In response to a co-occurring non-native scale infestation and Phragmites australis dieback in southeast Louisiana, normalized difference vegetation index (NDVI) satellite mapping was implemented to track P. australis condition in the lower Mississippi River Delta. While the NDVI mapping successfully documented relative condition changes, identification of cause required a quantitative-biophysical metric directly related to P. australis marsh live vegetation proportion. During this study, a satellite mapping tool that quantified P. australis live fraction cover (LFC) magnitude was designed and implemented. The key to development of the quantitative LFC mapping was the field to satellite calibration design. The calibration of P. australis marsh LFC to optical satellite image data combined field and near-in-time satellite data collections in the fall of 2018 and summer of 2019. Basing the field-NDVI to field-LFC calibrations and the satellite-NDVI to field-NDVI calibrations on combined pre-senescence and peak-growth period data offers nearly year-round LFC mapping. The utility of the developed P. australis marsh LFC mapping tool was demonstrated by the creation of a yearly suite of Mississippi River Delta LFC status and change maps extending from 2009 to 2019. P. australis marsh LFC mapping relies on Sentinel-2 for current to future mapping and relies on Landsat for historical mapping.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201131","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Rangoonwala, A., Howard, R.J., and Ramsey, E.W., III, 2020, Mapping Phragmites australis live fractional cover in the lower Mississippi River Delta, Louisiana (ver. 1.1, January 2021): U.S. Geological Survey Open-File Report 2020–1131, 24 p., https://doi.org/10.3133/ofr20201131.","productDescription":"Report: vii, 24 p.; Data Release","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-119555","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":381145,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ASPB4E","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Phragmites australis live fractional cover yearly map from 2009 to 2019 of the lower Mississippi River Delta using Landsat and Sentinel-2 satellite data"},{"id":381143,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1131/coverthb2.jpg"},{"id":381144,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1131/ofr20201131.pdf","text":"Report","size":"6.69 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1131"},{"id":382663,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2020/1131/versionHist.txt","text":"Version History","size":"4.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2020–1131 version history"}],"country":"United States","state":"Louisiana","otherGeospatial":"Lower Mississippi River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.54544067382812,\n 28.930045059458923\n ],\n [\n -89.000244140625,\n 28.930045059458923\n ],\n [\n -89.000244140625,\n 29.40371231103247\n ],\n [\n -89.54544067382812,\n 29.40371231103247\n ],\n [\n -89.54544067382812,\n 28.930045059458923\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: December 14, 2020; Version 1.1: January 27, 2021","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
700 Cajundome Blvd.
Lafayette, Louisiana 70506
In conservation paradigms, management actions for umbrella species also benefit co‐occurring species because of overlapping ranges and similar habitat associations. The greater sage‐grouse (Centrocercus urophasianus) is an umbrella species because it occurs across vast sagebrush ecosystems of western North America and is the recipient of extensive habitat conservation and restoration efforts that might benefit sympatric species. Biologists' understanding of how non‐target species might benefit from sage‐grouse conservation is, however, limited. Reptiles, in particular, are of interest in this regard because of their relatively high diversity in shrublands and grasslands where sage‐grouse are found. Using spatial overlap of species distributions, land cover similarity statistics, and a literature review, we quantified which reptile species may benefit from the protection of intact sage‐grouse habitat and which may be affected by recent (since about 1990) habitat restoration actions targeting sage‐grouse. Of 190 reptile species in the United States and Canadian provinces where greater sage‐grouse occur, 70 (37%) occur within the range of the bird. Of these 70 species, about a third (11 snake and 11 lizard species) have >10% of their distribution area within the sage‐grouse range. Land cover similarity indices revealed that 14 of the 22 species (8 snake and 6 lizard species) had relatively similar land cover associations to those of sage‐grouse, suggesting greater potential to be protected under the sage‐grouse conservation umbrella and greater potential to be affected, either positively or negatively, by habitat management actions intended for sage‐grouse. Conversely, the remaining 8 species are less likely to be protected because of less overlap with sage‐grouse habitat and thus uncertain effects of sage‐grouse habitat management actions. Our analyses of treatment databases indicated that from 1990 to 2014 there were at least 6,400 treatments implemented on public land that covered approximately 4 million ha within the range of the sage‐grouse and, of that, >1.5 million ha were intended to at least partially benefit sage‐grouse. Whereas our results suggest that conservation of intact sagebrush vegetation communities could benefit ≥14 reptiles, a greater number than previously estimated, additional research on each species' response to habitat restoration actions is needed to assess broader claims of multi‐taxa benefits when it comes to manipulative sage‐grouse habitat management. Published 2020. This article is a U.S. Government work and is in the public domain in the USA.
The brown-headed cowbird (Molothrus ater; cowbird) is unique among North American blackbirds (Icteridae) because it is managed to mitigate the negative effects on endangered songbirds and economic losses in agricultural crops. Cowbird brood parasitism can further affect species that are considered threatened or endangered due to anthropogenic land uses. Historically, cowbirds have often been culled without addressing ultimate causes of songbird population declines. Similar to other North American blackbirds, cowbirds depredate agricultural crops, albeit at a lower rate reported for other blackbird species. Conflicting information exists on the extent of agricultural damage caused by cowbirds and the effectiveness of mitigation measures for application to management. In this paper, we reviewed the progress that has been made in cowbird management from approximately 2005 to 2020 in relation to endangered species. We also reviewed losses to the rice (Oryza sativa) crop attributed to cowbirds and the programs designed to reduce depredation. Of the 4 songbird species in which cowbirds have been managed, both the Kirtland’s warbler (Dendroica kirtlandii) and black-capped vireo (Vireo atricapilla) have been removed from the endangered species list following population increases in response to habitat expansion. Cowbird trapping has ceased for Kirtland’s warbler but continues for the vireo. In contrast, least Bell’s vireo (V. bellii pusillus) and southwestern willow flycatcher (Empidonax traillii extimus) still require cowbird control after modest increases in suitable habitat. Our review of rice depredation by cowbirds revealed models that have been created to determine the number of cowbirds that can be taken to decrease rice loss have been useful but require refinement with new data that incorporate cowbird population changes in the rice growing region, dietary preference studies, and current information on population sex ratios and female cowbird egg laying. Once this information has been gathered, bioenergetic and economic models would increase our understanding of the damage caused by cowbirds.
DGMETA (Dissolved Gas Modeling and Environmental Tracer Analysis) is a Microsoft Excel-based computer program that is used for modeling air-water equilibrium conditions from measurements of dissolved gases and for computing concentrations of environmental tracers that rely on air-water equilibrium model results. DGMETA can solve for the temperature, salinity, excess air, fractionation of gases, or pressure/elevation of water when it is equilibrated with the atmosphere. Models are calibrated inversely using one or more measurements of dissolved gases such as helium, neon, argon, krypton, xenon, and nitrogen. Excess nitrogen gas, originating from denitrification or other sources, also can be included as a fitted parameter or as a separate calculation from the dissolved gas modeling results. DGMETA uses the air-water equilibrium models to separate measured concentrations of gases and isotopes of gases into components that are used for tracing water in the environment. DGMETA calculates atmospheric dry-air mole fractions (mixing ratios) for transient atmospheric gas tracers such as chlorofluorocarbons, sulfur hexafluoride, and bromotrifluoromethane (Halon-1301); and concentrations of tritiogenic helium-3 and radiogenic helium-4, which accumulate from the decay of tritium in water and the decay of uranium and thorium in rocks, respectively.
Sample data can be graphed to identify applicable models of excess air, samples that contain excess nitrogen gas, or samples that have partially degassed, for example. Monte Carlo analysis of errors associated with dissolved gas equilibrium model results can be carried through computations of environmental tracer concentrations to provide robust estimates of error. In addition, graphical routines for separating helium sources using helium isotopes are included to refine estimates of tritiogenic helium-3 when terrigenic helium from mantle or crustal sources is present in samples. Environmental tracer concentrations and their errors computed from DGMETA can be used with other programs, such as TracerLPM (Jurgens and others, 2012), to determine groundwater ages and biogeochemical reaction rates. DGMETA also produces output files in a format that meets the U.S. Geological Survey open data requirements for documentation of model inputs and outputs.
DGMETA is a versatile and adaptable program that allows users to add solubility data for new gases, modify the existing set of gas solubility data, modify the default set of gases used for modeling, choose calculations based on real (non-ideal) gas behavior, and select various concentration units for data entry and results to match laboratory reports and study objectives. DGMETA comes with a set of gases widely used in hydrology and oceanography and many gases include multiple solubilities from previous work. Seventeen dissolved gases are included in the default version of the program: noble gases (helium, neon, argon, krypton, and xenon), reactive gases (nitrogen, oxygen, methane, carbon dioxide, carbon monoxide, hydrogen, and nitrous oxide), and environmental tracers (chlorofluorocarbon-11, chlorofluorocarbon-12, chlorofluorocarbon-113, sulfur hexafluoride, and Halon-1301).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm4F5","collaboration":"National Water Quality Assessment Project","usgsCitation":"Jurgens, B.C., Böhlke, J., Haase, K., Busenberg, E., Hunt, A.G., and Hansen, J.A., 2020, DGMETA (version 1)—Dissolved gas modeling and environmental tracer analysis computer program: U.S. Geological Survey Techniques and Methods 4-F5, 50 p., https://doi.org/10.3133/tm4F5.","productDescription":"Report: viii, 50 p.; Software Release","onlineOnly":"Y","ipdsId":"IP-100912","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":436689,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NQ1RFY","text":"USGS data release","linkHelpText":"DGMETA (Version 1): Dissolved Gas Modeling and Environmental Tracer Analysis Computer Program"},{"id":382045,"rank":3,"type":{"id":35,"text":"Software Release"},"url":"https://code.usgs.gov/cawsc/DGMETA","text":"DGMETA","linkHelpText":"- DGMETA (Dissolved Gas Modeling and Environmental Tracer Analysis) is a Microsoft Excel-based computer program that is used for modeling air-water equilibrium conditions from measurements of dissolved gases and for computing concentrations of environmental tracers that rely on air-water equilibrium model results."},{"id":382038,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/04/f05/coverthb.jpg"},{"id":382039,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/04/f05/tm4f5.pdf","text":"Report","size":"8.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 4-F5"}],"contact":"NAWQA Science Team
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 413
Reston, VA 20192–0002
Bathymetric geoprocessing analyses of the Florida Reef Tract have provided insights into trends of seafloor accretion and seafloor erosion over time and following major storm events. However, bathymetric surveys sometimes capture manmade structures and vegetation, which do not represent the desired bare-earth data. Therefore, ground truthing is essential to maintain the most accurate bathymetric data possible. Field procedures were developed in the Florida Reef Tract in order to quickly and accurately collect consistent imagery and habitat data across variable sites. Areas of significant elevation change were determined through elevation change analyses; these areas were targeted for ground truthing in order to check the reliability of the surveys. This report outlines the standard operating procedures for underwater photographic imagery and habitat data collection, as well as procedures for the storage of these photographs and associated metadata. These standard operating procedures ensure the reproducibility of photographic operations and habitat data collection in future field excursions, enable longitudinal visual comparisons alongside seafloor elevation change analyses, and also have the potential to be applied to similar studies in different coastal environments.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201118","usgsCitation":"Fehr, Z.W., and Yates, K.K., 2020, Underwater photographic reconnaissance and habitat data collection in the Florida Keys—A procedure for ground truthing remotely sensed bathymetric data: U.S. Geological Survey Open-File Report 2020–1118, 13 p., https://doi.org/10.3133/ofr20201118.","productDescription":"vii, 13 p.","numberOfPages":"13","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-114891","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":381619,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1118/ofr20201118.pdf","text":"Report","size":"5.71 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1118"},{"id":381618,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1118/coverthb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Florida Keys","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.53665161132812,\n 25.022150920405707\n ],\n [\n -80.1177978515625,\n 25.022150920405707\n ],\n [\n -80.1177978515625,\n 25.336579097268118\n ],\n [\n -80.53665161132812,\n 25.336579097268118\n ],\n [\n -80.53665161132812,\n 25.022150920405707\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
In 2019, total daily tight oil and gas production increased in the United States month over month, with annualized growth of 14% for oil and 12% for gas. Those gains leveled off in the first quarter of 2020 due to aggressive price competition and increases in international production. Then came the pandemic with a substantially larger dose of economic turmoil, driving down demand due in part to shelter in place orders and safety concerns around travel. Between March and May, tight oil and gas production dropped by nearly 2 million bpd and almost 5 Bcf/day before beginning to recover. Production has continued to increase for the most part through the second half of 2020, but drilling remains subdued throughout most of the U.S. and uncertainty around long term demand along with the current price environment and general state of the economy has contributed to layoffs throughout the industry.
Some shale-gas production has declined recently, but a few areas have seen expansion due to construction of LNG facilities along the East Coast of the U.S. (e.g., the Haynesville Formation). Current U.S. shale-gas production is still higher now than in 2019, with daily production of almost 71 Bcf as of October 2020 driven in large part by increased production from the Marcellus Shale in the Appalachian Basin and shales within the Permian Basin. Shale liquids production is down by around a million bpd to approximately 7.1 million (September 2020; U.S. EIA) from pre-pandemic production levels at the end of 2019 and beginning of 2020. Tight oil production remains dominated by plays in the Permian Basin as well as the Bakken and Eagle Ford Formations.
On the development and production front, new enhanced oil recovery approaches for tight shale reservoirs are being more widely implemented. Natural gas or CO2 injection is currently being utilized in the Bakken Formation, Eagle Ford Formation, Anadarko Basin, and the Permian Basin to optimize injection sequences and boost recovery. Refracturing of existing wells to reduce drilling costs, improve production, and prolong well productive life has also begun to occur more widely in developed plays.
International interest in exploiting hydrocarbons from unconventional reservoirs continues to develop, with active exploration projects on most continents. Europe remains relatively underexplored as compared to North America, although a total of 141 exploration and appraisal wells with a possible shale-gas exploration component have been spudded, including horizontal legs from vertical wells. Shale exploration has made a breakthrough in China with shale gas output in 2019 of 10 billion cubic meters (35.3 Bcf), 60% of which was produced from Sinopec’s Fuling Shale Gas field. Lacustrine shale oil exploration has also been successful in the Sichuan and Ordos Basins in central China, Junggar and Tarim Basins in northwest China, and Songliao Basin in north China, and Bohai Bay Basins in northeast China as of 2018.
South America’s potential as an unconventional shale gas and oil province is mainly in Argentina and Brazil, where the production from Neuquen Basin’s tight shale of the Vaca Muerta Formation has been steadily increasing since 2016, but only 4% of the shale resource has been developed thus far. According to International Energy Agency’s report in 2013, Brazil holds the 9th largest unconventional gas reserves. Brazil has shale oil and gas potential in the Parana, Solimoes and Amazon Basins and is actively producing from the oil shale unit of the Irati Formation. In 2019, the Brazil energy ministry launched REATE 2020 to boost onshore investments that include the expectation of drilling an experimental unconventional well in the northeast region.
For this inaugural report, the new AAPG EMD Tight Oil and Gas Committee (TO&G; formerly the Shale Gas & Liquids and Tight Gas Sands committees) has developed new commodity report requirements for contributors. This includes shorter annual reports focused on new developments, play concepts, along with the typical updates on production and new drilling in the play areas they cover. We are also asking contributors to collect background geologic and production related information into a document that summarizes important features of the plays they cover that will be stored on the TO&G webpage along with our commodity reports.
TO&G is currently working to expand the number of contributors to cover more play areas and replace committee and advisory board members that have recently stepped down. Changes to committee leadership occurred in October as recent chairs transition to EMD elected positions.
Biodiversity metrics are frequently used to guide conservation planning because they can summarize biogeographical attributes of plant and animal communities quickly and at multiple scales. Attributes include habitat features of high conservation value, representativeness, and redundancy of biological communities. We conducted a rapid ecological assessment of resident avian species in the west-central mountainous region of Puerto Rico in 2015, a landscape dominated by coffee cultivation. We focused on this landscape because shade-grown and restored shade-grown coffee plantations offer an opportunity to complement protected habitat (e.g., reserves) to enhance species persistence. We used species richness, which tallies the number of unique species, and a quadratic entropy index of diversity, which incorporates interspecific taxonomic differentiation to evaluate species representativeness and redundancy across sun- and shade-grown coffee plantations and secondary forest. We surveyed 120 sites, calculating both metrics using species-specific occupancy probabilities estimated from community-level occupancy models. Species representativeness and redundancy were high as neither metric was able to discriminate among habitat types, possibly because plant communities were redundant, and the avian community was dominated by species adept at exploiting altered habitats. Similarly, we could not discriminate among avian communities modeling each biodiversity metric as a function of site-specific habitat covariates. Our findings and available knowledge on avian community demographics suggest that conservation strategies could couple protected habitat (e.g., reserves) and restored habitat (e.g., coffee plantations) to enhance species diversity and persistence across human-modified landscapes.
","language":"English","publisher":"Eagle Hill Publications","usgsCitation":"Battle, K.E., Pacifici, K., Collazo, J.A., and Reigh, B.J., 2020, Using biodiversity metrics to guide conservation planning in altered tropical landscapes: Caribbean Naturalist, v. 77.","ipdsId":"IP-088027","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":394983,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"77","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Battle, K. E.","contributorId":272295,"corporation":false,"usgs":false,"family":"Battle","given":"K.","email":"","middleInitial":"E.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":831924,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pacifici, Krishna","contributorId":244494,"corporation":false,"usgs":false,"family":"Pacifici","given":"Krishna","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":831925,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collazo, Jaime A. 0000-0002-1816-7744","orcid":"https://orcid.org/0000-0002-1816-7744","contributorId":217287,"corporation":false,"usgs":true,"family":"Collazo","given":"Jaime","email":"","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":831926,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reigh, B. J.","contributorId":272296,"corporation":false,"usgs":false,"family":"Reigh","given":"B.","email":"","middleInitial":"J.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":831927,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70236941,"text":"70236941 - 2020 - Response of the tallest California building during the Mw7.1 July 5, 2019 Ridgecrest, California earthquake","interactions":[],"lastModifiedDate":"2022-09-29T16:35:21.297382","indexId":"70236941","displayToPublicDate":"2020-12-31T11:34:52","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"title":"Response of the tallest California building during the Mw7.1 July 5, 2019 Ridgecrest, California earthquake","docAbstract":"The 73-story Wilshire Grand in downtown Los Angeles is the recently constructed tallest building in California. It is designed in conformance with performance-based design procedures. The lateral load resisting system of the building is designed with concrete core shear walls, three outriggers with buckling restrained braces (BRBs) located along the height and two three-story truss-belt structural systems. The building is equipped with a 36-channel accelerometric seismic monitoring array that recorded the recent Mw7.1 Ridgecrest earthquake of July 5, 2019, as well as the Mw6.4 July 4, 2019 Ridgecrest Earthquake. In this paper, only the Mw7.1 July 5, 2019 event is studied because of a larger response of the subject building during that earthquake. The earthquake records of July 5, 2019 are specifically studied to determine its dynamic characteristics and building specific behavior. The structure exhibits torsional behavior most likely due to abrupt asymmetrical changes in the thickness and size in-plan of the core shear wall system. Modal shapes, frequencies and critical damping percentages of the building are identified. The translational and torsional modes during the earthquake are not closely coupled with fundamental NS, EW and torsional frequencies (periods) of 0.16 (6.25), 0.27(3.70) and 0.42 (2.38) Hz (seconds). This does not lead to a beating effect even though there is an appearance of it in the displacement records. Due to the relatively low amplitude of shaking during the earthquake, the drift ratios are too small to cause any damage. It is expected that during stronger shaking levels likely to be caused by future events, these characteristics may change and the effect of BRB’s can be better assessed.","conferenceTitle":"17th World Conference on Earthquake Engineering","conferenceDate":"Sept. 13-18, 2020","conferenceLocation":"Sendai, Japan","language":"English","publisher":"International Association for Earthquake Engineering","usgsCitation":"Celebi, M., Ghahari, S., Haddadi, H., and Taciroglu, E., 2020, Response of the tallest California building during the Mw7.1 July 5, 2019 Ridgecrest, California earthquake, 17th World Conference on Earthquake Engineering, Sendai, Japan, Sept. 13-18, 2020, C000253.","productDescription":"C000253","ipdsId":"IP-114622","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":407616,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Los Angeles","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.2613956928253,\n 34.04933483636836\n ],\n [\n -118.25936794281006,\n 34.04933483636836\n ],\n [\n -118.25936794281006,\n 34.05107714851305\n ],\n [\n -118.2613956928253,\n 34.05107714851305\n ],\n [\n -118.2613956928253,\n 34.04933483636836\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Celebi, Mehmet 0000-0002-4769-7357 celebi@usgs.gov","orcid":"https://orcid.org/0000-0002-4769-7357","contributorId":200969,"corporation":false,"usgs":true,"family":"Celebi","given":"Mehmet","email":"celebi@usgs.gov","affiliations":[],"preferred":true,"id":852751,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ghahari, S. F.","contributorId":296773,"corporation":false,"usgs":false,"family":"Ghahari","given":"S. F.","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":852752,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haddadi, Hamid","contributorId":296690,"corporation":false,"usgs":false,"family":"Haddadi","given":"Hamid","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":852753,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Taciroglu, Ertugrul","contributorId":176616,"corporation":false,"usgs":false,"family":"Taciroglu","given":"Ertugrul","email":"","affiliations":[],"preferred":false,"id":852754,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216078,"text":"70216078 - 2020 - North Atlantic right whale (Eubalaena glacialis) scenario planning summary report","interactions":[],"lastModifiedDate":"2021-10-01T16:33:48.598484","indexId":"70216078","displayToPublicDate":"2020-12-31T11:15:50","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5145,"text":"Technical Memorandum","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"MNFS-OPR-68","displayTitle":"North Atlantic right whale (Eubalaena glacialis) scenario planning summary report","title":"North Atlantic right whale (Eubalaena glacialis) scenario planning summary report","docAbstract":"Scenario planning provides a structured framework that can be used in strategic planning to help manage risk and prioritize actions (Schwartz 1996; Peterson et al. 2003). By providing a mechanism to communicate about complex situations, scenario planning encourages “out-of-the-box” thinking to help groups assess the impacts of plausible future scenarios on a target or resource. The outcomes from scenario planning can be used to improve management decisions, highlight data gaps, and/or identify future science priorities (Star et al. 2015; Borggaard et al. 2019).\nThe application of scenario planning by resource management organizations (e.g., Borggaard et al. 2019; Runyon et al. 2020; Star et al. 2015) and the urgency surrounding the recovery of the critically endangered North Atlantic right whale (Eubalaena glacialis), led to a 2018 NOAA Fisheries scenario planning initiative for the species. In addition to complementing the many management and conservation efforts already underway, this initiative was designed to address the uncertainties around future anthropogenic and environmental changes and how these uncertainties may impact species recovery.\nWe used a scenario planning framework to explore plausible future conditions for North Atlantic right whales and to develop possible options to address those conditions and improve recovery. Specific objectives were to: 1) better understand the challenges of right whale management in a changing climate; 2) identify potential research activities and recovery needs across the species’ range; 3) increase coordination and collaboration related to recovery efforts; and 4) explore how scenario planning can be used to support decisions.\nUsing projected changes in ocean conditions coupled with anthropogenic stressors, we built four plausible future scenarios for right whales. These scenarios helped identify priority research and management actions that NOAA Fisheries and our partners can undertake to improve right whale recovery. We identified priority actions related to science, management, and partnerships including, but not limited to, 1) research on shifting spatial and temporal distributions of right whales and prey in a changing climate; 2) development of technology to further reduce impacts from human activities; 3) continuation of ongoing management efforts related to vessel traffic and fishing; and 4) continued maintenance of existing and development of new partnerships (e.g., industry engagement in problem solving).\nThis scenario planning exercise helped prioritize North Atlantic right whale management and science needs in light of changing ocean conditions and anthropogenic impacts. It can also serve as a reference for how NOAA Fisheries and its partners can better prepare for multiple plausible futures while complementing other on-going initiatives. Priorities identified here can be considered in conjunction with implementation and monitoring actions such as with the Atlantic Large Whale Take Reduction Team (ALWTRT) and/or regional Right Whale U.S. Implementation Teams. The framework can also be repeated and improved upon as additional information becomes available to support future exercises.","language":"English","publisher":"NOAA","usgsCitation":"Borggaard, D., Dick, D., Star, J., Zoodsma, B., Alexander, M., Asaro, M.J., Barre, L., Bettridge, S., Burns, P., Crocker, J., Dortch, Q., Garrison, L., Gulland, F., Haskell, B., Hayes, S., Henry, A., Hyde, K., Milliken, H., Morin, D., Quinlan, J., Rowles, T., Saba, V., Staudinger, M., and Walsh, H., 2020, North Atlantic right whale (Eubalaena glacialis) scenario planning summary report: Technical Memorandum MNFS-OPR-68, 94 p.","productDescription":"94 p.","ipdsId":"IP-122509","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science 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Commercial pesticide applicators, farmers, and homeowners apply about 1.1 billion pounds of pesticides annually to agricultural land, non-crop land, and urban areas throughout the United States. Although intended for beneficial uses, there are also risks associated with pesticide applications, including contamination of groundwater and surface-water resources, which can adversely affect aquatic life and water supplies. Pesticides can contaminate groundwater and surface water directly through point sources (spills, disposal sites, or pesticide drift during an application). The main avenue of contamination, however, is indirect by non-point sources, which include agricultural and urban runoff, erosion, leaching from application sites, and precipitation that has become contaminated by upwind applications.
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\"}}]}","contact":"Director, Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Road
Carson City, Nevada 89701
Acidic deposition is the result of upwind sulfur (S) and nitrogen (N) emissions into the atmosphere from human activities. Environmental impacts from acidic deposition across forested landscapes include acidification of soil and drainage water, depletion of available soil nutrient bases, and impacts to and changes in forest and aquatic species composition and biodiversity. Acidic deposition can mobilize aluminum (Al) from soil-to-soil solution and subsequently to drainage water in forms that can be toxic to aquatic life. When exposed to decreasing levels of acidic deposition, which has been occurring in New York since the late 1970s, some soils and drainage waters have become gradually less acidic. Remaining questions relate to effects on stream resources, anticipated resource recovery under increasingly lower levels of deposition, and the levels of deposition (target loads, TLs) needed to reach a range of stream ecosystem recovery targets. Environmental scientists commonly estimate thresholds of air pollutant emissions and resulting atmospheric deposition at which adverse ecological effects are manifested. This analysis is often done using critical loads (CL) and/or TLs, using approaches that account for the spatial and temporal aspects of acidification and recovery. Exceedance represents the extent to which current levels of acidic deposition exceed the level expected to cause ecological harm. The research reported here is intended to help address S and N deposition TLs and ecosystem recovery of Adirondack streams, a resource that has been less thoroughly investigated than lakes. The overarching goal of this work is to highlight key considerations that will help inform decision-makers and ecosystem managers who are responsible for environmental policy in New York State and beyond. Salient aspects of stream TL modeling are discussed with an aim of informing not only scientists, but also policymakers, ecosystem managers, and nonscientists who are required to make decisions related to the effects of acidic deposition on natural ecosystems. Analyses reported herein quantify relations among chemical indicators and metrics of fish community health and biodiversity in streams of the Adirondack Park. This information is used to indicate levels of atmospheric deposition necessary to alleviate harmful effects on fish populations. Results of this investigation provide a framework that can be applied to better understand how modeled stream acid neutralizing capacity (ANC) values that are developed to support TL investigations can be adjusted to reflect high-flow ANC values that may be associated with toxic conditions. Since process models are often calibrated to a low-flow or average flow condition, the magnitude and spatial extent of TL exceedances increase substantially when episodic acidification is considered.
","language":"English","publisher":"New York State Energy Research and Development Authority","usgsCitation":"Driscoll, C., Shao, S., Sullivan, T.J., McDonnell, T.C., Baldigo, B.P., Burns, D., and Lawrence, G.B., 2020, The response of streams to changes in atmospheric deposition of sulfur and nitrogen in the Adirondack Mountains: Final Report 20-19, 166 p.","productDescription":"166 p.","ipdsId":"IP-103637","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":390128,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":390127,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.nyserda.ny.gov/-/media/Files/Publications/Research/Environmental/20-19-Responses-of-Streams-in-the-Adirondack-Mountains.pdf"}],"country":"United States","state":"New York","otherGeospatial":"Adirondack Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.00390625,\n 43.11702412135048\n ],\n [\n -73.41064453125,\n 43.44494295526125\n ],\n [\n -73.3447265625,\n 44.000717834282774\n ],\n [\n -73.32275390625,\n 44.32384807250689\n ],\n [\n -73.6083984375,\n 44.84029065139799\n ],\n [\n -74.014892578125,\n 44.933696389694674\n ],\n [\n -74.564208984375,\n 44.793530904744074\n ],\n [\n -75.091552734375,\n 44.53567453241317\n ],\n [\n -75.487060546875,\n 44.06390660801779\n ],\n [\n -75.35522460937499,\n 43.492782808225\n ],\n [\n -74.893798828125,\n 43.18114705939968\n ],\n [\n -74.520263671875,\n 43.068887774169625\n ],\n [\n -74.00390625,\n 43.11702412135048\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Driscoll, Charles T.","contributorId":240874,"corporation":false,"usgs":false,"family":"Driscoll","given":"Charles T.","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":803731,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shao, Shuai","contributorId":222597,"corporation":false,"usgs":false,"family":"Shao","given":"Shuai","email":"","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":803735,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sullivan, Timothy J.","contributorId":196720,"corporation":false,"usgs":false,"family":"Sullivan","given":"Timothy","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":803732,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McDonnell, Todd C.","contributorId":127622,"corporation":false,"usgs":false,"family":"McDonnell","given":"Todd","email":"","middleInitial":"C.","affiliations":[{"id":7087,"text":"Scientist, E&S Environmental Chemistry Inc, Corvallis OR","active":true,"usgs":false}],"preferred":false,"id":803736,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baldigo, Barry P. 0000-0002-9862-9119 bbaldigo@usgs.gov","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":1234,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","email":"bbaldigo@usgs.gov","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":803733,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Burns, Douglas A. 0000-0001-6516-2869","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":202943,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas A.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":803734,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lawrence, Gregory B. 0000-0002-8035-2350 glawrenc@usgs.gov","orcid":"https://orcid.org/0000-0002-8035-2350","contributorId":867,"corporation":false,"usgs":true,"family":"Lawrence","given":"Gregory","email":"glawrenc@usgs.gov","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":803737,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70217210,"text":"70217210 - 2020 - Potentiometric surface maps of selected confined aquifers in southern Maryland and Maryland's eastern shore, 2019","interactions":[],"lastModifiedDate":"2021-09-30T15:54:38.216304","indexId":"70217210","displayToPublicDate":"2020-12-31T10:47:46","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":128,"text":"Open-File Report","active":false,"publicationSubtype":{"id":2}},"seriesNumber":"20-02-01","title":"Potentiometric surface maps of selected confined aquifers in southern Maryland and Maryland's eastern shore, 2019","docAbstract":"This report presents potentiometric-surface maps of the Aquia and Magothy aquifers and the Upper Patapsco, Lower Patapsco, and Patuxent aquifer systems using water levels measured during the fall season of 2019. The potentiometric surface maps show water levels ranging from 56 feet above sea level to 163 feet below sea level in the Aquia aquifer, from 87 feet above sea level to 119 feet below sea level in the Magothy aquifer, from 114 feet above sea level to 120 feet below sea level in the Upper Patapsco aquifer system, from 136 feet above sea level to 174 feet below sea level in the Lower Patapsco aquifer system, and from 168 feet above sea level to 184 feet below sea level in the Patuxent aquifer system.
Cones of depression have formed around locations with significant aquifer withdrawals. The Aquia aquifer has depressed water levels around well fields at Lexington Park, Solomons Island, and central Talbot County. Cones of depression have formed in the Magothy aquifer around well fields at Waldorf, Arnold, and Easton. The Upper Patapsco aquifer system has depressed water levels around well fields in the Annapolis-Arnold area, Waldorf, the Lexington Park-Leonardtown area, and at Easton. The Lower Patapsco aquifer system has depressed water levels around well fields at Severndale, Broad Creek, Arnold, and Crofton Meadows as well as in central and western Charles County. Cones of depression have formed in the Patuxent aquifer system around well fields at Dorsey Road, Crofton, Arnold, northwestern Charles County, and at the Chalk Point power plant.
","language":"English","publisher":"Maryland Department of Natural Resources","usgsCitation":"Staley, A.W., Andreasen, D.C., and Marchand, E.H., 2020, Potentiometric surface maps of selected confined aquifers in southern Maryland and Maryland's eastern shore, 2019: Open-File Report 20-02-01, iii, 37 p.","productDescription":"iii, 37 p.","ipdsId":"IP-120572","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":390041,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":390040,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.mgs.md.gov/reports/OFR_20-02-01.pdf"}],"country":"United 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\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Staley, Andrew W.","contributorId":178867,"corporation":false,"usgs":false,"family":"Staley","given":"Andrew","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":808011,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andreasen, David C.","contributorId":178868,"corporation":false,"usgs":false,"family":"Andreasen","given":"David","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":808012,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marchand, Elizabeth H. 0000-0003-2291-6282","orcid":"https://orcid.org/0000-0003-2291-6282","contributorId":247604,"corporation":false,"usgs":true,"family":"Marchand","given":"Elizabeth","email":"","middleInitial":"H.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808013,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70220610,"text":"70220610 - 2020 - Council monitoring and assessment program (CMAP): Common monitoring program attributes and methodologies for the Gulf of Mexico Region","interactions":[],"lastModifiedDate":"2021-05-21T15:45:26.898403","indexId":"70220610","displayToPublicDate":"2020-12-31T10:37:21","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5134,"text":"NOAA Technical Memorandum","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"285","title":"Council monitoring and assessment program (CMAP): Common monitoring program attributes and methodologies for the Gulf of Mexico Region","docAbstract":"Executive Summary Under the Resources and Ecosystem Sustainability, Tourist Opportunities, and Revived Economies of the Gulf Coast States Act of 2012 (RESTORE Act), the Gulf Coast Ecosystem Restoration Council (RESTORE Council or Council) is required to report on the progress of funded projects and programs. Systematic monitoring of restoration at the project-specific and programmatic-levels (i.e., watershed and Gulf of Mexico) enables consistent reporting and gives the public confidence that the restoration investments selected by the RESTORE Council will be evaluated and adaptively managed accordingly. Monitoring information that has been collected at different spatial and temporal scales can be used as the foundation to illustrate progress towards comprehensive ecosystem restoration goals and objectives that promote holistic Gulf of Mexico recovery (see ‘RESTORE Council Background’ at the beginning of this report for additional Council information).
Federal, state and local agencies, universities, private industry, and non-governmental organizations (NGOs) have conducted and are conducting extensive monitoring activities around the Gulf of Mexico. In addition, each RESTORE Council-funded project will, at a minimum, perform project-specific monitoring. This collection of monitoring activities was inventoried and compiled into a framework of tools and resources by the Council-funded RESTORE Council Monitoring and Assessment Program (CMAP). CMAP was designed and funded to inventory and integrate existing water quality and habitat monitoring and mapping efforts to support discovery and accessibility of existing monitoring data and ensure the collected information is made available to support management decisions. Results of CMAP Inventory queries can be used to identify opportunities for efficiencies and support crossprogram review of performance across Gulf of Mexico ecosystem recovery efforts.
The fundamental approach being used to inform the build out of the CMAP Gulf of Mexico water quality monitoring, habitat monitoring, and mapping framework includes: 1. Adopt, or construct as needed, a comprehensive inventory of existing habitat and water quality observation, monitoring, and mapping programs in the Gulf of Mexico (hereafter referred to as the “Inventory”; NOAA and USGS, 2019a); 2. Evaluate the suitability/applicability of each program and its existing and prospective data for use in restoration activities; 3. Develop a process to use the Inventory to conduct gap assessments; 4. Develop a catalog of baseline assessments conducted in the Gulf of Mexico (NOAA and USGS, 2019b); and 5. Develop a searchable monitoring information portal/database to enable access to collected information and products.
","language":"English","publisher":"National Oceanic and Atmospheric Administration (NOAA)","doi":"10.25923/vxay-xz10","usgsCitation":"Bosch, J., Burkart, H.B., Chivoiu, B., Clark, R., Clement, C., Enwright, N., Giordano, S., Jeffrey, C., Johnson, E., Hart, R., Hile, S.D., Howell, J.S., Laurenzano, C., Lee, M., McCloskey, T., McTigue, T., Meyers, M.B., Miller, K.E., Mize, S., Monaco, M.E., Owen, K., Rebich, R., Rendon, S.H., Robertson, A., Sample, T., Sanks, K.M., Steyer, G., Suir, K., Swarzenski, C.M., and Thurman, H.R., 2020, Council monitoring and assessment program (CMAP): Common monitoring program attributes and methodologies for the Gulf of Mexico Region: NOAA Technical Memorandum 285, ii, 87 p., https://doi.org/10.25923/vxay-xz10.","productDescription":"ii, 87 p.","ipdsId":"IP-120968","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research 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","language":"English","publisher":"U.S. Bureau of Reclamation","usgsCitation":"Pasley, N.K., 2020, Identifying and assessing priority transboundary aquifers along the United States- Mexico border: CCAST Case Study on Actionable Science, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-123237","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":397397,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":394960,"type":{"id":15,"text":"Index Page"},"url":"https://usbr.maps.arcgis.com/apps/MapSeries/index.html?appid=659fa1717014452aa67e88e228e28c12"}],"country":"Mexico, United States","state":"Chihuahua, New Mexico, Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.5341796875,\n 30.44867367928756\n ],\n [\n -104.69970703125,\n 30.44867367928756\n ],\n [\n -104.69970703125,\n 32.194208672875384\n ],\n [\n -107.5341796875,\n 32.194208672875384\n ],\n [\n -107.5341796875,\n 30.44867367928756\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pasley, Nathaniel Kyle 0000-0001-7441-495X","orcid":"https://orcid.org/0000-0001-7441-495X","contributorId":272301,"corporation":false,"usgs":true,"family":"Pasley","given":"Nathaniel","email":"","middleInitial":"Kyle","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":831941,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70216569,"text":"70216569 - 2020 - An analysis of Twitter responses to the 2019 Ridgecrest Earthquake sequence","interactions":[],"lastModifiedDate":"2021-10-04T11:52:22.142345","indexId":"70216569","displayToPublicDate":"2020-12-31T10:03:26","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"An analysis of Twitter responses to the 2019 Ridgecrest Earthquake sequence","docAbstract":"Previous research has shown that online social networks can provide valuable insights regarding collective human responses to extreme natural events, such as earthquakes. Most previous studies focused on one large earthquake, while the 2019 Ridgecrest earthquakes involved two significant earthquakes occurring within a short period of time (a M6.4 foreshock on July 4 and a M7.1 mainshock on July 5 in southern California). These earthquakes were the first time in more than a decade that the southern California region, with an estimated population of 15 million, felt light to moderate shaking over an extended period of time. This valuable opportunity allows us to study how people respond dynamically to such sequences of extreme events. We collected 510,579 tweets about the 2019 Ridgecrest earthquakes to answer the following research questions: (1) Which Twitter accounts were the major players? Did they behave differently and get different responses? (2) How did the publics' response change during these sequential earthquakes? and (3) Which earthquake-related rumors were disseminated on Twitter during the earthquake sequence, by whom, and at what time?
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"2020 IEEE International Conference on Parallel and Distributed Processing with Applications, Big Data & Cloud Computing","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"2020 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom)","conferenceDate":"December 17-19, 2020","conferenceLocation":"Exeter, United Kingdom","language":"English","publisher":"International Conference on Social Computing and Networking","doi":"10.1109/ISPA-BDCloud-SocialCom-SustainCom51426.2020.00127","usgsCitation":"Ruan, T., Kong, Q., Zhang, Y., McBride, S., and Lv, Q., 2020, An analysis of Twitter responses to the 2019 Ridgecrest Earthquake sequence, in 2020 IEEE International Conference on Parallel and Distributed Processing with Applications, Big Data & Cloud Computing, Exeter, United Kingdom, December 17-19, 2020, p. 810-818, https://doi.org/10.1109/ISPA-BDCloud-SocialCom-SustainCom51426.2020.00127.","productDescription":"9 p.","startPage":"810","endPage":"818","ipdsId":"IP-118686","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":390122,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Ridgecrest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.157958984375,\n 35.42486791930558\n ],\n [\n -117.3614501953125,\n 35.42486791930558\n ],\n [\n -117.3614501953125,\n 35.92464453144099\n ],\n [\n -118.157958984375,\n 35.92464453144099\n ],\n [\n -118.157958984375,\n 35.42486791930558\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ruan, Tao 0000-0002-6718-7223","orcid":"https://orcid.org/0000-0002-6718-7223","contributorId":245222,"corporation":false,"usgs":false,"family":"Ruan","given":"Tao","email":"","affiliations":[{"id":12502,"text":"University of Colorado - Boulder","active":true,"usgs":false}],"preferred":false,"id":805648,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kong, Qingkai 0000-0002-7399-0661","orcid":"https://orcid.org/0000-0002-7399-0661","contributorId":245223,"corporation":false,"usgs":false,"family":"Kong","given":"Qingkai","email":"","affiliations":[{"id":6643,"text":"University of California - Berkeley","active":true,"usgs":false}],"preferred":false,"id":805649,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhang, Yawen 0000-0002-6867-0399","orcid":"https://orcid.org/0000-0002-6867-0399","contributorId":245225,"corporation":false,"usgs":false,"family":"Zhang","given":"Yawen","email":"","affiliations":[{"id":12502,"text":"University of Colorado - Boulder","active":true,"usgs":false}],"preferred":false,"id":805650,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McBride, Sara K. 0000-0002-8062-6542","orcid":"https://orcid.org/0000-0002-8062-6542","contributorId":206933,"corporation":false,"usgs":true,"family":"McBride","given":"Sara K.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":805651,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lv, Qin","contributorId":245227,"corporation":false,"usgs":false,"family":"Lv","given":"Qin","email":"","affiliations":[{"id":12502,"text":"University of Colorado - Boulder","active":true,"usgs":false}],"preferred":false,"id":805652,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70216703,"text":"70216703 - 2020 - Assessing the state of water resource knowledge and tools for future planning in the lower Rio Grande-Rio Bravo Basin","interactions":[],"lastModifiedDate":"2021-10-01T14:53:10.862751","indexId":"70216703","displayToPublicDate":"2020-12-31T09:51:38","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":9366,"text":"CCAST Case Study on Actionable Science","active":true,"publicationSubtype":{"id":1}},"title":"Assessing the state of water resource knowledge and tools for future planning in the lower Rio Grande-Rio Bravo Basin","docAbstract":"The Rio Grande/Rio Bravo Basin (hereinafter referred to as the Rio Grande) is a transboundary basin, with the Rio Grande forming the border between the United States and Mexico for approximately 2,034 km. The waters of the Rio Grande serve as a critical drinking source for 13 million people, connecting numerous population centers representing diverse backgrounds and cultures along its length. Cross-border ecosystems and communities make water management strategies particularly challenging. With different regulations and societal interests in the two countries, developing effective water-management strategies is challenging and requires the coordination of diverse interested parties representing different government agencies, institutions, and stakeholder groups with varying and sometimes conflicting objectives. To better evaluate the human and environmental water needs (environmental flows) of this constrained river system, an improved understanding of past and present water management objectives, policies, allocation practices, and water use is needed.
","language":"English","publisher":"Collaborative Conservation and Adaptation Strategy Toolbox (CCAST)","usgsCitation":"Casarez, I.R., Sandoval-Solis, S., and Ortiz-Partida, J.P., 2020, Assessing the state of water resource knowledge and tools for future planning in the lower Rio Grande-Rio Bravo Basin: CCAST Case Study on Actionable Science, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-123346","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":390121,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":390120,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://usbr.maps.arcgis.com/apps/MapSeries/index.html?appid=fdb848b819c94e2e8b1a800e7a5fc54c"}],"country":"Mexico, United States","otherGeospatial":"Lower Rio Grande-Río Bravo Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.80859375,\n 30.29701788337205\n ],\n [\n -104.67773437499999,\n 30.29701788337205\n ],\n [\n -104.67773437499999,\n 32.10118973232094\n ],\n [\n -108.80859375,\n 32.10118973232094\n ],\n [\n -108.80859375,\n 30.29701788337205\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Casarez, Ilana Renae 0000-0001-7690-3802","orcid":"https://orcid.org/0000-0001-7690-3802","contributorId":228961,"corporation":false,"usgs":true,"family":"Casarez","given":"Ilana","email":"","middleInitial":"Renae","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":805942,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sandoval-Solis, Samuel 0000-0003-0329-3243","orcid":"https://orcid.org/0000-0003-0329-3243","contributorId":257770,"corporation":false,"usgs":false,"family":"Sandoval-Solis","given":"Samuel","email":"","affiliations":[{"id":7082,"text":"University of California - Davis","active":true,"usgs":false}],"preferred":false,"id":824529,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ortiz-Partida, Jose P.","contributorId":266181,"corporation":false,"usgs":false,"family":"Ortiz-Partida","given":"Jose","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":824530,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70217611,"text":"70217611 - 2020 - Coastal permafrost erosion","interactions":[],"lastModifiedDate":"2021-01-25T15:43:05.846253","indexId":"70217611","displayToPublicDate":"2020-12-31T09:40:26","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":7564,"text":"Arctic Report Card","active":true,"publicationSubtype":{"id":1}},"title":"Coastal permafrost erosion","docAbstract":"Highlights
• Since the early 2000s, erosion of permafrost coasts in the Arctic has increased at 13 of 14 sites with observational data that extend back to ca. 1960 and ca. 1980, coinciding with warming temperatures, sea ice reduction, and permafrost thaw.
• Permafrost coasts along the US and Canadian Beaufort Sea experienced the largest increase in erosion rates in the Arctic, ranging from +80 to +160%, when comparing average rates from the last two decades of the 20th century with the first two decades of the 21st century.
• The initiation of several national and international research networks in recent years has enabled closer coordination and collaboration of measurements and a better understanding of pan-Arctic permafrost coastal dynamics.
The Dog River and northern part of the Badger Lake 7.5' quadrangles encompasses an area of ~201 km2 (77.6 mi2) of the High Cascades of north-central Oregon, lying across the eastern slopes of Mount Hood volcano (Figure 1-1; Plate 1; referred to herein as Dog River–Badger Lake area). Mount Hood, known as Wy’east to Native Americans, is Oregon’s tallest peak (3,427 m [11,241 ft]). The volcano has erupted episodically for the past 500,000 years, experiencing two major eruptive periods during the last 1,500 years (Scott and others, 1997a; Scott and others, 2003; Scott and Gardner, 2017). Cascade Range volcanism and structural development in the area dates back longer, with eruptive activity dating from latest Miocene to recent time; part of that volcano-tectonic record is detailed by new high-resolution geologic mapping presented here.
The geology of the Dog River–Badger Lake area was mapped by the Oregon Department of Geology and Mineral Industries (DOGAMI) between 2017 and 2020, in collaboration with geoscientists from the U. S. Geological Survey Cascade Volcano Observatory (USGS CVO) and Hamilton College, New York. The primary objective of this investigation is to provide an updated and spatially accurate geologic framework for the Dog River–Badger Lake area as part of a multi-year study of the geology of the larger Middle Columbia Basin (Figure 1-1, Figure 1-2). Additional key objectives of this project are to: 1) determine the geologic history of volcanic rocks in this part of the northern Oregon Cascade Range, including lava flows and volcaniclastic deposits erupted from Middle Pleistocene to Holocene Mount Hood volcano; 2) provide significant new details about the structure and fault history along the northern segment of the High Cascades intra-arc graben (Hood River graben); and 3) better understand geologic hazards in the region, related to earthquakes, volcanoes, and landslides. New detailed geologic data presented here also provides a basis for future geologic, geohydrologic, and geohazard studies in the greater Middle Columbia Basin. Detailed geologic mapping in this part of the Middle Columbia Basin is a high priority of the Oregon Geologic Map Advisory Committee (OGMAC), supported in part by grants from the STATEMAP component of the USGS National Cooperative Geologic Mapping Program (G17AC00210, G19AC00160). Additional funds were provided by the State of Oregon.
The core products of this study are this report, an accompanying geologic map and cross sections (Plate 1), an Esri ArcGIS™ geodatabase, and Microsoft Excel® spreadsheets tabulating point data for geochemistry, geochronology, magnetic polarity, orientation points, and well data. The geodatabase presents the new geologic mapping in a digital format consistent with the USGS National Cooperative Geologic Mapping Program Geologic Map Schema (GeMS) (U.S. Geological Survey National Cooperative Geologic Mapping Program, 2020). This geodatabase contains spatial information, including geologic polygons, contacts, structures, geochemistry, geochronology, magnetic observation, orientation points, and well data, as well as data about each geologic unit such as age, lithology, mineralogy, and structure. Digitization at scales of 1:8,000 or better was accomplished using a combination of high-resolution lidar topography and imagery. Surficial and bedrock geologic units contained in the geodatabase are depicted on the Plate 1 at a scale of 1:24,000. Both the geodatabase and geologic map are supported by this report describing the geology in detail.
","language":"English","publisher":"Oregon Department of Geology and Mineral Industries","usgsCitation":"McClaughry, J.D., Scott, W., Duda, C.J., and Conrey, R.M., 2020, Geologic map of the Dog River and northern part of the Badger Lake 7.5′ quadrangles, Hood River County, Oregon: Geological Map 126, Report: 154 p.; 1 Plate 48 x 52 inches; Database; Metadata.","productDescription":"Report: 154 p.; 1 Plate 48 x 52 inches; Database; Metadata","ipdsId":"IP-126371","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":385093,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":383245,"type":{"id":15,"text":"Index Page"},"url":"https://www.oregongeology.org/pubs/gms/p-GMS-126.htm"}],"scale":"24000","country":"United States","state":"Oregon","county":"Hood River County","otherGeospatial":"Dog River and Northern Part of the Badger Lake 7.5' Quadrangles","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.87683105468749,\n 44.97839955494438\n ],\n [\n -120.5914306640625,\n 44.97839955494438\n ],\n [\n -120.5914306640625,\n 45.73494252455993\n ],\n [\n -121.87683105468749,\n 45.73494252455993\n ],\n [\n -121.87683105468749,\n 44.97839955494438\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McClaughry, Jason D.","contributorId":194544,"corporation":false,"usgs":false,"family":"McClaughry","given":"Jason","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":810242,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scott, William E. 0000-0001-8156-979X","orcid":"https://orcid.org/0000-0001-8156-979X","contributorId":250706,"corporation":false,"usgs":true,"family":"Scott","given":"William E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":810243,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duda, Carlie J. M.","contributorId":250707,"corporation":false,"usgs":false,"family":"Duda","given":"Carlie","email":"","middleInitial":"J. M.","affiliations":[{"id":32397,"text":"Oregon Department of Geology and Mineral Industries","active":true,"usgs":false}],"preferred":false,"id":810244,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conrey, Richard M.","contributorId":194345,"corporation":false,"usgs":false,"family":"Conrey","given":"Richard","email":"","middleInitial":"M.","affiliations":[{"id":13203,"text":"School of the Environment, Washington State University","active":true,"usgs":false}],"preferred":false,"id":810245,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70230002,"text":"70230002 - 2020 - Biology characterization breakout report","interactions":[],"lastModifiedDate":"2022-03-23T14:35:20.517308","indexId":"70230002","displayToPublicDate":"2020-12-31T09:31:17","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Biology characterization breakout report","docAbstract":"The primary goal of the biology characterization breakout group was to identify the strategies, tools, data priorities, and key partnerships needed to conduct baseline biological characterizations of deep-sea benthic environments across the U.S. EEZ in the Pacific. Discussions focused primarily on priorities for the\ncharacterization of deep-water (>200-meter depths) benthic biological communities; however, the group also emphasized that such characterizations need to be linked to efforts to characterize the overlying water column. The group was tasked with identifying how to prioritize exploration and characterization efforts, including how to identify priority geographic areas and specific methodologies needed to execute exploration activities. The expert community that provided input included representatives from various stakeholder groups actively working on deep-sea issues across the Pacific, including researchers and managers from government agencies, academic institutions, nongovernmental institutions, and the private sector. This report provides a summary of specific guidance identified as key for the successful exploration of deep-sea benthic habitats within the U.S. EEZ in the Pacific, as well as in adjacent international waters.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Report on the Workshop to Identify National Ocean Exploration Priorities in the Pacific","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Consortium for Ocean Leadership","usgsCitation":"Demopoulos, A., Wagner, D., Baco-Taylor, A., Itano, D., Amon, D., Cordes, E.E., Levin, L., Edwards, P.H., Kosaki, R., Pomponi, S., and Gittings, S., 2020, Biology characterization breakout report, in Report on the Workshop to Identify National Ocean Exploration Priorities in the Pacific, p. 22-27.","productDescription":"6 p.","startPage":"22","endPage":"27","ipdsId":"IP-123141","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":397460,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":397443,"type":{"id":15,"text":"Index Page"},"url":"https://oceanleadership.org/discovery/ocean-exploration-pacific-priorities-workshop/"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Demopoulos, Amanda 0000-0003-2096-4694","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":221145,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":838616,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wagner, Daniel","contributorId":289143,"corporation":false,"usgs":false,"family":"Wagner","given":"Daniel","affiliations":[{"id":16938,"text":"Conservation International","active":true,"usgs":false}],"preferred":false,"id":838617,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baco-Taylor, Amy","contributorId":289145,"corporation":false,"usgs":false,"family":"Baco-Taylor","given":"Amy","email":"","affiliations":[{"id":7092,"text":"Florida State University","active":true,"usgs":false}],"preferred":false,"id":838618,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Itano, David","contributorId":289147,"corporation":false,"usgs":false,"family":"Itano","given":"David","email":"","affiliations":[{"id":62057,"text":"Western Pacific Fishery Management Council","active":true,"usgs":false}],"preferred":false,"id":838619,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Amon, Diva","contributorId":289148,"corporation":false,"usgs":false,"family":"Amon","given":"Diva","email":"","affiliations":[{"id":39858,"text":"Natural History Museum London","active":true,"usgs":false}],"preferred":false,"id":838620,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cordes, Erik E.","contributorId":37623,"corporation":false,"usgs":false,"family":"Cordes","given":"Erik","email":"","middleInitial":"E.","affiliations":[{"id":16710,"text":"Temple University, Department of Biology","active":true,"usgs":false}],"preferred":false,"id":838621,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Levin, Lisa","contributorId":289149,"corporation":false,"usgs":false,"family":"Levin","given":"Lisa","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":838622,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Edwards, Peter H.","contributorId":206598,"corporation":false,"usgs":false,"family":"Edwards","given":"Peter","email":"","middleInitial":"H.","affiliations":[{"id":35748,"text":"U. of Leicester","active":true,"usgs":false}],"preferred":false,"id":838623,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kosaki, Randall","contributorId":289151,"corporation":false,"usgs":false,"family":"Kosaki","given":"Randall","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":838624,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Pomponi, Shirley","contributorId":289153,"corporation":false,"usgs":false,"family":"Pomponi","given":"Shirley","email":"","affiliations":[{"id":15312,"text":"Florida Atlantic University","active":true,"usgs":false}],"preferred":false,"id":838625,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Gittings, Steve","contributorId":289154,"corporation":false,"usgs":false,"family":"Gittings","given":"Steve","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":838626,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70240295,"text":"70240295 - 2020 - Evaluating and optimizing the use of logistic regression for tree mortality models in the First Order Fire Effects Model (FOFEM)","interactions":[],"lastModifiedDate":"2023-02-03T15:25:05.570097","indexId":"70240295","displayToPublicDate":"2020-12-31T09:24:33","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Evaluating and optimizing the use of logistic regression for tree mortality models in the First Order Fire Effects Model (FOFEM)","docAbstract":"Wildland fires burn millions of forested hectares annually around the world, affecting biodiversity, carbon storage, hydrologic processes, and ecosystem services largely through fire-induced tree mortality (Bond-Lamberty et al. 2007; Dantas et al. 2016). In spite of this widespread importance, the underlying mechanisms of fire-caused tree mortality remain poorly understood, (Hood et al. 2018). Post-fire tree mortality has been traditionally modeled as an empirical function of tree defenses (bark thickness) and fire injury (crown scorch, stem char) (Ryan and Amman 1996; Woolley et al. 2012). Empirical models are commonly used in fire management to predict fire effects (Reinhardt et al. 1997), from the finescale software tools for fire management planning, to process-based succession models (Keane et al. 2011), and global models of the terrestrial carbon cycle (Hantson et al. 2016). Nevertheless, many fire-caused tree mortality models have undergone little evaluation.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the Fire Continuum-Preparing for the future of wildland fire","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"U.S. Forest Service","usgsCitation":"Cansler, C.A., Hood, S., Varner, J., and van Mantgem, P., 2020, Evaluating and optimizing the use of logistic regression for tree mortality models in the First Order Fire Effects Model (FOFEM), in Proceedings of the Fire Continuum-Preparing for the future of wildland fire, p. 239-246.","productDescription":"8 p.","startPage":"239","endPage":"246","ipdsId":"IP-106540","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":412676,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":412660,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.fs.usda.gov/research/treesearch/63223"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Hood, Sharon M.","contributorId":221183,"corporation":false,"usgs":false,"family":"Hood","given":"Sharon","email":"","middleInitial":"M.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":863362,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Drury, Stacy","contributorId":302054,"corporation":false,"usgs":false,"family":"Drury","given":"Stacy","email":"","affiliations":[],"preferred":false,"id":863363,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Steelman, Toddi A","contributorId":169893,"corporation":false,"usgs":false,"family":"Steelman","given":"Toddi","email":"","middleInitial":"A","affiliations":[{"id":18060,"text":"School of Environment and Sustainability, University of Saskatchewan, Canada","active":true,"usgs":false}],"preferred":false,"id":863364,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Steffens, Ron","contributorId":302055,"corporation":false,"usgs":false,"family":"Steffens","given":"Ron","email":"","affiliations":[],"preferred":false,"id":863365,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Cansler, C. Alina 0000-0002-2155-4438","orcid":"https://orcid.org/0000-0002-2155-4438","contributorId":225029,"corporation":false,"usgs":false,"family":"Cansler","given":"C.","email":"","middleInitial":"Alina","affiliations":[{"id":41022,"text":"Missoula Fire Science Lab","active":true,"usgs":false}],"preferred":false,"id":863286,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hood, Sharon","contributorId":147091,"corporation":false,"usgs":false,"family":"Hood","given":"Sharon","affiliations":[{"id":16786,"text":"U of Montana, Missoula, MT","active":true,"usgs":false}],"preferred":false,"id":863287,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Varner, J. Morgan","contributorId":265933,"corporation":false,"usgs":false,"family":"Varner","given":"J. Morgan","affiliations":[{"id":36874,"text":"Tall Timbers Research Station","active":true,"usgs":false}],"preferred":false,"id":863288,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van Mantgem, Phillip J. 0000-0002-3068-9422","orcid":"https://orcid.org/0000-0002-3068-9422","contributorId":204320,"corporation":false,"usgs":true,"family":"van Mantgem","given":"Phillip J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":863289,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70217610,"text":"70217610 - 2020 - America’s offshore critical mineral wealth","interactions":[],"lastModifiedDate":"2021-02-16T22:39:44.297129","indexId":"70217610","displayToPublicDate":"2020-12-31T09:12:22","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"America’s offshore critical mineral wealth","docAbstract":"No abstract available.
","language":"English","publisher":"Bureau of Ocean Energy Management","usgsCitation":"Bureau of Ocean Energy Management, and United States Geological Survey, 2020, America’s offshore critical mineral wealth, 6 p.","productDescription":"6 p.","ipdsId":"IP-120943","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":383161,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":383160,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.boem.gov/sites/default/files/documents/marine-minerals/fact-sheets/Critical-Mineral-State.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bureau of Ocean Energy Management","contributorId":251708,"corporation":true,"usgs":false,"organization":"Bureau of Ocean Energy Management","id":810363,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"United States Geological Survey","contributorId":128013,"corporation":true,"usgs":false,"organization":"United States Geological Survey","id":810360,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70210826,"text":"70210826 - 2020 - Recent planform changes in the Upper Mississippi River","interactions":[],"lastModifiedDate":"2021-11-03T14:42:36.620726","indexId":"70210826","displayToPublicDate":"2020-12-31T09:03:48","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5000,"text":"Long Term Resource Monitoring Technical Report","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"LTRM-2019GC8","title":"Recent planform changes in the Upper Mississippi River","docAbstract":"Geomorphic changes in the Upper Mississippi River (UMR) have long been a concern of river agencies charged with maintaining and restoring river habitat (GREAT 1980; Jackson et al. 1981; USFWS 1992). Large meandering alluvial rivers like the UMR are expected to constantly change and adjust their fluvial landforms within their riparian corridors as a result of the natural interaction of hydrologic processes, sediment movement, and vegetation over time. However, present geomorphic changes in the UMR reflect altered hydrologic, hydraulic, and sediment conditions caused by regulated flows, constructed agricultural levees and navigation dams, altered land use in the watershed, and climate change. Levees reduce lateral hydrologic and sediment connectivity between channels and floodplains on many tributaries and on the Mississippi River downstream of Pool 13. Between each of the dams are a repeating series of landforms associated with tailwater, intermediate, and impounded conditions. The dams maintain a minimum water level, thus creating many off-channel areas that act as sediment traps. Whereas high-head dams cut off sedimentological connectivity longitudinally through the river corridor (Skalak et al., 2013), low head dams on the UMR only slightly altered transport longitudinally. Deltaic-like sedimentation can be common in the impounded sections of dammed rivers. Erosion of relict land surfaces that remained above the raised impounded water levels has been the dominant change in UMR impounded sections due to increased wind fetch leading to increased wave action. Even though upland sources of sediment from tributaries have decreased over the middle to late 20th century, increased annual precipitation, the interplay of increased variability in flood magnitudes from year to year, and more fall and winter flooding have likely changed erosion and sedimentation patterns in the UMR (Belby, et al., 2019). Paradoxically, monitoring and research indicates that the concentration of some water column constituents like total suspended solids and phosphorous has decreased during the 1991 to 2014 time period (Kreiling and Houser, 2016). In areas prone to increased sedimentation, bed elevations rise and thereby water depths are reduced at a given discharge, resulting in loss of fish habitat. Sediment deposition or erosion further influences water exchange rates between main channel and off-channel areas in the river by increasing resistance in connecting channels or enlarging existing connecting channels. Water depth and water exchange rates are the most prominent features describing habitat quality in the UMR (De Jager et al. 2018), and in some cases, the trajectory of planform change from heightened deposition promises to threaten deep backwater habitats particularly important for overwintering fish.\n\nAlthough information on the rate of vertical change in bed elevation is needed for a complete assessment of geomorphic change associated with the loss of deep backwater habitats, mapping planform changes over time (i.e., lateral changes between the land-water boundary) provide needed information on the location, potential cause, and progressive direction of deposition, especially in the mid sections between dams where deltaic processes are the most pronounced. Several types of planform changes have been observed and identified as concerns. For example, island loss in the large impounded areas of the upper part of the UMR was one of the concerns identified by river managers in the 1980s and 90s, and subsequently island construction became a common form of restoration implemented by the Upper Mississippi River Restoration (UMRR) Program (USACE 2012). Other subtler planform changes, such as channel bank erosion and delta formation in backwaters, are perceived to be important, but have largely gone unquantified. A systemwide reconnaissance of the UMR and IWW conducted in 1998 concluded that 14-percent of the river banks were eroding (Nakato and Anderson 1998). However, stabilization of existing river banks has never been widely pursued as a restoration measure, due to the high cost and uncertain benefits. Delta formation reduces the amount of backwater habitat; however, the deltas maintain and create a mix of riparian and aquatic habitats, and that is generally considered to be beneficial for wildlife and fish. If recent hydrologic trends of more frequent and longer duration flood events continue, a better understanding of planform changes can help in describing past changes, and then be used to forecast potential future trajectories of change. If UMR resource managers determine that past and forecasted conditions are undesirable, then UMRR projects could be identified and prioritized to address those concerns.\n\nVegetative cover associations with landform changes have been used to detect and quantify planform changes in many rivers (Johnson 1985; Hiatt 2015; Volte et al. 2015). Freyer and Jefferson (2013) completed such a study in Pool 6 of the UMR using the landcover data from 12 dates over a 115-yr period, including the 1989, 2000, and 2010/2011 landcover/use (LCU) data from the UMRR Program. Planform change detected over the last 20 years represented by the UMRR Program data best reflect present-day geomorphic patterns, rates and processes. Changes occurring prior to dam construction and changes occurring soon after dam construction are likely not the same as those happening now, 50-70 years after dam construction and creation of the impoundments (McHenry et al., 1984; Bhowmik and Adams, 1986; WEST Consultants, 2000). \n\nThe LCU data from each of the 1989, 2000, and 2010/2011 imagery was developed using similar methods and is available in a Geographical Information System (GIS) for the entire UMR and therefore provides the opportunity for a more comprehensive planform change analysis. This study used GIS overlays of LCU classes to map and quantify changes in planform features over two periods, looking specifically for depositional areas where terrestrial and wetland vegetation expanded at the expense of open water. The land expansion was grouped into four possible process-based types common in large floodplain rivers, some following that used by Lewin et al. (2017). The four types include: crevasse deltas emanating from a breach from a main channel through a natural levee or narrow floodplain into backwaters (crevasse deltas), tributary deltas expanding into backwaters (tributary deltas), deltaic bars at the upstream end of impoundments (impounded deltas), and linear-like bars extending from the downstream ends of narrow levees and remnant floodplains (bar-tail limbs). The methods deployed for change detection addressed possible errors from a variety of sources.","language":"English","publisher":"US Army Corps of Engineers, Upper Mississippi River Restoration (UMRR) Program","usgsCitation":"Rogala, J.T., Fitzpatrick, F., and Hendrickson, J.S., 2020, Recent planform changes in the Upper Mississippi River: Long Term Resource Monitoring Technical Report LTRM-2019GC8, 33 p.","productDescription":"33 p.","ipdsId":"IP-113610","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":391325,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":391323,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://umesc.usgs.gov/documents/publications/2020/rogala_a_2020.html"}],"country":"United States","state":"Illinois, Iowa, Minnesota, Missouri, Wisconsin","otherGeospatial":"Upper Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90,\n 38.58252615935333\n ],\n [\n -91.0546875,\n 40.07807142745009\n ],\n [\n -90,\n 41.86956082699455\n ],\n [\n -90.8349609375,\n 43.29320031385282\n ],\n [\n -91.2744140625,\n 44.465151013519616\n ],\n [\n -93.55957031249999,\n 46.01222384063236\n ],\n [\n -93.4716796875,\n 46.619261036171515\n ],\n [\n -95.1416015625,\n 46.46813299215554\n ],\n [\n -94.52636718749999,\n 45.24395342262324\n ],\n [\n -93.251953125,\n 44.55916341529182\n ],\n [\n -91.93359375,\n 43.866218006556394\n ],\n [\n -91.1865234375,\n 42.4234565179383\n ],\n [\n -90.791015625,\n 42.22851735620852\n ],\n [\n -91.14257812499999,\n 41.705728515237524\n ],\n [\n -91.669921875,\n 41.07935114946899\n ],\n [\n -91.97753906249999,\n 39.842286020743394\n ],\n [\n -91.318359375,\n 38.89103282648846\n ],\n [\n -90,\n 38.58252615935333\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rogala, James T. 0000-0002-1954-4097 jrogala@usgs.gov","orcid":"https://orcid.org/0000-0002-1954-4097","contributorId":2651,"corporation":false,"usgs":true,"family":"Rogala","given":"James","email":"jrogala@usgs.gov","middleInitial":"T.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":791606,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fitzpatrick, Faith A. 0000-0002-9748-7075","orcid":"https://orcid.org/0000-0002-9748-7075","contributorId":209612,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Faith A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":791607,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hendrickson, Jon S.","contributorId":177520,"corporation":false,"usgs":false,"family":"Hendrickson","given":"Jon","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":791608,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}