifying waterbird hotspots, with the goal of developing insights about the appropriate use of these methods. We selected four commonly used measures to identify persistent areas of high use: kernel density estimation, Getis-Ord Gi*, hotspot persistence, and hotspots conditional on presence, which represent the range of quantitative hotspot estimation approaches used in waterbird analyses. We applied each of the methods to aerial survey waterbird count data collected in the Great Lakes from 2012-2014 using a 5 km2 grid. For each approach, we identified areas of high use for seven species/species groups and then compared the results across all methods.
3. Our results indicate that formal hotspot analysis frameworks do not always lead to the same conclusions. The kernel density and Getis-Ord Gi* methods yielded the most similar results across all species analyzed. We found that these two models can differ substantially from the hotspot persistence and hotspots conditional on presence estimation approaches, which were not consistently similar to one another. The hotspot persistence approach differed most significantly from the other methods but is the only method to explicitly account for temporal variation.
4. We recommend considering the ecological question and scale of any conservation or management activities prior to designing survey methodologies. Deciding the appropriate definition and scale for analysis is critical for interpretation of hotspot analysis results. Combining methods using an integrative approach, either within a single analysis or post-hoc, could lead to greater consistency in the identification of waterbird hotspots.
","language":"English","publisher":"British Ecological society","doi":"10.1111/2041-210X.13209","usgsCitation":"Sussman, A.L., Gardner, B., Adams, E.M., Salas, L., Kenow, K.P., Luukkonen, D.R., Monfils, M.J., Mueller, W.P., Williams, K.A., Leduc-Lapierre, M., and Zipkin, E.F., 2019, A comparative analysis of common methods to identify waterbird hotspots: Methods in Ecology and Evolution, v. 10, no. 9, p. 1454-1468, https://doi.org/10.1111/2041-210X.13209.","productDescription":"15 p.","startPage":"1454","endPage":"1468","ipdsId":"IP-091670","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":467621,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.13209","text":"Publisher Index Page"},{"id":367534,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Erie, Lake Huron, Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.76953125,\n 41.21172151054787\n ],\n [\n -78.75,\n 41.21172151054787\n ],\n [\n -78.75,\n 46.164614496897094\n ],\n [\n -88.76953125,\n 46.164614496897094\n ],\n [\n -88.76953125,\n 41.21172151054787\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"9","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Sussman, Allison L.","contributorId":219074,"corporation":false,"usgs":false,"family":"Sussman","given":"Allison","email":"","middleInitial":"L.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":771216,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gardner, Beth","contributorId":91612,"corporation":false,"usgs":false,"family":"Gardner","given":"Beth","affiliations":[{"id":13553,"text":"University of Washington-Seattle","active":true,"usgs":false}],"preferred":false,"id":771217,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adams, Evan M.","contributorId":139994,"corporation":false,"usgs":false,"family":"Adams","given":"Evan","email":"","middleInitial":"M.","affiliations":[{"id":6928,"text":"BioDiversity Research Institute, Gorham, ME 04038","active":true,"usgs":false}],"preferred":false,"id":771218,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Salas, Leo","contributorId":219075,"corporation":false,"usgs":false,"family":"Salas","given":"Leo","email":"","affiliations":[{"id":17734,"text":"Point Blue Conservation Science","active":true,"usgs":false}],"preferred":false,"id":771219,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kenow, Kevin P. 0000-0002-3062-5197 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Extension","active":true,"usgs":false}],"preferred":false,"id":771221,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mueller, William P.","contributorId":219078,"corporation":false,"usgs":false,"family":"Mueller","given":"William","email":"","middleInitial":"P.","affiliations":[{"id":39958,"text":"Western Great Lakes Bird and Bat Observatory","active":true,"usgs":false}],"preferred":false,"id":771222,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Williams, Kate A.","contributorId":219079,"corporation":false,"usgs":false,"family":"Williams","given":"Kate","email":"","middleInitial":"A.","affiliations":[{"id":37436,"text":"Biodiversity Research Institute","active":true,"usgs":false}],"preferred":false,"id":771223,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Leduc-Lapierre, Michelle","contributorId":219080,"corporation":false,"usgs":false,"family":"Leduc-Lapierre","given":"Michelle","email":"","affiliations":[{"id":13509,"text":"Great Lakes Commission","active":true,"usgs":false}],"preferred":false,"id":771224,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Zipkin, Elise F. 0000-0003-4155-6139","orcid":"https://orcid.org/0000-0003-4155-6139","contributorId":192755,"corporation":false,"usgs":false,"family":"Zipkin","given":"Elise","email":"","middleInitial":"F.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":771225,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70203727,"text":"70203727 - 2019 - Identifying common decision problem elements for the management of emerging fungal diseases of wildlife","interactions":[],"lastModifiedDate":"2019-06-06T14:24:22","indexId":"70203727","displayToPublicDate":"2019-05-11T14:23:35","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3405,"text":"Society and Natural Resources","active":true,"publicationSubtype":{"id":10}},"title":"Identifying common decision problem elements for the management of emerging fungal diseases of wildlife","docAbstract":"Emerging infectious diseases (EIDs) of wildlife have characteristics that make them difficult to manage, leading to reactive and often ineffective management strategies. Currently, two fungal pathogens, Pseudogymnoascus destructans (Pd) and Batrachochytrium salamandrivorans (Bsal), are causing declines in novel host species. To improve the application of management strategies addressing the risk of these pathogens to North American wildlife, we queried wildlife managers about their concerns regarding managing populations of bats and amphibians potentially impacted by Pd and Bsal. Using these responses, we identified aspects of each decision problem that were shared across pathogens, regions and agencies – and found similarities in decision-problem elements for disease management. Reframing management problems as decisions can enable managers to identify similarities across EIDs, i.e. uncertainties within management actions, and improve reactive responses if proactive management is not possible. Such an approach recognizes context-specific constraints and identifies relevant uncertainties that must be reduced in developing a response.","language":"English","publisher":"Taylor and Francis","doi":"10.1080/08941920.2019.1610820","usgsCitation":"Bernard, R.F., and Campbell Grant, E.H., 2019, Identifying common decision problem elements for the management of emerging fungal diseases of wildlife: Society and Natural Resources, v. 32, no. 9, p. 1040-1055, https://doi.org/10.1080/08941920.2019.1610820.","productDescription":"16 p.","startPage":"1040","endPage":"1055","ipdsId":"IP-095794","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":364470,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":364469,"type":{"id":15,"text":"Index Page"},"url":"https://www.tandfonline.com/doi/full/10.1080/08941920.2019.1610820"}],"volume":"32","issue":"9","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2019-05-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Bernard, R. F.","contributorId":216081,"corporation":false,"usgs":false,"family":"Bernard","given":"R.","email":"","middleInitial":"F.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":763838,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":763837,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}