{"pageNumber":"334","pageRowStart":"8325","pageSize":"25","recordCount":41078,"records":[{"id":70204257,"text":"70204257 - 2019 - Hydrocarbons in upland groundwater, Marcellus Shale Region, Northeastern Pennsylvania and Southern New York, USA","interactions":[],"lastModifiedDate":"2019-07-17T11:44:31","indexId":"70204257","displayToPublicDate":"2019-06-27T14:57:31","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Hydrocarbons in upland groundwater, Marcellus Shale Region, Northeastern Pennsylvania and Southern New York, USA","docAbstract":"

Water samples from 50 domestic wells located <1 km (proximal) and >1 km (distal) from shale-gas wells in upland areas of the Marcellus Shale region were analyzed for chemical, isotopic, and groundwater-age tracers. Uplands were targeted because natural mixing with brine and hydrocarbons from deep formations is less common in those areas compared to valleys. CH4-isotope, predrill CH4-concentration, and other data indicate that one proximal sample (5% of proximal samples) contains thermogenic CH4 (2.6 mg/L) from a relatively shallow source (Catskill/Lock Haven Formations) that appears to have been mobilized by shale-gas production activities. Another proximal sample contains five other volatile hydrocarbons (0.03–0.4 μg/L), including benzene, more hydrocarbons than in any other sample. Modeled groundwater-age distributions, calibrated to 3H, SF6, and 14C concentrations, indicate that water in that sample recharged prior to shale-gas development, suggesting that land-surface releases associated with shale-gas production were not the source of those hydrocarbons, although subsurface leakage from a nearby gas well directly into the groundwater cannot be ruled out. Age distributions in the samples span ∼20 to >10000 years and have implications for relating occurrences of hydrocarbons in groundwater to land-surface releases associated with recent shale-gas production and for the time required to flush contaminants from the system.

","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.9b01440","usgsCitation":"McMahon, P.B., Lindsey, B.D., Conlon, M.D., Hunt, A.G., Belitz, K., Jurgens, B., and Varela, B.A., 2019, Hydrocarbons in upland groundwater, Marcellus Shale Region, Northeastern Pennsylvania and Southern New York, USA: Environmental Science & Technology, v. 53, no. 14, p. 8027-8035, https://doi.org/10.1021/acs.est.9b01440.","productDescription":"9 p.","startPage":"8027","endPage":"8035","ipdsId":"IP-104959","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true},{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"links":[{"id":437401,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93M7JCD","text":"USGS data release","linkHelpText":"Data Release for Hydrocarbons in Upland Groundwater, Marcellus Shale Region, Northeastern Pennsylvania and Southern New York, USA"},{"id":365631,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York, Pennsylvania","volume":" 53","issue":"14","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-06-27","publicationStatus":"PW","contributors":{"authors":[{"text":"McMahon, Peter B. 0000-0001-7452-2379 pmcmahon@usgs.gov","orcid":"https://orcid.org/0000-0001-7452-2379","contributorId":724,"corporation":false,"usgs":true,"family":"McMahon","given":"Peter","email":"pmcmahon@usgs.gov","middleInitial":"B.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":766203,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lindsey, Bruce D. 0000-0002-7180-4319 blindsey@usgs.gov","orcid":"https://orcid.org/0000-0002-7180-4319","contributorId":175346,"corporation":false,"usgs":true,"family":"Lindsey","given":"Bruce","email":"blindsey@usgs.gov","middleInitial":"D.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":766204,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Conlon, Matthew D. 0000-0001-8266-9610 mconlon@usgs.gov","orcid":"https://orcid.org/0000-0001-8266-9610","contributorId":201291,"corporation":false,"usgs":true,"family":"Conlon","given":"Matthew","email":"mconlon@usgs.gov","middleInitial":"D.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":766205,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hunt, Andrew G. 0000-0002-3810-8610 ahunt@usgs.gov","orcid":"https://orcid.org/0000-0002-3810-8610","contributorId":1582,"corporation":false,"usgs":true,"family":"Hunt","given":"Andrew","email":"ahunt@usgs.gov","middleInitial":"G.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":766206,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Belitz, Kenneth 0000-0003-4481-2345","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":201889,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":766207,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jurgens, Bryant C. 0000-0002-1572-113X","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":203409,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant","middleInitial":"C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":766208,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Varela, Brian A. 0000-0001-9849-6742 bvarela@usgs.gov","orcid":"https://orcid.org/0000-0001-9849-6742","contributorId":178091,"corporation":false,"usgs":true,"family":"Varela","given":"Brian","email":"bvarela@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":766209,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70204037,"text":"70204037 - 2019 - Morphology and genesis of giant seafloor depressions on the southeasterncontinental shelf of the Korean Peninsula","interactions":[],"lastModifiedDate":"2019-06-28T09:25:09","indexId":"70204037","displayToPublicDate":"2019-06-27T14:31:58","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Morphology and genesis of giant seafloor depressions on the southeasterncontinental shelf of the Korean Peninsula","docAbstract":"

We identify and describe five giant seafloor depressions from the southeastern continental shelf of the Korean Peninsula using multibeam bathymetry, sub-bottom profiler, and multi-channel seismic reflection data, supplemented by piston cores. Multibeam bathymetry data from the shelf show four crescent-shaped depressions (SD1 to SD4) and one near-circular depression (SD5) within a group of NW-SE trending depressions, the largest covering an area of about 7 km2 on the seafloor. The depressions reach up to ~4.5 km in width and ~2 km in length and have asymmetric cross-sections. Some have depths as large as 40 m below the surrounding seafloor with walls as steep as 45°. The depressions are confined to water depths between 130 and 170 m and bounded on the north by a large submarine channel that was plausibly formed by fluvial or tidal processes during the Last Glacial Maximum (LGM) sea-level lowstand. Multi-channel seismic and sub-bottom profiler data reveal truncated depression walls and the presence of sediment drift deposits within the depressions, indicating that both erosion and deposition are active processes. Flaser and lenticular bedding in the cored drift deposits along with variable grain size (ranging between ~2.6 phi and ~4.3 phi) are diagnostic features of the bottom currents influenced by tidal forces. Depressions SD1 to SD4 lack evidence of fluid or gas escape. In contrast, many features of depression SD5 are characteristic of gas escapes and blowouts, including acoustic anomalies, a 20-m-high carbonate mound or carbonate-encrusted mound, and mud dikes and mud patches in cores. Based on the SD5 example, we think it is likely that the other crescent-shaped seafloor depressions formed originally as pockmarks by gas/fluid venting, and have since become inactive. The pockmarks represent zones of weakened sediment that were eroded, expanded, and merged by bottom currents to form larger seafloor depressions. Modern currents are strong enough to transport shelf sediments, and these currents were probably much stronger at lower sea levels when the Korea Strait was a more restricted passage between the East China Sea and East Sea.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2019.105966","usgsCitation":"Cukur, D., Kong, G., Chun, J., Kang, M., Um, I., Kwon, T., Jordan, S.E., and Kim, K., 2019, Morphology and genesis of giant seafloor depressions on the southeasterncontinental shelf of the Korean Peninsula: Marine Geology, v. 415, 105966, 13 p., https://doi.org/10.1016/j.margeo.2019.105966.","productDescription":"105966, 13 p.","ipdsId":"IP-106382","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":365123,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"North Korea, South Korea","otherGeospatial":"Korea Strait","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 127.869873046875,\n 33.284619968887675\n ],\n [\n 130.97900390625,\n 33.284619968887675\n ],\n [\n 130.97900390625,\n 37.18657859524883\n ],\n [\n 127.869873046875,\n 37.18657859524883\n ],\n [\n 127.869873046875,\n 33.284619968887675\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"415","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cukur, Deniz","contributorId":216636,"corporation":false,"usgs":false,"family":"Cukur","given":"Deniz","email":"","affiliations":[{"id":39491,"text":"Korea Institute of Geoscience and Mineral Resources (KIGAM","active":true,"usgs":false}],"preferred":false,"id":765221,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kong, Gee-Soo","contributorId":216637,"corporation":false,"usgs":false,"family":"Kong","given":"Gee-Soo","email":"","affiliations":[{"id":39491,"text":"Korea Institute of Geoscience and Mineral Resources (KIGAM","active":true,"usgs":false}],"preferred":false,"id":765254,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chun, Jong-Hwa","contributorId":216638,"corporation":false,"usgs":false,"family":"Chun","given":"Jong-Hwa","email":"","affiliations":[{"id":39491,"text":"Korea Institute of Geoscience and Mineral Resources (KIGAM","active":true,"usgs":false}],"preferred":false,"id":765223,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kang, Moo-Hee","contributorId":216639,"corporation":false,"usgs":false,"family":"Kang","given":"Moo-Hee","email":"","affiliations":[{"id":39491,"text":"Korea Institute of Geoscience and Mineral Resources (KIGAM","active":true,"usgs":false}],"preferred":false,"id":765224,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Um, In-Kwon","contributorId":216640,"corporation":false,"usgs":false,"family":"Um","given":"In-Kwon","email":"","affiliations":[{"id":39491,"text":"Korea Institute of Geoscience and Mineral Resources (KIGAM","active":true,"usgs":false}],"preferred":false,"id":765225,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kwon, Taekhyun","contributorId":216641,"corporation":false,"usgs":false,"family":"Kwon","given":"Taekhyun","email":"","affiliations":[{"id":39491,"text":"Korea Institute of Geoscience and Mineral Resources (KIGAM","active":true,"usgs":false}],"preferred":false,"id":765226,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jordan, Samuel E. 0000-0001-6074-3330","orcid":"https://orcid.org/0000-0001-6074-3330","contributorId":216635,"corporation":false,"usgs":true,"family":"Jordan","given":"Samuel","email":"","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":765220,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kim, Kyong-O","contributorId":216642,"corporation":false,"usgs":false,"family":"Kim","given":"Kyong-O","email":"","affiliations":[{"id":39491,"text":"Korea Institute of Geoscience and Mineral Resources (KIGAM","active":true,"usgs":false}],"preferred":false,"id":765227,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70263727,"text":"70263727 - 2019 - Evaluating tradeoffs in the response of Sora (Porzana carolina) and waterfowl to the timing of early autumn wetland inundation","interactions":[],"lastModifiedDate":"2025-02-20T19:12:23.90001","indexId":"70263727","displayToPublicDate":"2019-06-27T13:04:35","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3731,"text":"Waterbirds","onlineIssn":"19385390","printIssn":"15244695","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Evaluating tradeoffs in the response of Sora (Porzana carolina) and waterfowl to the timing of early autumn wetland inundation","title":"Evaluating tradeoffs in the response of Sora (Porzana carolina) and waterfowl to the timing of early autumn wetland inundation","docAbstract":"

Wetland loss has increased the importance of multi-species management in remaining wetlands, which provide habitat for a multitude of wetland-dependent species. Many public wetlands across the mid-latitude United States are managed as moist soil impoundments with emphasis on migratory waterfowl. However, how the timing of these water management decisions affects rails is still uncertain. Wetland managers identified this as an area of uncertainty regarding timing of alternative water management strategies to benefit waterfowl and rails, which was addressed through a 3-year management experiment. Sora (Porzana carolina) and waterfowl were surveyed on 10 public wetland properties in Missouri, USA from 2014-2016, and their responses to early autumn inundation of managed palustrine wetlands were compared. A total of 558 Sora surveys detected 5,755 birds (20.6 birds/survey ± 30.8 SD), and 1,304 waterfowl surveys detected 1,411,779 birds (15,686.4 birds/survey ± 23,933.9 SD). Sora responded positively (birds/ha) to inundation of moist soil impoundments earlier in autumn migration (August). The top model for Sora included treatment, year and region of Missouri. There was no difference in waterfowl abundance between early or late inundation. Inundating wetlands earlier in autumn migration can provide habitat for migrating Sora without negative effects on waterfowl use of those wetlands, and wetland managers can incorporate this into their decision-making framework.

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Arkansas","active":true,"usgs":false}],"preferred":false,"id":927966,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Raedeke, Andy","contributorId":341916,"corporation":false,"usgs":false,"family":"Raedeke","given":"Andy","affiliations":[{"id":16971,"text":"Missouri Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":927967,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Krementz, David G. 0000-0002-5661-4541 dkrementz@usgs.gov","orcid":"https://orcid.org/0000-0002-5661-4541","contributorId":2827,"corporation":false,"usgs":true,"family":"Krementz","given":"David","email":"dkrementz@usgs.gov","middleInitial":"G.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":927968,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70204078,"text":"70204078 - 2019 - Spatial conservation planning under uncertainty: Adapting to climate change risks using modern portfolio theory","interactions":[],"lastModifiedDate":"2020-12-08T18:02:17.95215","indexId":"70204078","displayToPublicDate":"2019-06-27T12:47:12","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Spatial conservation planning under uncertainty: Adapting to climate change risks using modern portfolio theory","docAbstract":"

Climate change and urban growth impact habitats, species, and ecosystem services. To buffer against global change, an established adaptation strategy is designing protected areas to increase representation and complementarity of biodiversity features. Uncertainty regarding the scale and magnitude of landscape change complicates reserve planning and exposes decision makers to risk of failing to meet conservation goals. Conservation planning tends to treat risk as an absolute measure, ignoring the context of the management problem and risk preferences of stakeholders. Application to conservation of risk management theory emphasizes diversification of portfolio of assets, with the goal of reducing the impact of system volatility on investment return. We use principles of Modern Portfolio Theory (MPT), which quantifies risk as the variance and correlation among assets, to formalize diversification as an explicit strategy for managing risk in climate‐driven reserve design. We extend MPT to specify a framework that evaluates multiple conservation objectives, allows decision makers to balance management benefits and risk when preferences are contested or unknown, and includes additional decision options such as parcel divestment when evaluating candidate reserve designs. We apply an efficient search algorithm that optimizes portfolio design for large conservation problems and a game theoretic approach to evaluate portfolio tradeoffs that satisfy decision makers with divergent benefit and risk tolerances, or when a single decision maker cannot resolve their own preferences. Evaluating several risk profiles for a case study in South Carolina, our results suggest that a reserve design may be somewhat robust to differences in risk attitude but that budgets will likely be important determinants of conservation planning strategies, particularly when divestment is considered a viable alternative. We identify a possible fiscal threshold where adequate resources allow protecting a sufficiently diverse portfolio of habitats such that the risk of failing to achieve conservation objectives is considerably lower. For a range of sea‐level rise projections, conversion of habitat to open water (14‐180%) and wetland loss (1‐7%) are unable to be compensated under the current protected network. In contrast, optimal reserve design outcomes are predicted to ameliorate expected losses relative to current and future habitat protected under the existing conservation estate.

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0000-0002-6209-7915","orcid":"https://orcid.org/0000-0002-6209-7915","contributorId":216713,"corporation":false,"usgs":true,"family":"Yurek","given":"Simeon","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":765411,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haider, Zulqarnain","contributorId":216714,"corporation":false,"usgs":false,"family":"Haider","given":"Zulqarnain","email":"","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":765412,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martin, Julien 0000-0002-7375-129X julienmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-7375-129X","contributorId":5785,"corporation":false,"usgs":true,"family":"Martin","given":"Julien","email":"julienmartin@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":765417,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Fred 0000-0002-5854-3695","orcid":"https://orcid.org/0000-0002-5854-3695","contributorId":216715,"corporation":false,"usgs":true,"family":"Johnson","given":"Fred","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":765413,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Udell, Bradley","contributorId":216709,"corporation":false,"usgs":false,"family":"Udell","given":"Bradley","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":765414,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Charkhgard, Hadi","contributorId":216710,"corporation":false,"usgs":false,"family":"Charkhgard","given":"Hadi","email":"","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":765415,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kwon, Changhyun","contributorId":216711,"corporation":false,"usgs":false,"family":"Kwon","given":"Changhyun","email":"","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":765416,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70203662,"text":"sir20195050 - 2019 - Flood-inundation maps for the Iowa River at the Meskwaki Settlement in Iowa, 2019","interactions":[],"lastModifiedDate":"2019-06-27T12:31:59","indexId":"sir20195050","displayToPublicDate":"2019-06-27T11:30:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5050","displayTitle":"Flood-Inundation Maps for the Iowa River at the Meskwaki Settlement in Iowa, 2019","title":"Flood-inundation maps for the Iowa River at the Meskwaki Settlement in Iowa, 2019","docAbstract":"

Digital flood-inundation maps for a 9.3-mile reach of the Iowa River along the Meskwaki Settlement, Iowa, were created by the U.S. Geological Survey (USGS) in cooperation with the Sac and Fox Tribe of the Mississippi in Iowa. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science website at https://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage 05451770 on the Iowa River at County Highway E49 near Tama, Iowa. Near-real-time stages at this streamgage may be obtained on the internet from the USGS National Water Information System at https://waterdata.usgs.gov/ or the National Weather Service (NWS) Advanced Hydrologic Prediction Service  at https://water.weather.gov/ahps/, which also forecasts flood hydrographs at this site.

Flood profiles were computed for the stream reach by means of a calibrated one-dimensional and two-dimensional step-backwater hydraulic model. The model was calibrated by using the current stage-discharge relation at the USGS streamgage 05451770 on the Iowa River at County Highway E49 near Tama, Iowa, and stage and discharge data from historic flooding events that were recorded at the streamgage.

The hydraulic model was then used to compute eight water-surface profiles for flood stages at 1-foot intervals referenced to the streamgage datum and ranging from the NWS “action stage” of 11 feet (ft) to 18 ft, the stage exceeding the estimated 0.2-percent annual exceedance probability (500-year recurrence interval) flood, as determined at the USGS streamgage 05451770. The simulated water-surface profiles were then combined with a geographic information system digital elevation model to delineate the area flooded at each flood stage (water level).

In addition, potential modifications to hydraulic structures within the flood plain were modeled so any effects from the potential modifications could be evaluated. Four comparison points, which were along the flood plain, showed little to no change (less than 0.1 ft) in flood elevation from the existing conditions within the flood plain for the 11- to 16-ft stages as referenced to the USGS streamgage 05451770. There were greater changes (more than 0.1 ft) in flood elevation for the 2 comparison points that were closest to the modified hydraulic structure for the 2 highest modeled stages of 17 and 18 ft.

The availability of these maps, along with internet information regarding current stage from the USGS streamgage and forecasted high-flow stages from the NWS, will provide emergency management personnel and residents with information that is critical for flood-response activities such as evacuations and road closures, as well as for postflood recovery efforts.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195050","collaboration":"Prepared in cooperation with the Sac and Fox Tribe of the Mississippi in Iowa","usgsCitation":"Cigrand, C.V., 2019, Flood-inundation maps for the Iowa River at the Meskwaki Settlement in Iowa, 2019: U.S. Geological Survey Scientific Investigations Report 2019–5050, 12 p., https://doi.org/10.3133/sir20195050.","productDescription":"12 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-103795","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":365048,"rank":3,"type":{"id":30,"text":"Data Release"},"url":" https://doi.org/10.5066/P912FO3L ","text":"USGS data release","description":"USGS data release","linkHelpText":"Geospatial datasets for the flood-inundation study for the Iowa River at the Meskwaki Settlement in Iowa, 2019"},{"id":365046,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5050/coverthb.jpg"},{"id":365047,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5050/sir20195050.pdf","text":"Report","size":"26.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5050"}],"country":"United States","state":"Iowa","otherGeospatial":"Meskwaki Settlement","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92.7175,41.916666666666664 ], [ -92.7175,42.034166666666664 ], [ -92.55,42.034166666666664 ], [ -92.55,41.916666666666664 ], [ -92.7175,41.916666666666664 ] ] ] } } ] }","contact":"

Director, Central Midwest Water Science Center
U.S. Geological Survey
400 South Clinton Street, Suite 269
Iowa City, IA 52240

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2019-06-27","noUsgsAuthors":false,"publicationDate":"2019-06-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Cigrand, Charles V. 0000-0002-4177-7583","orcid":"https://orcid.org/0000-0002-4177-7583","contributorId":201575,"corporation":false,"usgs":true,"family":"Cigrand","given":"Charles","email":"","middleInitial":"V.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":763447,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70203661,"text":"ofr20191035 - 2019 - Petrologic and mineral physics database for use with the U.S. Geological Survey National Crustal Model","interactions":[],"lastModifiedDate":"2019-06-27T11:05:44","indexId":"ofr20191035","displayToPublicDate":"2019-06-27T11:15:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1035","displayTitle":"Petrologic and Mineral Physics Database for Use with the U.S. Geological Survey National Crustal Model","title":"Petrologic and mineral physics database for use with the U.S. Geological Survey National Crustal Model","docAbstract":"

We present a petrologic and mineral physics database as part of the U.S. Geological Survey National Crustal Model (NCM). Each of 209 geologic units, 134 of which are currently part of the geologic framework within the NCM, was assigned a mineralogical composition according to generalized classifications with some refinement for specific geologic formations. This report is concerned with the petrology and mineral physics of each geologic unit within the NCM, which control the physical behavior of the solid mineral matrix within the rock.

This mineral physics database builds on the work of Abers and Hacker to include 13 minerals specific to continental rock types. We explored the effect of this database on zero-porosity anharmonic P- and S-wave rock velocities and density relative to a well-used empirical study of relations between wavespeeds and density by Brocher. We found that empirical relations between P-wave velocity and S-wave velocity or density do well on average but can differ from mineral physics calculations by up to 15 percent in S-wave velocity and almost 40 percent in density. This is consistent with Brocher’s study where he obtained similar results for in situ measurements and laboratory rock specimens.

Additionally, the substantial presence of quartz in many rocks plays a major role in crustal seismic velocities and density due to quartz’s α–β phase transition, which can interfere with these empirical relationships. With increasing depth, quartz P-wave velocity can suddenly jump by 15 percent accompanied by little change in S-wave velocity and a modest decrease in density. Empirical relations based on observed P-wave velocity where P-wave velocity is positively correlated with S-wave velocity and density would then significantly overestimate both S-wave velocity and density.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191035","usgsCitation":"Sowers, T., and Boyd, O.S., 2019, Petrologic and mineral physics database for use with the U.S. Geological Survey National Crustal Model: U.S. Geological Survey Open-File Report 2019–1035, 17 p.,https://doi.org/10.3133/ofr20191035.","productDescription":"17 p.","onlineOnly":"Y","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":437403,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FK25WM","text":"USGS data release","linkHelpText":"MinVel"},{"id":364257,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HN170G","text":"USGS data release","linkHelpText":"Petrologic and Mineral Physics Database for use with the USGS National Crustal Model - Data Release"},{"id":365082,"rank":4,"type":{"id":4,"text":"Application Site"},"url":"https://github.com/usgs/MinVel","text":"MinVel ","linkHelpText":"software that supports this report is available in the GitHub repository."},{"id":364255,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1035/coverthb.jpg"},{"id":364256,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1035/ofr20191035.pdf","text":"Report","size":"1.20 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1035"}],"contact":"

Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, MS-966
Denver, CO 80225-0046

","tableOfContents":"","publishedDate":"2019-06-27","noUsgsAuthors":false,"publicationDate":"2019-06-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Sowers, Theron A. 0000-0002-3208-5411","orcid":"https://orcid.org/0000-0002-3208-5411","contributorId":215933,"corporation":false,"usgs":false,"family":"Sowers","given":"Theron","middleInitial":"A.","affiliations":[{"id":39330,"text":"California State University at Sacramento","active":true,"usgs":false}],"preferred":false,"id":763445,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boyd, Oliver S. 0000-0001-9457-0407 olboyd@usgs.gov","orcid":"https://orcid.org/0000-0001-9457-0407","contributorId":140739,"corporation":false,"usgs":true,"family":"Boyd","given":"Oliver","email":"olboyd@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":763446,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70223516,"text":"70223516 - 2019 - Cerulean Warbler (Setophaga cerulea) response to operational silviculture in the central Appalachian region","interactions":[],"lastModifiedDate":"2021-08-31T12:43:42.798781","indexId":"70223516","displayToPublicDate":"2019-06-27T07:36:35","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Cerulean Warbler (Setophaga cerulea) response to operational silviculture in the central Appalachian region","docAbstract":"

The Cerulean Warbler (Setophaga cerulea) is a species of conservation need, with declines linked in part to forest habitat loss on its breeding grounds. Active management of forests benefit the Cerulean Warbler by creating the complex structural conditions preferred by the species, but further research is needed to determine optimal silvicultural strategies. We quantified and compared the broad-scale influence of timber harvests within central Appalachian hardwood forests on estimated abundance and territory density of Cerulean Warblers. We conducted point counts at seven study areas across three states within the central Appalachian region (West Virginia [n = 4], Kentucky [n = 1], Virginia [n = 2]) and territory mapping at two of the study areas in West Virginia, pre- and post-harvest, for up to five breeding seasons from 2013 to 2017. Our primary objective was to relate change in abundance to topographic and vegetation metrics to evaluate the effectiveness of current Cerulean Warbler habitat management guidelines. We used single-species hierarchical (N-mixture) models to estimate abundance while accounting for detection biases. Pre-harvest mean basal area among study areas was 29.3 m2/ha. Harvesting reduced mean basal area among study areas by 40% (mean 17.2 m2/ha) at harvest interior and harvest edge points. Territory density increased 100% (P = 0.003) from pre-harvest to two years post-harvest. Cerulean Warbler abundance increased with increasing percentage of basal area that comprised tree species preferred for foraging and nesting (i.e., white oak species, sugar maple [Acer saccharum], hickories) or of large diameter trees (≥40.6 cm diameter at breast height). Positive population growth was predicted to occur where these vegetation metrics were >50% of residual basal area. Post-harvest abundance at harvest interior points was greater than at reference points and when accounting for years-post-harvest in modeling abundance, Cerulean Warbler abundance increased at harvest interior and reference points two years post-harvest and subsequently decreased three years post-harvest. Modeled abundance remained the same at harvest edge points. Increases in abundance and territory density were greater in stands with low pre-harvest densities (<2 birds/point or <0.40 territory/ha) of Cerulean Warblers, whereas populations within stands with higher densities pre-harvest had minimal changes in abundance and territory density. Overall, our results indicate that harvests based on the Cerulean Warbler Management Guidelines for Enhancing Breeding Habitat in Appalachian Hardwood Forests, at all available slope positions and aspects where pre-harvest densities are <0.40 territory/ha, may provide breeding habitat for Cerulean Warblers for at least two years post-harvest in the central Appalachian region.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2019.05.062","usgsCitation":"Nareff, G.E., Wood, P.B., Brown, D., Fearer, T., Larkin, J.L., and Ford, W., 2019, Cerulean Warbler (Setophaga cerulea) response to operational silviculture in the central Appalachian region: Forest Ecology and Management, v. 448, p. 409-423, https://doi.org/10.1016/j.foreco.2019.05.062.","productDescription":"15 p.","startPage":"409","endPage":"423","ipdsId":"IP-104413","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467499,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2019.05.062","text":"Publisher Index Page"},{"id":388681,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West 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Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":822256,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70203676,"text":"sir20195048 - 2019 - Groundwater movement and interaction with surface water near the confluence of the Platte and Elkhorn rivers, Nebraska, 2016–18","interactions":[],"lastModifiedDate":"2019-06-27T07:50:01","indexId":"sir20195048","displayToPublicDate":"2019-06-26T16:55:17","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5048","displayTitle":"Groundwater Movement and Interaction with Surface Water near the Confluence of the Platte and Elkhorn Rivers, Nebraska, 2016–18","title":"Groundwater movement and interaction with surface water near the confluence of the Platte and Elkhorn rivers, Nebraska, 2016–18","docAbstract":"

The State of Nebraska requires a sustainable balance between long-term water supplies and uses of groundwater and surface water and requires Natural Resources Districts to include the effect of groundwater use on surface-water systems as part of their respective integrated management plans. Recent droughts in Nebraska (2000–6; 2012–13) have amplified concerns about the long-term sustainability of groundwater and surface-water resources in the state, and concerns about the effect of groundwater irrigation on both streamflow and the water supplies needed to meet wildlife, recreational, and municipal needs. The lower Platte River provides nearly 100 percent of drinking-water supplies to Lincoln, Nebraska, 40 to 60 percent of drinking-water supplies to Omaha, Nebr., and critical aquatic and riparian habitat for threatened and endangered species. The Lower Platte River Basin-wide Management Plan has been jointly developed by the Nebraska Department of Natural Resources and seven Natural Resources Districts to address some of these concerns by managing groundwater and surface-water resources conjunctively.

To sustain flows in the lower Platte River that are needed for municipal water supplies, water managers have proposed projects aimed at temporary storage of surface water in upstream parts of the basin to mitigate periods of low flow in the lower Platte River. To increase scientific understanding and provide support for any potential future streamflow augmentation projects, the Papio-Missouri River Natural Resources District, the Lower Platte North Natural Resources District, and the Nebraska Department of Natural Resources, in cooperation with the U.S. Geological Survey, initiated this study to examine groundwater/surface-water interaction along the lower Platte and Elkhorn Rivers upstream from their confluence. The study design described herein focused on understanding seasonal characteristics of groundwater movement and interaction with surface water during periods of high groundwater demand (June through August) and low groundwater demand (all other months). Understanding how groundwater movement and interaction with surface water are affected by streamflow conditions and local groundwater demand is critical to the development of any streamflow augmentation project intended to sustain streamflow and mitigate periods of low flow in the lower Platte River.

The characteristics of groundwater movement and interaction with surface water are affected by hydrologic and local climatic conditions. For the study area, 2016–18 conditions can be broadly characterized as above normal precipitation. The flows measured at the Elkhorn River at Waterloo, Nebr., streamflow-gaging station (U.S. Geological Survey station 06800500) were above the long-term median, and the streamflow of the Platte River near Leshara, Nebr., streamflow-gaging station (06796500) remained normal or slightly above normal for the duration of this study.

Continuous streamflow and water-level data were interpreted to examine differences in groundwater movement and interaction with surface water between the Platte and Elkhorn Rivers during high and low groundwater demand periods. Although the streamflow for the Platte and Elkhorn Rivers and their tributaries was less during the high groundwater demand period, the hydraulic gradient along a transect of recorder wells was identical (0.0012 foot per foot) during the high and low groundwater demand synoptic water-level and streamflow surveys. The hydraulic gradient between the Platte and Elkhorn Rivers generally remained between 0.0011 and 0.0012 foot per foot. It can be inferred that the hydraulic gradient, which is the only temporally variable factor in Darcy’s Law, is consistent throughout the study period and that groundwater flow does not vary appreciably along this transect.

The northern part of the study area (north of the transect of recorder wells) has consistent groundwater and tributary flow from Big Slough, Rawhide Creek (Old Channel), and Rawhide Creek for low and high groundwater demand periods. In the southern part of the study area (south of the transect of recorder wells), tributary flow is more variable and dependent on local groundwater demand and flow conditions of the Platte River. Small decreases (less than 2 feet) in the groundwater levels, such as those measured during the high groundwater demand period, can have substantial changes in the streamflow in an unnamed tributary to the Elkhorn River. The streamflow measured during the high groundwater demand synoptic water-level and streamflow survey had decreased by nearly a factor of 20 when compared to the low groundwater demand period.

The volume of groundwater discharge received by the Elkhorn River was estimated by examining the changes in streamflow between measurement locations. Streamflow measurements indicate that the groundwater discharge received by the Elkhorn River in the southern part of the study area was seasonably variable, making it difficult if not impossible to estimate an annual value. In the Elkhorn River, between the Elkhorn River at Waterloo, Nebr., streamflow-gaging station and the Q Street Bridge, streamflow measurements collected during the low groundwater demand period indicated a gain of 80 cubic feet per second, which is comparable to the gain estimated using aerial thermal infrared imagery and water temperature data. Streamflow measurements collected during the high groundwater demand period indicate a loss of 80 cubic feet per second across this same reach. In assessing water supply conditions in the lower Platte River system, the term “loss” in reference to streamflow in the Elkhorn River should be used with caution. Most likely, flow from the Elkhorn River which is “lost” to the groundwater system will later discharge to surface water closer to the confluence of the Platte and Elkhorn Rivers as underflow. A calibrated groundwater flow model of the study area likely is required to predict the fate of this water and to quantify groundwater discharge during varying hydrologic conditions along this reach.

Aerial thermal infrared imagery indicated that much of the groundwater discharge in the southern part of the study area is focused across a 3-mile reach where the Elkhorn River turns southwest, perpendicular to the regional groundwater flow direction. Points of focused groundwater discharge were not detected with aerial thermal infrared imagery, indicating that groundwater discharge is diffuse rather than concentrated at focused points. Temperature-based streambed flux estimates indicated that strong regional groundwater gradients are not driving groundwater discharge and hyporheic flow is the dominant groundwater/surface-water exchange process.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195048","collaboration":"Prepared in cooperation with the Papio-Missouri River and Lower Platte North Natural Resources Districts and the Nebraska Department of Natural Resources","usgsCitation":"Hobza, C.M., Johnson, M.J., Woodward, P.W., Strauch, K.R., and Schepers, A.R., 2019, Groundwater movement and interaction with surface water near the confluence of the Platte and Elkhorn Rivers, Nebraska, 2016–18: U.S. Geological Survey Scientific Investigations Report 2019–5048, 38 p., https://doi.org/10.3133/sir20195048.","productDescription":"Report: vi, 38 p.; Data Release","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-101680","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":365092,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5048/sir20195048.pdf","text":"Report","size":"4.36 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5048"},{"id":365093,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EZLGSC","text":"USGS data release ","description":"USGS Data Release","linkHelpText":"Water-level and aerial thermal infrared imagery data collected along the lower Platte and Elkhorn Rivers, Nebraska, 2016–2017"},{"id":365091,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5048/coverthb.jpg"}],"country":"United States","state":"Nebraska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.503662109375,\n 40.613952441166596\n ],\n [\n -95.7073974609375,\n 40.613952441166596\n ],\n [\n -95.7073974609375,\n 42.09007006868398\n ],\n [\n -97.503662109375,\n 42.09007006868398\n ],\n [\n -97.503662109375,\n 40.613952441166596\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2019-06-26","noUsgsAuthors":false,"publicationDate":"2019-06-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Hobza, Christopher M. 0000-0002-6239-934X cmhobza@usgs.gov","orcid":"https://orcid.org/0000-0002-6239-934X","contributorId":2393,"corporation":false,"usgs":true,"family":"Hobza","given":"Christopher","email":"cmhobza@usgs.gov","middleInitial":"M.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":763562,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Mason J. 0000-0002-0026-0780","orcid":"https://orcid.org/0000-0002-0026-0780","contributorId":215975,"corporation":false,"usgs":true,"family":"Johnson","given":"Mason","email":"","middleInitial":"J.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":763563,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woodward, Paul W.","contributorId":215976,"corporation":false,"usgs":false,"family":"Woodward","given":"Paul","email":"","middleInitial":"W.","affiliations":[{"id":39339,"text":"Papio-Missouri River Natural Resources District, Omaha, Nebr.","active":true,"usgs":false}],"preferred":false,"id":763564,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Strauch, Kellan R. 0000-0002-7218-2099","orcid":"https://orcid.org/0000-0002-7218-2099","contributorId":208562,"corporation":false,"usgs":true,"family":"Strauch","given":"Kellan R.","affiliations":[{"id":84311,"text":"Central Plains Water Science Center","active":true,"usgs":true},{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":763566,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schepers, Aaron R.","contributorId":206492,"corporation":false,"usgs":false,"family":"Schepers","given":"Aaron","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":763565,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70208325,"text":"70208325 - 2019 - Trends and carrying capacity of sea otters in Southeast Alaska","interactions":[],"lastModifiedDate":"2020-02-04T11:14:56","indexId":"70208325","displayToPublicDate":"2019-06-26T11:08:56","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Trends and carrying capacity of sea otters in Southeast Alaska","docAbstract":"Sea otter populations in Southeast Alaska (SEAK) have increased dramatically from fewer than 500 translocated animals in the late 1960s. The recovery of sea otters to ecosystems from which they had been absent has affected coastal food webs, including commercially important fisheries, and thus information on expected growth and equilibrium abundances can help inform resource management. We compile available survey data for SEAK and fit a Bayesian state-space model to estimate past trends and current abundance. Our model improves upon previous analyses by partitioning and quantifying sources of estimation error, accounting for over-dispersion of aerial count data, and providing realistic measurements of uncertainty around point estimates of abundance at multiple spatial scales. We also provide the first estimates of carrying capacity (K) for SEAK, at both regional and sub-regional scales, and analyze growth rates, current population status and expected future trends. At the regional scale, the population increased from 13,221 otters in 2003 (95% credible interval 9,990 – 16,828) to 25,584 otters in 2011 (CI95 18,739 – 33,163). The average annual growth rate in southern SEAK (7.8%) was higher than northern SEAK (2.7%); however, growth varied at the sub-regional scale and there was a negative relationship between growth rates and the number of years sea otters were present in an area. Local populations vary in terms of current densities and expected future growth: the mean estimated density at K was 4.2 (1.58) sea otters per km2 of habitat (defined as the sub-tidal benthos between 0-40m depth) and current densities correspond on average to 50% of projected equilibrium values (range = 1% to 97%) with the earliest-colonized sub-regions tending to be closer to K. Assuming a similar range of equilibrium densities for currently un-occupied habitats in SEAK, the projected value of K for all of SEAK is 74,650 sea otters (CI95 =36,778–136,506). Future analyses can improve upon the precision of K estimates by employing more frequent surveys at index sites and incorporating environmental covariates into the process model to generate habitat-specific estimates of equilibrium density.","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21685","usgsCitation":"Tinker, M.T., Gill, V.A., Esslinger, G.G., Bodkin, J.L., Monk, M., Mangel, M., Monson, D., Raymond, W.W., and Kissling, M., 2019, Trends and carrying capacity of sea otters in Southeast Alaska: Journal of Wildlife Management, v. 83, no. 5, p. 1073-1089, https://doi.org/10.1002/jwmg.21685.","productDescription":"17 p.","startPage":"1073","endPage":"1089","ipdsId":"IP-098286","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":467500,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.21685","text":"Publisher Index Page"},{"id":437406,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PYG92B","text":"USGS data release","linkHelpText":"Sea Otter Aerial Survey Data from Southeast Alaska, 2002-2003"},{"id":437405,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SBAFF6","text":"USGS data release","linkHelpText":"Sea Otter Aerial Survey Data from Glacier Bay National Park and Preserve, 1999-2012"},{"id":372007,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -141.064453125,\n 59.93300042374631\n ],\n [\n -137.63671875,\n 57.42129439209407\n ],\n [\n -134.38476562499997,\n 54.92714186454645\n ],\n [\n -132.626953125,\n 52.214338608258196\n ],\n [\n -130.166015625,\n 51.72702815704774\n ],\n [\n -129.638671875,\n 54.16243396806779\n ],\n [\n -130.166015625,\n 56.41390137600676\n ],\n [\n -134.47265625,\n 59.80063426102869\n ],\n [\n -140.009765625,\n 60.457217797743944\n ],\n [\n -141.064453125,\n 59.93300042374631\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"83","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-06-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Tinker, M. 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The measurements are done in the line of sight (LOS) to each satellite, within an area of size ~450 km2, at the locations of hundreds of thousands permanent and distributed scatterers. Thirty descending (satellite moves north to south) and 45 ascending (south to north) images were used from Envisat, and 63 descending and 65 ascending from Sentinel. A decomposition into average vertical and east horizontal components is also performed in more than 35,000 100-m pixels where both types of LOS measurements are available. The main observations at CGF include: (1) a subsidence area of size ~70 km2, with a maximum subsidence of –27.6 mm/year for the Envisat period and lower maximum subsidence of –19.1 mm/year for the Sentinel period; (2) eastward movements in the western part of the subsidence area, with Envisat maximum of +23.9 mm/year and a lower Sentinel maximum of +15.9 mm/year; (3) westward displacements in the eastern part of the subsidence area, with Envisat maximum of ̶ 14.2 mm/year and Sentinel maximum of –11.9 mm/year; (4) very good agreement of the InSAR observations with leveling survey data; (5) earthquake clusters in the subsidence area and hypocentral cross-sections showing clusters at various depths and migration in time; and (6) good predictions of the overall geothermal resource, based on poroelastic modeling using both leveling and InSAR data. The ultimate goal of the project is to provide geothermal operators with tools that can be used in reservoir management.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"GRC Transactions","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"2018 GRC Annual Meeting","conferenceLocation":"Reno, NV","language":"English","publisher":"Geothermal Resources Council","usgsCitation":"Eneva, M., Barbour, A., Adams, D., Hsiao, V., Blake, K., Falorni, G., and Locatelli, R., 2019, Satellite observations of surface deformation at the Coso Geothermal Field, California, in GRC Transactions, v. 42, Reno, NV, 1033950.","productDescription":"1033950","onlineOnly":"Y","ipdsId":"IP-098800","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":365023,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Coso Geothermal Field, Naval Air Warfare Center China Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.75730133056642,\n 35.59087713155274\n ],\n [\n -117.75730133056642,\n 35.59087713155274\n ],\n [\n -117.75730133056642,\n 35.59087713155274\n ],\n [\n -117.75730133056642,\n 35.59087713155274\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.87231445312499,\n 35.92353244718235\n ],\n [\n -117.72125244140625,\n 35.92353244718235\n ],\n [\n -117.72125244140625,\n 36.0513195750255\n ],\n [\n -117.87231445312499,\n 36.0513195750255\n ],\n [\n -117.87231445312499,\n 35.92353244718235\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Eneva, Mariana","contributorId":167022,"corporation":false,"usgs":false,"family":"Eneva","given":"Mariana","email":"","affiliations":[{"id":24596,"text":"Imageair Inc.","active":true,"usgs":false}],"preferred":false,"id":762027,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barbour, Andrew","contributorId":215305,"corporation":false,"usgs":true,"family":"Barbour","given":"Andrew","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":762026,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adams, David","contributorId":148050,"corporation":false,"usgs":false,"family":"Adams","given":"David","affiliations":[],"preferred":false,"id":762028,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hsiao, Vicky","contributorId":215306,"corporation":false,"usgs":false,"family":"Hsiao","given":"Vicky","email":"","affiliations":[{"id":39221,"text":"TRE Altamira Inc.","active":true,"usgs":false}],"preferred":false,"id":762029,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blake, Kelly","contributorId":197142,"corporation":false,"usgs":false,"family":"Blake","given":"Kelly","affiliations":[],"preferred":false,"id":762030,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Falorni, Giacomo","contributorId":215307,"corporation":false,"usgs":false,"family":"Falorni","given":"Giacomo","email":"","affiliations":[{"id":39221,"text":"TRE Altamira Inc.","active":true,"usgs":false}],"preferred":false,"id":762031,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Locatelli, Roberto","contributorId":215308,"corporation":false,"usgs":false,"family":"Locatelli","given":"Roberto","email":"","affiliations":[{"id":39221,"text":"TRE Altamira Inc.","active":true,"usgs":false}],"preferred":false,"id":762032,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70203821,"text":"70203821 - 2019 - Integrating behavior and physiology into strategies for amphibian conservation","interactions":[],"lastModifiedDate":"2019-09-13T11:05:24","indexId":"70203821","displayToPublicDate":"2019-06-25T11:48:52","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Integrating behavior and physiology into strategies for amphibian conservation","docAbstract":"The amphibian decline crisis has been challenging to address because of the complexity of factors—and their multitude of interactive effects—that drive this global issue. Dissecting such complexity could benefit from strategies that integrate multiple disciplines and address the mechanistic underpinnings of population declines and extirpations. We examine how the disciplines of behavior and physiology could be used to develop conservation strategies for amphibians and identify eight research gaps that provide future directions for the emerging fields of conservation behavior and conservation physiology. We present two case studies on imperiled salamanders that show how studies of behavior and physiology may support amphibian conservation efforts. We found several applications of stress physiology to amphibian conservation, but long-term studies are needed to understand how stress ultimately affects individual fitness and population resilience. Additionally, multiple measures of physiological health are needed to provide a more holistic assessment of an individual’s overall condition. Previous behavioral and physiological studies have been instrumental for understanding how amphibians respond to habitat modification, pathogens and parasites, contaminants, and invasive species. Some behavior-based approaches to mitigating invasive species issues have been successful in short-term studies with individual species. However, widespread application of these tactics has not yet been integrated into conservation and management strategies for ecologically-similar species. A diversity of modeling approaches has enhanced understanding of how climate change may impact amphibian populations, but model predictions need empirical tests to provide conservation managers with workable approaches to multiple perturbations associated with global environmental change. We illustrate that behavior and physiology can have broad utility for amphibian conservation, but evidence is scant that such studies have actually been used to inform strategies for amphibian conservation and management.","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2019.00234","usgsCitation":"Walls, S., and Gabor, C., 2019, Integrating behavior and physiology into strategies for amphibian conservation: Frontiers in Ecology and Evolution, v. 7, 234; 13 p., https://doi.org/10.3389/fevo.2019.00234.","productDescription":"234; 13 p.","ipdsId":"IP-104505","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":467501,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2019.00234","text":"Publisher Index Page"},{"id":364701,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2019-06-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Walls, Susan C. 0000-0001-7391-9155","orcid":"https://orcid.org/0000-0001-7391-9155","contributorId":216235,"corporation":false,"usgs":true,"family":"Walls","given":"Susan","middleInitial":"C.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":764270,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gabor, Caitlin R","contributorId":216236,"corporation":false,"usgs":false,"family":"Gabor","given":"Caitlin R","affiliations":[{"id":6677,"text":"Texas State University","active":true,"usgs":false}],"preferred":false,"id":764271,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70204604,"text":"70204604 - 2019 - Seasonal precipitation influences streamflow vulnerability to the 2015 drought in the western United States","interactions":[],"lastModifiedDate":"2019-08-06T11:06:50","indexId":"70204604","displayToPublicDate":"2019-06-25T11:03:22","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2344,"text":"Journal of Hydrometeorology","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal precipitation influences streamflow vulnerability to the 2015 drought in the western United States","docAbstract":"Streamflow was exceptionally low in the spring and summer of 2015 across much of the western United States because of a regional drought that exploited the sensitivity of both snow- and rain-dominant rivers. Streamflow during 2015 was examined at 324 gauges in the region to assess its response to the amount, form, and seasonal timing of precipitation and the viability of using spatially aggregated, normative models to assess streamflow vulnerability to drought. Seasonal rain and spring snowmelt had the strongest effects on runoff during the same season, but their effects persisted into subsequent seasons as well. Below-normal runoff in the spring of 2015 was pervasive across the region, while distinct seasonal responses were evident in different hydroclimatic settings: January–March (winter) runoff was above normal in most snow-dominant rivers and runoff in all seasons was above normal for much of the desert Southwest. Summer precipitation contributed to summer runoff in both the Pacific Northwest and desert Southwest. A first-order model that presumes runoff is a constant fraction of precipitation (the precipitation elasticity of runoff, E = 1) could be used for assessing and forecasting runoff responses to precipitation deficits across the region, but runoff generally is more vulnerable to drought (E > 1) than predicted by a first-order model. Uncertainty in spring and summer precipitation forecasts remain critical issues for forecasting and predicting summer streamflow vulnerability to drought across much of the western United States.","language":"English","publisher":"AMS","doi":"10.1175/JHM-D-18-0121.1","collaboration":"NOAA","usgsCitation":"Konrad, C., 2019, Seasonal precipitation influences streamflow vulnerability to the 2015 drought in the western United States: Journal of Hydrometeorology, v. 20, p. 1261-1274, https://doi.org/10.1175/JHM-D-18-0121.1.","productDescription":"14 p.","startPage":"1261","endPage":"1274","ipdsId":"IP-087008","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":460349,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jhm-d-18-0121.1","text":"Publisher Index Page"},{"id":366291,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":366280,"type":{"id":15,"text":"Index Page"},"url":"https://journals.ametsoc.org/doi/full/10.1175/JHM-D-18-0121.1"}],"volume":"20","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-06-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Konrad, Christopher 0000-0002-7354-547X","orcid":"https://orcid.org/0000-0002-7354-547X","contributorId":217886,"corporation":false,"usgs":true,"family":"Konrad","given":"Christopher","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":767746,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70205055,"text":"70205055 - 2019 - Recognizing the Famine Early Warning Systems Network: Over 30 years of drought early warning science advances and partnerships promoting global food security","interactions":[],"lastModifiedDate":"2019-11-20T14:57:37","indexId":"70205055","displayToPublicDate":"2019-06-25T09:16:59","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1112,"text":"Bulletin of the American Meteorological Society","onlineIssn":"1520-0477","printIssn":"0003-0007","active":true,"publicationSubtype":{"id":10}},"title":"Recognizing the Famine Early Warning Systems Network: Over 30 years of drought early warning science advances and partnerships promoting global food security","docAbstract":"On a planet with more than 7 billion people, how do we identify the millions of drought-afflicted people who face a real threat of livelihood disruption or death without humanitarian assistance? Typically, these people are poor and heavily dependent on rainfed agriculture and livestock. Most live in Africa, Central America, or Southwest Asia. When the rains fail, incomes diminish while food prices increase, cutting off the poorest (most often women and children) from access to adequate nutrition. As seen in Ethiopia in 1984 and Somalia in 2011, food shortages can lead to famine. Yet these slow onset disasters also provide opportunities for effective intervention, as seen in Ethiopia in 2015 and Somalia in 2017.\n\nSince 1985, the US Agency for International Development's Famine Early Warning Systems Network (FEWS NET) has been providing evidence-based guidance for effective humanitarian relief efforts. FEWS NET depends on a Drought Early Warning System (DEWS) to help understand, monitor, model and predict food insecurity. Here we provide an overview of FEWS NET's DEWS using examples from recent climate extremes. While drought monitoring and prediction provides just one part of FEWS NET's monitoring system, it draws from many disciplines - remote sensing, climate prediction, agro-climatic monitoring, and hydrologic modeling. Here we describe FEWS NET's multi-agency multi-disciplinary DEWS and Food Security Outlooks. This DEWS uses diagnostic analyses to guide predictions. Mid-season droughts are monitored using multiple cutting-edge earth observing systems. Crop and hydrologic models can translate these observations into impacts. This information feeds into FEWS NET reports, helping to save lives by motivating and targeting timely humanitarian assistance.","language":"English","publisher":"AMS","doi":"10.1175/BAMS-D-17-0233.1","usgsCitation":"Funk, C., Shraddhanand Shukla, Thiaw, W.M., Rowland, J., Andrew Hoell, Husak, G., and Novella, N., 2019, Recognizing the Famine Early Warning Systems Network: Over 30 years of drought early warning science advances and partnerships promoting global food security: Bulletin of the American Meteorological Society, p. 1011-1027, https://doi.org/10.1175/BAMS-D-17-0233.1.","productDescription":"17 p.","startPage":"1011","endPage":"1027","ipdsId":"IP-098117","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":467503,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/bams-d-17-0233.1","text":"Publisher Index Page"},{"id":367055,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Funk, Chris 0000-0002-9254-6718","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":218640,"corporation":false,"usgs":true,"family":"Funk","given":"Chris","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":false,"id":769770,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shraddhanand Shukla","contributorId":218641,"corporation":false,"usgs":false,"family":"Shraddhanand Shukla","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":769771,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thiaw, Wassila Mamadou","contributorId":218642,"corporation":false,"usgs":false,"family":"Thiaw","given":"Wassila","email":"","middleInitial":"Mamadou","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":769772,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rowland, James 0000-0003-4837-3511 rowland@usgs.gov","orcid":"https://orcid.org/0000-0003-4837-3511","contributorId":145846,"corporation":false,"usgs":true,"family":"Rowland","given":"James","email":"rowland@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":769773,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Andrew Hoell","contributorId":218643,"corporation":false,"usgs":false,"family":"Andrew Hoell","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":769774,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Husak, Gregory","contributorId":145811,"corporation":false,"usgs":false,"family":"Husak","given":"Gregory","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":769775,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Novella, Nicholas","contributorId":218644,"corporation":false,"usgs":false,"family":"Novella","given":"Nicholas","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":769776,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70209110,"text":"70209110 - 2019 - Enhanced landslide mobility by basal liquefaction: the 2014 SR530 (Oso), Washington landslide","interactions":[],"lastModifiedDate":"2020-03-17T07:24:07","indexId":"70209110","displayToPublicDate":"2019-06-25T07:19:46","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1786,"text":"Geological Society of America Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Enhanced landslide mobility by basal liquefaction: the 2014 SR530 (Oso), Washington landslide","docAbstract":"Landslide mobility can vastly amplify the consequences of slope failure. As a compelling example, the March 22, 2014 landslide near Oso, Washington (USA) was particularly devastating, traveling across a 1-km+ wide river valley, killing 43 people, destroying dozens of homes, and temporarily closing a well-traveled highway. To resolve causes for the landslide’s behavior and mobility, we conducted detailed post-event field investigations and material testing. Geologic and structure mapping revealed a progression of geomorphological structures ranging from debris flow lobes at the distal end, through hummock fields, laterally continuous landslide blocks, back-rotated blocks, and finally colluvial slides and falls at the landslide headscarp. Primary structures, as well as stratigraphic and vegetation patterns, in the landslide deposit indicated rapid extensional motion of the approximately nine-million-m3 source volume in a closely timed sequence of events. We identified hundreds of transient sand boils in the landslide runout zone – evidence of widespread elevated pore-water pressures with consequent shear-strength reduction at the base of the slide. During the event, underlying wet alluvium liquefied and allowed quasi-intact slide hummocks to extend and translate long distances across the flat valley. Most of the slide material itself did not liquefy. Using geotechnical testing and numerical modeling, we examined rapid undrained loading, shear and collapse of loose saturated alluvium, and strong ground shaking as potential liquefaction mechanisms. Our analyses show that some layers in the alluvium can liquefy when sheared, as could occur with rapid undrained loading. Simultaneous ground shaking could have contributed to pore-pressure generation as well. Two key elements, a large and rapid failure overriding wet liquefiable sediments, enabled the landslide’s high mobility. Basal liquefaction may enhance mobility of other landslides in similar settings.","language":"English","publisher":"Geological Society of America","doi":"10.1130/B35146.1","usgsCitation":"Collins, B.D., and Reid, M.E., 2019, Enhanced landslide mobility by basal liquefaction: the 2014 SR530 (Oso), Washington landslide: Geological Society of America Bulletin, v. 132, no. 3/4, p. 451-476, https://doi.org/10.1130/B35146.1.","productDescription":"26 p.","startPage":"451","endPage":"476","ipdsId":"IP-098841","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":467504,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/b35146.1","text":"Publisher Index Page"},{"id":373309,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.62939453125001,\n 48.09275716032736\n ],\n [\n -121.00341796874999,\n 48.09275716032736\n ],\n [\n -121.00341796874999,\n 48.83579746243093\n ],\n [\n -122.62939453125001,\n 48.83579746243093\n ],\n [\n -122.62939453125001,\n 48.09275716032736\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"132","issue":"3/4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-06-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Collins, Brian D. 0000-0003-4881-5359 bcollins@usgs.gov","orcid":"https://orcid.org/0000-0003-4881-5359","contributorId":149278,"corporation":false,"usgs":true,"family":"Collins","given":"Brian","email":"bcollins@usgs.gov","middleInitial":"D.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":784960,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reid, Mark E. 0000-0002-5595-1503 mreid@usgs.gov","orcid":"https://orcid.org/0000-0002-5595-1503","contributorId":1167,"corporation":false,"usgs":true,"family":"Reid","given":"Mark","email":"mreid@usgs.gov","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":784961,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70215499,"text":"70215499 - 2019 - Variability in synthetic earthquake ground motions caused by source variability and errors in wave propagation models","interactions":[],"lastModifiedDate":"2020-10-21T15:30:34.656635","indexId":"70215499","displayToPublicDate":"2019-06-24T10:26:30","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"Variability in synthetic earthquake ground motions caused by source variability and errors in wave propagation models","docAbstract":"

Numerical simulations of earthquake ground motions are used both to anticipate the effects of hypothetical earthquakes by forward simulation and to infer the behaviour of the real earthquake source ruptures by the inversion of recorded ground motions. In either application it is necessary to assume some Earth structure that is necessarily inaccurate and to use a computational method that is also inaccurate for simulating the wavefield Green's functions. We refer to these two sources of error as ‘propagation inaccuracies’, which might be considered to be epistemic. We show that the variance of the Fourier spectrum of the synthetic earthquake seismograms caused by propagation inaccuracies is related to the spatial covariance on the rupture surface of errors in the computed Green's functions, which we estimate for the case of the 2009 L'Aquila, Italy, earthquake by comparing erroneous computed Green's functions with observed L'Aquila aftershock seismograms (empirical Green's functions). We further show that the variance of the synthetic seismograms caused by the rupture variability (aleatory uncertainty) is related to the spatial covariance on the rupture surface of aleatory variations in the rupture model, and we investigate the effect of correlated variations in Green's function errors and variations in rupture models. Thus, we completely characterize the variability of synthetic earthquake seismograms induced by errors in propagation and variability in the rupture behaviour. We calculate the spectra of the variance of the ground motions of the L'Aquila main shock caused by propagation inaccuracies for two specific broad-band stations, the AQU and the FIAM stations. These variances are distressingly large, being comparable or in some cases exceeding the data amplitudes, suggesting that the best-fitting L'Aquila rupture model significantly overfits the data and might be seriously in error. If these computed variances are typical, the accuracy of many other rupture models for past earthquakes may need to be reconsidered. The results of this work might be useful in seismic hazard estimation because the variability of the computed ground motion, caused both by propagation inaccuracies and variations in the rupture model, can be computed directly, not requiring laborious consideration of multiple Earth structures.

","language":"English","publisher":"Oxford Academic","doi":"10.1093/gji/ggz275","usgsCitation":"Spudich, P.A., Cirella, A., Scognamiglio, L., and Tinti, E., 2019, Variability in synthetic earthquake ground motions caused by source variability and errors in wave propagation models: Geophysical Journal International, v. 219, no. 1, p. 346-372, https://doi.org/10.1093/gji/ggz275.","productDescription":"27 p.","startPage":"346","endPage":"372","ipdsId":"IP-101827","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":467505,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gji/ggz275","text":"Publisher Index Page"},{"id":379592,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"219","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-06-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Spudich, Paul A. 0000-0002-9484-4997","orcid":"https://orcid.org/0000-0002-9484-4997","contributorId":243550,"corporation":false,"usgs":true,"family":"Spudich","given":"Paul","email":"","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":802512,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cirella, Antonella","contributorId":200468,"corporation":false,"usgs":false,"family":"Cirella","given":"Antonella","email":"","affiliations":[],"preferred":false,"id":802513,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scognamiglio, Laura","contributorId":200469,"corporation":false,"usgs":false,"family":"Scognamiglio","given":"Laura","email":"","affiliations":[],"preferred":false,"id":802514,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tinti, Elisa","contributorId":200470,"corporation":false,"usgs":false,"family":"Tinti","given":"Elisa","email":"","affiliations":[],"preferred":false,"id":802515,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70203202,"text":"sir20195036 - 2019 - ModelMuse Version 4: A graphical user interface for MODFLOW 6","interactions":[],"lastModifiedDate":"2019-06-25T11:59:32","indexId":"sir20195036","displayToPublicDate":"2019-06-24T10:00:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5036","displayTitle":"ModelMuse Version 4: A Graphical User Interface for MODFLOW 6","title":"ModelMuse Version 4: A graphical user interface for MODFLOW 6","docAbstract":"ModelMuse, a graphical user interface for groundwater-modeling software, was modified to support MODFLOW 6. ModelMuse works with two types of spatial discretization in MODFLOW 6: structured grids (DIS) and discretization by vertices (DISV). Quadtree refinement is used to generate a DISV model from a structured-grid model. The locations and weights for ghost nodes used to improve DISV model accuracy are computed automatically by ModelMuse using a new algorithm. ModelMuse does not support other types of DISV grids and unstructured grids. ModelMuse supports options in MODFLOW 6 that designate individual cells as confined or convertible and remove inactive cells associated with discontinuous layers, thereby reducing the computational burden. ModelMuse can specify fully three-dimensional (3D), spatially variable anisotropy in hydraulic conductivity. Although MODFLOW 6 does not support the parameters supported by MODFLOW–2005, ModelMuse provides backward compatibility by allowing ModelMuse parameters to specify scale-factor variables in MODFLOW 6 time-series files within packages that support time-series files. ModelMuse can automatically convert the data for many of the packages from other MODFLOW models to the new data for these packages in MODFLOW 6. Some packages, such as the Streamflow-Routing (SFR) package, changed significantly enough that only a partial conversion is possible. Head and flow observations in older models are also converted to observation locations in the MODFLOW 6 Observation utility. ModelMuse accommodates the ability of MODFLOW 6 to store specific discharge components by allowing the user to visualize the components of a specific discharge on the model grid. ModelMuse supports the versions of MODPATH and ZONEBUDGET compatible with MODFLOW 6.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195036","usgsCitation":"Winston, R.B., 2019, ModelMuse version 4—A graphical user interface for MODFLOW 6: U.S. Geological Survey Scientific Investigations Report 2019–5036, 10 p., https://doi.org/10.3133/sir20195036.","productDescription":"v, 10 p.","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-101951","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":437409,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P974NRIX","text":"USGS data release","linkHelpText":"ModelMuse version 4.2"},{"id":437408,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9X9NW2V","text":"USGS data release","linkHelpText":"Software Release ModelMuse Version 4.1"},{"id":364718,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5036/sir20195036.pdf","text":"Report","size":"627 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5036"},{"id":364717,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5036/coverthb.jpg"},{"id":364787,"rank":3,"type":{"id":18,"text":"Project Site"},"url":" https://www.usgs.gov/software/modelmuse-a-graphical-user-interface-groundwater-models","linkHelpText":"- Software -- ModelMuse: A Graphical User Interface for Groundwater Models"}],"contact":"

Director, Integrated Modeling and Prediction Division
U.S. Geological Survey
MS 415 National Center
12201 Sunrise Valley Drive
Reston, VA 20192

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2019-06-24","noUsgsAuthors":false,"publicationDate":"2019-06-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Winston, Richard B. 0000-0002-6287-8834 rbwinst@usgs.gov","orcid":"https://orcid.org/0000-0002-6287-8834","contributorId":3567,"corporation":false,"usgs":true,"family":"Winston","given":"Richard","email":"rbwinst@usgs.gov","middleInitial":"B.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":761630,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70203981,"text":"70203981 - 2019 - The evolving threat of rapid Ohia death (ROD) to Hawaii’s native ecosystems and rare plant species","interactions":[],"lastModifiedDate":"2019-06-26T09:32:44","indexId":"70203981","displayToPublicDate":"2019-06-24T09:23:44","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The evolving threat of Rapid ‘Ōhi‘a Death (ROD) to Hawai‘i’s native ecosystems and rare plant species","title":"The evolving threat of rapid Ohia death (ROD) to Hawaii’s native ecosystems and rare plant species","docAbstract":"

Hawai‘i’s most widespread native tree, ‘ōhi‘a lehua (Metrosideros polymorpha), has been dying across large areas of Hawai‘i Island mainly due to two fungal pathogens (Ceratocystis lukuohia and Ceratocystis huliohia) that cause a disease collectively known as Rapid ‘Ōhi‘a Death (ROD). Here we examine patterns of positive detections of C. lukuohia as it has been linked to the larger mortality events across Hawai‘i Island. Our analysis compares the environmental range of C. lukuohia and its spread over time through the known climatic range and distribution of ‘ōhi‘a. Analyses show this fungal pathogen generally encompassed the core, but not the extremes of the climatic range of ‘ōhi‘a. We further modeled the potential distribution of C. lukuohiaacross the Hawaiian Archipelago to estimate the risk of ROD to other islands. Given the potential for C. lukuohia to alter the structure of ‘ōhi‘a dominated forests, we used our projected potential distribution of C. lukuohia to assess the risk of ROD to threatened and endangered plant species across Hawai‘i. Many native plants are likely vulnerable to these types of large ‘ōhi‘a mortality events: of 234 endangered native plant species considered, 147 (62.8%) have more than half of their range within current and expanding C. lukuohia suitable areas. We also found evidence that protecting habitat by fencing out introduced feral ungulates reduces the prevalence of the disease likely by reducing physical damage caused by these animals to ‘ōhi‘a trees, a precondition for Ceratocystis infection. Given the ongoing spread of C. lukuohia, we developed a dynamic web portal to host our results online, where models and analyses are updated with new lab-confirmed detections to provide managers with a useful tool to help monitor and assess the risk of C. lukuohia as it continues to spread.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2019.06.025","usgsCitation":"Fortini, L., Kaiser, L.R., Keith, L., Price, J., Hughes, R., Jacobi, J.D., and Friday, J.B., 2019, The evolving threat of rapid Ohia death (ROD) to Hawaii’s native ecosystems and rare plant species: Forest Ecology and Management, v. 448, p. 376-385, https://doi.org/10.1016/j.foreco.2019.06.025.","productDescription":"10 p.","startPage":"376","endPage":"385","ipdsId":"IP-106268","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":437410,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94ESGQB","text":"USGS data release","linkHelpText":"Hawaiian Islands Ceratocystis rapid ohia death spatial analysis 2019"},{"id":365055,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Flint","contributorId":111314,"corporation":false,"usgs":true,"family":"Hughes","given":"R. Flint","affiliations":[],"preferred":false,"id":765084,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jacobi, James D. 0000-0003-2313-7862 jjacobi@usgs.gov","orcid":"https://orcid.org/0000-0003-2313-7862","contributorId":3705,"corporation":false,"usgs":true,"family":"Jacobi","given":"James","email":"jjacobi@usgs.gov","middleInitial":"D.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":765085,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Friday, J. B.","contributorId":216579,"corporation":false,"usgs":false,"family":"Friday","given":"J.","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":765095,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70204158,"text":"70204158 - 2019 - Review: Endophytic microbes and their potential applications in crop management","interactions":[],"lastModifiedDate":"2019-09-16T12:21:37","indexId":"70204158","displayToPublicDate":"2019-06-22T14:29:55","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3035,"text":"Pest Management Science","active":true,"publicationSubtype":{"id":10}},"title":"Review: Endophytic microbes and their potential applications in crop management","docAbstract":"

Endophytes are microbes (mostly bacteria and fungi) present in plants. Endophytic microbes are often functional in that they may carry nutrients from the soil into plants, modulate plant development, increase stress tolerance of plants, suppress virulence in pathogens, increase disease resistance in plants, and suppress development of competitor plant species. Endophytic microbes have been shown: 1) obtain nutrients in soils and transfer nutrients to plants in the rhizophagy cycle and other nutrient‐transfer symbioses; 2) increase plant growth and development; 3) reduce oxidative stress of hosts; 4) protect plants from disease; 5) deter feeding by herbivores; and 6) suppress growth of competitor plant species. Because of the effective functions of endophytic microbes, we suggest that endophytic microbes may significantly reduce use of agrochemicals (fertilizers, fungicides, insecticides, and herbicides) in the cultivation of crop plants. The loss of endophytic microbes from crop plants during domestication and long‐term cultivation could be remedied by transfer of endophytes from wild relatives of crops to crop species. Increasing atmospheric carbon dioxide levels could reduce the efficiency of the rhizophagy cycle due to repression of reactive oxygen used to extract nutrients from microbes in roots.

","language":"English","publisher":"Wiley","doi":"10.1002/ps.5527","usgsCitation":"White, J., Kingsley, K.L., Elmore, M.T., Verma, S.K., Gond, S.K., and Kowalski, K., 2019, Review: Endophytic microbes and their potential applications in crop management: Pest Management Science, v. 75, no. 10, p. 2558-2565, https://doi.org/10.1002/ps.5527.","productDescription":"8 P.","startPage":"2558","endPage":"2565","ipdsId":"IP-106524","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":467508,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ps.5527","text":"Publisher Index Page"},{"id":365392,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":365388,"type":{"id":15,"text":"Index Page"},"url":"https://onlinelibrary.wiley.com/doi/abs/10.1002/ps.5527"}],"volume":"75","issue":"10","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-27","publicationStatus":"PW","contributors":{"authors":[{"text":"White, James F.","contributorId":152046,"corporation":false,"usgs":false,"family":"White","given":"James F.","affiliations":[],"preferred":false,"id":765750,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kingsley, Kathryn L.","contributorId":203176,"corporation":false,"usgs":false,"family":"Kingsley","given":"Kathryn","email":"","middleInitial":"L.","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":765751,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elmore, Matthew T.","contributorId":206820,"corporation":false,"usgs":false,"family":"Elmore","given":"Matthew","email":"","middleInitial":"T.","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":765752,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Verma, Satish Kumar","contributorId":203175,"corporation":false,"usgs":false,"family":"Verma","given":"Satish","email":"","middleInitial":"Kumar","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":765753,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gond, Surendra K","contributorId":216841,"corporation":false,"usgs":false,"family":"Gond","given":"Surendra","email":"","middleInitial":"K","affiliations":[{"id":39528,"text":"Banaras Hindu University","active":true,"usgs":false}],"preferred":false,"id":765754,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kowalski, Kurt P. 0000-0002-8424-4701 kkowalski@usgs.gov","orcid":"https://orcid.org/0000-0002-8424-4701","contributorId":3768,"corporation":false,"usgs":true,"family":"Kowalski","given":"Kurt P.","email":"kkowalski@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":765749,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70228003,"text":"70228003 - 2019 - Estimating density and detection of bobcats in fragmented Midwestern landscapes using spatial capture-recapture data from camera traps","interactions":[],"lastModifiedDate":"2022-02-04T14:40:11.294887","indexId":"70228003","displayToPublicDate":"2019-06-21T11:13:21","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Estimating density and detection of bobcats in fragmented Midwestern landscapes using spatial capture-recapture data from camera traps","docAbstract":"

Camera-trapping data analyzed with spatially explicit capture–recapture (SCR) models can provide a rigorous method for estimating density of small populations of elusive carnivore species. We sought to develop and evaluate the efficacy of SCR models for estimating density of a presumed low-density bobcat (Lynx rufus) population in fragmented landscapes of west-central Illinois, USA. We analyzed camera-trapping data from 49 camera stations in a 1,458-km2 area deployed over a 77-day period from 1 February to 18 April 2017. Mean operational time of cameras was 52 days (range = 32–67 days). We captured 23 uniquely identifiable bobcats 113 times and recaptured these same individuals 90 times; 15 of 23 (65.2%) individuals were recaptured at ≥2 camera traps. Total number of bobcat capture events was 139, of which 26 (18.7%) were discarded from analyses because of poor image quality or capture of only a part of an animal in photographs. Of 113 capture events used in analyses, 106 (93.8%) and 7 (6.2%) were classified as positive and tentative identifications, respectively; agreement on tentative identifications of bobcats was high (71.4%) among 3 observers. We photographed bobcats at 36 of 49 (73.5%) camera stations, of which 34 stations were used in analyses. We estimated bobcat density at 1.40 individuals (range = 1.00–2.02)/100 km 2. Our modeled bobcat density estimates are considerably below previously reported densities (30.5 individuals/100 km 2) within the state, and among the lowest yet recorded for the species. Nevertheless, use of remote cameras and SCR models was a viable technique for reliably estimating bobcat density across west-central Illinois. Our research establishes ecological benchmarks for understanding potential effects of colonization, habitat fragmentation, and exploitation on future assessments of bobcat density using standardized methodologies that can be compared directly over time. Further application of SCR models that quantify specific costs of animal movements (i.e., least-cost path models) while accounting for landscape connectivity has great utility and relevance for conservation and management of bobcat populations across fragmented Midwestern landscapes.

","language":"English","publisher":"Wildlife Society","doi":"10.1002/wsb.968","usgsCitation":"Jacques, C., Klaver, R.W., Swearingen, T.C., Davis, E.D., Anderson, C., Jenks, J., DePerno, C.S., and Bluett, R.D., 2019, Estimating density and detection of bobcats in fragmented Midwestern landscapes using spatial capture-recapture data from camera traps: Wildlife Society Bulletin, v. 43, no. 2, p. 256-264, https://doi.org/10.1002/wsb.968.","productDescription":"9 p.","startPage":"256","endPage":"264","ipdsId":"IP-099506","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467513,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/0695d4aeb0ef43ef984fb13bc46339bd","text":"External Repository"},{"id":395373,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois","county":"Handcock, Schuyler","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.2139892578125,\n 40.01289077952615\n ],\n [\n -90.45867919921875,\n 40.01289077952615\n ],\n [\n -90.45867919921875,\n 40.330842639095756\n ],\n [\n -91.2139892578125,\n 40.330842639095756\n ],\n [\n -91.2139892578125,\n 40.01289077952615\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","issue":"2","noUsgsAuthors":false,"publicationDate":"2019-06-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Jacques, Christopher N.","contributorId":264323,"corporation":false,"usgs":false,"family":"Jacques","given":"Christopher N.","affiliations":[{"id":49637,"text":"Western Illinois University","active":true,"usgs":false}],"preferred":false,"id":833067,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Klaver, Robert W. 0000-0002-3263-9701 bklaver@usgs.gov","orcid":"https://orcid.org/0000-0002-3263-9701","contributorId":3285,"corporation":false,"usgs":true,"family":"Klaver","given":"Robert","email":"bklaver@usgs.gov","middleInitial":"W.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":832877,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swearingen, Tim C.","contributorId":274286,"corporation":false,"usgs":false,"family":"Swearingen","given":"Tim","email":"","middleInitial":"C.","affiliations":[{"id":49637,"text":"Western Illinois University","active":true,"usgs":false}],"preferred":false,"id":833068,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davis, Edward D.","contributorId":274508,"corporation":false,"usgs":false,"family":"Davis","given":"Edward","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":833069,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anderson, Charles R.","contributorId":274287,"corporation":false,"usgs":false,"family":"Anderson","given":"Charles R.","affiliations":[{"id":39887,"text":"Colorado Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":833070,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jenks, Jonathan A.","contributorId":274288,"corporation":false,"usgs":false,"family":"Jenks","given":"Jonathan A.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":833071,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"DePerno, Christopher S.","contributorId":10327,"corporation":false,"usgs":true,"family":"DePerno","given":"Christopher","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":833072,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bluett, Robert D.","contributorId":274290,"corporation":false,"usgs":false,"family":"Bluett","given":"Robert","email":"","middleInitial":"D.","affiliations":[{"id":40911,"text":"Illinois DNR","active":true,"usgs":false}],"preferred":false,"id":833073,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70203940,"text":"70203940 - 2019 - Facilitating adaptation to climate change while restoring a montane plant community","interactions":[],"lastModifiedDate":"2019-12-22T14:27:27","indexId":"70203940","displayToPublicDate":"2019-06-20T16:12:52","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Facilitating adaptation to climate change while restoring a montane plant community","docAbstract":"

Montane plant communities throughout the world have responded to changes in temperature regimes by shifting ranges upward in elevation, and made downslope movements to track shifts in climatic water balance. Organisms that cannot disperse or adapt biologically to projected climate scenarios in situ may decrease in distributional range and abundance over time. Restoration strategies will need to incorporate the habitat suitability of future predicted conditions to ensure long-term persistence. We propagated seedlings of three native Hawaiian montane plant species from high- (~2,500 m asl) and low-elevation (~1,900 m asl) sources, planted them in 8 common plots along a 500 m elevation gradient, and monitored microclimate at each plot for 20 weeks. We explored how temperature and precipitation influenced survival and growth differently among high- and low-elevation origin seedlings. Significantly more seedlings of only one species, Dodonaea viscosa, from high-elevation origin (75.2%) survived than seedlings from low-elevation origin (58.7%) across the entire elevation gradient. Origin also influenced survival in generalized linear mixed models that controlled for temperature, precipitation, and elevation in D. viscosa and Chenopodium oahuense. Survival increased with elevation and soil moisture for Sophora chrysophylla, while it decreased for the other two species. Responses to microclimate varied between the three montane plant species; there were no common patterns of growth or survival. Although limited in temporal scope, our experiment represents one of the few attempts to examine local adaptation to prospective climate scenarios and addresses challenges to restoration efforts within species’ current ranges.

","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0218516","usgsCitation":"Leopold, C., and Hess, S.C., 2019, Facilitating adaptation to climate change while restoring a montane plant community: PLoS ONE, v. 14, e0218516; 17 p., https://doi.org/10.1371/journal.pone.0218516.","productDescription":"e0218516; 17 p.","ipdsId":"IP-099400","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":467514,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0218516","text":"Publisher Index Page"},{"id":364971,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Mauna Kea Forest Reserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.6227111816406,\n 19.796425363822532\n ],\n [\n -155.58013916015625,\n 19.755071768505005\n ],\n [\n -155.49087524414062,\n 19.703364698733452\n ],\n [\n -155.39886474609375,\n 19.73439094891939\n ],\n [\n -155.35491943359375,\n 19.826141627230633\n ],\n [\n -155.3631591796875,\n 19.898471023853403\n ],\n [\n -155.49087524414062,\n 19.93591434153325\n ],\n [\n -155.6227111816406,\n 19.796425363822532\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-06-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Leopold, Christina 0000-0003-0499-3196","orcid":"https://orcid.org/0000-0003-0499-3196","contributorId":178961,"corporation":false,"usgs":false,"family":"Leopold","given":"Christina","affiliations":[],"preferred":false,"id":764853,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hess, Steve C. 0000-0001-6403-9922 shess@usgs.gov","orcid":"https://orcid.org/0000-0001-6403-9922","contributorId":150366,"corporation":false,"usgs":true,"family":"Hess","given":"Steve","email":"shess@usgs.gov","middleInitial":"C.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":764852,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70204098,"text":"70204098 - 2019 - Digital mapping of ecological land units using a nationally scalable modeling framework","interactions":[],"lastModifiedDate":"2019-07-05T15:40:57","indexId":"70204098","displayToPublicDate":"2019-06-20T15:37:53","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"title":"Digital mapping of ecological land units using a nationally scalable modeling framework","docAbstract":"

Ecological site descriptions (ESDs) and associated state-and-transition models (STMs) provide a nationally consistent classification and information system for defining ecological land units for management applications in the United States. Current spatial representations of ESDs, however, occur via soil mapping and are therefore confined to the spatial resolution used to map soils within a survey area. Land management decisions occur across a range of spatial scales and therefore require ecological information that spans similar scales. Digital mapping provides an approach for optimizing the spatial scale of modeling products to best serve decision makers and have the greatest impact in addressing land management concerns. Here, we present a spatial modeling framework for mapping ecological sites using machine learning algorithms, soil survey field observations, soil survey geographic databases, ecological site data, and a suite of remote sensing-based spatial covariates (e.g., hyper-temporal remote sensing, terrain attributes, climate data, land-cover, lithology). Based on the theoretical association between ecological sites and landscape biophysical properties, we hypothesized that the spatial distribution of ecological sites could be predicted using readily available geospatial data. This modeling approach was tested at two study areas within the western United States, representing 6.1 million ha on the Colorado Plateau and 7.5 million ha within the Chihuahuan Desert. Results show our approach was effective in mapping grouped ecological site classes (ESGs), with 10-fold cross-validation accuracies of 70% in the Colorado Plateau based on 1405 point observations across eight expertly-defined ESG classes and 79% in the Chihuahuan Desert based on 2589 point observations across nine expertly-defined ESG classes. Model accuracies were also evaluated using external-validation datasets; resulting in 56 and 44% correct classification for the Colorado Plateau and Chihuahuan Desert, respectively. National coverage of the training and covariate data used in this study provides opportunities for a consistent national-scale mapping effort of ecological sites.

","language":"English","publisher":"Alliance of Crop, Soil, and Environmental Science Societies (ACSESS)","doi":"10.2136/sssaj2018.09.0346","usgsCitation":"Maynard, J.J., Nauman, T.W., Salley, S.W., Bestelmeyer, B.T., Duniway, M.C., Talbot, C.J., and Brown, J.R., 2019, Digital mapping of ecological land units using a nationally scalable modeling framework, v. 83, no. 3, p. 666-686, https://doi.org/10.2136/sssaj2018.09.0346.","productDescription":"21 p.","startPage":"666","endPage":"686","ipdsId":"IP-102201","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":365309,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chihuahuan Desert, Colorado Plateau","volume":"83","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Maynard, Jonathan J.","contributorId":216782,"corporation":false,"usgs":false,"family":"Maynard","given":"Jonathan","email":"","middleInitial":"J.","affiliations":[{"id":39514,"text":"USDA-Agricultural Resource Service, Jornada Experimental Range, Las Cruces, NM 88003, USA","active":true,"usgs":false}],"preferred":false,"id":765492,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nauman, Travis W. 0000-0001-8004-0608 tnauman@usgs.gov","orcid":"https://orcid.org/0000-0001-8004-0608","contributorId":169241,"corporation":false,"usgs":true,"family":"Nauman","given":"Travis","email":"tnauman@usgs.gov","middleInitial":"W.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":765491,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Salley, Shawn W.","contributorId":216783,"corporation":false,"usgs":false,"family":"Salley","given":"Shawn","email":"","middleInitial":"W.","affiliations":[{"id":39514,"text":"USDA-Agricultural Resource Service, Jornada Experimental Range, Las Cruces, NM 88003, USA","active":true,"usgs":false}],"preferred":false,"id":765493,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bestelmeyer, Brandon T.","contributorId":26180,"corporation":false,"usgs":false,"family":"Bestelmeyer","given":"Brandon","email":"","middleInitial":"T.","affiliations":[{"id":6973,"text":"USDA-ARS Jornada Experimental Range and Jornada Basin LTER, Las Cruces, NM; New Mexico State University, Dept. of Plant and Environmental Sciences, Las Cruces, NM","active":true,"usgs":false}],"preferred":false,"id":765494,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":765495,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Talbot, Curtis J.","contributorId":177878,"corporation":false,"usgs":false,"family":"Talbot","given":"Curtis","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":765496,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brown, Joel R.","contributorId":177880,"corporation":false,"usgs":false,"family":"Brown","given":"Joel","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":765497,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70203903,"text":"70203903 - 2019 - LANDFIRE remap prototype mapping effort: Developing a new framework for mapping vegetation classification, change, and structure","interactions":[],"lastModifiedDate":"2019-06-20T12:40:50","indexId":"70203903","displayToPublicDate":"2019-06-20T12:37:40","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5678,"text":"Fire","active":true,"publicationSubtype":{"id":10}},"title":"LANDFIRE remap prototype mapping effort: Developing a new framework for mapping vegetation classification, change, and structure","docAbstract":"LANDFIRE (LF) National (2001) was the original product suite of the LANDFIRE program, which included Existing Vegetation Cover (EVC), Height (EVH), and Type (EVT). Subsequent refinements after feedback from data users resulted in updated products, referred to as LF 2001, that now served as LANDFIRE’s baseline datasets and are the basis for all subsequent LANDFIRE updates. These updates account for disturbances and vegetation transitions changes that may not represent current vegetation conditions. Therefore, in 2016 LANDFIRE initiated the Remap prototype to determine how to undertake a national-scale remap of the LANDFIRE primary vegetation datasets. EVC, EVH, and EVT were produced (circa 2015) via modeling for ecologically variable prototyping areas in the Pacific Northwest (NW) and Grand Canyon (GC). An error analysis within the GC suggested an overall accuracy of 52% (N = 800) for EVT, and a goodness of fit of 51% (N = 38) for percent cover (continuous EVC) and 53% (N = 38) for height (continuous EVH). The prototyping effort included a new 81-class map using the National Vegetation Classification (NVC) within the NW. This paper presents a narrative of the innovative methodologies in image processing and mapping used to create the new LANDFIRE vegetation products.","language":"English","publisher":"MDPI","doi":"10.3390/fire2020035","usgsCitation":"Picotte, J.J., Dockter, D., Long, J., Tolk, B.L., Davidson, A., and Peterson, B., 2019, LANDFIRE remap prototype mapping effort: Developing a new framework for mapping vegetation classification, change, and structure: Fire, v. 2, no. 2, p. 1-26, https://doi.org/10.3390/fire2020035.","productDescription":"26 p.","startPage":"1","endPage":"26","ipdsId":"IP-108452","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":467515,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/fire2020035","text":"Publisher Index Page"},{"id":364836,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":364823,"type":{"id":15,"text":"Index Page"},"url":"https://www.mdpi.com/2571-6255/2/2/35"}],"volume":"2","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2019-06-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Picotte, Joshua J. 0000-0002-4021-4623 jpicotte@usgs.gov","orcid":"https://orcid.org/0000-0002-4021-4623","contributorId":4626,"corporation":false,"usgs":true,"family":"Picotte","given":"Joshua","email":"jpicotte@usgs.gov","middleInitial":"J.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":764692,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dockter, Daryn 0000-0003-1914-8657","orcid":"https://orcid.org/0000-0003-1914-8657","contributorId":216392,"corporation":false,"usgs":false,"family":"Dockter","given":"Daryn","affiliations":[],"preferred":false,"id":764693,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Long, Jordan 0000-0002-4814-464X jlong@usgs.gov","orcid":"https://orcid.org/0000-0002-4814-464X","contributorId":3609,"corporation":false,"usgs":true,"family":"Long","given":"Jordan","email":"jlong@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":764694,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tolk, Brian L. 0000-0002-9060-0266 tolk@usgs.gov","orcid":"https://orcid.org/0000-0002-9060-0266","contributorId":2992,"corporation":false,"usgs":true,"family":"Tolk","given":"Brian","email":"tolk@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":764695,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Davidson, Anne","contributorId":197967,"corporation":false,"usgs":false,"family":"Davidson","given":"Anne","email":"","affiliations":[],"preferred":false,"id":764696,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Peterson, Birgit 0000-0002-4356-1540 bpeterson@usgs.gov","orcid":"https://orcid.org/0000-0002-4356-1540","contributorId":192353,"corporation":false,"usgs":true,"family":"Peterson","given":"Birgit","email":"bpeterson@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":764697,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70203321,"text":"sir20195039 - 2019 - Simulation of water availability in the Southeastern United States for historical and potential future climate and land-cover conditions","interactions":[],"lastModifiedDate":"2019-06-20T09:36:30","indexId":"sir20195039","displayToPublicDate":"2019-06-19T15:45:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5039","displayTitle":"Simulation of Water Availability in the Southeastern United States for Historical and Potential Future Climate and Land-Cover Conditions","title":"Simulation of water availability in the Southeastern United States for historical and potential future climate and land-cover conditions","docAbstract":"

A study was conducted by the U.S. Geological Survey (USGS), in cooperation with the Gulf Coastal Plains and Ozarks Landscape Conservation Cooperative (GCPO LCC) and the Department of the Interior Southeast Climate Adaptation Science Center, to evaluate the hydrologic response of a daily time step hydrologic model to historical observations and projections of potential climate and land-cover change for the period 1952–2099. The model simulations were used to compute the potential changes in hydrologic response and streamflow statistics across the Southeastern United States, using historical observations of climate and streamflow. Thirteen downscaled general circulation models with four representative concentration pathways were used to represent a range of potential future changes in climate (a total of 45 future simulations) from the Coupled Model Intercomparison Project Phase 5. The streamflow statistics were selected to describe streamflow conditions that may be most useful in defining the suitability for each river or stream to support sustaining populations of priority aquatic species across the GCPO LCC. An application of the Precipitation-Runoff Modeling System (included as part of the USGS National Hydrologic Model) was used to develop the hydrologic simulations. The results showed increases in air temperature across the study area, with the highest increases occurring in the northern part of the study area during July to September. The results showed a mix of increases and decreases in precipitation accumulation across the study area and across seasons, with decreases in precipitation accumulation across all seasons for the southwestern part of the study area. Actual evapotranspiration decreased for the southeastern part of the study area and increased for the northwestern part of the study area. The results showed general decreases in runoff across the study area, with increases in runoff in areas surrounding large metropolitan regions where potential future increases in impervious area occur. Results from a statistical analysis (Kolmogorov-Smirnov test) showed that the downscaled general circulation models generally have more skill in producing historical streamflow statistics in the duration and magnitude categories and less skill in producing historical streamflow statistics in the frequency, rate of change, and timing categories for this study area. The potential changes in the streamflow statistics and the results of the Kolmogorov-Smirnov test are available through the GCPO LCC Conservation Planning Atlas, an online science-based mapping platform built specifically for land managers and planners.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195039","collaboration":"Prepared in cooperation with the Gulf Coastal Plains and Ozarks Landscape Conservation Cooperative and the Department of the Interior Southeast Climate Adaptation Science Center","usgsCitation":"LaFontaine, J.H., Hart, R.M., Hay, L.E., Farmer, W.H., Bock, A.R., Viger, R.J., Markstrom, S.L., Regan, R.S., and Driscoll, J.M., 2019, Simulation of water availability in the Southeastern United States for historical and potential future climate and land-cover conditions: U.S. Geological Survey Scientific Investigations Report 2019–5039, 83 p., https://doi.org/10.3133/sir20195039.","productDescription":"Report: x, 83 p.; Data release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-075743","costCenters":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":364749,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5039/coverthb.jpg"},{"id":364750,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5039/sir20195039.pdf","text":"Report","size":"63.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5039"},{"id":364806,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F74X56PH","text":"USGS data release","description":"USGS data release","linkHelpText":"Model Input and Output for Hydrologic Simulations of the Southeastern United States for Historical and Future Conditions"}],"country":"United States","state":"Alabama, Arkansas, Florida, Georgia, Illinois, Kansas, Kentucky, Louisiana, Mississippi, Missouri, North Carolina, Oklahoma, Tennessee, Texas, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.515625,\n 40.51379915504413\n ],\n [\n -95.185546875,\n 38.89103282648846\n ],\n [\n -95.2734375,\n 37.37015718405753\n ],\n [\n -97.294921875,\n 35.96022296929667\n ],\n [\n -97.646484375,\n 35.17380831799959\n ],\n [\n -95.97656249999999,\n 33.578014746143985\n ],\n [\n -95.537109375,\n 32.32427558887655\n ],\n [\n -96.328125,\n 31.50362930577303\n ],\n [\n -97.734375,\n 30.977609093348686\n ],\n [\n -96.85546875,\n 30.600093873550072\n ],\n [\n -96.240234375,\n 28.536274512989916\n ],\n [\n -93.69140625,\n 29.38217507514529\n ],\n [\n -91.93359375,\n 29.305561325527698\n ],\n [\n -90.087890625,\n 29.075375179558346\n ],\n [\n -89.12109375,\n 29.075375179558346\n ],\n [\n -89.47265625,\n 29.916852233070173\n ],\n [\n -88.24218749999999,\n 30.372875188118016\n ],\n [\n -86.484375,\n 30.372875188118016\n ],\n [\n -85.166015625,\n 29.6880527498568\n ],\n [\n -84.0234375,\n 29.916852233070173\n ],\n [\n -82.880859375,\n 29.38217507514529\n ],\n [\n -81.9140625,\n 28.998531814051795\n ],\n [\n -82.44140625,\n 29.611670115197377\n ],\n [\n -81.474609375,\n 31.42866311735861\n ],\n [\n -83.49609375,\n 34.74161249883172\n ],\n [\n -81.9140625,\n 35.24561909420681\n ],\n [\n -81.9140625,\n 37.3002752813443\n ],\n [\n -85.95703125,\n 35.53222622770337\n ],\n [\n -88.41796875,\n 37.020098201368114\n ],\n [\n -89.82421875,\n 39.232253141714885\n ],\n [\n -91.7578125,\n 39.232253141714885\n ],\n [\n -93.515625,\n 40.51379915504413\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210

","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2019-06-19","noUsgsAuthors":false,"publicationDate":"2019-06-19","publicationStatus":"PW","contributors":{"authors":[{"text":"LaFontaine, Jacob H. 0000-0003-4923-2630 jlafonta@usgs.gov","orcid":"https://orcid.org/0000-0003-4923-2630","contributorId":2258,"corporation":false,"usgs":true,"family":"LaFontaine","given":"Jacob","email":"jlafonta@usgs.gov","middleInitial":"H.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":762140,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hart, Rheannon M. 0000-0003-4657-5945 rmhart@usgs.gov","orcid":"https://orcid.org/0000-0003-4657-5945","contributorId":5516,"corporation":false,"usgs":true,"family":"Hart","given":"Rheannon","email":"rmhart@usgs.gov","middleInitial":"M.","affiliations":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":762141,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hay, Lauren E. 0000-0003-3763-4595","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":211478,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren E.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":762142,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Farmer, William H. 0000-0002-2865-2196 wfarmer@usgs.gov","orcid":"https://orcid.org/0000-0002-2865-2196","contributorId":4374,"corporation":false,"usgs":true,"family":"Farmer","given":"William","email":"wfarmer@usgs.gov","middleInitial":"H.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":762144,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bock, Andy R. 0000-0001-7222-6613","orcid":"https://orcid.org/0000-0001-7222-6613","contributorId":207395,"corporation":false,"usgs":true,"family":"Bock","given":"Andy","email":"","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":false,"id":762143,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Viger, Roland J. 0000-0003-2520-714X rviger@usgs.gov","orcid":"https://orcid.org/0000-0003-2520-714X","contributorId":168799,"corporation":false,"usgs":true,"family":"Viger","given":"Roland","email":"rviger@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":762145,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Markstrom, Steven L. 0000-0001-7630-9547 markstro@usgs.gov","orcid":"https://orcid.org/0000-0001-7630-9547","contributorId":146553,"corporation":false,"usgs":true,"family":"Markstrom","given":"Steven","email":"markstro@usgs.gov","middleInitial":"L.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":762146,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Regan, R. Steve 0000-0003-4803-8596 rsregan@usgs.gov","orcid":"https://orcid.org/0000-0003-4803-8596","contributorId":196973,"corporation":false,"usgs":true,"family":"Regan","given":"R.","email":"rsregan@usgs.gov","middleInitial":"Steve","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":762147,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Driscoll, Jessica M. 0000-0003-3097-9603 jdriscoll@usgs.gov","orcid":"https://orcid.org/0000-0003-3097-9603","contributorId":167585,"corporation":false,"usgs":true,"family":"Driscoll","given":"Jessica","email":"jdriscoll@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":762148,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70202680,"text":"sir20195017 - 2019 - Development of a flood-inundation map library and precipitation-runoff modeling for the Clear Fork Mohican River in and near Bellville, Ohio","interactions":[],"lastModifiedDate":"2019-06-20T09:28:26","indexId":"sir20195017","displayToPublicDate":"2019-06-19T15:15:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5017","displayTitle":"Development of a Flood-Inundation Map Library and Precipitation-Runoff Modeling for the Clear Fork Mohican River in and near Bellville, Ohio","title":"Development of a flood-inundation map library and precipitation-runoff modeling for the Clear Fork Mohican River in and near Bellville, Ohio","docAbstract":"

The U.S. Geological Survey (USGS), in cooperation with the Muskingum Watershed Conservancy District, led hydrologic and hydraulic analyses within the Clear Fork Mohican River Basin in and near Bellville, Ohio. The analyses included the development of digital flood-inundation maps for an approximately 2.5-mile reach of the Clear Fork Mohican River and the development of a precipitation-runoff model for a portion of the Clear Fork Mohican River Basin.

Data collection for the study involved the installation and operation of 2 streamgages (Clear Fork Mohican River at Bellville, Ohio, and Cedar Fork above Bellville, Ohio); 1 lake-level gage (Clear Fork Reservoir near Lexington, Ohio); 2 precipitation gages (Clear Fork Reservoir near Lexington, Ohio, and Rain Gage at Cedar Fork above Bellville, Ohio); and 12 submersible pressure transducers on Clear Fork Mohican River and 4 of its tributaries. Data collection also included field surveys of hydraulic structures and channel cross sections.

Flood profiles were computed for the 2.5-mile reach of the Clear Fork Mohican River by means of a one-dimensional step-backwater model. The model was calibrated to 16 measured events and to a portion (stages 9 to 11 feet) of the current stage-streamflow relation at the USGS streamgage Clear Fork Mohican River at Bellville, Ohio, and to stage recorded at a submersible pressure transducer site near the downstream study limit. After calibration the step-backwater model was used to compute nine flood profiles for stages ranging from 9 to 17 feet. The flood profiles were then used in combination with a digital elevation model to delineate the area that would be inundated at each stage.

A precipitation-runoff model was developed and calibrated using data from the streamgage, precipitation gage, and 11 submersible pressure transducers. The modeling included data during 10 runoff events that were used for model calibration and validation, with focus on 6 events. The Nash-Sutcliffe model efficiency coefficients for six peak streamflow events ranged from 0.459 to 0.851.

The models produced by this study can be used to assess possible flood mitigation options and define flood hazard areas that could contribute to the protection of life and property. The availability of flood-inundation maps, internet information from USGS streamgages, and forecasted stages from the National Weather Service could provide emergency management personnel and residents with information on forecasting floods, appropriate flood response activities, and post-flood recovery efforts.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195017","collaboration":"Prepared in cooperation with the Muskingum Watershed Conservancy District and Richland County","usgsCitation":"Ostheimer, C.J., and Huitger, C.A., 2019, Development of a flood-inundation map library and precipitation-runoff modeling for the Clear Fork Mohican River in and near Bellville, Ohio: U.S. Geological Survey Scientific Investigations Report 2019–5017, 34 p., including 1 appendix, https://doi.org/10.3133/sir20195017.","productDescription":"Report, iv, 34 p.; Data release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-100979","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":364753,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5017/coverthb.jpg"},{"id":364755,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95NMIDF","text":"USGS data release","description":"USGS data release","linkHelpText":"Geospatial data sets for flood-inundation maps in and near Bellville, Ohio"},{"id":364754,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5017/sir20195017.pdf","text":"Report","size":"17.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5017"}],"country":"United States","state":"Ohio","county":"Richland County","city":"Bellville","otherGeospatial":"Clear Fork Mohican River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.39265441894531,\n 40.58475654701271\n ],\n [\n -82.40020751953125,\n 40.603526799885884\n ],\n [\n -82.52792358398436,\n 40.660847697284815\n ],\n [\n -82.57598876953125,\n 40.70875101828792\n ],\n [\n -82.62405395507812,\n 40.758700379161006\n ],\n [\n -82.68722534179688,\n 40.76182096906601\n ],\n [\n -82.72430419921875,\n 40.71916022743469\n ],\n [\n -82.71194458007812,\n 40.658764163202925\n ],\n [\n -82.49153137207031,\n 40.58345286156245\n ],\n [\n -82.41462707519531,\n 40.56937143958841\n ],\n [\n -82.39471435546875,\n 40.57328324298059\n ],\n [\n -82.39265441894531,\n 40.58475654701271\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
6460 Busch Boulevard Ste 100
Columbus, OH 43229

","tableOfContents":"","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"publishedDate":"2019-06-19","noUsgsAuthors":false,"publicationDate":"2019-06-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Ostheimer, Chad J. 0000-0002-4528-8867","orcid":"https://orcid.org/0000-0002-4528-8867","contributorId":213950,"corporation":false,"usgs":true,"family":"Ostheimer","given":"Chad","email":"","middleInitial":"J.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":759455,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huitger, Carrie A. 0000-0003-4534-3245 chuitger@usgs.gov","orcid":"https://orcid.org/0000-0003-4534-3245","contributorId":207180,"corporation":false,"usgs":true,"family":"Huitger","given":"Carrie","email":"chuitger@usgs.gov","middleInitial":"A.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":759456,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70204662,"text":"70204662 - 2019 - Modulation of seismic activity in Kīlauea’s Upper East Rift Zone by summit pressurization","interactions":[],"lastModifiedDate":"2019-08-09T10:20:55","indexId":"70204662","displayToPublicDate":"2019-06-19T13:40:12","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Modulation of seismic activity in Kīlauea’s Upper East Rift Zone by summit pressurization","docAbstract":"Kīlauea Volcano is underlain by a complex, laterally-extensive magmatic plumbing system. Although in recent decades it has mainly erupted through vents along the middle East Rift Zone and summit caldera, eruptions can occur anywhere along its two laterally extensive rift zones, as demonstrated by the dramatic eruptive activity of 2018. Forecasting eruptive activity requires an understanding of whether an episode of volcano-seismic unrest at Kīlauea or a similar volcano is caused directly at the edges of an active magmatic intrusion or reservoir, or in a volume of wall rock at a distance from the intrusion. Seismic unrest in Kīlauea’s Upper East Rift Zone (UERZ) has to date been interpreted as the result of either magma intrusion in this region of the volcano or of stresses due to seaward flank migration. However, recent observations suggest that UERZ seismicity may result from variable pressurization of Kīlauea’s summit magma system. We analyze seismic and deformation (multi-temporal InSAR and GPS) data during a period of variable summit deformation and UERZ seismicity in mid- to late-2007 and calculate Coulomb stress changes on UERZ faults due to modeled summit inflation or deflation. UERZ seismicity during our study period can be explained entirely by stresses arising from pressure changes within Kīlauea’s two summit reservoirs. Furthermore, a comparison of UERZ fault plane solutions (FPS) calculated for this study to published UERZ FPS for previous periods suggests the UERZ has undergone a transition from a mechanically-strong, discontinuous and immature magma transport system to a mature, mechanically-weak and fully-connected transport system over the course of the 1983-2018 eruption.","language":"English","publisher":"Geological Society of America","doi":"10.1130/G46000.1","usgsCitation":"Wauthier, C., Roman, D.C., and Poland, M.P., 2019, Modulation of seismic activity in Kīlauea’s Upper East Rift Zone by summit pressurization: Geology, 5 p., https://doi.org/10.1130/G46000.1.","productDescription":"5 p.","ipdsId":"IP-106972","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":366397,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-06-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Wauthier, Christelle","contributorId":176224,"corporation":false,"usgs":false,"family":"Wauthier","given":"Christelle","email":"","affiliations":[],"preferred":false,"id":767965,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roman, Diana C.","contributorId":176225,"corporation":false,"usgs":false,"family":"Roman","given":"Diana","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":767966,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":146118,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":767964,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}